Engineering Proceedings doi: 10.3390/engproc2026154025

Authors: Veneta Aleksieva Hristo Valchanov

In today’s digital infrastructure, organizations and enterprises increasingly rely on distributed and remote IT environments. These environments may include multiple network sites, remote branch offices, employee home networks, or servers hosted in geographically distant locations. Monitoring and managing these networks presents a critical challenge, especially when administrators are expected to maintain security, performance, and uptime across all nodes. This paper presents an architecture for a cross-platform, multi-tenant network monitoring and management system that enables centralized visibility and control over a distributed infrastructure.

Engineering Proceedings doi: 10.3390/engproc2026152004

Authors: Nermin Özcan Imam Barket Ghiloubi

Accurate parameter estimation of photovoltaic (PV) models is essential for performance evaluation, efficiency enhancement, and reliable energy forecasting in solar energy systems. However, the nonlinear, multimodal, and implicit nature of the current–voltage (I–V) relationship makes this task challenging for conventional optimization methods, which often suffer from premature convergence and sensitivity to initial conditions. In this study, a modified variant of the Artificial Circulatory System Algorithm, termed Dynamic Elite Cooperative ACSA (DEC-ACSA), is proposed for estimating the unknown parameters of the Single-Diode Model (SDM). The proposed approach extends the original ACSA by incorporating dynamic population grouping, elite-guided cooperative interaction, and directional elite refinement, thereby aiming to improve convergence stability and the utilization of high-quality population information. The objective is to minimize the residual root mean square error (RMSE) of the implicit SDM equation using measured I–V data from four established benchmarks: the RTC France solar cell and the PWP201, STM6-40/36, and STP6-120/36 PV modules. The performance of DEC-ACSA is evaluated against the original ACSA, Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Henry Gas Solubility Optimization (HGSO) over 30 independent runs under an equal budget of 50,100 function evaluations. The DEC-ACSA configuration selected on RTC France was retained unchanged for the three additional module benchmarks. DEC-ACSA achieved mean residual RMSE values of 1.2514 × 10−3, 2.656 × 10−3, 2.647 × 10−3, and 1.8108 × 10−2 for RTC France, PWP201, STM6-40/36, and STP6-120/36, respectively, while consistently reducing run-to-run variability relative to ACSA. Holm-corrected tests showed no significant difference from PSO on RTC France and PWP201, whereas significant differences from all comparison algorithms were observed on STM6-40/36 and STP6-120/36. I–V reconstruction further confirmed close agreement with the measured data across all four PV systems.

Engineering Proceedings doi: 10.3390/engproc2026154023

Authors: Antonina Ivanova Georgi Kolev Fatima Sapundzhi Teodora Bakardjieva Slavi Georgiev

Large Language Models (LLMs) are increasingly incorporated into software systems. Their non-deterministic behavior, external hosting, response latency, and operational cost create challenges for established design approaches such as Clean Architecture. This paper examines the integration of an LLM component into a layered software system and compares three possible placements within Clean Architecture: Domain, Application, and Infrastructure. The evaluation considers dependency management, testability, separation of concerns, and implementation complexity. The study proposes an approach in which the LLM is implemented in the Infrastructure layer and accessed through an interface defined in the Application layer. This approach is combined with the Command and Query Responsibility Segregation pattern to isolate LLM interaction within dedicated query handlers. The proposed pattern is demonstrated through the implementation of Budget, a personal finance tracking system that uses GPT-4.1 to convert free-form natural language input into structured transaction records. The results show that placement in the infrastructure layer provides the clearest separation between business logic and external AI services and avoids the introduction of non-deterministic behavior into the core application logic.

Engineering Proceedings doi: 10.3390/engproc2026147019

Authors: Mana Dastoum

Despite significant advances in computational daylight simulation, translating performance metrics into practical architectural decisions remains a major challenge in façade design. This paper proposes a Performance-Informed Design Framework (PIDF) that bridges this gap by systematically linking design context, daylight performance objectives, environmental evaluation, and tessellated façade design variables. Developed through literature synthesis and conceptual modelling, the framework introduces a Performance-to-Design Translation Matrix that converts quantitative daylight indicators into actionable architectural strategies. The proposed methodology supports evidence-based, context-responsive façade design and promotes a shift from performance evaluation toward performance-informed architectural thinking.

Engineering Proceedings doi: 10.3390/engproc2026146021

Authors: Fang Liu Jianing Wang Miaocheng Weng Kaiwen Ling

The complex structure of inclined T-shaped tunnels significantly increases the difficulty of smoke exhaust and rescue operations. This study aimed to investigate the effects of fire source location, bifurcation angle, and opposite jet velocity on smoke control in the opposite jet side. Meanwhile, the smoke flow characteristics were examined during synergistic operation. The results show that the smoke spread length on the opposite jet side approaches a minimum when the opposite jet velocity reaches 1.5 m/s. A smaller bifurcation angle results in a longer smoke spread length. The smoke propagation length downstream of the bifurcation zone is independent of the fire source location. Under synergistic smoke control, optimal extraction performance is achieved when exhaust vent is positioned near the bifurcation zone of the branch tunnel. A prediction model is proposed between the branch tunnel ceiling temperature decay patterns and the exhaust volume during synergistic smoke control in inclined T-shaped tunnels, ensuring both economic efficiency and safety in real-world applications.

Engineering Proceedings doi: 10.3390/engproc2026154022

Authors: Aizhan Oshmanova Valentina Grichshenko Ivaylo Stoyanov

This paper presents a comparative reliability analysis of spacecraft onboard control systems based on their structural representation using directed graph models. A modified approach to reliability assessment is proposed, grounded in representing onboard control systems as directed functional graphs and applied to the analysis of spacecraft architectures in terms of structural fault tolerance. The initial functional schemes are simplified by identifying key system elements and the relationships between them. Based on the resulting representations, graph models are constructed, reflecting the structure of control signal propagation. Structural reliability and fault tolerance assessment are performed using an analysis of graph topological characteristics, including connectivity, graph centrality metrics, the presence of alternative paths, and identification of critical nodes. For systems with a comparable number of elements, differences in structural connectivity significantly affect system resilience to failures. It is shown that a higher degree of connectivity and the presence of redundant control pathways enhance the fault tolerance of the onboard control system. The obtained results confirm the effectiveness of graph-based models for structural reliability and robustness analysis of complex technical systems and can be applied in the design of spacecraft onboard control systems. The proposed approach focuses on the structural and topological properties of the system architecture and does not include probabilistic failure modeling.

Engineering Proceedings doi: 10.3390/engproc2026154024

Authors: Penka Zlateva Angel Terziev Krastin Yordanov Nevena Mileva

This study presents a system-level and subsystem-level evaluation of energy performance in an industrial polyethylene film production system based on real operational data. The analysis focuses on specific energy consumption (SEC) as a key performance indicator, considering both total system behavior and the contribution of energy-intensive subsystems, namely extrusion and converting processes. The initial system exhibits SEC values ranging from 1.267 to 1.688 kWh/kg, indicating relatively high energy intensity compared to established industrial benchmarks. Following technological modernization, SEC is reduced to 0.43 kWh/kg for extrusion and 0.09 kWh/kg for converting, corresponding to improvements exceeding 60%. The total annual energy saving potential is estimated at 906 MWh (39%), accompanied by a proportional reduction in CO2 emissions. The results demonstrate that energy performance is strongly influenced by production load, material losses, and process stability. The novelty of the study lies in the subsystem-level quantification of energy performance using real industrial data and in the identification of the interaction between production efficiency, waste generation, and energy consumption. The findings provide a practical framework for energy optimization in polymer processing systems and allow comparison with European best practices.

Engineering Proceedings doi: 10.3390/engproc2026146024

Authors: Shaohong Zhu

Calcium silicate hydrate (C-S-H) serves as the primary hydration product of cement and constitutes the fundamental strength contributor in concrete matrices. This study presents a novel approach for synthesizing an early-strength admixture for hydrated calcium silicate through the sol–gel methodology. A comprehensive experimental investigation was conducted to evaluate its performance characteristics. The research findings demonstrate that the synthesized admixture, prepared using high-speed mechanical agitation in conjunction with a proprietary dispersant solution, exhibits optimal particle size distribution and dispersion stability at ambient temperature conditions (25 °C). When incorporated into cementitious systems, this innovative additive significantly reduces the energy barrier for nucleation processes, thereby accelerating cement hydration kinetics. The resulting concrete specimens show marked reductions in initial setting times and substantial improvements in early-age compressive strength development.

Engineering Proceedings doi: 10.3390/engproc2026154020

Authors: Tarık Talan Serkan Gökkaya Adem Korkmaz Ivan Beloev

This study aims to autonomously detect and classify Unmanned Aerial Vehicles (UAVs), which are becoming increasingly widespread, based on their emitted radio frequency (RF) signals in highly noisy and interference-prone RF environments where traditional optical and radar-based methods prove insufficient. The dataset used in this study is the “Noisy Drone RF Signal Classification” dataset, which consists of seven classes in total—six different drone models and one noise class—and is balanced across classes. As the methodological approach, a multimodal hybrid deep learning (DL) architecture was developed, integrating raw time-domain IQ signals (1D-CNN) with frequency-domain spectrogram representations (2D-CNN). To enhance model performance and generalization capability, techniques such as Batch Normalization, Dropout, Label Smoothing, and Gradient Clipping were incorporated into the architecture. The model was trained using the AdamW optimization algorithm alongside a cosine annealing learning rate scheduler. In order to efficiently process large-scale datasets, memory management optimizations including memory-mapped files (mmap) and lazy loading were implemented. Experimental results demonstrate that the proposed multimodal model achieves an accuracy of 87.42% and an F1-score of 0.87, indicating strong detection performance. SNR-based analyses reveal that the model achieves accuracy levels ranging between 64.52% and 82.40% under negative-SNR conditions (−20 to 0 dB), while exceeding 89% accuracy under positive-SNR conditions. The findings indicate that multimodal DL approaches can achieve high performance in UAV detection and classification even in noisy RF environments.

Engineering Proceedings doi: 10.3390/engproc2026152003

Authors: Mirinchige B. D. K. Siriwardena Abdul R. Nihmiya Udara S. P. R. Arachchige

Alkaline water electrolysis (AWE) is a promising technology for sustainable hydrogen production, although its performance is limited by electrode overpotential, interfacial charge-transfer resistance, and limited electrochemically accessible surface area. In this study, a monolayer ternary carbon nanomaterial (CNM) composite comprising reduced graphene oxide (rGO), carbon nanotubes (CNTs), and Vulcan XC-72 was fabricated on stainless steel (SS) using a hybrid polyvinyl alcohol–polytetrafluoroethylene (PVA–PTFE) binder. Thermal treatment generated a porous conductive network that enhanced electrolyte accessibility and electron transport. Electrochemical characterization in 0.12 M NaOH showed that the CNM-modified electrode exhibited substantially higher current response and CV-derived double-layer capacitance (Cdl) of 62.61–78.51 mF/cm2, compared with 3.43–3.74 mF/cm2 for bare SS. Electrochemical fitting further showed markedly higher exchange-current density (i0) parameters for the modified electrode, along with a reduced solution resistance (Rs) of ~2.1–2.2 Ω·cm2 and a lower Rct. The oxyhydrogen (HHO) production rate reached 0.304 mL/min at 3.8 V, compared with 0.262 mL/min for bare SS at 4.0 V. Repeated HHO measurements showed ~2% variation (n = 3), indicating good reproducibility of the gas-production response. These results demonstrate that the rGO/CNT/XC-72 composite provides an effective and reproducible surface-engineering approach for enhancing electrochemical performance and HHO production in alkaline electrolysis systems.

Engineering Proceedings doi: 10.3390/engproc2026150137

Authors: Mariyana Kovacheva Vera Katrandzhieva

Governments have a pivotal role in the realm of AI. In order to achieve success within the context of the AI revolution, it is essential to possess robust political intentions. The capacity to exert influence over these entities is predicated on the formulation of policies, rules, and incentives. In the global competition to develop AI and data-driven businesses, the EU’s investments in public computing infrastructure are a key part of encouraging AI innovation across Europe. In this aspect, we look for the internal and external factors under which the countries of the European Union, and specifically AI factories, are clustered and differentiated from one another. The object of the present study is the current artificial intelligence ecosystem in Europe’s efforts to be recognized as a global leader in supercomputing technologies. Contribution: Our strategic points in this study are to indicate the geographical diversification between the two leaders, France and Germany, and the other member states of the European Union.

Engineering Proceedings doi: 10.3390/engproc2026146022

Authors: Ziwei Ma Haiyang Li Xiaoting Wang Tao Wang

This paper proposes a convolutional neural network (CNN)-based image recognition method for crack detection in masonry walls to improve accuracy and efficiency. A sample database is constructed using laboratory-captured images of cracked masonry walls, augmented through rotation, mirroring, gamma correction, contrast adjustment, and brightness modification. A dual-scale CNN architecture is designed by integrating the characteristics of VGG-16 and GoogleNet, enabling multi-scale feature extraction for load-bearing masonry wall images. The network adopts two input scales: a modified VGG-16 branch with 100 × 100 inputs and an optimized GoogleNet branch with 50 × 50 inputs. Both branches undergo feature extraction and classifier training. Leveraging transfer learning, the model is pre-trained on the large-scale ImageNet dataset and fine-tuned using our self-built masonry wall database. Multi-scale features from dual branches are weighted and fused to generate final crack recognition results. Experimental results demonstrate a training accuracy of 94.33%, precision of 94.78%, and F1-score of 94.68%, outperforming traditional CNN models. The proposed method achieves high recognition accuracy for masonry load-bearing wall cracks and provides reliable technical support for practical engineering applications.

Engineering Proceedings doi: 10.3390/engproc2026152006

Authors: Panha Soth Sokna San Socheat Yay Heng Tang Chivon Choeung

Grid-following inverters play a vital role in integrating renewable energy systems into modern power grids. However, their performance deteriorates under grid voltage unbalance and uncertain grid impedance, resulting in current distortion and double-frequency active-power oscillations. This paper proposes a robust dual-sequence current control strategy for a three-phase grid-following inverter operating under these adverse conditions. The inverter model explicitly incorporates grid impedance uncertainty and is represented using a polytopic uncertainty model. Positive- and negative-sequence current controllers are independently designed based on a state-feedback integral structure, where the control gains are synthesized using linear matrix inequality (LMI) optimization to guarantee robust stability over the entire uncertainty range. In addition, sequence-based reference-current generation is employed to suppress the negative-sequence current and eliminate double-frequency power oscillations under unbalanced grid voltages. The effectiveness of the proposed approach is evaluated through simulation studies and compared with a previous robust power controller. The results suggest that the proposed controller significantly suppresses the 120 Hz active-power oscillation despite the presence of grid voltage unbalance and impedance uncertainty. Compared with a previous controller, the magnitude of the 120 Hz component is reduced by approximately 91%, demonstrating improved power-quality performance under grid voltage unbalance and impedance uncertainty.

Engineering Proceedings doi: 10.3390/engproc2026152005

Authors: Imam Barket Ghiloubi Nermin Özcan

Mobile robots are increasingly deployed in autonomous navigation tasks where both tracking performance and reduction in the cumulative control-effort index are critical. This work proposes a control-effort index-aware tuning framework for a nonlinear backstepping controller applied to a two-wheeled mobile robot. The gains are optimized using the Cuckoo Search Algorithm (CSA) under three tuning strategies: accuracy-oriented optimization, weighted control-effort-performance optimization, and an adaptive switching approach. Comprehensive simulations on circular and lemniscate trajectories demonstrate that the proposed adaptive switching strategy achieves an effective compromise between tracking accuracy and control-effort index, reducing control-effort index by up to 12% on complex trajectories while maintaining satisfactory tracking performance.

Engineering Proceedings doi: 10.3390/engproc2026154019

Authors: Darena Mihaylova Velizar Vassilev

This study aims to develop a neural network for the early detection and prevention of insider threats in civil aviation. The approach is based on 23 behavioral indicators represented as binary input features. A multilayer neural network with two hidden layers is designed to model nonlinear relationships between the indicators. Due to the lack of real data, a synthetic dataset is generated based on expert-defined rules. The model is trained using a supervised learning approach and evaluated using standard metrics. The results show stable training and good generalization capability, achieving 89.36% accuracy on the test dataset, confirming the applicability of the proposed approach.

Engineering Proceedings doi: 10.3390/engproc2026154018

Authors: Stefan Tenev Aleksandrina Bankova Anastas Yangyozov Asparuh Atanasov

Particular attention is devoted to the characteristics of elastic couplings as essential connecting elements within machine drive systems. The operational characteristics of such couplings are determined under both static and dynamic loading conditions, while also taking into consideration the nature of the working environment and the specific type of driven machinery, such as crushing machines, mills, and related industrial equipment. The relationship between the transmitted torque load and the deformation of the coupling’s rubber working elements constitutes a significant factor contributing to the compensation of vibrations and shaft misalignments. Furthermore, the rubber elements are characterized by inherent damping properties and residual elastic deformation. The parameters governing damping behavior and deformation exhibit variations over time, which is of particular importance in deformation analysis and measurement. A series of experimental investigations was carried out to evaluate the influence of measurement time on the deformation state of the rubber element in a “SEGME”-type coupling. Four time intervals—5, 10, 20, and 30 s—are considered for recording the instantaneous deformation of the working element. Based on the obtained experimental data, mathematical relationships describing the energy dissipation and damping capacity of the rubber working elements are established as functions of the deformation measurement time. In addition, a coefficient characterizing the influence of deformation measurement duration was determined.

Engineering Proceedings doi: 10.3390/engproc2026146023

Authors: Kunxian Lin Jindong Liu Kefu Nie Bo Pang Jian Yang

Verifying the as-built conformity of reinforcing stirrups is challenging due to occlusion and noise inherent in 3D laser scans. Addressing the limitations of manual inspection and the data dependency of deep learning, this paper proposes an unsupervised, design-driven workflow for automated quality inspection. We first introduce the pose adjustment step to refine orientation, followed by utilizing the slice-based projection to decompose the complex point cloud into candidate clusters. Subsequently, a greedy detect-and-remove strategy is applied to iteratively extract individual stirrup instances. To evaluate alignment reliability, we develop a soft similarity metric based on probabilistic volumetric overlap. This measure robustly quantifies the geometric consistency between CAD templates and noisy fragments, accommodating partial data loss where traditional methods fail. Comprehensive experiments on real-world and synthetic datasets demonstrate that the proposed method significantly outperforms unsupervised baselines. The framework maintains high robustness even with only 25% of data retained, providing a precise, efficient solution for the digital quality control of precast components.

Engineering Proceedings doi: 10.3390/engproc2026154015

Authors: Mariyana Sestrimska Nikolay Komitov

Modeling an artificial neural network to predict the behavior of a heating and domestic hot water system in a residential building is the basis of this report. The heating system includes three types of energy sources: biofuel, solar, and electricity. During transitional seasons, such as spring and autumn, it is possible to use all three sources periodically or simultaneously, which leads to increased consumption and inefficiency in the system. In order to study the dynamics of the process and optimize the control, a monitoring system based on Raspberry Pi Pico W was developed. Data on the operating parameters of the boiler, tank, and radiator is transmitted in real-time to the ThingSpeak cloud platform, using the free access option that requires only registration. Due to the reinforced concrete structure of the building, the local Wi-Fi connection drops at times, so an additional router was added. Although individual values from the data are missing, they can be used to obtain graphs of the transient process. The data received in the platform does not arrive evenly due to the time required for transmission. The artificial neural network was created in MATLAB (v2025, MathWorks, Natick, MA, USA) and uses the raw data to predict changes in the processes. The missing fragments of the data have no impact, and a good match of the actual values with the predicted values was obtained for the tank and radiator, while for the boiler, the match was satisfactory.

Engineering Proceedings doi: 10.3390/engproc2026154017

Authors: Gökhan Uçkan Engin Oğuzay

Emotion analysis through facial recognition has significant potential for enhancing security within organizational and industrial contexts by enabling early risk detection, reducing human error, and supporting real-time decision-making. However, existing systems often demand high computational resources and advanced imaging equipment, limiting their adoption in small and medium-sized facilities. This study presents a cost-effective and practical emotion analysis application based on facial recognition, designed for seamless integration into diverse environments and IoT platforms. The system dynamically adapts its operation to the emotional state of the authorized user, mitigating potential errors when psychological resilience is insufficient. A Convolutional Neural Network (CNN) model was developed for emotion analysis using Conv2D, MaxPooling2D, and Dropout layers. Additionaly, several face recognition algorithms were tested to ensure reliable identification under different conditions. The proposed emotion analysis model achieved 98% overall accuracy and an 89% weighted F1 score. The system was trained and tested on a dataset with 58,179 training images and 28,706 test images, reaching the highest validation accuracy of 98.71% at the 25th epoch. By using a face recognition library, the system provided both high accuracy and fast processing. The developed face recognition-based folder security system offers a more user-friendly and innovative alternative to traditional password-based security methods.

Engineering Proceedings doi: 10.3390/engproc2026154014

Authors: Muazzam Artikova Dilshodbek Jamoliddinov

This paper presents an automated computational workflow for the acquisition, instrument-response correction and three-dimensional visualization of multi-component seismic records obtained from the IRIS Federation of Digital Seismograph Networks (FDSNs) using the open-source ObsPy (v1.5.0) package. The workflow targets engineering applications and consists of four stages: (i) selection of three-component (3C) broadband stations, (ii) bandpass filtering and spectral deconvolution of the instrument response to obtain ground displacement in physical units, (iii) calculation of theoretical P- and S-wave arrival times with the Tau-P kinematic algorithm based on the IASP91 reference Earth velocity model, and (iv) construction of an interactive 3D particle motion visualization in which segments associated with the P-wave, S-wave and background are color-coded. The pipeline is demonstrated on three seismic events recorded in February 2023 by the broadband station KO.BNN, including the destructive Mw 7.8 Kahramanmaraş earthquake. The workflow yields the absolute three-dimensional displacement vector and produces interactive visualizations that are intended for use by structural engineers as a complement to traditional one-dimensional acceleration records.

Engineering Proceedings doi: 10.3390/engproc2026154016

Authors: Krasimir Ivanov Georgi Velev Ivaylo Lazarov

Lightning strikes with large current amplitudes and a steep current wave front in cases of multiple lightning strikes can cause significant overvoltages. The number of overvoltage impulses depends significantly on the lightning parameters, the overhead line parameters and the tower grounding impedance. While the probability for back flashovers from towers to phase conductors (power line trips) depends on lightning current amplitude, impulse steepness and tower grounding resistance, the magnitudes of overvoltages reaching the nearby substation, Ground Potential Rise (GPR) and step and touch voltage distribution profiles depend exclusively on substation grounding impedance. In order to study and take into account such a large number of parameters influencing the probability for overvoltages to occur, several models in the ATP simulation program (v. 7.6) have been implemented. This allows us to study the influence of tower and substation grounding impedances on the magnitude and the form of atmospheric overvoltages and their impact on the safety of personnel in the substation area in cases of direct lightning strikes on nearby power line towers or lightning protection cables. A differentiation has been made between grounding resistance and grounding impulse impedance as a prerequisite for more accurate modeling and more precise calculations.

Engineering Proceedings doi: 10.3390/engproc2026136012

Authors: Yen-Hong A. Chen Yu-Chu M. Li Kai-Jan Lin

We examined the performance of a novel early streamer emission air terminal (ESEAT), which is used as a lightning protection device. ESEAT was tested under a laboratory-simulated lightning strike scenario and compared with a classical air terminal (CAT). The results demonstrate that ESEAT is more effective at capturing artificial lightning in the laboratory setting than CAT. Data on failed lightning captures indicate that the failure rate of the ESEAT is approximately one-tenth that of CAT. These findings validate the effectiveness of the new ESEAT in a controlled laboratory environment.

Engineering Proceedings doi: 10.3390/engproc2026131051

Authors: Umberto Galietti Gabriele Arcidiacono Luigi Bruno Davide Castagnetti Cristiana Delprete Mario Guagliano Vigilio Fontanari Aurelio Somà Nicola Bonora

The AIAS (Italian Scientific Society of Mechanical Engineering Design) was founded in 1971, originally as an association focused on stress analysis, bringing together researchers from academia, research centers and industry to discuss, share and develop scientific knowledge on the subject [...]

Engineering Proceedings doi: 10.3390/engproc2026154013

Authors: Ivan Ivanov Filip Tsvetanov

Secure delivery of packages by drones requires reliable management of cryptographic keys, despite limited on-board resources, multiple users, and the risk of interception or manipulation. This paper proposes a hierarchical model of a Key Distribution Center that manages the generation, distribution, storage, control, and destruction of cryptographic keys. The model uses public-key mechanisms for secure transmission of session keys and lightweight symmetric encryption for communication between the drone and the recipient. A session key lifecycle is defined, including verification, encrypted storage, validity control, and secure deletion. The operational workflow for the secure delivery of packages is also described. The proposed approach improves confidentiality, scalability, and access control.

Engineering Proceedings doi: 10.3390/engproc2026147018

Authors: Kaouther Kerboua Nour El Imene Brahmi Abderrahmane Selmani Nour Hane Merabet

The design of efficient small-scale hydrogen energy storage systems requires balancing hydrogen production rate, electrical efficiency, and system simplicity. This study experimentally investigates the energetic compromise imposed by separator material and electrolyzer architecture through a comparative analysis of finite-gap alkaline, finite-gap acidic, and zero-gap proton exchange membrane (PEM) electrolyzers. Zirfon® Pearl 500 (Agfa, Mortsel, Belgium) diaphragms were employed in alkaline electrolysis using 25 wt.% KOH, whereas Nafion™ 117 (Chemours, Wilmington, DE, USA) membranes were used in both finite-gap acidic electrolysis (2.55 M H2SO4) and a commercial five-cell zero-gap PEM electrolyzer supplied with deionized water. Electrochemical performance was evaluated in terms of polarization behavior, apparent resistance, hydrogen production rate, Faradaic efficiency, and energy conversion efficiency. The zero-gap PEM architecture exhibited the best electrochemical performance, with an apparent resistance of only 0.138 Ω per cell, corresponding to reductions of approximately 43-, 51-, and 64-fold compared with the finite-gap PEM, stainless steel/Zirfon alkaline, and nickel/Zirfon alkaline configurations, respectively. The zero-gap electrolyzer delivered currents from 1.53 to 10.0 A while operating below 2.8 V, demonstrating the benefit of minimizing the ionic transport path. In contrast, the finite-gap acidic configuration achieved higher hydrogen production rates than the alkaline system owing to the superior proton conductivity of Nafion™ 117, whereas the alkaline Ni/Zirfon configuration reached the highest Faradaic efficiency (≈98%) and energy conversion efficiency (≈36%) because of improved gas separation and reduced hydrogen crossover. Electrochemical impedance spectroscopy further revealed that the normalized ohmic resistance of the zero-gap PEM cell was only 0.029 Ω, with charge-transfer processes accounting for approximately 96.2% of the total impedance. These results demonstrate that separator properties and cell architecture govern the trade-off between reaction kinetics and energy efficiency, providing practical guidelines for selecting electrolyzer configurations dedicated to decentralized and small-scale hydrogen energy storage.

Engineering Proceedings doi: 10.3390/engproc2026150136

Authors: Tasho Tashev Radostina Tasheva

The Generalized Nets (GN) apparatus is applied here to describe the Longest_Port_First (LPF)-algorithm for computing a conflict-free schedule for a crossbar switch. The results for throughput (TH) on a switch node with the LPF-algorithm using computer simulations with patterns of uniform load traffic are presented. Using the numerical procedure it is shown that the upper bound of the TH of the LPF-algorithm tends to 100%, with the accuracy increasing three-fold as the buffer value increases approximately twice. The necessary computations were executed on the supercomputer AVITOHOL, which is located in IICT-BAS, Sofia, Bulgaria.

Engineering Proceedings doi: 10.3390/engproc2026150135

Authors: Petr Salač Miroslav Brzezina Jana Příhonská

The contribution deals with the numerical results for the identification problem for heat-transfer coefficient between the outward surface of the mould and the environment, and for the flux density of the modified mass of the glass coefficients between the glass and the mould, and the glass and the plunger. The continuous problem was formulated in detail at AMEE’49. The numerical results were received by the software FreeFem++ version 4.2.1 for the sample of the real vase from the experiment carried out at the Technical University of Liberec in 1999, which was used as a data source for the identification problem. Identification is realized with respect to the measured temperature values at 10 points of the mould and the plunger. The distribution of the searched coefficients along the respective boundaries in the initial, the 10th, the 20th, the 60th and the 100th iterations together with the distribution of temperature throughout the system in the 100th iteration are presented.

Engineering Proceedings doi: 10.3390/engproc2026154012

Authors: Theodora-Maria Maroulaki Despoina Grigoriou Yannis Orphanos Nektarios A. Papadogiannis Vasilis Dimitriou Evaggelos Kaselouris

This study investigates the vibro-acoustic behavior of a thin square aluminum plate with a central clamped hole, inspired by splash cymbal configurations. The structural dynamics are analyzed using finite element method (FEM) modal and frequency response function (FRF) simulations, while experimental measurements validate the modal characteristics. A semi-analytical Rayleigh–Ritz model is also employed to estimate the natural frequencies and provide an additional reference for comparison. Excellent agreement is observed between the predicted and measured resonance frequencies and overall dynamic response. Acoustic radiation is evaluated through coupled structural–acoustic analyses using a Rayleigh integral formulation and an indirect variational boundary element method (BEM). The sound pressure radiated to a field point above the plate is compared with the FEM-derived FRF results. The results demonstrate a correlation between structural vibration and acoustic response, with variations in radiation efficiency influenced by the central clamp and higher-frequency modal behavior. The Rayleigh approach shows good agreement but exhibits numerical noise and overprediction of modal contributions. In contrast, the BEM provides smoother responses and more physically consistent results. These findings are relevant for noise control, vibration reduction, and sound synthesis applications in mechanical systems.

Engineering Proceedings doi: 10.3390/engproc2026154006

Authors: Raid Anis Kerkatou Hacene Belhadef Aicha Eutamene Svetlana Stefanova

Quantum Machine Learning (QML) has recently emerged as a promising approach for cybersecurity applications due to its ability to encode data into high-dimensional Hilbert spaces. However, most QML-based intrusion detection systems rely on a single quantum embedding strategy, limiting representation diversity. This paper proposes a Multi-Embedding Quantum Ensemble (ME-QE) framework that combines Angle Embedding and IQP Embedding using concatenation and weighted fusion strategies. The proposed approach is evaluated on the NSL-KDD dataset for binary intrusion detection using stratified 5-fold cross-validation. Experimental results show that the best fusion configuration achieves 94.75% accuracy, while the classical Random Forest baseline reaches 97.50%. The analysis further demonstrates that Angle Embedding contributes more effectively to classification performance than IQP Embedding in this context. In addition, the study highlights important scalability limitations of quantum kernel methods due to the computational cost of pairwise kernel evaluation. The proposed framework provides insights into hybrid quantum–classical intrusion detection and establishes a foundation for future scalable quantum cybersecurity architectures.

Engineering Proceedings doi: 10.3390/engproc2026131050

Authors: Umberto Galietti Gabriele Arcidiacono Luigi Bruno Davide Castagnetti Cristiana Delprete Mario Guagliano Vigilio Fontanari Aurelio Somà Nicola Bonora

In submitting conference proceedings to Engineering Proceedings, the Volume Editors of the proceedings would like to certify to the publisher that all papers published in this volume have been subjected to peer review by the designated expert referees and were administered by the Volume Editors strictly following the policies announced on the conference website [...]

Engineering Proceedings doi: 10.3390/engproc2026154011

Authors: Ana-Maria Grigoras Oanca Mihaela Andrei Daniela Tarniceriu

This paper presents a polar-coded anti-jamming communication system designed to improve reliability and security in channels affected by Gaussian jamming and impulsive α-stable noise. The proposed configuration combines polar decoding with an Anti-Jamming (AJ) mechanism based on Processing Gain (PG). Several configurations, including standalone polar decoding, anti-jamming only, and their combination, are evaluated using Bit Error Rate (BER) versus Signal-to-Jamming Ratio (SJR). Simulation results show that the combined Successive Cancellation List (SCL) decoder with anti-jamming achieves the best performance, offering about a 3 dB gain over standalone SCL decoding. The study also demonstrates improved physical-layer security through enhanced secrecy capacity.

Engineering Proceedings doi: 10.3390/engproc2026154008

Authors: Dimitrina Koeva Dimitar Slavov

The transition toward decarbonized power systems has led to the large-scale integration of inverter-connected renewable energy sources (ICRES) and the decommissioning of traditional synchronous generators. This shift significantly reduces system inertia, increasing the rate of change of frequency (RoCoF) and vulnerability during power imbalances. This paper investigates a hybrid system combining a thermal power plant (TPP) with a battery energy storage system (BESS) in grid-forming mode to enhance stability. Using MATLAB/Simulink and technical parameters from an existing turbogenerator, three scenarios with 0%, 30% and 50% renewable penetration were simulated. Results show that as the inertia constant Hsys decreases from 2.32 s to a critical 1.43 s, the frequency during a 20% deficit falls below the 49 Hz under-frequency load shedding (UFLS) threshold. Implementing virtual inertia control allows the BESS to successfully limit RoCoF and maintain frequency above safety limits. These findings justify BESS grid-forming technology as a vital solution for grid stability under low-inertia conditions.

Engineering Proceedings doi: 10.3390/engproc2026154007

Authors: Viktoria Ivanova Delyan Genkov

Due to the large amount of network traffic, manual network security management has become increasingly difficult. This paper proposes an open-source network anomaly detection system prototype that operates with the Security Onion 2.4 platform. The system relies on a custom Python engine that uses the machine learning (ML) algorithm Isolation Forest to detect anomalies in multiple Zeek datasets. The prototype was developed as a virtual machine (VM), which is hosted on a server running the software for virtualization VMware ESXi 6.0.0. For the experimental tests, live network telemetry from a university network was used. The results show that the system achieves a constant anomaly detection rate of 5.4% after a volumetric threshold of 5000 logs is reached within operating periods ranging from fifteen to thirty minutes. During testing, it was discovered that the detection logic has a minimal resource impact (less than 1 GB) on the running system beyond the defined baseline of average Random Access Memory (RAM) usage. This proposed solution is an open-source and zero-cost alternative to other paid network security solutions, demonstrating that abnormal behavior detection in network traffic can be effectively integrated on existing computer configurations without the need for expensive licenses.

Engineering Proceedings doi: 10.3390/engproc2026154010

Authors: Hristina Stoycheva Stanimir Sadinov Georgi Mihalev Nikolay Manchev Boyan Karapenev

River floods are considered a serious threat to human life and infrastructure; therefore, effective monitoring and early warning solutions are required. In this paper, an intelligent system based on a distributed network of ESP32 sensor nodes is proposed for real-time monitoring of river water levels. The sensor nodes are deployed at multiple locations along the river, where hydrological data are continuously collected and transmitted to a central unit. The acquired time-series data are analyzed by means of a nonlinear autoregressive model with exogenous inputs (NARX) and artificial intelligence techniques, so that complex hydrological dynamics can be captured and future water-level variations can be predicted. The proposed system enables the early detection of potential flood events and supports timely decision-making. The solution is implemented as a low-cost Wireless Sensor Network (WSN), which makes it suitable for deployment in remote and resource-constrained areas and contributes to improved flood risk management. The architectures of the applied systems are presented, and an approach for implementing a NARX-based model for river water-level prediction is proposed.

Engineering Proceedings doi: 10.3390/engproc2026154009

Authors: Ismail Mehmedov Darina Dobreva Zoya Tsoneva Momchil Tachev

The study focuses on the influence of airflow on the separation of the three primary materials under investigation: sand, sawdust, and ash. These materials were selected to facilitate a comparative analysis between two distinct airflows. The primary objective of the research is to increase the separation yield while maintaining the original design of the 2A mechanical cyclone model. The model utilized in this study was designed using SolidWorks 2025 and fabricated via a Raise3D Pro2 3D printer (Raise3D Technologies, Inc. 2019, Nantong, China, Е2). The purpose of the experiment is to determine how variations in flow affect the separation of fine particulate matter under 3 μm.

Engineering Proceedings doi: 10.3390/engproc2026148048

Authors: Vasugi Ramdass Dhilip Kumar Venkatesan Oana Geman Roxana Toderean

Counting bacterial colonies by hand is one of the most common tasks in microbiology, but it is slow and often yields different results depending on who does the counting. This paper presents an automated system for detecting and classifying bacterial colonies from Petri plate images. We tested four models: Support Vector Machine (SVM), Artificial Neural Network (ANN), Convolutional Neural Network (CNN), and a hybrid CNN+Vision Transformer (CNN+ViT). The system uses OpenCV for image preprocessing and extracts features such as area, perimeter, and circularity. Colonies are then classified by size and health condition. Confusion matrix results show that SVM and ANN achieved the highest overall accuracy (95.6%), while CNN+ViT eliminated false positives entirely. A Streamlit-based web interface allows real-time colony analysis directly in laboratory environments.

Engineering Proceedings doi: 10.3390/engproc2026148047

Authors: Olga Adriana Caliman-Sturdza Roxana Filip

The problem of antimicrobial resistance (AMR) is a significant worldwide health risk, which is why experts are interested in using artificial intelligence (AI) or machine learning (ML) to employ antibiotics more wisely. Diagnostic, empiric antibiotic choices, dosing, and surveillance in stewardship programs are AI-driven promises to make the process straightforward. This narrative review is a synthesis of the recent evidence (within the last 10 years) on the use of AI in antibiotic stewardship. It analyzed the literature on AI-based diagnostic systems, prescribing decision-support systems, resistance prediction models, real-time surveillance systems, and dose algorithms. The use of AI tools by clinicians and stewardship programs must be approached with discretion and human supervision and assessment.

Engineering Proceedings doi: 10.3390/engproc2026150134

Authors: Petr Salač Miroslav Brzezina Jana Příhonská

The article deals with finding a steady heat source that can replace a periodical non-steady heat source representing the repeated cooling of pressed glass products in a system consisting of a mould, glass piece, plunger and plunger cavity during the glass forming process. The stationary heat source is designed to supply the same amount of energy during the cooling period as would be extracted from the glass piece if its surface temperature was reduced linearly to the desired value.

Engineering Proceedings doi: 10.3390/engproc2026154004

Authors: Stanimir Yordanov Hristina Stoycheva Georgi Mihalev Stefan Ivanov

This paper presents a secure data transmission framework for intelligent IoT sensor networks, specifically designed for an electronic nose system used in food quality analysis. The proposed architecture integrates a heterogeneous sensor array with an ESP32-based processing unit and GSM/GPRS communication module. To ensure data confidentiality over public mobile networks, a hybrid security scheme combining cryptographic encryption (ChaCha20) and chaotic modulation (Brusselator + DCSK) is introduced. The data packet is first encrypted using the ChaCha20 stream cipher, then converted into a bipolar bit stream. The chaotic system used to generate a chaotic signal is a nonlinear Brusselator model. The system was implemented on a LILYGO TTGO T-Call V1.4 (ESP32 + SIM800L) and tested for discrimination of olive oil and sunflower oil mixtures. Experimental results demonstrate 98.7% classification accuracy using a neural network, 96% first-try transmission success rate over GPRS with 2.3 s average packet transmission time, and 99% overall reliability under RSSI above −85 dBm.

Engineering Proceedings doi: 10.3390/engproc2026150133

Authors: Georgi Todorov Konstantin Kamberov Konstantin Dimitrov

This study explores a simple free-falling problem, focusing on the determination of the coefficient of restitution for a steel ball through virtual and physical experiment evaluation. Different effects influencing the dynamic behavior and accuracy of the experiment are explored through variation in the physical objects’ diameters. Physical testing results were obtained through high-speed capturing and visual-tracking software in a series of physical experiments. This allowed us to correctly determine the main dynamic parameters of the system and to compare them to the results obtained by numerical simulation of the virtual model. Detected differences and the level of correspondence of the virtual model with the physical one are reviewed and discussed. Further recommendations for virtual prototyping of drop tests are presented.

Engineering Proceedings doi: 10.3390/engproc2026145015

Authors: Alperen Acer Mumin Tolga Emirler

This study presents a computational framework for determining the complete set of stabilizing PID controller parameters for high-order systems using the singular frequency decoupling method. By fixing the proportional gain Kp, the stability boundaries in the (Ki, Kd) plane are derived analytically, enabling automatic identification of stabilizing polygons without grid-based searches. The methodology is extended to uncertain plants through a vertex plant approach: stabilizing Kp intervals are computed for each vertex and intersected to yield a common solution, and the corresponding (Ki, Kd) polygons are intersected to guarantee robust stability. Results are visualized as 2D robust polygons and 3D stabilizing solids, providing designers with an efficient and reliable tool for robust PID synthesis.

Engineering Proceedings doi: 10.3390/engproc2026154001

Authors: Ivelina Balabanova Georgi Georgiev

This paper proposes a methodology for diagnosing the network environment in terms of disturbances and performance metrics in communication infrastructures. An approach for identifying GWN and PRN based on Artificial Intelligence is integrated. Naïve Bayes classification in Gaussian and Kernel probability density functions of datasets are created with confirmed verification using Resubstitution and Cross-Validation techniques. The high efficiency of the GRNNs created for GWN and PRN recognition has been established. An approach for finding an optimum in non-linear minimization with inequality constraints using Interior-point, SQP, Active-set and Genetic Algorithm techniques has been synthesized regarding an analytical model for SRT performance index prediction.

Engineering Proceedings doi: 10.3390/engproc2026154005

Authors: Diyan Dinev Gergana Spasova

Secure QR-based data transfer requires a careful balance between confidentiality, payload size, decoding reliability, and resistance to visual degradation. This paper presents a reproducible comparative framework for studying secure QR code transmission under controlled distortions. The framework combines protected payload generation, batch experimentation, and comparative visual analysis to examine how payload mode, error-correction level, decoder backend, and image degradation influence transmission success, overhead, QR complexity, and processing time. The results highlight key trade-offs among robustness, efficiency, and symbol density, and provide practical guidance for selecting suitable secure QR transmission settings in distortion-prone environments. Unlike existing evaluation approaches that address security and robustness factors in isolation, the proposed framework offers the first unified experimental environment for their joint reproducible assessment, making it directly applicable to systematic research in secure QR transmission design.

Engineering Proceedings doi: 10.3390/engproc2026148046

Authors: Vicoveanu Dragoș Scheuleac Adelina Vizitiu Lakhdari Elena

This paper proposes a real-time physiological monitoring and biofeedback model based on the console of an indoor cycling bike, applied within high-school physical education. The system uses heart rate (HR) as a control signal for exercise intensity within a closed-loop human–machine system, complemented by the Borg Scale of Perceived Exertion (RPE 6–20) as a subjective validation of the objective feedback loop. The 12-week intervention, conducted with 48 adolescents aged 15–17 years, was evaluated using a battery of six standardized psychomotor tests from EUROFIT and cardiovascular indicators, including 1-min heart rate recovery (HRR). The results show significant improvements in balance, coordination, agility, and autonomic recovery in the experimental group, confirming the effectiveness of the integrated biofeedback system as an accessible biomedical monitoring platform in the school setting. These findings suggest that heart-rate-based biofeedback, delivered through the bicycle console, may represent an accessible and effective strategy for regulating exercise intensity and supporting psychomotor and cardiovascular adaptation in the school environment.

Engineering Proceedings doi: 10.3390/engproc2026154003

Authors: Nikolay Komitov Yosif Munev Margarita Terziyska Mariyana Sestrimska Veselin Mengov Angel Nikolov

The present work is aimed at developing and researching a robotic arm with five degrees of freedom, manufactured using 3D-printing technology and controlled by an ESP32 microcontroller. This technology is increasingly used in robotics, especially in the educational process, due to the possibilities for rapid prototyping, modification and restoration of individual components. In the development process, the mechanical, hardware and software parts of the system were implemented, and a basic kinematic analysis of the manipulator was performed. A control program was created, allowing the performance of “pick and place” tasks, as well as visualization and manual control through a developed application. The results obtained show that the developed system provides sufficient functionality and flexibility for use in robotics training, while at the same time allowing expansion and upgrading with additional functionalities. The main contribution of the work lies in the implementation of an accessible and adaptable robotic platform, suitable for educational and experimental purposes.

Engineering Proceedings doi: 10.3390/engproc2026154002

Authors: Aydan Haka

This paper investigates the behavior of the Received Signal Strength Indicator (RSSI) in Z-Wave networks through a comparison between simulation-generated and experimentally measured data. A prototype star-topology Z-Wave network was implemented and RSSI values were measured at distances from 1 m to 5 m with a gradually increasing number of active end devices in a laboratory environment. In parallel, a software simulation environment was used to reproduce the same topology and generate RSSI values under different propagation assumptions. In order to compare the results obtained from real and simulated environments, the average deviation between the range of measured values for RSSI was calculated. The experimental results show that the RSSI values from the simulation product follow the trend of deteriorating values with increasing distance between the central and end devices. The calculated average deviation between the range of RSSI values in real and simulated environments shows that the simulated results are closest to the real ones at an exponential coefficient n ≈ 2, and the calculated deviation is from 2 dBm to 2.3 dBm. The results obtained support the evaluation of the simulation model and show its potential for studying signal behavior and aiding the design of reliable Z-Wave-based Internet of Things environments.

Engineering Proceedings doi: 10.3390/engproc2026137030

Authors: Seila Permoni Suci Muhammad Noor Asnan Fitriyati Agustina

The increasing polypropylene (PP) plastic cup waste requires sustainable utilization. This study examines the effect of adding 45 mm PP waste fibers on concrete flexural strength and its compliance with the 2018 Bina Marga Specification. Using an experimental method, beam specimens (15 × 15 × 60 cm) and cylinders (15 × 30 cm) with fc’ 25 MPa were tested. Variations included normal concrete, concrete with 1% PP fibers, and nylon fibers. At 28 days, flexural strengths were 4.27 MPa (normal), 3.56 MPa (PP), and 3.89 MPa (nylon), all below the 4.7 MPa requirement. However, fiber addition enhanced beam ductility, supporting PP waste as a potential eco-friendly material for rigid pavement.

Engineering Proceedings doi: 10.3390/engproc2026151038

Authors: Sigmund Arntsønn Tronvoll

The signatory of this statement, Sigmund Arntsønn Tronvoll, served as the volume editor of these proceedings and as Academic Editor, with David Morin serving as Academic Editor on selected papers to manage cases with conflicts of interest [...]

Engineering Proceedings doi: 10.3390/engproc2026151037

Authors: Sigmund Arntsønn Tronvoll

The 16th International Aluminium Conference (INALCO 2026) was held in Trondheim, Norway, from 10 to 12 June 2026 [...]

Engineering Proceedings doi: 10.3390/engproc2023059249

Authors: Pranavi Reddy Andrew J

The journal retracts the article titled “Diagnosis of Autism in Children Using Deep Learning Techniques by Analyzing Facial Features” [...]

Engineering Proceedings doi: 10.3390/engproc2026148045

Authors: Simona Miclaus Maxime Elisabeth Ladislau Matekovits

The advancement of 5G/6G infrastructure requires specifications that are challenging from an engineering point of view. Some of the advanced field-manipulation techniques rely on High Impedance Surfaces (HISs), including modulated appearances. However, their intense near-field energy localization for some frequencies poses challenges for bioelectromagnetic safety. Measurements of such hot spots require special attention; traditional metallic probes are often invasive and locally distort fields. This paper proposes and validates a non-invasive methodology using Transient Infrared (IR) Thermography for high-resolution mapping of a substantial area (in terms of wavelength). By capturing the initial thermal gradient (dT/dt) on a HIS built on an Arlon AD430 substrate, we estimate the local specific absorption rate (SAR) of energy deposition before heat diffusion occurs. Cross-validation with electric (E)-field measurements at two different distances from the HIS in the sub-6 GHz 5G frequency spectrum, namely at 2 mm and at 22 mm, reveals a remarkable spatial correlation between thermal hot-spots and peak intensities, which decrease by ~83% across these distances. This study demonstrates that transient IR thermography is a rapid, non-perturbing tool for auditing electromagnetic safety compliance, providing a robust framework for determining SAR in human tissues exposed to radiation from future 5G devices.

Engineering Proceedings doi: 10.3390/engproc2026146020

Authors: Hao Zhang Sanxing Zheng Lei Chen

This paper analyzes the influence of different parameters on the seismic performance of reinforced concrete shear walls under granular lateral pressure through numerical simulation. The study focuses on the effects of these parameters on the yield load, peak load, and initial stiffness of the specimens, accompanied by parameter sensitivity analyses. The results indicate that as the grain loading height increases, the ultimate bearing capacity of the shear wall continuously decreases, while increases in concrete strength, axial compression ratio, and wall longitudinal reinforcement ratio lead to continuous improvement in the ultimate bearing capacity. Compared with concrete strength and wall longitudinal reinforcement ratio, increasing the axial compression ratio enhances the bearing capacity more significantly. Moreover, increasing the concrete strength and axial compression ratio effectively improves the initial stiffness of the specimen, whereas the influence of grain loading height and the wall longitudinal reinforcement ratio on the initial stiffness is limited. Within the parameter range considered, the standardized coefficients of concrete strength, axial compression ratio, grain loading height, and wall longitudinal reinforcement ratio on the peak load are 0.463, 0.678, −0.308, and 0.243, respectively. This further confirms that increasing the axial compression ratio can effectively improve the bearing capacity of the specimens.

Engineering Proceedings doi: 10.3390/engproc2026151034

Authors: Mohammed M. M. Sohail Sigmund Arntsønn Tronvoll

This study investigates the effect of sinusoidal arc oscillation frequency on bead geometry accuracy in Cold Metal Transfer-based Wire Arc Additive Manufacturing (CMT-WAAM) of the Al-4043 alloy. Single-pass depositions were performed at frequencies of 0–4 Hz (1.0 mm amplitude) and 0–5 Hz (1.5 mm amplitude), followed by multi-pass, multi-layer builds using optimal parameters. Cross-sectional analysis revealed that a 3–4 Hz frequency window minimizes wetting angle asymmetry and maximizes bead width-to-height ratio. At 4 Hz with 1.5 mm amplitude, the arc oscillation yielded a symmetric wetting angle deviation of only 1.22°. Multi-layer builds indicated that oscillation improved the effective cross-sectional area ratio from 75% (non-oscillating) to 82%, suggesting superior geometric efficiency and reduced material waste in post-machining.

Engineering Proceedings doi: 10.3390/engproc2026149010

Authors: Veronica Casadei Rebecca Montanari Giuseppe Di Modica

This paper presents the SCORPiò-NIDI project as a case study for the implementation of collaborative digital workflows aimed at enhancing the value and accessibility of archaeological heritage through 3D modelling. The study outlines a replicable pipeline that integrates rigorous CAD-based scientific modelling, functional animation, high-quality rendering, and web-based dissemination, aligned with FAIR principles and international standards for cultural heritage visualisation. The 3D models of the scorpion and ballista are conceived not merely as visual assets but as epistemic and narrative instruments, enabling scientific analysis, effective communication, and immersive, interactive engagement through collaborative platforms such as ATON and WordPress.

Engineering Proceedings doi: 10.3390/engproc2026147017

Authors: Nour El Imene Brahmi Kaouther Kerboua

Efficient small-scale hydrogen production via proton exchange membrane (PEM) electrolysis is a key pathway for advancing green hydrogen technologies. This study experimentally investigates a five-cell zero-gap PEM electrolyzer stack to evaluate energy losses, thermal behavior, and hydrogen generation efficiency. Faradaic efficiency increased with current density, reaching 98.03% at 0.232 A·cm−2, while infrared (IR) thermography reveals non-uniform temperature distributions across the electrolyzer stack, with inter-cell and in-plane temperature gradients exceeding 9 °C. Although increasing current density led to higher ohmic and electrochemical losses, energy efficiency increased from 39.4% at 0.106 A·cm−2 to 56.28% at 0.232 A· cm−2, as the reduced relative contribution of activation overpotential predominated over the increase in resistive losses within the investigated range. The results demonstrate the strong coupling between electrochemical resistance growth, thermal gradients, and reduced hydrogen production efficiency. Overall, these findings underscore the importance of optimized thermal management and operating strategies for improving the performance and durability of small-scale PEM electrolyzers in green hydrogen applications.

Engineering Proceedings doi: 10.3390/engproc2026147016

Authors: Helal Uddin Qodirova Lola Zafar Qazi Md. Rasel Ahmed

Hybrid solar–thermal energy harvesting systems are an important advancement in renewable energy technology, enabling simultaneous production of electrical power and useful thermal energy within a single compact platform. However, their performance is often limited by poor heat transfer and inefficient mass transport of working fluids, leading to photovoltaic thermal degradation and significant exergy losses. This study aims to optimize heat and mass transport processes in a hybrid solar–thermal mechanical system to enhance energy recovery and ensure long-term operational reliability. A three-dimensional numerical model based on the finite volume method (FVM) was developed using the governing equations of continuity, momentum, and energy conservation. A Multi-Objective Genetic Algorithm (MOGA) was employed to determine optimal microchannel geometries by analyzing variable cross-section effects on flow behavior and thermal boundary layer disruption. At the Reynolds number of 2000, the optimized configuration increases the average Nusselt number by 43.5% compared to a smooth channel. Consequently, the photovoltaic operating temperature decreases by 12.6 °C, improving electrical efficiency by 9.3%. The system achieves a maximum thermal efficiency and net energy gain of 76.8%, while maintaining an acceptable 16.3% increase in pumping power. The results confirm that optimizing mass transport is essential for effective thermal regulation and improved energy conversion performance, providing a strong foundation for high-efficiency solar collector design.

Engineering Proceedings doi: 10.3390/engproc2026144017

Authors: Charaf Laghlimi Younes Ziat Zakaryaa Zarhri Noureddine Lakouari Hamza Belkhanchi Abdelaziz Moutcine

The STR2E conference (International Conference on Sciences and Techniques for Renewable Energy and the Environment), organized by the research team focused on chemistry, computer science and artificial intelligence (ERCI2A) at the Faculty of Sciences and Techniques-Al Hoceima, the Moroccan Association of Science and Technology for Sustainable Development (MASTSD) and Abdelmalek Essaadi University, Tétouan, Morocco, aims to promote scientific exchange and interdisciplinary collaboration in all fields of engineering sciences and techniques related to renewable energy and the environment [...]

Engineering Proceedings doi: 10.3390/engproc2026144019

Authors: Muhammad Arif Budiyanto Achmad Fatchur Utama

Indonesia, as one of the world’s largest maritime nations, has substantial fishery potential in the Java Sea, yet fleet modernization remains limited. This study proposes a novel integrated framework that combines computer-aided vessel design with techno-economic feasibility analysis for a 30-GT steel fishing vessel as a replacement for traditional wooden fleets. The novelty lies in the simultaneous evaluation of technical design parameters and investment performance within a single framework tailored to small-scale fisheries. The vessel, with principal dimensions of 16 m (L), 4 m (B), 1.85 m (D), and 1.2 m (T), demonstrates adequate stability and operational capability. Financial results show positive NPV and an IRR above the benchmark, confirming technical and economic feasibility. The results confirm that 30-GT steel vessels provide a technically and economically feasible solution to support sustainable fishery development.

Engineering Proceedings doi: 10.3390/engproc2026146019

Authors: Ye Haoyu Luo Xin Luo

The Longmenshan Fault Zone, as the steep boundary on the eastern edge of the Qinghai–Xizang Plateau, is the seismogenic structure that includes strong earthquakes such as the 7.9 magnitude Wenchuan earthquake in 2008 and the 6.6 magnitude Lushan earthquake in 2013. Based on the U.S. Geological Survey (M ≥ 2.5) earthquake catalogue from 2000 to 2025, this study systematically analyzed the spatio-temporal evolution of seismic activities in this area. We determined the completeness of the seismic magnitude by time periods and drew a spatial B-value distribution map using the maximum likelihood estimation method to reveal its variation characteristics. The analysis is divided into three intervals: 2000–2007 (pre-Wenchuan), 2008–2012 (co- and post-Wenchuan), and 2013–2025 (long-term postseismic stage; the 2008–2025 interval includes an observational and forecast assessment window). Low b values persist in the central and southern parts of the LMSF, indicating that the degree of stress concentration in these two regions is relatively high. After 2008, the b value of the Wenchuan Fault Zone rose briefly. After 2013, the b value gradually declined. This fluctuation confirmed the re-accumulation process of regional stress. The analysis results of the Z-value rate change show that there is obvious stillness in the central fault zone (Z > 2), while there is slight activation in some southern areas of the LMSF (Z ≈ −0.5 to 0). These patterns are roughly consistent with the spatial B-value structure, and our research results also provide diagnostic conclusions for interpreting the long-term seismic activity evolution and stress heterogeneity of the LMSF.

Engineering Proceedings doi: 10.3390/engproc2026144018

Authors: Muhammad Arif Budiyanto Xaviera Fidela Wardi Renaldi

Indonesia has significant fisheries potential; however, limited cold chain infrastructure at small-scale fishing ports contributes to post-harvest losses and quality degradation of fishery products. This study presents the design and techno-economic assessment of a modular portable cold storage unit for tuna fisheries integrated with renewable energy systems. The system (7 × 3 × 5 m) uses polyurethane sandwich panels and requires a maximum cooling load of 6.14 kW with peak power consumption of 7.93 kW. The estimated capital cost is approximately USD 34,100, while the operational cost is about USD 198 per cycle. A comparative analysis using the Levelized Cost of Energy (LCOE) method indicates that diesel generators provide the lowest cost at approximately USD 0.56/kWh, whereas standalone photovoltaic (PV) systems exhibit the highest cost at around USD 0.89/kWh. However, hybrid PV systems offer the best balance between cost efficiency and environmental performance by reducing carbon emissions. The results demonstrate that integrating hybrid renewable energy into modular cold storage enhances cold chain reliability, reduces fish losses, and supports sustainable coastal development. This approach contributes to low-carbon fisheries infrastructure and aligns with global sustainability and renewable energy transition goals.

Engineering Proceedings doi: 10.3390/engproc2026146018

Authors: Binghao Zhang Jing Luo

This study investigates fire behavior and personnel evacuation safety in a nuclear chemical workshop based on the Fire Dynamics Simulator (FDS) and real fire experiment. The typical fire scenario caused by cable faults at middle distribution box locations was analyzed to evaluate the effects of ignition position on fire growth and smoke propagation. The FDS results show that the upper-layer temperature reaching approximately 180 °C at 173 s, while visibility at 2 m height decreases to 10 m at 176 s and CO2 concentration rises to 1%. The CO concentration at 2 m reaches 500 ppm at around 290 s. The calculated Available Safe Egress Time (ASET) of 145 s exceeds the Required Safe Egress Time (RSET) of 117 s, indicating acceptable evacuation safety under this scenario. A full-scale real fire experiment was further conducted under a 5 MW fire. Temperature measurements showed that the thermocouple tree nearest the fire source reached a maximum temperature of approximately 620 °C, posing a severe threat to unprotected steel roof structures. The temperatures below 2 m remained relatively lower, decreasing from about 250 °C to 150 °C. These results demonstrate that the concentrated fire scenario primarily endangers roof load-bearing structures, whereas the thermal conditions in the evacuation zone are comparatively less severe.

Engineering Proceedings doi: 10.3390/engproc2026150132

Authors: Dimitar Petrov Durhan Saliev

One of the primary responsibilities of local authorities is to develop infrastructure that meets the needs of its users. Roundabouts are widely used worldwide; however, clear criteria for selecting roundabouts instead of conventional four-way intersections are often lacking. In different countries, guidelines regarding their applicability exist, but despite this, numerous examples of problematic locations with traffic congestion caused by roundabouts can still be observed. In this study, a comparative analysis is conducted using the specialized traffic simulation software PTV Vissim. The analysis examines a real roundabout that has been implemented in place of a previously existing three-way intersection, comparing the capacity of the two configurations. Additionally, an analysis of the measures introduced after the construction of the roundabout to improve its capacity is also carried out.

Engineering Proceedings doi: 10.3390/engproc2026147015

Authors: Zafar Turakulov Jasmina Elmurodova Jaloliddin Eshbobaev Noilakhon Yakubova Elyor Samadov Golib Nazarov Khasan Niyozov Mirolim Aripov

Early-stage estimation of total biogas yield is useful for preliminary screening of anaerobic digestion substrates when detailed kinetic parameters, long-term reactor data and substrate-specific biochemical methane potential tests are not yet available. This study develops a compact Gradient Boosting Regression model for estimating total biogas yield from basic substrate and operating descriptors commonly reported in anaerobic digestion studies. A literature-informed reconstructed benchmark dataset containing 120 records from twelve organic substrate groups was used. The response variable was total biogas yield, expressed as mL g−1 volatile solids (VS) added; methane yield and methane content were not used as interchangeable target variables. Seven input variables were considered: volatile solids content, total solids content, carbon-to-nitrogen ratio, residence time descriptor, digestion temperature, pH and organic loading rate. The model was evaluated using the coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), five-fold cross-validation and residual diagnostics. On the test subset, the model achieved R2 = 0.9885, MAE = 13.40 mL g−1 VS, RMSE = 16.16 mL g−1 VS and MAPE = 3.73%. The mean five-fold cross-validation score was R2 = 0.9720 ± 0.0180, indicating stable interpolation performance within the investigated data domain. Feature-importance analysis identified C/N ratio as the dominant predictor, followed by volatile solids and total solids. However, residual diagnostics showed heteroscedasticity, and the low apparent importance of pH and temperature was attributed to their narrow ranges in the compiled dataset, rather than to biological irrelevance. The proposed model is therefore intended as an early-stage screening tool for total biogas yield estimation, not as a universal methane yield or design-level prediction model.

Engineering Proceedings doi: 10.3390/engproc2026143067

Authors: Eleni Petropoulou George F. Fragulis

This paper studies the topics of chaos and cryptography, and how chaotic systems can be used in data encryption. Previous research show that chaos can generate pseudo-random sequences and help protect data, but there are problems because many studies do not analyze security deeply, and chaotic systems can be attacked. In this work, chaotic systems are studied, and a variation of a chaotic encryption algorithm is implemented. The security and performance of this algorithm are tested and analyzed. The results show some advantages but also limitations of chaotic encryption, and give important information for future use and research in cryptography.

Engineering Proceedings doi: 10.3390/engproc2026151032

Authors: Asle J. Tomstad Ivan Bunaziv Magnus Eriksson

Numerically efficient and user-friendly modelling of component distortions is the key for enabling numerical design of thin-plate structures accounting for welding distortions. This especially concerns large structures, e.g., bridges or ship panels. The direct description of inherent strains is a method for introducing inherent strains into a commercial finite element solver. The presented version utilizes thermo-mechanical local modelling with 3D solid elements in Abaqus as a source for the inherent distortion fields. The resulting inherent strain fields are post-processed and subsequently applied to a low-fidelity component model utilizing 3D thin shell elements in Abaqus. The new direct description method of introducing the inherent strain fields for thin shell elements is presented in this paper, and it shows promising results.

Engineering Proceedings doi: 10.3390/engproc2026151033

Authors: Christoffer N. Hellstrøm Sigmund Arntsønn Tronvoll

Deployable metallic structures offer a new design approach for overcoming the geometric limitations of laser powder bed fusion by enabling compact as-built configurations to be expanded after printing into larger, lightweight architectures suitable for efficient packing and aerospace applications. The formability of solution heat-treated, additively manufactured AlSi10Mg alloy was investigated using U-shaped specimens with controlled radius and thickness parameters, designed to evaluate bending-driven deployment. Across all configurations, the alloy exhibited substantial plastic deformation, reaching bending angles between 90.2° and 179.5°. Full deployment was achieved in the t2 r4 specimen, corresponding to an r/t ratio of 2.0, which straightened to 179.5° without failure while maintaining the lowest measured strain of 18.8%. Experimental observations and numerical analysis indicate that failure is governed not by a single critical strain, but by strain localization at the inner radius, followed by surface slip, crack initiation and crack propagation. These findings demonstrate that heat-treated AlSi10Mg provides a promising route towards lightweight, additively manufactured deployable structures with tunable deformation capacity.

Engineering Proceedings doi: 10.3390/engproc2026145012

Authors: Abd Elkarim Ammar Bassem Hichri Simone Musacchio Jean-Daniel Kiefer Jean-Régis Hadji-Minaglou

Off-highway vehicle electrification requires traction motors combining high torque density with reliable performance across demanding duty cycles, yet finite-element-based optimization remains computationally demanding for broad design-space exploration. This study addresses the gap with a sensitivity-analysis-based, surrogate-assisted multi-objective optimization framework for a 12-pole/72-slot, 120 kW Interior Permanent-Magnet Synchronous Motor (IPMSM) for a compact wheel-loader drivetrain, coupling Ansys Motor-CAD with Ansys OptiSLang. A Latin Hypercube sensitivity study of thirteen geometric parameters identifies the dominant design drivers, and an evolutionary algorithm operating on the validated surrogate produces a Pareto-optimal set, from which the final design is selected using the CRITIC–TOPSIS method applied to finite-element-validated feasible designs. Relative to the baseline, the validated performance shows a 7.4% increase in continuous torque, a 4.0% increase in peak torque, a 4.0% increase in efficiency, and a 53.5% reduction in torque ripple, with mass essentially unchanged, while also revealing that surrogate predictions were markedly optimistic relative to the finite-element results. These findings demonstrate an efficient, reliable route to high-performance IPMSM design for off-highway applications.

Engineering Proceedings doi: 10.3390/engproc2026143066

Authors: Ritchfildjay L. Mariscal

The growing demand for scalable and cost-effective digital learning environments has increased interest in lightweight cloud-based learning management solutions that can support instructional delivery without the complexity and infrastructure requirements of conventional Learning Management Systems (LMSs). While enterprise LMS platforms provide extensive functionality, their deployment and maintenance often require substantial technical, financial, and administrative resources. This study proposes a lightweight cloud-based LMS architecture using low-code web technologies as an alternative framework for educational content management, learner engagement, resource distribution, and instructional support. The proposed architecture integrates four functional system layers: course management, performance management, content delivery, and productivity support. These components are designed to operate within a cloud-hosted environment that leverages web-based content management, embedded digital resources, collaborative productivity tools, and centralized storage services. The architecture emphasizes accessibility, modularity, low deployment overhead, and cross-platform compatibility, enabling rapid implementation in resource-constrained educational settings. To evaluate the feasibility of the proposed architecture, a large-scale deployment was conducted involving 1765 end users interacting with the platform within an educational environment. System functionality was assessed through feature-level evaluation across the core LMS components and supported by user capability indicators related to digital engagement and platform utilization. Analytical results demonstrated strong functional performance across all architectural modules, with course management and content delivery components exhibiting the highest operational effectiveness. Findings further indicated that the cloud-based architecture successfully supported essential LMS functions through integrated web services and low-code platform technologies. The study contributes a replicable systems architecture and deployment framework for lightweight learning management environments. The proposed model offers a practical foundation for the development of cloud-based educational platforms that support scalable content delivery, learner interaction, instructional management, and future integration with learning analytics, adaptive learning engines, and intelligent educational support systems. The framework provides an engineering-oriented approach for designing accessible and sustainable digital learning infrastructures using low-code technologies.

Engineering Proceedings doi: 10.3390/engproc2026133207

Authors: Florian Mock Lukas Kettenhofen Daniel Alboldt Kai-Uwe Schröder

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Engineering Proceedings doi: 10.3390/engproc2026137029

Authors: Indah Pratiwi Yusuf Masykur Darmawan Mohd Nasrull Abdol Rahman

Enggal Jaya MSME is a small-scale enterprise specializing in metal casting and the production of fire rings, with a monthly capacity exceeding 15,000 units. Currently, its production process exhibits significant inefficiencies across the seven wastes of lean manufacturing: overproduction, defects, inventory, motion, transportation, overprocessing, and waiting. This study aims to map the information and production workflows for fire ring components, analyze the types and root causes of waste, and propose actionable solutions to improve shop-floor efficiency. Value Stream Mapping (VSM) and the Waste Assessment Model (WAM) were utilized as the primary methodologies. The current-state VSM revealed a Process Cycle Efficiency (PCE) of 69%, whereas the proposed future-state VSM demonstrates an improved PCE of 73%. Furthermore, Waste Assessment Questionnaire (WAQ) calculations identified five major types of critical waste: overproduction (19.2%), defects (18.0%), inventory (16.1%), motion (15.2%), and transportation (13.3%). Proposed countermeasures include systematically recording production activities, developing Standard Operating Procedures (SOPs), integrating appropriate material handling tools, and implementing rigorous production forecasting and scheduling.

Engineering Proceedings doi: 10.3390/engproc2026147014

Authors: Hulkar Abdusalomova Azizbek Kamolov Zafar Turakulov Jaloliddin Eshbobaev Komil Usmanov Sarvar Rejabov Botir Usmonov Bobiromon Kodirov Elbek Ortikov Adham Norkobilov

Higher education institutions are increasingly expected to reduce greenhouse gas emissions while maintaining reliable educational, laboratory, and administrative operations. This challenge is particularly relevant in transition economies, where university campuses often depend on fossil-fuel-based electricity systems, natural-gas heating, and aging infrastructure. This study presents a campus-scale decarbonization assessment for the Tashkent Institute of Chemical Technology in Uzbekistan. The quantified inventory covered Scope 1 emissions from natural-gas combustion and Scope 2 emissions from purchased electricity. Paper use, digital services, behavioural measures, and campus greening were assessed as supplementary institutional indicators and were excluded from the quantified total because consistent pre- and post-intervention activity data were unavailable. The assessment combined institutional utility records for 2023–2025 with information on renewable-energy deployment, heating modernization, digital transformation, sustainability awareness, and campus greening. A 300 kW solar photovoltaic system comprising 666 modules was commissioned in May 2023, with a documented annualized generation potential of approximately 520,000 kWh. Purchased grid electricity amounted to 711,402, 745,947, and 749,060 kWh in 2023, 2024, and 2025, respectively, while annual natural-gas consumption was 144,775, 161,200, and 142,031 m3. Using a conservative standard-based net calorific value of 31.8 MJ/m3 together with IPCC stationary-combustion factors, annual Scope 1 and Scope 2 emissions were estimated at 637.53, 685.29, and 652.65 tCO2-eq, respectively. The 2025 total was 4.76% below the 2024 value but 2.37% above the 2023 value. The annualized PV technical potential corresponds to a theoretical maximum Scope 2 displacement of 276.64 tCO2-eq/year under 100% self-consumption. This value does not represent measured generation or a realized emission reduction and was not included in the quantified inventory. Digitalization, behavioural engagement, and greening were evaluated as complementary measures rather than assigned separate emission-reduction credits. The study provides a transparent and regionally relevant framework for universities in transition economies seeking to strengthen campus carbon management under incomplete data conditions.

Engineering Proceedings doi: 10.3390/engproc2026144016

Authors: Charaf Laghlimi Younes Ziat Zakaryaa Zarhri Noureddine Lakouari Hamza Belkhanchi Abdelaziz Moutcine

In submitting conference proceedings for the 2nd International Conference on Sciences and Techniques for Renewable Energy and the Environment (STR2E 2026) to Engineering Proceedings, the Volume Editors of the proceedings would like to certify to the publisher that all papers published in this volume have been subjected to peer review by the designated expert referees and were administered by the Volume Editors strictly following the policies announced on the conference website [...]

Engineering Proceedings doi: 10.3390/engproc2026152002

Authors: Lavinia Cretu Liliana Rusu

In the context of increased international efforts to reduce greenhouse gas emissions through various measures included in climate agreements, regulatory frameworks, and decarbonization strategies, the utilisation of renewable energy resources represents a solution to sustainable global development. Wave energy is a marine renewable resource that has great potential but has not yet been fully exploited. Considering this, the current work examines the Black Sea’s wave climate variability and wave energy dynamics using SWAN model results applied throughout the basin. Attention is given to the long-term assessment of wave conditions and wave power, the characterization of dominant wave patterns, and the identification of possible changes in sea state parameters over an extended period (30 years). Recent wave climate variability and projections of future changes under the RCP4.5 and RCP8.5 climatic scenarios are evaluated. The assessment of the potential effects of climate change on sea state conditions and the spatial distribution of wave energy resources in the Black Sea basin is performed by comparing the historical and future projections, thereby also facilitating the observation of climate change pattern evolution. The results offer a forward-looking assessment of wave energy potential in the Black Sea and its reliability as a sustainable energy resource in relation to climate change.

Engineering Proceedings doi: 10.3390/engproc2026149009

Authors: Adriana Rossi Mario Guagliano Giuseppe Di Modica

This paper presents a summary of the activities carried out in relation to the shared objectives of the SCORPiò-NIDI project, an interdisciplinary research initiative aimed at investigating ballistic traces preserved along the northern fortification of Pompeii, produced by Roman siege engines during the siege of 89 BC. The study integrates digital surveying, computational modeling, experimental archaeology, and visualization techniques to document, analyze, and interpret specific types of anthropic damage caused by large stone projectiles and metal-tipped darts. High-resolution 3D acquisitions and reverse engineering processes guided the formulation of reconstructive hypotheses concerning projectile trajectories, impact velocities, and energy transfer mechanisms, supporting the determination of dimensional modules on the basis of which ancient treatises describe the proportional design of dart-throwing and stone-throwing machines in siege conditions. Mechanical simulations and comparative analysis provided quantitative validation of the virtual demonstrators prototyped and/or reconstructed using techniques and materials compatible with the pre-Christian period. The project further developed interactive digital models, animations, and visualization tools to support knowledge dissemination and public engagement. By combining archaeological data, engineering analysis, and human–computer interaction strategies, this research demonstrates the potential of digital technologies to enhance the study, interpretation, and communication of cultural heritage.

Engineering Proceedings doi: 10.3390/engproc2026143065

Authors: Gerald T. Goboy Melbert M. Gregorio Thursday Joy G. Gaac Reclaire Joy M. Galicia Rosame R. Magada Kim Jemar F. Falo

Improving foundational mathematical competency remains an important challenge in educational technology and instructional system design. This study presents the design, development, and evaluation of Z-Card, a game-based instructional framework intended to improve students’ mastery of fundamental integer operations. The instructional intervention was developed using the ADDIE instructional design model and validated through expert evaluation based on instructional objectives, design quality, organizational structure, playability, and instructional usefulness. A quasi-experimental pre-test–post-test design involving Grade 7 students was employed to evaluate learning effectiveness using paired sample t-tests and ANCOVA. The results demonstrated statistically significant improvements in mathematical performance among students exposed to the Z-Card framework, with a large treatment effect after controlling for prior knowledge. Expert evaluations likewise indicated high acceptability across all design dimensions. The findings demonstrate that structured game-based instructional systems can effectively integrate learner engagement, conceptual reinforcement, and assessment-driven instructional support. The proposed framework contributes to educational technology by providing a scalable model for designing interactive learning environments that enhance foundational mathematics instruction.

Engineering Proceedings doi: 10.3390/engproc2026151036

Authors: Yugo Maeno Arata Ishikawa Muneyoshi Iyota

In recent years, increasing environmental concerns have intensified the demand for lightweight vehicle bodies to improve fuel efficiency. Consequently, aluminum alloys have been increasingly applied to automotive body structures. Resistance spot welding (RSW), which enables high-volume production, is widely used in the automotive industry; however, variability in nugget shape causes fluctuations in nugget diameter, resulting in instability in joint strength. In this study, a hole was introduced on the surface of an aluminum alloy sheet to suppress nugget shape variability. Specifically, a hole with a diameter of 2 mm was machined at the center of the aluminum alloy sheet between the sheet and the electrode. The results showed that the variation in nugget diameter was significantly reduced under the hole condition compared with the condition without a hole. Observations of the joint interface revealed that nugget shape variability was also suppressed under the hole condition. These findings indicate that the introduction of a hole stabilizes nugget formation at the faying interface, thereby reducing variation in nugget diameter.

Engineering Proceedings doi: 10.3390/engproc2026151035

Authors: Yugesh Raajha Maheswari Siddarthan Chanmi Moon Geir Ringen Torgeir Welo

This study evaluates the formability of single-pass and double-pass friction stir-welded AA6082 tailor-welded blanks produced at a 1000 rpm rotational speed and 100 mm/min welding speed. The objective is to understand the effect of multi-pass welding strategies on stir zone (SZ) softening, load-bearing capacity, and strain localization during biaxial stretching. Formability was assessed using limiting dome height (LDH) tests, supported by hardness mapping, tensile tests, 3D digital image correlation, and complementary finite element (FE) simulations. The results exhibit similar dome heights (~14 mm) in both weld conditions, but single-pass welds sustain 5 kN higher peak load, better strength, and ductility. Shell-based FE models reproduce the load–displacement response and strain localization within ~5% of experimental results.

Engineering Proceedings doi: 10.3390/engproc2026151030

Authors: Nanaha Taniwake Seiya Sugimoto Takeshi Matsukage Keisuke Kinoshita Yufu Watanabe Taishi Tarui Muneyoshi Iyota

With the increasing adoption of gigacasting in the automotive industry, establishing joining technologies between aluminum casting alloys and rolled aluminum alloys has become an important challenge. In resistance spot welding (RSW) of these dissimilar materials, nugget formation is often absent, and the factors governing joint strength remain unclear. This study aims to clarify the factors affecting joint strength in RSW joints between aluminum casting alloy and rolled aluminum alloy. The relationship between fracture morphology and joint characteristics was systematically investigated through cross-tension tests, cross-sectional observations, hardness measurements, and numerical simulations. The results indicate that cross-tension strength (CTS) is strongly correlated with crack propagation behavior in the rolled aluminum alloy. In contrast, conventional factors such as penetration and plug diameter show weak correlation with CTS. Furthermore, the deformation range of the rolled aluminum alloy affects the distribution of plastic strain, which in turn controls crack propagation angle and joint strength. These findings demonstrate that the deformation behavior of the rolled aluminum alloy plays a dominant role in determining joint strength in nugget-free RSW joints.

Engineering Proceedings doi: 10.3390/engproc2026137028

Authors: Indah Pratiwi Muhammad Fahmi Rizkiandi Mohd Nasrull Abdol Rahman

In the small and medium industries producing red bricks in Indonesia, the production process still uses traditional tools. At the workstation, operators in bent postures, which increases the potential for musculoskeletal disorders (MSDs) to occur and requires corrective actions at the workstation. This research aims to reduce the risk of unhealthy operator work postures by designing red-brick molding tools that are more ergonomic and efficient, thereby speeding up the production process. The research uses the axiomatic design method and integrates it with the Ulrich and Eppinger’s product design and development stages. At the product concept development stage, five alternative design solutions were generated, and the second solution was determined as the selected concept. The solution was design and tested virtually. The research results show that the REBA method test score is one, which means that the red-brick molding work using this tool carries a negligible level of risk and does not require corrective action. Based on the designed specifications, this tool can reduce molding time by 92.5% compared to the molding time of traditional tools.

Engineering Proceedings doi: 10.3390/engproc2026135041

Authors: Margherita Evangelisti Vincent Pons Marco Maglionico

The paper investigates the integration of permeable pavements into sustainable urban mobility planning in Bologna, Italy. The study evaluates stormwater management benefits under the current and future climate conditions through hydrological and hydraulic modeling with EPA SWMM. A residential catchment of about 50 hectares was analyzed, with potential permeable pavement implementation on pedestrian paths and parking areas. Results show a 40% reduction in stormwater volumes under the current climate and 38% under future scenarios, confirming the resilience and effectiveness of green infrastructure. Findings support Bologna’s Urban Plan for Sustainable Mobility, highlighting permeable pavements as a strategy to enhance resilience and sustainability.

Engineering Proceedings doi: 10.3390/engproc2026143064

Authors: Kavitha K J Keerthi S

The rapid integration of digital technologies including cloud infrastructures, Internet of Things ecosystems, artificial intelligence, and large-scale enterprise platforms has reshaped the operational and architectural foundations of contemporary organizations. Although these technologies enhance flexibility, scalability, and analytics-driven decision processes, they simultaneously increase system complexity, broaden attack surfaces, and intensify governance requirements. This manuscript adopts an engineering-oriented viewpoint on digital governance and enterprise cybersecurity, focusing on secure system architectures, policy-driven control mechanisms, and resilience-focused operational strategies. An integrated framework that unifies governance structures, quantitative risk assessment, compliance automation, cybersecurity engineering is introduced to enable secure-sustainable digital transformation across enterprise environments.

Engineering Proceedings doi: 10.3390/engproc2026143063

Authors: Mel Eduard A. Magracia Ian Peter R. Madrona Jeremias F. Fabito Onemig Mortel Jomar V. Malsi Lynie M. Mariño

The MENRO: Monitoring and Management System is a digital solution developed to modernize the manual operations of the Municipal Environment and Natural Resources Office (MENRO). The system provides a secure and user-friendly platform designed to streamline document handling, automate monitoring tasks, and ensure accurate environmental data management. This project specifically aims to: (1) develop a user-friendly interface that enables seamless document and record management, allowing administrators to effortlessly add, edit, update, and store essential information, and (2) design a system that is capable of automatically generating comprehensive lists of apprehension receipts, including violations and penalties issued to establishments under MENRO’s jurisdiction. These functions address long-standing inefficiencies in manual monitoring, recordkeeping, and compliance tracking. The system was evaluated using the ISO/IEC 25010:2011 software quality standards, focusing on functional suitability, performance efficiency, reliability, usability, compatibility, maintainability, portability, and security. Results show high usability and strong security features, ensuring that the platform meets operational needs while safeguarding sensitive environmental and legal records. By integrating real-time data access, automated reporting, and digitized forms used in environmental compliance checks, the system enhances MENRO’s capability to uphold environmental governance with greater transparency, accuracy, and accountability.

Engineering Proceedings doi: 10.3390/engproc2026142018

Authors: Md Salah Uddin

Additively manufactured AlSi10Mg aluminum alloy was investigated at two-layer build orientations: 0° and 90°. Impact-induced fractures were generated per the ASTM standard Charpy test. The resulting fracture surfaces were analyzed using the multi-image-based fractal analysis method. We used a digital microscope to analyze the fracture surface and examined compression, neutral, and tension zones on the surface. We found that the crack propagated symmetrically across the surface. The results showed that the compression zone has the lowest fractal dimension compared to the tension and neutral zones. The 0° orientation samples have a higher fractal dimension than the 90° orientation samples.

Engineering Proceedings doi: 10.3390/engproc2026148044

Authors: Gyuri Bodi Mihaela Ioana Baritz Angela Repanovici Alexandra Maria Lazăr Anca Ioana Tătaru (Ostafe)

The cornea, a transparent avascular connective tissue, is the most important refractive component of the eye system, along with the overlapping tear film. In addition, due to its protective, transparent and refractive characteristics, it protects the sensitive content of the eyeball and provides clear vision. However, both experimental and clinical modeling/simulation studies are needed for a holistic understanding of corneal behavior alongside tear film and contact lenses. As such, this study develops a simulator for analyzing the orthokeratology procedure, with the aim of highlighting the biomechanical aspects of contact between the cornea, tear fluid and the ortho-K lens in different situations. The computer simulator (Matlab) allows the development of multiscenario variants for effective and practical understanding and applicability.

Engineering Proceedings doi: 10.3390/engproc2026150131

Authors: Margarita Deneva Maria Marinova

Optical interference structures (OISs) are of particular interest due to their attractive potential for use in many practical applications involving laser light. They have many interesting properties, including the ability to smoothly tune the wavelength of the incident laser beam, simple implementation of the elements and the absence of electrical and magnetic influences. Here, the focus is on a new theoretical approach to the action of OIS, based on our newly introduced multi-layer interference wedge structure, which improves the reflection and transmission characteristics of the classical single-gap interference structure. This new approach is based on multi-beam interference and the implementation of the parallel algorithm programming principle.

Engineering Proceedings doi: 10.3390/engproc2026146017

Authors: Hao Wang Miaoling Wang Liang Kong Mushuang Liu Xinxin Zhu

Construction accident investigation reports provide rich narrative evidence for understanding why incidents occur, yet conventional text-mining studies in safety analytics often prioritize frequent patterns and may overlook low-frequency but high-consequence scenarios. This paper proposes a tail-risk profiling approach for construction accidents using text data. We transform accident narratives into semantic scene representations and organize reports into ten stable scene clusters (S1–S10) using spherical K-means with HDBSCAN-based robustness validation. Tail behavior is quantified at the scene level via quantile-based indicators, where P50 represents typical consequences and P90 represents extreme consequences; we further derive the Heavy-Tail Index (HTI = P90/P50) and the P90 exceedance rate to measure extreme-outcome tendency. A case study on 409 official accident reports shows that the proposed profiling can distinguish “tail-heavy” scenarios and support severity-sensitive scenario prioritization beyond frequency statistics. The results indicate that tail-risk profiling offers an interpretable and scalable basis for targeted safety interventions focusing on extreme-risk scenarios.

Engineering Proceedings doi: 10.3390/engproc2026150130

Authors: Kalina Kamarska Ivalina Petrova Radoslava Terzieva Iva Naydenova Radka Koleva

The widespread application of plain S235JR steel across various industries often involves its exposure to degradative conditions, such as the organic acid concentrations typically found in various foodstuffs. This study investigates the corrosion behavior of S235JR steel immersed in several common beverages. The corrosion of steel S235JR was evaluated by gravimetric and electrochemical study. Statistical modeling via multiple linear regression and ANOVA was utilized to verify the experimental dataset. Based on the results, the highest early-stage corrosion occurs in coffee and tomato juice, though apple cider vinegar stands out for its steadily intensifying corrosive effect over the immersion period. Conversely, the presence of citric acid in lemon and orange juices appears to act as an inhibitor, leading to the lowest observed corrosion rates. The strong correlation between electrochemical parameters (Icorr and Eocp) and physical mass loss confirms that the chemical nature of each beverage significantly governs the corrosion kinetics of S235JR.

Engineering Proceedings doi: 10.3390/engproc2026149007

Authors: Vincenzo Minutolo Eugenio Ruocco Simone Palladino Renato Zona

The mechanical interpretation of impact traces on historical masonry structures offers a promising pathway for identifying the typology of ancient projectiles used in past conflicts. In recent years, inverse analysis approaches have been increasingly employed to infer projectile characteristics from residual damage patterns observed on archaeological remains. However, the reliability of such reconstructions strongly depends on the mechanical representation adopted for the impacted masonry. Ancient masonry walls, particularly those composed of tuff blocks and mortar joints, exhibit a marked heterogeneity that cannot always be adequately captured through simplified homogeneous material models. In this study, a numerical framework is developed to investigate how different assumptions regarding masonry homogenization influence the identification of projectile parameters derived from impact evidence. The mechanical response of the masonry is modeled through a homogenization procedure based on representative volume elements (RVE), allowing the heterogeneous brick—mortar assemblage to be translated into an equivalent macroscopic constitutive description. The resulting elastic and limit mechanical properties are then employed within a Finite Element Limit Analysis (FELA) formulation grounded in Melan’s lower bound theorem to evaluate collapse mechanisms and energy dissipation during impact.The methodology is applied to a case study inspired by the masonry walls of Pompeii, where parametric variations in mortar thickness are considered to assess their influence on the homogenized stiffness and strength domain. The results highlight how even simplified yet mechanically consistent models are capable of capturing the anisotropic behavior of masonry and its implications for energy absorption. In particular, the study shows that adopting a homogenization-based representation leads to more reliable inverse estimates of projectile velocity and momentum compared to purely homogeneous approximations. Overall, the proposed approach provides a computationally efficient yet mechanically grounded framework for supporting archaeological interpretations of impact traces, contributing to a more quantitative understanding of ancient warfare technologies.

Engineering Proceedings doi: 10.3390/engproc2026143062

Authors: Dana Kaye Fabiala Jhun August Mendez Maria Belinda Galivo Shairane Potoy Liza Melchor Hannah Grace Fampulme Mary Diane M. Mortel

The increasing demand for technology-supported instructional solutions has created opportunities to develop learning systems that integrate curriculum alignment, instructional design, and learner-centered interaction within a unified educational framework. This study presents the design and validation of a Technology-Aided Interactive Mathematics Learning Framework that functions as an instructional support system for Grade 3 subtraction involving three- to four-digit numbers with and without regrouping. The proposed framework adopts the Four-D (4D) instructional development model as its system development methodology and incorporates structured content organization, interactive learning components, and curriculum-driven instructional configuration. A mixed-method developmental research approach was employed involving fourteen participants, including twelve Grade 3 teachers and two master teachers from public elementary schools in Alcantara, Romblon, Philippines. A needs assessment identified subtraction with regrouping as the highest-priority instructional challenge. The resulting instructional system was evaluated using the Department of Education Evaluation Rating Sheet for Print Resources and achieved an overall Very Satisfactory rating across content integrity, interface organization, presentation, instructional architecture, and information accuracy. Qualitative analysis further demonstrated that the framework supports curriculum alignment, contextual adaptability, learner engagement, and reusable instructional deployment while identifying opportunities for improving inclusivity and interface presentation. The findings demonstrate that the proposed technology-aided instructional framework provides a practical, scalable, and sustainable learning support configuration that can serve as a foundation for future intelligent educational systems, adaptive learning platforms, and digital instructional environments.

Engineering Proceedings doi: 10.3390/engproc2026149008

Authors: Claudio Formicola Santiago Lillo Giner Adriana Rossi

This study develops workflows derived from the non-contact survey of small anthropic markers along the northern stretch of Pompeii’s urban walls. For valid reasons currently being verified, these indentations have been attributed to the impact of darts fired by Sulla’s artillery in 89 BC. Consistent with published findings, the morphometric data obtained from the casts of the impressions generated by the metal tips were used to obtain measurement modules suitable for measuring the reconstruction of SCORpiò-NIDI. To achieve this result, calibration formulas handed down directly from the Greeks and Romans were used. The method adopted reverses the usual sequence, starting from the effects and arriving at the causes. According to the principles handed down by ancient treatise writers, typical 2D-3D graphic modeling investigations guided the commensuration of parts. A family of dart-launcher prototypes was created based on the measurement module, to be tested and mechanically analyzed through reverse engineering processes. The creation of virtual models was not based on the dimensions of the findings, but rather on parameters that study the reaction of stone blocks to the impact of blunt objects. The results aim to raise operational criticism, contributing to the debate on “certified” typological families of reconstructions based on objective data and verifiable calculations.

Engineering Proceedings doi: 10.3390/engproc2026143061

Authors: Charmaine Shane S. Cuñada

The increasing deployment of Virtual Learning Environments (VLEs) within higher education has highlighted the need for systematic frameworks that support technology adoption among digitally diverse users. This study presents a human-centered evaluation framework for analyzing the adoption of VLEs by digital immigrant teachers within higher education systems. The framework was examined using qualitative evidence obtained from thirteen educators aged 50 years and above at a Philippine state university through Husserlian descriptive phenomenology and Colaizzi’s seven-step analytical approach. The analysis identified three interconnected framework dimensions—System Transition Challenges, Adaptive Configuration Strategies, and Technology-Enabled Instructional Opportunities—representing the progression from initial system adoption to sustained digital integration. Findings indicate that technical complexity, increased workload, and interaction constraints initially hinder effective VLE utilization. However, structured professional development, instructional redesign, and collaborative support functioned as key framework components that improved system usability, digital competence, and instructional performance. The proposed framework conceptualizes VLE adoption as a socio-technical process integrating user capabilities, institutional support mechanisms, and digital platform functionality. These findings contribute to the design of more resilient, user-centered, and scalable VLE implementation strategies for higher education information systems.

Engineering Proceedings doi: 10.3390/engproc2026150129

Authors: Petr Velmisov Andrey Ankilov

The paper considers a linear differential operator and a nonlinear integro-differential operator, on the basis of which the equations of vibration of a deformable plate are written down. The nonlinear operator takes into account the nonlinearity of the longitudinal force arising from the elongation of the plate due to its deformation. Based on the proposed equations, the mathematical models of the mechanical system “pipeline–pressure sensor” are developed. The system consists of a pipeline attached at one end to the combustion chamber of an aircraft engine and a sensor designed to measure the pressure in the combustion chamber at the other end. The sensing element of the sensor that transmits the pressure information is a deformable plate. The models take into account the transfer of heat flow through the pipeline with the working medium (gas or liquid) from the engine to the elastic element and the aerohydrodynamic effect of this medium on the plate. On the basis of the small parameter method, the asymptotic equations describing the joint dynamics of the working medium in the pipeline and the deformable element of the sensor are obtained. The dynamics study is based on the application of the Galerkin method and numerical experiment in Mathematica 12.0. The case of rigid fixation of the elastic element ends is considered. A comparative analysis of solutions for linear and nonlinear models is made. The insignificant influence of the nonlinearity of the longitudinal force on the value of the plate deflection is shown.

Engineering Proceedings doi: 10.3390/engproc2026149006

Authors: Monil Mihirbhai Thakkar Amir Ardeshiri Lordejani Mario Guagliano

Roman artillery represents a key element of ancient military technology, reflecting the advanced level of technical knowledge achieved in the late Republican and early Imperial periods. However, the operational capabilities and the design methodology of these weapons are not adequately described in historical references. This study investigates the launch performance of Roman Scorpio catapult by integrating archeological evidence from impact craters on Pompeii’s northern walls with analytical modeling of torsion-spring behavior. The present study determines the required release velocity of an arrow capable of creating impact craters reported by applying ballistic and aerodynamic analytical models. Historically cited rope materials for torsion springs are evaluated using experimentally reported mechanical properties and geometric constraints. The integrated analysis highlights how material selection and drag-related energy losses influence projectile velocity, supporting the plausibility of the proposed catapult configuration and offering highlights into ancient artillery design.

Engineering Proceedings doi: 10.3390/engproc2026143060

Authors: Sherryll Fetalvero Tomas Faminial Emelyn Montoya Errol Foja Eddie Fetalvero Garry Vanz Blancia

The increasing digitalization of higher education has created the need for ICT-assisted instructional frameworks capable of supporting both technical competency development and pervasive skills acquisition. This study presents a data-driven framework for informing ICT-assisted instruction based on the assessment of accountancy students’ perceived importance and readiness regarding pervasive skills. An online survey was conducted among students enrolled in the Accountancy program at Romblon State University using a researcher-developed instrument covering personal attributes, intellectual and professional skills, interpersonal and communication skills, and professional ethics and moral values. Descriptive statistics and paired-samples t-tests were employed to identify readiness gaps across the four competency domains. Results indicate statistically significant differences between perceived importance and readiness, with communication-related competencies exhibiting the largest readiness gaps. These findings provide empirical requirements for designing human-centered ICT-assisted instructional systems that integrate digital collaboration platforms, simulations, adaptive learning technologies, and analytics-driven learning activities. The proposed framework supports evidence-based instructional configuration by aligning technology-enhanced learning environments with learner competency needs, thereby contributing to the development of more responsive educational information systems for accounting education.

Engineering Proceedings doi: 10.3390/engproc2026143059

Authors: George Kirkopoulos Stavros Gkanatsios George F. Fragulis

The subject of this study is the control of a two-degree-of-freedom robotic arm. Initially, the theoretical foundation employed in this study is presented. Subsequently, homogeneous transformation matrices are computed utilizing the Denavit–Hartenberg (D-H) method. Subsequently, the problem of forward kinematics and inverse kinematics is resolved. Subsequently, state space matrices are calculated, and finally, the parameters of the PID (Proportional Integral Derivative) controller are determined to ensure that specific specifications (e.g., overshoot, settling time, steady-state error) are met, even in the presence of disturbances.

Engineering Proceedings doi: 10.3390/engproc2026145011

Authors: Ibrahim Abdulwahab Badamasi Umar Umar Musa Sulaiman Haruna Sulaiman Ibrahim Abdullahi Shehu Ismaila Mahmud Aminu Jibrin Aliyu

The reliability and continuous operation of DC motors are essential in industrial and engineering applications. However, unexpected faults such as brush wear and commutator faults can lead to efficiency reduction and unplanned downtime. This paper presents a machine learning approach for fault detection and diagnosis (FDD) of DC motors using Long Short-Term Memory (LSTM). A publicly available dataset was employed to train the models. To compare the performance, two other models, K-nearest neighbor (KNN) and artificial neural network (ANN), were used. The performance of the models was assessed through accuracy, precision, recall, and F1-score, and presented using confusion matrices. The results obtained from the developed scheme were compared with those obtained when KNN and ANN were used. The results revealed that KNN, while simple and computationally efficient with an accuracy of 93.3%, was prone to misclassifications in overlapping feature spaces. ANN demonstrated improved accuracy of 94.7% by capturing non-linear relationships among features but lacked the ability to effectively exploit time-dependent characteristics of the data. In contrast, LSTM achieved the highest performance, with a validation accuracy of 97.3% and strong precision and recall across all the classes, owing to its ability to capture temporal dependencies in sequential motor data. The study concludes that LSTM significantly outperforms KNN and ANN, making it the most suitable model for DC motor fault detection and diagnosis.

Engineering Proceedings doi: 10.3390/engproc2026147013

Authors: Hulkar Abdusalomova Azizbek Kamolov Zafar Turakulov Botir Usmonov Qilichbek Safarov Jaloliddin Eshbobaev Sarvar Rejabov Komil Usmanov Yoldoshkhon Akramkhodjayev Adham Norkobilov Miroslav Variny Marcos Fallanza

Post-combustion amine absorption is the most mature CO2 capture technology, while membrane separation is a promising alternative due to its modularity and operational simplicity. Process intensification through exhaust gas recirculation (EGR) has also gained attention for increasing flue gas CO2 concentration and reducing capture energy demand. However, comprehensive techno-economic comparisons of absorption, membrane, and hybrid systems under EGR-integrated NGCC conditions remain limited. This study presents a techno-economic assessment of multiple CO2 capture configurations for a 450 MW NGCC power plant. Process simulations were performed using Aspen Plus and Aspen Custom Modeler to evaluate absorption, membrane, and hybrid systems integrated with conventional and selective EGR. The analysis considers full steam cycle integration and compares energy consumption, net plant efficiency, levelized cost of electricity (LCOE), and CO2 avoidance cost. The results show that EGR significantly improves carbon capture performance. Among all cases, selective EGR combined with amine absorption delivers the best performance, reducing the energy penalty by more than 30% compared with standalone absorption and by over 70% relative to membrane separation. This configuration achieves an LCOE of approximately 72 USD/MWh and a CO2 avoidance cost of about 39 USD/tCO2, outperforming the selective EGR–membrane system (77 USD/MWh and 51 USD/tCO2). These findings demonstrate that integrating selective EGR with amine absorption is a highly promising strategy for improving the technical and economic feasibility of CCSU in NGCC power plants.

Engineering Proceedings doi: 10.3390/engproc2026142019

Authors: Carlos C. Insaurralde

Aerospace engineering applications typically entail complex high-performance systems with sustainable safety. They are usually designed by multidisciplinary development teams where collaboration efficiency is undermined by the diversity of views (models) provided by the disciplines involved. This produces design deadlocks (augmenting risks and costs) when crosschecking modeling representations to assess the impact of different models on each other to maintain system integrity. This paper presents details of the design process of a planetary rover in which diverse stakeholders deal with distinct aspects of the above space ground vehicle. It includes preliminary results from requirements analysis and system design that are used to interlink system models for an autonomous model crosschecking design process. The approach reduces collaborative design efforts by enabling multiple developers to minimize potential design inconsistencies by cross-relating their system models. Concluding remarks and future research are also presented.

Engineering Proceedings doi: 10.3390/engproc2026147012

Authors: Haris Abdullah Muhammad Khubaib

Digital twins (DTs) have become a promising approach for intelligent building management by enabling real-time monitoring, simulation, and decision support. However, the operational integration of building energy and structural performance remains limited. This systematic review evaluates the current state of integrated energy–structural DTs, focusing on architectures, interoperability, semantic integration, validation, uncertainty, and scalability. Following PRISMA 2020 reporting guidance, the literature published between 2015 and 2025 was collected from Scopus, Web of Science, and IEEE Xplore, resulting in the synthesis of 82 studies. Among the reviewed studies, 68.3% addressed energy applications, 53.7% focused on structural applications, while only 17.1% demonstrated partial integration and 12.2% reported bidirectional information exchange. Most studies relied on scenario- or simulation-based validation (69.5%), and only 8.5% considered district-scale implementations. The review identifies BIM, IoT, BEM, FEM/SHM, semantic models, and APIs as key enabling technologies, while synchronized co-simulation, semantic interoperability, uncertainty propagation, and long-term field validation remain major challenges. The study contributes a five-level operational maturity framework, a conceptual integrated energy–structural DT architecture, a distinction between topical co-occurrence and operational integration, and a future research roadmap for developing interoperable, scalable, and lifecycle-oriented building digital twins.

Engineering Proceedings doi: 10.3390/engproc2026150128

Authors: Adelina Ivanova Boryana Deliyska Anna Rozeva

Bioenergy (including biofuel) production and use are prerequisites for reducing greenhouse emissions and achieving sustainable development. In this work, on the basis of review and analysis of research achievements and elaborated ontologies in the field, an ontology of sustainable bioenergy is proposed. A methodology for its development includes: goals and scope definition, text corpus composition and extraction of the main concepts, controlled vocabulary and thesaurus building, ontology coding, reasoning, verification and querying. The established ontology has links to other related ontologies and is published in GitHub/Borydel/OSBE repository. Further extension of the sustainable bioenergy ontology is planned as well as its embedding in a dedicated repository.