Designs

16 pages, 4576 KiB

Open AccessArticle

EMM Project—LD GRIDS: Design of a Charged Dust Analyser for Moon Exploration

by Diego Scaccabarozzi, Abdelrahman Mohamed Ragab M. Ahmed, Andrea Appiani, Bortolino Saggin, Carmen Porto and Francesca Esposito

Designs 2025, 9(3), 70; https://doi.org/10.3390/designs9030070 - 10 Jun 2025

Abstract

This work presents a comparative design of the sensing elements for the Lunar Dust GRID System (LD GRIDS), a dust analyser conceived to measure charged particles on future lunar missions. LD GRIDS replaces traditional electrodes with continuous conductive grids, i.e., the sensing elements [...] Read more.

This work presents a comparative design of the sensing elements for the Lunar Dust GRID System (LD GRIDS), a dust analyser conceived to measure charged particles on future lunar missions. LD GRIDS replaces traditional electrodes with continuous conductive grids, i.e., the sensing elements of the instrument, which are able to collect induced charge when charged particles pass through them. The investigation focuses on evaluating the influence of various grid geometrical parameters (size, thickness, and patterns) on the sensor’s performance, either from an electrical or a mechanical perspective. All simulations were carried out using off-the-shelf numerical modelling software, where electrostatic simulation (i.e., induction performance), modal analysis, and quasi-static structural responses under a high acceleration quasi-static load were examined. The results indicate that while grids with round patterns tend to produce a higher induced charge, they also experience higher localised stresses compared to square pattern ones. Moreover, grid size does not significantly affect the instrument sensitivity, whereas increasing the grid thickness significantly reduces peak stresses, with only minor effects on electrostatic performance. Overall, the findings provided valuable insights for optimising the LD GRIDS design, aimed at balancing either electrostatic sensitivity or mechanical resistance, facing the harsh lunar environment. Full article

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24 pages, 6049 KiB

Open AccessArticle

Bayesian Optimized of CNN-M-LSTM for Thermal Comfort Prediction and Load Forecasting in Commercial Buildings

by Chi Nghiep Le, Stefan Stojcevski, Tan Ngoc Dinh, Arangarajan Vinayagam, Alex Stojcevski and Jaideep Chandran

Designs 2025, 9(3), 69; https://doi.org/10.3390/designs9030069 - 4 Jun 2025

Abstract

Heating, ventilation, and air conditioning (HVAC) systems account for 60% of the energy consumption in commercial buildings. Each year, millions of dollars are spent on electricity bills by commercial building operators. To address this energy consumption challenge, a predictive model named Bayesian optimisation [...] Read more.

Heating, ventilation, and air conditioning (HVAC) systems account for 60% of the energy consumption in commercial buildings. Each year, millions of dollars are spent on electricity bills by commercial building operators. To address this energy consumption challenge, a predictive model named Bayesian optimisation Convolution Neural Network Multivariate Long Short-term Memory (BO CNN-M-LSTM) is introduced in this research. The proposed model is designed to perform load forecasting, optimizing energy usage in commercial buildings. The CNN block extracts local features, whereas the M-LSTM captures temporal dependencies. The hyperparameter fine tuning framework applied Bayesian optimization to enhance output prediction by modifying model properties with data characteristics. Moreover, to improve occupant well-being in commercial buildings, the thermal comfort adaptive model developed by de Dear and Brager was applied to ambient temperature in the preprocessing stage. As a result, across all four datasets, the BO CNN-M-LSTM consistently outperformed other models, achieving an 8% improvement in mean percentage absolute error (MAPE), 2% in normalized root mean square error (NRMSE), and 2% in R² score.This indicates the consistent performance of BO CNN-M-LSTM under varying environmental factors, highlight the model robustness and adaptability. Hence, the BO CNN-M-LSTM model is a highly effective predictive load forecasting tool for commercial building HVAC systems. Full article

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24 pages, 3541 KiB

Open AccessArticle

Substructure Optimization for a Semi-Submersible Floating Wind Turbine Under Extreme Environmental Conditions

by Kevin Fletcher, Edem Tetteh, Eric Loth, Chris Qin and Rick Damiani

Designs 2025, 9(3), 68; https://doi.org/10.3390/designs9030068 - 3 Jun 2025

Abstract

A barrier to the adoption of floating offshore wind turbines is their high cost relative to conventional fixed-bottom wind turbines. The largest contributor to this cost disparity is generally the floating substructure, due to its large size and complexity. Typically, a primary driver [...] Read more.

A barrier to the adoption of floating offshore wind turbines is their high cost relative to conventional fixed-bottom wind turbines. The largest contributor to this cost disparity is generally the floating substructure, due to its large size and complexity. Typically, a primary driver of the geometry and size of a floating substructure is the extreme environmental load case of Region 4, where platform loads are the greatest due to the impact of extreme wind and waves. To address this cost issue, a new concept for a floating offshore wind turbine’s substructure, its moorings, and anchors was optimized for a reference 10-MW turbine under extreme load conditions using OpenFAST. The levelized cost of energy was minimized by fixing the above-water turbine design and minimizing the equivalent substructure mass, which is based on the mass of all substructure components (stem, legs, buoyancy cans, mooring, and anchoring system) and associated costs of their materials, manufacturing, and installation. A stepped optimization scheme was used to allow an understanding of their influence on both the system cost and system dynamic responses for the extreme parked load case. The design variables investigated include the length and tautness ratio of the mooring lines, length and draft of the cans, and lengths of the legs and the stem. The dynamic responses investigated include the platform pitch, platform roll, nacelle horizontal acceleration, and can submergence. Some constraints were imposed on the dynamic responses of interest, and the metacentric height of the floating system was used to ensure static stability. The results offer insight into the parametric influence on turbine motion and on the potential savings that can be achieved through optimization of individual substructure components. A 36% reduction in substructure costs was achieved while slightly improving the hydrodynamic stability in pitch and yielding a somewhat large surge motion and slight roll increase. Full article

(This article belongs to the Special Issue Design and Analysis of Offshore Wind Turbines)

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18 pages, 9335 KiB

Open AccessArticle

Image Matching Algorithm for Transmission Towers Based on CLAHE and Improved RANSAC

by Ruihua Chen, Pan Yao, Shuo Wang, Chuanlong Lyu and Yuge Xu

Designs 2025, 9(3), 67; https://doi.org/10.3390/designs9030067 - 29 May 2025

Abstract

To address the lack of robustness against illumination and blurring variations in aerial images of transmission towers, an improved image matching algorithm for aerial images is proposed. The proposed algorithm consists of two main components: an enhanced AKAZE algorithm and an improved three-stage [...] Read more.

To address the lack of robustness against illumination and blurring variations in aerial images of transmission towers, an improved image matching algorithm for aerial images is proposed. The proposed algorithm consists of two main components: an enhanced AKAZE algorithm and an improved three-stage feature matching strategy, which are used for feature point detection and feature matching, respectively. First, the improved AKAZE enhances image contrast using Contrast-Limited Adaptive Histogram Equalization (CLAHE), which highlights target features and improves robustness against environmental interference. Subsequently, the original AKAZE algorithm is employed to detect feature points and construct binary descriptors. Building upon this, an improved three-stage feature matching strategy is proposed to estimate the geometric transformation between image pairs. Specifically, the strategy begins with initial feature matching using the nearest neighbor ratio (NNR) method, followed by outlier rejection via the Grid-based Motion Statistics (GMS) algorithm. Finally, an improved Random Sample Consensus (RANSAC) algorithm computes the transformation matrix, further enhancing matching efficiency. Experimental results demonstrate that the proposed method exceeds the original AKAZE algorithm’s matching accuracy by 4∼15% on different image sets while achieving faster matching speeds. Under real-world conditions with UAV-captured aerial images of transmission towers, the proposed algorithm achieves over 95% matching accuracy, which is higher than other algorithms. Our proposed algorithm enables fast and accurate matching of transmission tower aerial images. Full article

(This article belongs to the Section Electrical Engineering Design)

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19 pages, 9237 KiB

Open AccessArticle

Mechanical Properties of 17-4 PH Stainless Steel Manufactured by Atomic Diffusion Additive Manufacturing

by Animesh Kumar Basak, Jasim Mohammed Sali and Alokesh Pramanik

Designs 2025, 9(3), 66; https://doi.org/10.3390/designs9030066 - 28 May 2025

Abstract

Atomic diffusion additive manufacturing (ADAM) is a specialized extrusion-based metal additive manufacturing (MAM) process where metal parts are produced through a three-stage process of printing, de-binding and sintering. Several scientific facts, such as dimensional error, surface quality, tensile behavior and the internal structure [...] Read more.

Atomic diffusion additive manufacturing (ADAM) is a specialized extrusion-based metal additive manufacturing (MAM) process where metal parts are produced through a three-stage process of printing, de-binding and sintering. Several scientific facts, such as dimensional error, surface quality, tensile behavior and the internal structure of this process for specific materials for certain conditions, are not well explained in the existing literature. To address these issues, the present manuscript investigates the effect of infill type and shell thickness on 17-4 precipitation-hardened (PH) stainless steels on the dimensional accuracy, surface roughness and mechanical properties of the printed specimens. It was found that the strength (maximum ultimate tensile strength up to 1049.1 MPa) and hardness (290 HRB) of the specimens mainly depend on shell thickness, while infill type plays a relatively minor role. The principle of atomic diffusion may be the reason behind this pattern, as an increase in shell thickness is essentially an increase in the density of material deposited during printing, allowing more fusion during sintering and thus increasing its strength. The two different infill types (triangular and gyroid) contribute towards minimal changes, although it should be noted that triangular specimens exhibited greater ultimate tensile strength, whereas the gyroid had slightly longer elongation at break. Dimensional accuracy and surface roughness for all the specimens remain reasonably consistent. The cross-section of the tensile tested specimens revealed significant pores in the microstructure that could contribute to a reduction in the mechanical properties of the specimens. Full article

(This article belongs to the Special Issue Post-manufacturing Testing and Characterization of Materials)

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22 pages, 1554 KiB

Open AccessArticle

Designing Sustainable Asphalt Pavement Structures with a Cement-Treated Base (CTB) and Recycled Concrete Aggregate (RCA): A Case Study from a Developing Country

by Oswaldo Guerrero-Bustamante, Rafael Camargo, Jose Duque, Gilberto Martinez-Arguelles, Rodrigo Polo-Mendoza, Carlos Acosta and Michel Murillo

Designs 2025, 9(3), 65; https://doi.org/10.3390/designs9030065 - 20 May 2025

Abstract

Pavement structures are one of the most critical civil infrastructures for the socio-economic development of communities. However, pavement construction demands an elevated financial budget and generates large amounts of environmental impacts. Accordingly, the new trends in daily engineering practices have integrated sustainability criteria [...] Read more.

Pavement structures are one of the most critical civil infrastructures for the socio-economic development of communities. However, pavement construction demands an elevated financial budget and generates large amounts of environmental impacts. Accordingly, the new trends in daily engineering practices have integrated sustainability criteria verification into traditional pavement design procedures. Thus, this research explores the sustainability implications of asphalt pavement incorporating a Cement-Treated Base (CTB) and Recycled Concrete Aggregate (RCA) within the local context of a Global South country. The environmental and economic performances of four different types of asphalt structures were assessed, each differing in how the CTB is employed. These structures include conventional flexible pavement, semi-rigid pavement, inverted base pavement, and simple composite pavement. Furthermore, each structure is evaluated under four varying contents of coarse RCA (i.e., 0%, 15%, 30%, and 45%) in their asphalt mixtures. This approach results in a comprehensive analysis spanning 16 unique scenarios, providing valuable insights into the interplay between RCA content and CTB inclusion for sustainable infrastructure development. It is important to highlight that the Life-Cycle Assessment and Life-Cycle Cost Analysis methodologies were implemented to perform the environmental and economic inspections, respectively. Overall, this investigation demonstrates that although pavement structures comply with mechanistic design standards, they can yield significantly different cost effectiveness and environmental burdens from each other. Therefore, executing a sustainability-related appraisal is essential for accomplishing definitive infrastructure designs. Consequently, this research effort is expected to be used by stakeholders (e.g., civil engineers, designers, and governmental agencies) to support data-driven decision making in the road infrastructure industry. Full article

(This article belongs to the Special Issue Sustainable Construction: Innovations in Design, Engineering, and the Circular Economy)

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21 pages, 6647 KiB

Open AccessArticle

Optimizing Beam Stiffness and Beam Modal Response with Variable Spacing and Extrusion (VaSE)

by Patrick N. Murphy, Richard A. Vittum III and Bashir Khoda

Designs 2025, 9(3), 64; https://doi.org/10.3390/designs9030064 - 19 May 2025

Abstract

This paper presents a novel algorithm, Variable Spacing and Extrusion (VaSE), designed to optimize the infill pattern of material extrusion (ME) 3D-printed parts for specified mechanical performance while ensuring manufacturability. The algorithm adjusts deposition spacing and width across layers to achieve functionally graded [...] Read more.

This paper presents a novel algorithm, Variable Spacing and Extrusion (VaSE), designed to optimize the infill pattern of material extrusion (ME) 3D-printed parts for specified mechanical performance while ensuring manufacturability. The algorithm adjusts deposition spacing and width across layers to achieve functionally graded infill distributions derived from input density maps. First, the variable line spacing algorithm is implemented by normalizing the weighted density distribution. Errors in between the desired density and the density from the line spacing are corrected with a varying extrusion width algorithm. Two application scenarios are demonstrated with the proposed VaSE algorithm. First, beam samples are optimized for flexural stiffness and tested under three-point bending, showing a 10.8–19.2% stiffness increase compared to homogeneous infill, except at low (25%) volume fractions, where local buckling dominated failure. The second scenario involves maximizing the frequency of the first three modes of beams under an induced vibration. The optimized beams, taken straight from a topology optimization algorithm performed in the ANSYS 2023 finite element software, were compared to the beams that were instead put through the VaSE algorithm after the topology optimization. While all manufactured beams underperform relative to simulation, the VaSE-optimized beams show substantial frequency gains (34–63% for the first mode, 0.82–65% for the second mode) over purely geometry-based designs, with the exception of high-mass-fraction beams. These findings highlight the significance of the VaSE algorithm in enhancing mechanical performance and extending the design space of ME additive manufacturing beyond conventional homogeneous infill strategies. Full article

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25 pages, 5202 KiB

Open AccessArticle

Hybrid Adaptive Sheep Flock Optimization and Gradient Descent Optimization for Energy Management in a Grid-Connected Microgrid

by Sri Harish Nandigam, Krishna Mohan Reddy Pothireddy, K. Nageswara Rao and Surender Reddy Salkuti

Designs 2025, 9(3), 63; https://doi.org/10.3390/designs9030063 - 16 May 2025

Abstract

Distributed generation has emerged as a viable solution to supplement traditional grid problems and lessen their negative effects on the environment worldwide. Nevertheless, distributed generation issues are unpredictable and intermittent and impede the power system’s ability to operate effectively. Moreover, the problems associated [...] Read more.

Distributed generation has emerged as a viable solution to supplement traditional grid problems and lessen their negative effects on the environment worldwide. Nevertheless, distributed generation issues are unpredictable and intermittent and impede the power system’s ability to operate effectively. Moreover, the problems associated with outliers and denial of service (DoS) attacks hinder energy management. Therefore, efficient energy management in grid-connected microgrids is critical to ensure sustainability, cost efficiency, and reliability in the presence of uncertainties, outliers, denial-of-service attacks, and false data injection attacks. This paper proposes a hybrid optimization approach that combines adaptive sheep flock optimization (ASFO) and gradient descent optimization (GDO) to address the challenges of energy dispatch and load balancing in MG. The ASFO algorithm offers robust global search capabilities to explore complex search spaces, while GDO safeguards precise local convergence to optimize the dispatch schedule and energy cost and maximize renewable energy utilization. The hybrid method ASFOGDO leverages the strengths of both algorithms to overcome the limitations of standalone approaches. Results demonstrate the efficiency of the proposed hybrid algorithm, achieving substantial improvements in energy efficiency and cost reduction compared to traditional methods like interior point optimization, gradient descent, branch and bound, and a population-based algorithm named Golden Jackal optimization. In case 1, the overall cost in scenario 1 and scenario 2 was reduced from 1620.4 rupees to 1422.84 rupees, whereas, in case 2, the total cost was reduced from 12,350 rupees to 12,017 rupees with the proposed hybrid ASFOGDO algorithm. Further, a detailed impact of attacks and outliers on scheduling, operational cost, and reliability of supply is presented in case 3. Full article

(This article belongs to the Collection Editorial Board Members’ Collection Series: Smart Energy Systems Design)

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17 pages, 9985 KiB

Open AccessArticle

Mechanical Design of a Novel Functionally Graded Lattice Structure for Long Bone Scaffolds

by Fabio Distefano, Gabriella Epasto, Mahsa Zojaji and Heidi-Lynn Ploeg

Designs 2025, 9(3), 62; https://doi.org/10.3390/designs9030062 - 16 May 2025

Abstract

Open-cellular Ti6Al4V lattice structures have found application in porous scaffolds that can match the properties of human bone, which consists of a dense cortical shell and a less-dense cancellous core with an apparent density ranging from 1.3 to 2.1 g/cm³ and 0.1 [...] Read more.

Open-cellular Ti6Al4V lattice structures have found application in porous scaffolds that can match the properties of human bone, which consists of a dense cortical shell and a less-dense cancellous core with an apparent density ranging from 1.3 to 2.1 g/cm³ and 0.1 to 1.3 g/cm³, respectively. The implantation of porous scaffolds is essential for treating large bone defects and must mimic natural bone’s geometric and mechanical behaviour. Functionally graded lattice structures offer spatial variation in mechanical properties, making them suitable for biomedical applications. While the mechanical behaviour of lattice structures is typically evaluated under compression, their flexural properties remain largely underexplored. The aim of this research is to assess the flexural rigidity of a novel lattice material, namely Triply Arranged Octagonal Rings (TAORs), with both uniform and functionally graded architectures, to reproduce the flexural properties of long bones. Titanium alloy scaffolds have been designed with a TAOR cell, whose relative densities range from 10% to 40% with full and hollow sections. Morphological considerations were carried out during the design process to obtain a scaffold geometry which complies with the optimal characteristics required to promote osteointegration. A non-linear finite element (FE) model was developed. Three- and four-point bending tests were simulated, and the results were compared with those of a bone surrogate for long bones. Scaffolds with 10% and 20% relative densities showed flexural rigidity close to that of the bone surrogate and proved to be potential candidates for application in biomedical devices for long bones. Full article

(This article belongs to the Section Bioengineering Design)

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25 pages, 3758 KiB

Open AccessArticle

An Efficient Framework for Secure Communication in Internet of Drone Networks Using Deep Computing

by Vivek Kumar Pandey, Shiv Prakash, Aditya Ranjan, Sudhanshu Kumar Jha, Xin Liu and Rajkumar Singh Rathore

Designs 2025, 9(3), 61; https://doi.org/10.3390/designs9030061 - 13 May 2025

Abstract

The rapid deployment of the Internet of Drones (IoD) across different fields has brought forth enormous security threats in real-time data communication. To overcome authentication vulnerabilities, this paper introduces a secure lightweight framework integrating deep learning-based user behavior analysis and cryptographic protocols. The [...] Read more.

The rapid deployment of the Internet of Drones (IoD) across different fields has brought forth enormous security threats in real-time data communication. To overcome authentication vulnerabilities, this paper introduces a secure lightweight framework integrating deep learning-based user behavior analysis and cryptographic protocols. The proposed framework is verified through AVISPA security verification against replay, man-in-the-middle, and impersonation attacks. Performance analysis via NS2 simulations based on changing network parameters (5–50 drones, 1–20 users, 2–8 ground stations) validates enhancements in computation overhead, authentication delay, memory usage, power consumption, and communication effectiveness in comparison with recent models such as LDAP, TAUROT, IoD-Auth, and LEMAP, thereby establishing our system as an optimal choice for safe IoD operation. Full article

(This article belongs to the Collection Editorial Board Members’ Collection Series: Drone Design)

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25 pages, 25281 KiB

Open AccessArticle

Blending Nature with Technology: Integrating NBSs with RESs to Foster Carbon-Neutral Cities

by Anastasia Panori, Nicos Komninos, Dionysis Latinopoulos, Ilektra Papadaki, Elisavet Gkitsa and Paraskevi Tarani

Designs 2025, 9(3), 60; https://doi.org/10.3390/designs9030060 - 9 May 2025

Abstract

Nature-based solutions (NBSs) offer a promising framework for addressing urban environmental challenges while also enhancing social and economic resilience. As cities seek to achieve carbon neutrality, the integration of NBSs with renewable energy sources (RESs) presents both an opportunity and a challenge, requiring [...] Read more.

Nature-based solutions (NBSs) offer a promising framework for addressing urban environmental challenges while also enhancing social and economic resilience. As cities seek to achieve carbon neutrality, the integration of NBSs with renewable energy sources (RESs) presents both an opportunity and a challenge, requiring an interdisciplinary approach and an innovative planning strategy. This study aims to explore potential ways of achieving synergies between NBSs and RESs to contribute to urban resilience and climate neutrality. Focusing on the railway station district in western Thessaloniki (Greece), this research is situated within the ReGenWest project, part of the EU Cities Mission. This study develops a comprehensive, well-structured framework for integrating NBSs and RESs, drawing on principles of urban planning and energy systems to address the area’s specific spatial and ecological characteristics. Using the diverse typologies of open spaces in the district as a foundation, this research analyzes the potential for combining NBSs with RESs, such as green roofs with photovoltaic panels, solar-powered lighting, and solar parking shaders, while assessing the resulting impacts on ecosystem services. The findings reveal consistent benefits for cultural and regulatory services across all interventions, with provisioning and supporting services varying according to the specific solution applied. In addition, this study identifies larger-scale opportunities for integration, including the incorporation of NBSs and RESs into green and blue corridors and metropolitan mobility infrastructures and the development of virtual power plants to enable smart, decentralized energy management. A critical component of the proposed strategy is the implementation of an environmental monitoring system that combines hardware installation, real-time data collection and visualization, and citizen participation. Aligning NBS–RES integration with Positive Energy Districts is another aspect that is stressed in this paper, as achieving carbon neutrality demands broader systemic transformations. This approach supports iterative, adaptive planning processes that enhance the efficiency and responsiveness of NBS–RES integration in urban regeneration efforts. Full article

(This article belongs to the Special Issue Design and Applications of Positive Energy Districts)

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20 pages, 15690 KiB

Open AccessArticle

Taguchi’s L₁₈ Design of Experiments for Investigating the Effects of Cutting Parameters on Surface Integrity in X5CrNi18-10 Turning

by Csaba Felhő, Tanuj Namboodri and Raghawendra Pratap Singh Sisodia

Designs 2025, 9(3), 59; https://doi.org/10.3390/designs9030059 - 8 May 2025

Abstract

X5CrNi18-10 is becoming highly popular due to its excellent properties like corrosion resistance and high toughness. These properties make it difficult to machine and reach a surface finish with high precision and class accuracy, which the automotive and marine industries require. Manufacturers can [...] Read more.

X5CrNi18-10 is becoming highly popular due to its excellent properties like corrosion resistance and high toughness. These properties make it difficult to machine and reach a surface finish with high precision and class accuracy, which the automotive and marine industries require. Manufacturers can achieve a high-quality surface finish by analyzing surface integrity. This research aims to understand the effect of cutting parameters on surface integrity and highlight the parameters that provide good results. This study uses Taguchi’s L₁₈ orthogonal array (OA) to examine the effects of cutting parameters and their impact on surface integrity. To completely understand the results, correlation analysis, confocal microscopy, light optical microscopy, and microhardness analysis were performed to analyze the effects of cutting parameters on the surface integrity. Results suggest that depth of cut (DOC) and cutting speed (v_c) have minimal effect, while feed rate (f) has more effects on the surface quality. In correlation analysis, it was found that feed rate influences arithmetic average surface roughness (R_a) and mean surface roughness depth (R_z). It can be concluded that v_c—300 m/min, DOC (a_p)—0.5 mm, and f—0.08 mm/rev provide good results in turning X5CrNi18-10. Full article

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29 pages, 4751 KiB

Open AccessArticle

Development of Impact Factors Reverse Analysis Method for Software Complexes’ Support Automation

by Andrii Pukach, Vasyl Teslyuk, Nataliia Lysa and Liubomyr Sikora

Designs 2025, 9(3), 58; https://doi.org/10.3390/designs9030058 - 8 May 2025

Abstract

This research represents a corresponding and developed specialized impact factors reverse analysis method for software complexes’ support automation; it is intended for the analysis of impact factors affecting the supported software’s (or processes of its comprehensive support) subjective perception results, as one of [...] Read more.

This research represents a corresponding and developed specialized impact factors reverse analysis method for software complexes’ support automation; it is intended for the analysis of impact factors affecting the supported software’s (or processes of its comprehensive support) subjective perception results, as one of the constituent tasks of the more complex problem of software complexes’ support automation. The developed method provides the possibility to restore certain boundaries of impact factors by classifying the multilayer perceptron’s hidden layer neurons and calculating the probability coefficients of the belonging of these neurons to the corresponding specific pre-determined impact factors. The problem of determining the influence of impact factors on the subjective perception of the object of support (the supported software or the processes of its comprehensive support) by the relevant subjects (interacting with this object, providing and implementing its support) was resolved through the approach developed and proposed by the authors in the scope of this research. A key feature of the proposed approach is to assign the neurons of the hidden layers (of the multilayer perceptron type of artificial neural networks) functional–semantic meaning(s), which they have been deprived of a priori, performing (before this) by default an exclusively operational (calculation) function mainly for the correctness of the training and functioning of the multilayer perceptron itself. The potential of the developed method allows us to apply it for solving a huge number of applied practical tasks, such as the one provided in the scope of this research, which is as follows: a practical task of the support team members’ portrait determination, followed by a further search (detection) of the interchangeable members of this support team to ensure the possibility of quick transfer of the stack of tickets (which are in the middle of the active resolution process) between these members. Full article

(This article belongs to the Special Issue Mixture of Human and Machine Intelligence in Digital Manufacturing)

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13 pages, 1401 KiB

Open AccessArticle

Design of a Knife Mill with a Drying Adaptation for Lignocellulose Biomass Milling: Peapods and Coffee Cherry

by Paula Andrea Ramírez Cabrera, Alejandra Sophia Lozano Pérez and Carlos Alberto Guerrero Fajardo

Designs 2025, 9(3), 57; https://doi.org/10.3390/designs9030057 - 4 May 2025

Abstract

Effective grinding of residual agricultural materials helps to improve yield in the production of chemical compounds through hydrothermal technology. Milling pretreatment has different types of pre-treatment where ball mills, roller mills, and finally, the knife mill stand out. The knife mill being a [...] Read more.

Effective grinding of residual agricultural materials helps to improve yield in the production of chemical compounds through hydrothermal technology. Milling pretreatment has different types of pre-treatment where ball mills, roller mills, and finally, the knife mill stand out. The knife mill being a mill with continuous processing, its multiple benefits and contributions highlight the knife milling process; however, it is a process that is generally carried out with dry biomass that generates extra processing of the biomass before grinding, implying longer times and wear than other equipment. This work presents the design of a knife mill with an adaptation of free convection drying as a joint process of knife milling and drying. The design is based on lignocellulosic biomass, and the knife milling results are presented for two biomasses: peapods and coffee cherries. The knife mill is designed with a motor, a housing with an integrated drive system, followed by a knife system and a feeding system with a housing and finally the free convection drying system achieving particle sizes in these biomasses smaller than 30 mm, depending on the time processed. The data demonstrate the significant impact of particle size on the yields of various platform chemicals obtained from coffee cherry and peapod waste biomass. For coffee cherry biomass, smaller particle sizes, especially 0.5 mm, result in higher total yields compared to larger sizes while for peapod biomass at the smallest particle size of 0.5 mm, the total yield is the highest, at 45.13%, with notable contributions from sugar (15.63%) and formic acid (19.14%). Full article

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28 pages, 7146 KiB

Open AccessArticle

Dual-Level Fault-Tolerant FPGA-Based Flexible Manufacturing System

by Gehad I. Alkady, Ramez M. Daoud, Hassanein H. Amer, Yves Sallez and Hani F. Ragai

Designs 2025, 9(3), 56; https://doi.org/10.3390/designs9030056 - 2 May 2025

Abstract

This paper proposes a fault-tolerant flexible manufacturing system (FMS) that features a dual-level fault tolerance mechanism at both the workcell and system levels to enhance reliability. The workcell controller was implemented on a Field Programmable Gate Array (FPGA). Reconfigurable duplication was used as [...] Read more.

This paper proposes a fault-tolerant flexible manufacturing system (FMS) that features a dual-level fault tolerance mechanism at both the workcell and system levels to enhance reliability. The workcell controller was implemented on a Field Programmable Gate Array (FPGA). Reconfigurable duplication was used as the first level of fault tolerance at the workcell level. It was shown how to detect and recover from FPGA faults such as Single Event Upsets (SEUs), hard faults, and Single Event Functional Interrupts (SEFIs). The prototype of the workcell controller was successfully implemented using two Zybo Z7-20 AMD boards and an Arduino DUE. Petri Nets were used to prove that controller reliability increased by 346% after 1440 operational hours. The second level of fault tolerance was at the FMS level; the Supervisor (SUP) took over the responsibilities of any malfunctioning workcell controller. Riverbed software was used to prove that the system successfully met the end-to-end delay requirements. Finally, Matlab showed that there is a further increase in performability. Full article

(This article belongs to the Topic Digital Manufacturing Technology)

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Graphical abstract

24 pages, 2269 KiB

Open AccessReview

A Review of the Performance of Smart Lawnmower Development: Theoretical and Practical Implications

by Elwin Nesan Selvanesan, Kia Wai Liew, Chai Hua Tay, Jian Ai Yeow, Yu Jin Ng, Peng Lean Chong and Chun Quan Kang

Designs 2025, 9(3), 55; https://doi.org/10.3390/designs9030055 - 2 May 2025

Abstract

Smart lawnmowers are becoming increasingly integrated into daily life as their performance continues to improve. To ensure consistent advancement, it is important to conduct a comprehensive analysis of the performance of various modern smart lawnmowers. However, there appears to be a lack of [...] Read more.

Smart lawnmowers are becoming increasingly integrated into daily life as their performance continues to improve. To ensure consistent advancement, it is important to conduct a comprehensive analysis of the performance of various modern smart lawnmowers. However, there appears to be a lack of thorough performance evaluation and analysis of their broader impact. This review explores the key performance indicators influencing smart lawnmower performance, particularly in navigation and obstacle avoidance, operational efficiency, and human–machine interaction (HMI). Key performance indicators identified for evaluation include operating time, Effective Field Capacity (FCe), and field efficiency (%). Additionally, it examines the theoretical and practical implications of smart lawnmower development. Smart lawnmowers have been found to contribute to advancements in machine learning algorithms and possibly swarm robotics. Environmental benefits, such as reduced emissions and noise pollution, were also highlighted in this review. Future research directions are discussed, both in the short and long term, to further optimize smart lawnmower performance. This review serves as a foundation for future studies and experimental investigations aimed at enhancing the real-world applicability of smart lawnmowers. Full article

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23 pages, 4964 KiB

Open AccessArticle

Artificial-Intelligence-Based Prediction of Crack and Shrinkage Intensity Factor in Clay Soils During Desiccation

by Abolfazl Baghbani, Tanveer Choudhury and Susanga Costa

Designs 2025, 9(3), 54; https://doi.org/10.3390/designs9030054 - 29 Apr 2025

Abstract

Desiccation-induced cracking in clay soils significantly affects the structural performance and durability of geotechnical systems. This study presents a data-driven approach to predict the Crack and Shrinkage Intensity Factor (CSIF), a comprehensive index quantifying both crack formation and shrinkage behavior in drying soils. [...] Read more.

Desiccation-induced cracking in clay soils significantly affects the structural performance and durability of geotechnical systems. This study presents a data-driven approach to predict the Crack and Shrinkage Intensity Factor (CSIF), a comprehensive index quantifying both crack formation and shrinkage behavior in drying soils. A database of 100 controlled desiccation tests was developed using five clay mixtures with varying plasticity indices, which were subjected to a range of drying rates, soil thicknesses and initial conditions. Four predictive models—Multiple Linear Regression (MLR), Classification and Regression Random Forest (CRRF), Artificial Neural Network (ANN) and Genetic Programming (GP)—were evaluated. The ANN model using Bayesian Regularization demonstrated superior performance (R = 0.99, MAE = 5.44), followed by CRRF and symbolic GP equations. Sensitivity analysis identified drying rate and soil thickness as the most influential parameters, while initial moisture content and ambient conditions were found to be redundant when the drying rate was included. This study not only advances the predictive modeling of desiccation cracking but also introduces interpretable equations for practical engineering uses. The developed models offer valuable tools for crack risk assessment in clay liners, soil covers and expansive soil foundations. Full article

(This article belongs to the Special Issue Innovative Approaches in Infrastructure Design, Resilience, and Maintenance)

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21 pages, 7921 KiB

Open AccessArticle

Modeling and Research of the Process of Bench Tests of Plunger Hydraulic Cylinders with Energy Recovery

by Alexander Rybak, Besarion Meskhi, Dmitry Rudoy, Anastasiya Olshevskaya, Svetlana Teplyakova, Yuliya Serdyukova and Alexey Pelipenko

Designs 2025, 9(3), 53; https://doi.org/10.3390/designs9030053 - 29 Apr 2025

Abstract

The practice of operating hydraulic machines and equipment shows that failures can occur earlier than the specified lifespan. At the same time, at the stage of carrying out strength calculations of the designed machines and equipment, significant safety margins are incorporated into parts [...] Read more.

The practice of operating hydraulic machines and equipment shows that failures can occur earlier than the specified lifespan. At the same time, at the stage of carrying out strength calculations of the designed machines and equipment, significant safety margins are incorporated into parts and units. That is, calculated machine lifespans often exceed actual values. Accurate data require full-scale lifespan testing or observations of operation. However, resource tests are economically expensive, since they require a significant amount of energy, and, as a result, lead to a negative impact on the environment. It is possible to level out the listed shortcomings during resource tests by using energy-efficient and energy-saving technologies, such as energy recovery. This study enhances energy efficiency and assesses engineering systems during equipment design. In particular, we present a hydromechanical drive design for testing reciprocating hydraulic machines. The study analyzes energy-saving and energy recovery methods during operation. On the basis of the analysis and previously conducted studies, we developed a mathematical model for hydraulic equipment testing. The developed model is based on the volumetric stiffness theory, enabling analysis of the design and functional characteristics of test stand components on their dynamic behavior and energy efficiency. Full article

(This article belongs to the Topic Digital Manufacturing Technology)

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39 pages, 15451 KiB

Open AccessArticle

Monitoring Occupant Posture Using a Standardized Sensor Interface with a Vehicle Seat

by Alberto Vergnano, Alessandro Pelizzari, Claudio Giorgianni, Jan Kovanda, Alessandro Zimmer, Joed Lopes da Silva, Hamed Rezvanpour and Francesco Leali

Designs 2025, 9(2), 52; https://doi.org/10.3390/designs9020052 - 20 Apr 2025

Abstract

Car safety can be enhanced by enabling the Airbag Control Unit (ACU) to adaptively deploy different charges based on the occupant’s position once the crash occurs. In this context, monitoring the occupant’s position using a sensorized seat integrated with an Inertial Measurement Unit [...] Read more.

Car safety can be enhanced by enabling the Airbag Control Unit (ACU) to adaptively deploy different charges based on the occupant’s position once the crash occurs. In this context, monitoring the occupant’s position using a sensorized seat integrated with an Inertial Measurement Unit (IMU) offers a practical and cost-effective solution. However, certain challenges still need to be addressed. The adoption of sensorized seats in research and vehicle set-up is still under consideration. This study investigates an interface device that can be reconfigured to suit almost any seat model. This reconfigurability makes it easily adaptable to new vehicles under development and applicable to any passenger seat in the vehicle. This paper details the device’s design, including its programming using calibration and monitoring features, which significantly improves its reliability compared to earlier prototypes. Extensive testing through real driving experiments with multiple participants demonstrated an accuracy range of 45–100%. The testing involved both drivers and passengers, showcasing the device’s ability to effectively monitor various in-car scenarios. Full article

(This article belongs to the Collection Editorial Board Members’ Collection Series: Designs of New Generation Vehicles)

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