Applied Sciences

18 pages, 347 KB

Open AccessArticle

Comparing Extraction Techniques and Varieties in Grape Stems: A Chemical Assessment of Antioxidant Phenolics

by Gloria Domínguez-Rodríguez, Juan Antonio Nieto, Susana Santoyo and Laura Jaime

Appl. Sci. 2026, 16(2), 877; https://doi.org/10.3390/app16020877 (registering DOI) - 14 Jan 2026

Grape stems are undervalued winemaking by-products that constitute a promising source of bioactive phenolics with notable antioxidant potential and diverse industrial applications, including food preservation, cosmetics, and pharmaceuticals. Effective valorisation of this resource requires not only efficient extraction strategies, but also the strategic [...] Read more.

Grape stems are undervalued winemaking by-products that constitute a promising source of bioactive phenolics with notable antioxidant potential and diverse industrial applications, including food preservation, cosmetics, and pharmaceuticals. Effective valorisation of this resource requires not only efficient extraction strategies, but also the strategic selection of grape stem varieties to tailor phenolic profiles for specific high-value uses. In this study, a comparative assessment of three extraction techniques, pressurized liquid extraction (PLE), ultrasound-assisted extraction (UAE), and conventional solid–liquid extraction (SLE), across six grape stem varieties was conducted. By integrating spectrophotometric analyses of total phenolics and antioxidant capacity with HPLC-DAD profiling of individual phenolic compounds, the combined influence of extraction method and varietal composition on phenolic recovery was demonstrated. PLE and UAE significantly enhanced both yield and antioxidant capacity relative to SLE, with PLE providing the broadest spectrum of phenolic compounds. Varietal differences were also pronounced; e.g., Cabernet Sauvignon stems yielded higher antioxidant phenolic compound content, particularly under UAE, reinforcing the importance of aligning extraction technique and stem variety with the intended functional application. Full article

(This article belongs to the Special Issue Sustainable Recovery of Bioactive Compounds from Food Industry By-Products)

18 pages, 797 KB

Open AccessArticle

BI-GBDT: A Graph-Free Behavioral Interaction-Aware Gradient Boosting Framework for Fraud Detection in Large-Scale Payment Systems

by Mustafa Berk Keles and Mehmet Gokturk

Appl. Sci. 2026, 16(2), 876; https://doi.org/10.3390/app16020876 (registering DOI) - 14 Jan 2026

Abstract

Detecting fraudulent and anomalous transactions in large-scale digital payment systems is significantly challenging due to severe class imbalance and the fact that transactional risk is tightly coupled to the historical interactions and behaviors of transacting parties. In this study, a scalable Behavioral Interaction-Aware [...] Read more.

Detecting fraudulent and anomalous transactions in large-scale digital payment systems is significantly challenging due to severe class imbalance and the fact that transactional risk is tightly coupled to the historical interactions and behaviors of transacting parties. In this study, a scalable Behavioral Interaction-Aware Gradient Boosting (BI-GBDT) framework is proposed for anomaly detection in tabular transaction data to overcome these challenges. The methodology models sending and receiving behaviors separately through direction-specific clustering based on transaction frequency and amount. Each transaction is characterized by cluster-pair prevalence ratios, which capture the population-level prevalence of sender–receiver interaction patterns. To handle extreme class imbalance, all transactions are clustered, and a cluster-level risk score is computed as the ratio of anomalous transactions to the total number of transactions within each cluster. This score is incorporated as a feature, serving as a behavioral risk prior highlighting concentrated anomaly. These interaction-aware features are integrated into a GBDT in a big data environment. Experiments were conducted on a large masked real-world payment dataset spanning six months and containing more than 456 million transactions, with the prediction task defined as binary classification between fraudulent and non-fraudulent transactions. Unlike standard GBDT models trained only on transactional attributes and graph-based approaches, BI-GBDT captures sender–receiver interaction patterns in a graph-free manner and outperforms a baseline GBDT, reducing the false positive rate from 37.0% to 4.3%, increasing recall from 52.3% to 72.0%, and improving accuracy from 63.0% to 95.7%. Full article

(This article belongs to the Special Issue Machine Learning and Its Application for Anomaly Detection)

19 pages, 1945 KB

Open AccessArticle

Deep Learning for Building Attribute Classification from Street-View Images for Seismic Exposure Modeling

by Rajesh Kumar, Claudio Rota, Flavio Piccoli and Gianluigi Ciocca

Appl. Sci. 2026, 16(2), 875; https://doi.org/10.3390/app16020875 (registering DOI) - 14 Jan 2026

Abstract

Exposure models are essential for seismic risk assessment to determine environmental vulnerabilities during earthquakes. However, developing these models at scale is challenging because it relies on manual inspection of buildings, which increases costs and introduces significant delays. Developing fast, consistent, and easy-to-deploy automated [...] Read more.

Exposure models are essential for seismic risk assessment to determine environmental vulnerabilities during earthquakes. However, developing these models at scale is challenging because it relies on manual inspection of buildings, which increases costs and introduces significant delays. Developing fast, consistent, and easy-to-deploy automated methods to support this process has become a priority. In this study, we investigate the use of deep learning to accelerate the classification of architectural and structural attributes from street-view imagery. Using the Alvalade dataset, which contains 4007 buildings annotated with 10 multi-class attributes, we evaluated the performance of multiple architecture types. Our analysis shows that deep learning models can successfully extract key structural features, achieving an average macro accuracy of 57%, and a Precision, Recall, and F1-score of 61%, 57%, and 56%, respectively. We also show that prediction quality is further improved by leveraging multi-view imagery of the target buildings. These results demonstrate that deep learning can be an effective solution to reduce the manual effort required for the development of reliable large-scale exposure models, offering a practical solution toward more efficient seismic risk assessment. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

22 pages, 17055 KB

Open AccessArticle

Effects of Wheel-Ground Conditions on Racing Car Aerodynamics Under Ride-Height-Related Attitude Variations

by Xiaojing Ma, Jie Li, Kun Zhang, Yi Zou and Matteo Massaro

Appl. Sci. 2026, 16(2), 874; https://doi.org/10.3390/app16020874 - 14 Jan 2026

Abstract

In racing cars, a low ride height is crucial for inverted wings and ground-effect systems to function effectively, significantly enhancing aerodynamic performance but also increasing sensitivity to pitch and roll variations. However, the specific impact of wheel-ground conditions on racing cars under ride-height-related [...] Read more.

In racing cars, a low ride height is crucial for inverted wings and ground-effect systems to function effectively, significantly enhancing aerodynamic performance but also increasing sensitivity to pitch and roll variations. However, the specific impact of wheel-ground conditions on racing cars under ride-height-related attitude variations has not received attention. This study employed numerical simulations (compared with wind tunnel test data) to investigate these effects on racecar aerodynamic characteristics, analyzing three specific wheel-ground combinations: moving ground with rotating wheels (MR), moving ground with stationary wheels (MS), and stationary ground with stationary wheels (SS). A systematic analysis was conducted on aerodynamic changes associated with wheel-plane total pressure coefficient differences, upper-lower surface pressure coefficient variations, and front-rear axle aerodynamic force distributions, elucidating individual component contributions to overall performance changes induced by wheel-ground alterations. Results indicate that wheel conditions, especially rear wheels and their localized interactions with the diffuser-equipped body predominantly influence drag. In contrast, ground conditions primarily affect the body and front wing to alter downforce, with induced drag variations further amplifying total drag differences. Moreover, ground conditions’ impact on the front wing is modulated by vehicle attitude, resulting in either increased or decreased front wing downforce and thus altering aerodynamic balance. These insights highlight that ride-height related attitudes are critical variables when evaluating combined wheel-ground effects, and while wheel rotation is significant, the aerodynamic force and balance changes induced by ground conditions (as modulated by attitude) warrant greater attention. This understanding provides valuable guidance for racecar aerodynamic design. Full article

(This article belongs to the Section Fluid Science and Technology)

24 pages, 3727 KB

Open AccessArticle

Secure and Efficient Authentication Protocol for Underwater Wireless Sensor Network Environments Using PUF

by Jinsu Ahn, Deokkyu Kwon and Youngho Park

Appl. Sci. 2026, 16(2), 873; https://doi.org/10.3390/app16020873 - 14 Jan 2026

Abstract

Underwater wireless sensor networks (UWSNs) are increasingly used in marine monitoring and naval coastal surveillance, where limited bandwidth, long propagation delays, and physically exposed nodes make efficient authentication critical. This paper analyzes the maritime-surveillance-oriented protocol of Jain and Hussain and identifies vulnerabilities to [...] Read more.

Underwater wireless sensor networks (UWSNs) are increasingly used in marine monitoring and naval coastal surveillance, where limited bandwidth, long propagation delays, and physically exposed nodes make efficient authentication critical. This paper analyzes the maritime-surveillance-oriented protocol of Jain and Hussain and identifies vulnerabilities to physical capture, replay, and denial-of-service (DoS) attacks. We propose a PUF-assisted mutual authentication and session key agreement protocol for UWSNs. The design relies on lightweight symmetric primitives (one-way hash and XOR) and uses a fuzzy extractor to support stable PUF-based key material. In addition, a lightweight continuous authentication procedure is introduced to facilitate fast re-authentication under intermittent link disruptions commonly observed in underwater communication. Security is evaluated using BAN logic, the Real-or-Random (ROR) model, and security verification with the Scyther tool. An analytical overhead evaluation reports a computational cost of 5.972 ms per mutual authentication and a 1152-bit communication overhead, supporting a practical security–efficiency trade-off for resource-constrained UWSN deployments. Full article

(This article belongs to the Special Issue Recent Research and New Challenges in Underwater Communications and Wireless Sensor Networks)

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23 pages, 5568 KB

Open AccessArticle

The Effect of Dynamic Injurious Axial Impact on Human Cervical Intervertebral Disc Pressure Response: Methodology & Initial Results

by Sara Sochor, Mark R. Sochor, Juan M. Asensio-Gil, Carlos Rodríguez-Morcillo García and Francisco J. Lopez-Valdes

Appl. Sci. 2026, 16(2), 872; https://doi.org/10.3390/app16020872 - 14 Jan 2026

Abstract

Cervical spine (c-spine) injuries are a prominent concern in sporting activities, and dynamic axial (i.e., head-first) impacts are associated with a high risk of c-spine trauma. This methodology study implanted pressure sensors in post-mortem human subject (PMHS) cervical intervertebral discs (CIVDs) to assess [...] Read more.

Cervical spine (c-spine) injuries are a prominent concern in sporting activities, and dynamic axial (i.e., head-first) impacts are associated with a high risk of c-spine trauma. This methodology study implanted pressure sensors in post-mortem human subject (PMHS) cervical intervertebral discs (CIVDs) to assess biomechanical response and disc pressure changes during dynamic injurious axial impacts. Two fresh frozen male head–neck PMHS (cephalus with complete c-spine) were instrumented with miniature pressure sensors (Model 060S, Precision Measurement Company, Ann Arbor, MI, USA) at three CIVD levels (upper, middle, and lower c-spine). Experiments replicated the Nightingale et al. studies, simulating a rigid unconstrained head vertex (0°) axial impact. PMHS were raised to a drop height of 0.53 m to reach the desired impact velocity of ~3.2 m/s and were allowed to drop vertically. Results showed characteristic c-spine deformations/buckling motion patterns and marked CIVD pressure differences between CIVD levels. The more cranial (C2–C4) and caudal (C6–T1) CIVD exhibited greater and more comparable pressure values than those of the mid-spine (C4–C6), and the pressure in upper/lower levels was at least ~four to six times higher than that of the middle. This study establishes the feasibility and assesses the potential of CIVD pressure as a biomechanical metric for assessing injurious axial loading and contributes a novel experimental framework for future injury tolerance research and model validation. Full article

(This article belongs to the Special Issue Sports Biomechanics and Injury Prevention)

37 pages, 12417 KB

Open AccessArticle

Rate-Dependent Fracturing Mechanisms of Granite Under Different Levels of Initial Damage

by Chunde Ma, Chenyang Li, Wenyuan Yang, Chenyu Wang, Qiang Gong and Hongbo Zhou

Appl. Sci. 2026, 16(2), 871; https://doi.org/10.3390/app16020871 - 14 Jan 2026

Abstract

Excavation of underground spaces often causes significant initial damage to surrounding rock, which can notably alter its mechanical properties. However, most studies on loading rate effects neglect the role of initial damage. This study investigates how initial damage and loading rate together affect [...] Read more.

Excavation of underground spaces often causes significant initial damage to surrounding rock, which can notably alter its mechanical properties. However, most studies on loading rate effects neglect the role of initial damage. This study investigates how initial damage and loading rate together affect granite’s mechanical behavior and fracturing characteristics. Granite specimens with different initial damage levels were subjected to uniaxial compression at varying loading rates to assess their mechanical parameters, stress thresholds, failure modes, energy evolution, and associated acoustic emission (AE) activity. Results indicate that granite’s mechanical behavior exhibits greater sensitivity to loading rate than to initial damage. As the loading rate increases, both strength and elastic modulus initially decrease and then rise, while the dissipated-to-input energy ratio reaches a maximum when the strength is at its lowest. This phenomenon occurs because, when cracks are allowed to fully develop, a relatively higher loading rate increases the likelihood of crack initiation and propagation, thereby reducing strength. The AE responses of initial damage granite samples (IDGSs), including counts, RA/AF value, b-value, and entropy, exhibit stage-dependent variations and contain precursory information before failure. Moreover, AE signals display multifractal characteristics across different loading rates. These findings reveal the mechanisms underlying granite’s mechanical response when both initial damage and loading rate act together: initial damage primarily affects the complexity and number of local microcracks, while loading rate determines the dominant crack initiation and propagation modes. Moreover, how the failure time of IDGSs varies with loading rate can be described by an inverse exponential function. These findings enhance insight into the coupling mechanism of initial damage and loading rate, with significant implications for failure warning and the cost-effectiveness of underground excavation. Full article

20 pages, 2984 KB

Open AccessArticle

Demagnetization Fault Location of Direct-Drive Permanent Magnet Synchronous Motor Based on Search Coil Data-Driven

by Caixia Gao, Zhen Jiang, Xiaozhuo Xu and Jikai Si

Appl. Sci. 2026, 16(2), 870; https://doi.org/10.3390/app16020870 - 14 Jan 2026

Abstract

Demagnetization faults in direct-drive permanent magnet synchronous motors (DDPMSM) can cause significant performance degradation and unplanned downtime. Traditional fault location methods, which rely on manual feature extraction, exhibit limited accuracy and efficiency in complex and variable operating conditions. To address these limitations, this [...] Read more.

Demagnetization faults in direct-drive permanent magnet synchronous motors (DDPMSM) can cause significant performance degradation and unplanned downtime. Traditional fault location methods, which rely on manual feature extraction, exhibit limited accuracy and efficiency in complex and variable operating conditions. To address these limitations, this study presents a demagnetization fault location method based on a search coil employing a data-driven one-dimensional convolutional neural network (1D-CNN). Firstly, the arrangement of search coils was determined, and a partitioned mathematical model was established, using the residual back electromotive force (back-EMF) of the search coil over a single electrical cycle as the fundamental unit. Secondly, the residual back-EMF in the search coil is analyzed under various demagnetization parameters and operating conditions to assess the robustness of the proposed method. Furthermore, a 1D-CNN-based fault location model was developed using residual back-EMF signals as the input and targeting the identification of demagnetized permanent magnet types. Simulation and experimental results demonstrate that the proposed method can effectively detect and locate demagnetization faults across different operating conditions. When the demagnetization degree is not less than 10%, the fault location accuracy reaches 99.58%, and the minimum detectable demagnetization degree is 8%. The approach demonstrates excellent robustness and generalization, offering an intelligent solution for demagnetization fault location in PMSMs. Full article

(This article belongs to the Special Issue Fault Diagnosis for Electrical Machines, Power Electronics, and Drives)

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19 pages, 1131 KB

Open AccessArticle

Competitiveness Analysis and Freight Volume Forecast of High-Speed Rail Express: A Case Study of China

by Liwei Xie and Lei Dai

Appl. Sci. 2026, 16(2), 869; https://doi.org/10.3390/app16020869 - 14 Jan 2026

Abstract

To assess the market competitiveness of high-speed rail (HSR) express and forecast its freight volume, this paper develops an integrated framework combining strategic analysis, market forecasting, and competition assessment. A hybrid SWOT-AHP model identifies and quantifies key strategic factors, clarifying HSR express positioning. [...] Read more.

To assess the market competitiveness of high-speed rail (HSR) express and forecast its freight volume, this paper develops an integrated framework combining strategic analysis, market forecasting, and competition assessment. A hybrid SWOT-AHP model identifies and quantifies key strategic factors, clarifying HSR express positioning. Considering macroeconomic and consumption factors, a GM(1,N) model forecasts intercity express volume. Based on a generalized cost function covering timeliness, economy, safety, and stability, an improved Logit model calculates HSR’s mode share against road and air express, deriving future HSR freight volume. Using China as a case study, results show: (1) A proactive strategy leveraging intrinsic strengths is recommended, supported by rapid intercity express growth; (2) HSR can capture over 20% mode share initially, showing strong competitiveness in medium-long distance transport; (3) Transport cost is the most sensitive factor, a 20% reduction raises mode share by 10%, while rising timeliness demands enhance long distance advantages. This study offers a quantitative basis for HSR express strategic planning. Full article

(This article belongs to the Special Issue Advances in Land, Rail and Maritime Transport and in City Logistics)

26 pages, 4843 KB

Open AccessArticle

Selection of Rotor Geometry to Minimize the Contribution of Stator Slot Harmonics to the Torque Ripple of a SynRM Motor

by Zbigniew Gmyrek

Appl. Sci. 2026, 16(2), 868; https://doi.org/10.3390/app16020868 - 14 Jan 2026

Abstract

This article discusses the process of determining the shape and size of flux barriers in the rotor of a SynRM motor. This approach aims to reduce the contribution of stator slot harmonics to torque ripple. The research object was a low-power motor with [...] Read more.

This article discusses the process of determining the shape and size of flux barriers in the rotor of a SynRM motor. This approach aims to reduce the contribution of stator slot harmonics to torque ripple. The research object was a low-power motor with compact geometric dimensions, in which the previously used salient-pole rotor was modified. The study investigated the influence of the stator lamination form on the generation of higher torque harmonics, as well as the contribution of induced stator slot harmonics. The whole investigation found that by properly selecting the shape and size of the flux barriers, stator slot harmonics’ contribution to torque ripple may be significantly reduced. Full article

(This article belongs to the Collection Modeling, Design and Control of Electric Machines: Volume II)

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20 pages, 8641 KB

Open AccessArticle

A Novel Stochastic Finite Element Model Updating Method Based on Multi-Point Sensitivities

by Zheng Yang, Zhiyu Shi and Jinyan Li

Appl. Sci. 2026, 16(2), 867; https://doi.org/10.3390/app16020867 - 14 Jan 2026

Abstract

A novel stochastic finite element model updating method based on multi-point sensitivities is proposed to improve the reproduction and prediction ability of finite element models for experimental data. Drawing upon the theory of small perturbations, this approach employs the sensitivity matrix in conjunction [...] Read more.

A novel stochastic finite element model updating method based on multi-point sensitivities is proposed to improve the reproduction and prediction ability of finite element models for experimental data. Drawing upon the theory of small perturbations, this approach employs the sensitivity matrix in conjunction with the probability distribution of responses evaluated at multiple parameter points to determine the probability density associated with each parameter point and to estimate the statistical properties of the parameters. To achieve this objective, principal component analysis is employed to unify the dimensionality of the parameters and the responses; the least squares method was used to estimate the characteristics of the parameters. The reliability and validity of this method were confirmed through experimentation with a 3-degree-of-freedom spring-mass system and an aerospace thermal insulation structure. A comparison of this method with classical methods reveals significant advantages in terms of robustness across varying computational scales. Notably, it attains superior accuracy with smaller sample sizes while maintaining precision comparable to conventional methods with large samples. Consequently, this characteristic confers upon the method a distinct advantage in scenarios where the costs of finite element computation are prohibitively high. Full article

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19 pages, 3167 KB

Open AccessArticle

A Novel Synergistic System for Geothermal Energy Extraction and Coal Seam Cooling in Deep Coal Mine Aquifers: A Numerical Simulation Study

by Yuliang Sun, Hongtao An and Xuehua Li

Appl. Sci. 2026, 16(2), 866; https://doi.org/10.3390/app16020866 - 14 Jan 2026

Abstract

As shallow coal resources become increasingly depleted, coal mining is extending to greater depths, making mine thermal hazards an increasingly prominent issue. This paper proposes a novel system for synergistic geothermal energy extraction from deep coal mine aquifers and coal seam cooling, aimed [...] Read more.

As shallow coal resources become increasingly depleted, coal mining is extending to greater depths, making mine thermal hazards an increasingly prominent issue. This paper proposes a novel system for synergistic geothermal energy extraction from deep coal mine aquifers and coal seam cooling, aimed at achieving integrated geothermal exploitation and mine thermal hazard control. Based on a high-temperature mine in the Yuanyanghu Mining Area of Ningxia, a dual-stage, single-branch three-dimensional numerical model was established to simulate the effects of water injection pressure, water injection temperature, and level spacing on the system’s cooling performance and geothermal energy extraction efficiency. The results indicate that increasing injection pressure enhances early-stage geothermal energy extraction capacity and coal seam cooling rate, but the heat extraction power declines over long-term operation as the produced water temperature approaches the injection temperature. Lowering injection temperature significantly improves water–rock heat exchange efficiency, accelerates coal seam cooling, and increases geothermal energy extraction. Increasing level spacing helps improve geothermal energy extraction power but weakens the direct cooling effect on the coal seam. Considering the influence patterns of each parameter, the optimal combination was determined as water injection pressure of 10 MPa, water injection temperature of 10 °C, and level spacing of 80 m, which delivers the best overall performance by enabling rapid coal seam cooling and sustained geothermal energy extraction, with a cumulative geothermal output reaching 129.45 MW after 10 years of operation. This study provides a theoretical basis and technical reference for the integrated management of thermal hazards and geothermal resource development in deep coal mines. Full article

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21 pages, 3713 KB

Open AccessArticle

The Potential of Material and Product Passports for the Circular Management of Heritage Buildings

by Antonella Violano, Roxana Georgiana Aenoai, Genesis Camila Cervantes Puma and Luís Bragança

Appl. Sci. 2026, 16(2), 865; https://doi.org/10.3390/app16020865 - 14 Jan 2026

Abstract

Interventions on Heritage Buildings (HBs) involve significant challenges due to their tangible (embodied in the material, architectural, physical and technical integrity of the cultural asset), and intangible values (linked to socio-historical–cultural and collective identity, memory, customs and symbols meanings), which must be preserved [...] Read more.

Interventions on Heritage Buildings (HBs) involve significant challenges due to their tangible (embodied in the material, architectural, physical and technical integrity of the cultural asset), and intangible values (linked to socio-historical–cultural and collective identity, memory, customs and symbols meanings), which must be preserved while also adapting to current sustainability and circular economy goals. However, current conservation and management practices often lack systematic tools to trace, assess, and organise material and component information, hindering the implementation of circular strategies. In line with the European Union’s objectives for climate neutrality and resource efficiency and sufficiency, Material and Product Passports (MPPs) have emerged as digital tools that enhance data traceability, interoperability and transparency throughout a building’s lifecycle. This paper examines the potential of MPPs to support circular management of HBs by analysing the structure of MPPs and outlining the information flows generated by rehabilitation, maintenance and adaptive reuse strategies. A mixed methods approach, combining literature review and data structure analysis, is adopted to identify how the different categories of data produced during maintenance, rehabilitation and adaptive reuse processes can be integrated into MPP modules. The research highlights the conceptual opportunities of MPPs to document and interlink historical, cultural, and technical data, thereby improving decision-making and transparency across intervention stages. The analysis suggests that adapting MPPs to the specificities of historic contexts, such as authenticity preservation, reversibility, and contextual sensitivity, can foster innovative, sustainable, and circular practices in the conservation and management of HBs. Full article

(This article belongs to the Special Issue Heritage Buildings: Latest Advances and Prospects)

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20 pages, 4086 KB

Open AccessArticle

Integrated Hydro-Operational Risk Assessment (IHORA) for Sewage Treatment Facilities

by Taesoo Eum, Euntaek Shin, Dong Sop Rhee and Chang Geun Song

Appl. Sci. 2026, 16(2), 864; https://doi.org/10.3390/app16020864 - 14 Jan 2026

Abstract

Climate change has exacerbated flood risks for urban infrastructure, rendering sewage treatment facilities (STFs) particularly vulnerable due to their typical low-lying topographic placement. However, conventional flood risk assessment methodologies often rely solely on physical hazard parameters such as inundation depth, neglecting the functional [...] Read more.

Climate change has exacerbated flood risks for urban infrastructure, rendering sewage treatment facilities (STFs) particularly vulnerable due to their typical low-lying topographic placement. However, conventional flood risk assessment methodologies often rely solely on physical hazard parameters such as inundation depth, neglecting the functional interdependencies and operational criticality of individual treatment units. To address this limitation, this study proposes the Integrated Hydro-Operational Risk Assessment (IHORA) framework. The IHORA framework synthesizes 2D hydrodynamic modeling with a modified Hazard and Operability Study(HAZOP) study to systematically identify unit-specific physical failure thresholds and employs the Analytic Hierarchy Process (AHP) to quantify the relative operational importance of each process based on expert elicitation. The framework was applied to an underground STF under both fluvial flooding and internal structural breach scenarios. The results revealed a significant risk misalignment in traditional assessments; vital assets like electrical facilities were identified as high-risk hotspots despite moderate physical exposure, due to their high operational weight. Furthermore, Cause–Consequence Analysis (CCA) was utilized to trace cascading failure modes, bridging the gap between static risk metrics and dynamic emergency response protocols. This study demonstrates that the IHORA framework provides a robust scientific basis for prioritizing mitigation resources and enhancing the operational resilience of environmental facilities. Full article

(This article belongs to the Section Civil Engineering)

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23 pages, 3514 KB

Open AccessArticle

Study on Failure Mechanisms and Mechanical Properties of Rock Masses with Discontinuous Joints Based on 3D Printing Technology

by Yanshuang Yang, Junjie Zeng, Zhen Cui and Jinghan Yin

Appl. Sci. 2026, 16(2), 863; https://doi.org/10.3390/app16020863 - 14 Jan 2026

Abstract

Within natural rock masses, discontinuous joints are more prevalent than continuous joints. Discontinuous joints refer to non-persistent structural planes separated by intact rock bridges and can be quantified by the continuity coefficient K_A. They significantly affect the macroscopic mechanical properties of [...] Read more.

Within natural rock masses, discontinuous joints are more prevalent than continuous joints. Discontinuous joints refer to non-persistent structural planes separated by intact rock bridges and can be quantified by the continuity coefficient K_A. They significantly affect the macroscopic mechanical properties of rock masses. Therefore, investigating discontinuous jointed rock masses with diverse morphologies carries considerable theoretical and engineering significance. Using 3D printing technology, resin-based specimens with discontinuous joints were subjected to laboratory mechanical tests to explore the evolution of failure mechanisms and mechanical properties of discontinuous jointed rock masses with different inclinations, undulation amplitudes, and structural plane continuity. Results show that under compression, discontinuous jointed rock masses consistently undergo combined tensile and shear stresses, with joint undulation amplitude and continuity governing coplanar crack initiation. As the joint inclination angle ranges from 0° to 90°, the peak compressive strength first decreases and then increases: specimens with continuous joints or discontinuous joints (continuity coefficient K_A < 0.25) follow a “V”-shaped trend, while those with K_A > 0.25 exhibit a “U”-shaped trend. Joint continuity is a key factor governing rock mass strength: at the same rock column radius, higher continuity results in lower strength, and vice versa. Joint morphology also influences strength, with specimens with regular zigzag joints and rectangular corrugated joints exhibiting 6.7% and 11.2% higher strength than smooth-jointed specimens, respectively. These results clarify the effects of joint continuity and undulation on rock mass strength, providing a theoretical foundation for the rapid determination of K_A via borehole imaging and laser scanning in engineering practice, and enabling direct prediction of rock mass strength trends. Full article

(This article belongs to the Special Issue Artificial Intelligence in the Design and Innovation of High-Performance Concrete Materials)

38 pages, 1508 KB

Open AccessReview

Renewable Energy-Driven Pumping Systems and Application for Desalination: A Review of Technologies and Future Directions

by Levon Gevorkov, Ehsan Saebnoori, José Luis Domínguez-García and Lluis Trilla

Appl. Sci. 2026, 16(2), 862; https://doi.org/10.3390/app16020862 - 14 Jan 2026

Abstract

Desalination is a vital solution to global water scarcity, yet its substantial energy demand persists as a major challenge. As the core energy-consuming components, pumps are fundamental to both membrane and thermal desalination processes. This review provides a comprehensive analysis of renewable energy [...] Read more.

Desalination is a vital solution to global water scarcity, yet its substantial energy demand persists as a major challenge. As the core energy-consuming components, pumps are fundamental to both membrane and thermal desalination processes. This review provides a comprehensive analysis of renewable energy source (RES)-driven pumping systems for desalination, focusing on the integration of solar photovoltaic and wind technologies. It examines the operational principles and efficiency of key pump types, such as high-pressure feed pumps for reverse osmosis, and underscores the critical role of energy recovery devices (ERDs) in minimizing net energy consumption. Furthermore, the paper highlights the importance of advanced control and energy management systems (EMS) in mitigating the intermittency of renewable sources. It details essential control strategies, including maximum power point tracking (MPPT), motor drive control, and supervisory EMS, that optimize the synergy between pumps, ERDs, and variable power inputs. By synthesizing current technologies and control methodologies, this review aims to identify pathways for designing more resilient, energy-efficient, and cost-effective desalination plants, supporting a sustainable water future. Full article

(This article belongs to the Section Energy Science and Technology)

18 pages, 2317 KB

Open AccessArticle

Valorization of Invasive Tree Species (Black Locust, Tree-of-Heaven) Bark in Commercial Lime Mortars: Effects on Composites’ Physical, Hygroscopic and Mechanical Performance

by Vasiliki Kamperidou, Georgia Paschalidou and Ioannis Barboutis

Appl. Sci. 2026, 16(2), 861; https://doi.org/10.3390/app16020861 - 14 Jan 2026

Abstract

Fast-growing invasive tree species management produces a significant amount of low-density and low-value biomass, which offers a chance for waste valorization in the environmentally friendly construction sector. This study examines the utilization potential of low-value natural waste materials of tree bark, obtained from [...] Read more.

Fast-growing invasive tree species management produces a significant amount of low-density and low-value biomass, which offers a chance for waste valorization in the environmentally friendly construction sector. This study examines the utilization potential of low-value natural waste materials of tree bark, obtained from invasive hardwood species, in the production of environmentally friendly building mortars. More specifically, this study focuses on mixing bark powder of black locust (Robinia pseudoacacia L.) and tree-of-heaven (Ailanthus altissima (Miller) Swingle), with two commercial commonly found lime-based mortar powders in five different ratios of bark content (0%, 5%, 10%, 20% and 30%) characterizing the produced composites, in terms of physical, hygroscopic and mechanical properties. Slightly lighter composites were created with the use of bark additives especially at the bark content of 20% and 30%. As regards the compressive strength, the bark shares of 10% and 20% exhibited the most beneficial performance among those studied, though only the weaker performance of mortar type (M1) benefited significantly from bark incorporation. For both mortars, the composites containing black locust bark presented higher resistance to compression strength and elasticity, demonstrating higher composite integration in general and milder, plastic fraction in relation to tree-of-heaven bark-based specimens, the properties of which are considered crucial for the durability of structural materials. However, black locust bark exhibited higher water absorption compared to tree-of-heaven-based specimens. Despite the drawback of higher hygroscopicity, the results show that black locust bark, especially at lower incorporation rates (10–20%), is a promising functional additive for generating lighter, more ductile mortars, supporting the creation of novel building materials and sustainable waste management. Full article

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21 pages, 37629 KB

Open AccessArticle

FacadeGAN: Facade Texture Placement with GANs

by Elif Şanlıalp and Muhammed Abdullah Bulbul

Appl. Sci. 2026, 16(2), 860; https://doi.org/10.3390/app16020860 - 14 Jan 2026

Abstract

This study presents a texture-aware image synthesis framework designed to generate material-consistent façades using adversarial learning. The proposed architecture incorporates a mask-guided channel-wise attention mechanism that adaptively merges segmentation information with texture statistics to reconcile structural guiding with textural fidelity. A thorough comparative [...] Read more.

This study presents a texture-aware image synthesis framework designed to generate material-consistent façades using adversarial learning. The proposed architecture incorporates a mask-guided channel-wise attention mechanism that adaptively merges segmentation information with texture statistics to reconcile structural guiding with textural fidelity. A thorough comparative analysis was performed utilizing three internal variants—Vanilla GAN, Wasserstein GAN (WGAN), and WGAN-GP—against leading baselines, including TextureGAN and Pix2Pix. The assessment utilized a comprehensive multi-metric framework that included SSIM, FID, KID, LPIPS, and DISTS, in conjunction with a VGG-19 based perceptual loss. Experimental results indicate a notable divergence between pixel-wise accuracy and perceptual realism; although established baselines attained elevated PSNR values, the suggested Vanilla GAN and WGAN models exhibited enhanced perceptual fidelity, achieving the lowest LPIPS and DISTS scores. The WGAN-GP model, although theoretically stable, produced smoother but less complex textures due to the regularization enforced by the gradient penalty term. Ablation investigations further validated that the attention mechanism consistently enhanced structural alignment and texture sharpness across all topologies. Thus, the study suggests that Vanilla GAN and WGAN architectures, enhanced by attention-based fusion, offer an optimal balance between realism and structural fidelity for high-frequency texture creation applications. Full article

(This article belongs to the Special Issue AI-Driven Computer Vision and Pattern Recognition: Challenges and Applications)

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32 pages, 2659 KB

Open AccessReview

Exposure to Nitrogen Dioxide (NO₂) Emitted from Traffic-Related Sources: Review

by Walter Mucha and Anna Mainka

Appl. Sci. 2026, 16(2), 859; https://doi.org/10.3390/app16020859 - 14 Jan 2026

Abstract

Nitrogen dioxide (NO₂) remains one of the most relevant traffic-related air pollutants in urban environments, despite decades of regulatory efforts and advances in vehicle emission control technologies. This review synthesizes current knowledge on ambient NO₂ concentrations associated with road transport, [...] Read more.

Nitrogen dioxide (NO₂) remains one of the most relevant traffic-related air pollutants in urban environments, despite decades of regulatory efforts and advances in vehicle emission control technologies. This review synthesizes current knowledge on ambient NO₂ concentrations associated with road transport, identifies key determinants of spatial and temporal variability, and evaluates the effectiveness of mitigation approaches under increasingly stringent air quality standards. The study is based on a comprehensive review of peer-reviewed literature reporting NO₂ measurements in urban, traffic, and background environments worldwide, complemented by an assessment of regulatory frameworks and mitigation strategies. The evidence confirms that road transport is the dominant contributor to elevated NO₂ concentrations, particularly at traffic sites, with traffic intensity, fleet composition, driving behavior, cold-start emissions, and street geometry emerging as primary controlling factors. Meteorological conditions influence dispersion but generally play a secondary role compared with emission-related drivers. Urban infrastructure, especially street canyons and tunnels, amplifies near-road NO₂ levels and population exposure. Mitigation measures such as Low Emission Zones, vehicle fleet modernization, and infrastructural interventions can reduce NO₂ concentrations, but their effectiveness is moderate and highly context-dependent. Sustained compliance with EU limit values and World Health Organization guideline levels requires integrated, multi-scale mitigation strategies. Full article

(This article belongs to the Section Environmental Sciences)

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