Pub Date : 2026-01-01DOI: 10.1016/j.asej.2025.103950
Ali Mohammad Khodadoust , Mario Eduardo Rivero-Ángeles , Víctor Barrera-Figueroa
Shotgun cellular systems (SCSs) are stochastic models of wireless networks where base stations (BSs) are randomly deployed across spatial settings of dimension one, two, or three, under a Poisson point process (PPP). As the physical layer security (PLS) of SCSs depends on BS density—which is influenced by the network’s setup and deployment—and typically underperforms compared to ideal hexagonal cellular systems (HCSs), this paper proposes an enhancement of PLS—including average secrecy capacity (ASC), secrecy outage probability (SOP), and the probability of non-zero secrecy capacity (PNZSC)—by leveraging side information (SI) available at the transmitter in addition to the source message for Wyner’s three-node model under realistic conditions, where shadowing coefficients of the channels are arbitrarily correlated. Modeling the shadowing on both the main (transmitter–legitimate receiver) and eavesdropper (transmitter–eavesdropper) channels with a lognormal (LN) distribution—the standard and most accurate model for characterizing shadowing—yields closed-form expressions for the aforementioned PLS performance metrics, thereby providing rigorous analytical insights. Lastly, the correctness of the analytical findings is confirmed via Monte Carlo (MC) simulation experiments.
{"title":"Secure transmission enhancement in shotgun cellular systems using transmitter-side information over correlated shadowing channels","authors":"Ali Mohammad Khodadoust , Mario Eduardo Rivero-Ángeles , Víctor Barrera-Figueroa","doi":"10.1016/j.asej.2025.103950","DOIUrl":"10.1016/j.asej.2025.103950","url":null,"abstract":"<div><div>Shotgun cellular systems (SCSs) are stochastic models of wireless networks where base stations (BSs) are randomly deployed across spatial settings of dimension one, two, or three, under a Poisson point process (PPP). As the physical layer security (PLS) of SCSs depends on BS density—which is influenced by the network’s setup and deployment—and typically underperforms compared to ideal hexagonal cellular systems (HCSs), this paper proposes an enhancement of PLS—including average secrecy capacity (ASC), secrecy outage probability (SOP), and the probability of non-zero secrecy capacity (PNZSC)—by leveraging side information (SI) available at the transmitter in addition to the source message for Wyner’s three-node model under realistic conditions, where shadowing coefficients of the channels are arbitrarily correlated. Modeling the shadowing on both the main (transmitter–legitimate receiver) and eavesdropper (transmitter–eavesdropper) channels with a lognormal (LN) distribution—the standard and most accurate model for characterizing shadowing—yields closed-form expressions for the aforementioned PLS performance metrics, thereby providing rigorous analytical insights. Lastly, the correctness of the analytical findings is confirmed via Monte Carlo (MC) simulation experiments.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 1","pages":"Article 103950"},"PeriodicalIF":5.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.asej.2025.103937
Abderrahim Mokhefi , Eugenia Rossi di Schio , Sarra Youcefi , Paolo Valdiserri
Despite their passive ability to resist reverse flow, Tesla valves can experience altered performance under external influences such as magnetic fields, which can alter or even disrupt the proper functioning of Tesla valves particularly in microscale systems in electronic devices. In this framework, the present study aims to investigate the influence of a horizontal magnetic field on the hydrodynamic and thermal performance of a T45-R microscale Tesla valve integrated into a microsystem. Using computational fluid dynamics (CFD), the effect of the magnetic field, modeled via the Hartmann number (Ha = 0–100), on a laminar (Re = 500) Fe3O4-water ferro-nanofluid flow has been analyzed under both forward and reverse flow conditions. The studied flow is governed by the mass, momentum, and energy equations, which has been solved numerically using the finite element method. The results indicate that the magnetic field significantly affects both flow directions, inducing a pressure difference that increases by nearly 150 % for moderate magnetic flux densities (Ha ≈ 25) compared to the non-magnetic case. In forward flow, increased magnetic flux density enhances flow intensity and heat transfer while partially blocking the curved part of the valve, yet it may inadvertently support reverse flow. Diodicity analysis has revealed that valve performance decreases for Hartmann numbers below Ha ≈ 17, independent of nanoparticle concentration, while it improves beyond this threshold. Nevertheless, optimal valve performance is still observed in the absence of a magnetic field.
{"title":"Magnetic field effects on the thermo-hydrodynamic behavior of a microscale Tesla valve operating with Fe3O4-water ferro-nanofluid","authors":"Abderrahim Mokhefi , Eugenia Rossi di Schio , Sarra Youcefi , Paolo Valdiserri","doi":"10.1016/j.asej.2025.103937","DOIUrl":"10.1016/j.asej.2025.103937","url":null,"abstract":"<div><div>Despite their passive ability to resist reverse flow, Tesla valves can experience altered performance under external influences such as magnetic fields, which can alter or even disrupt the proper functioning of Tesla valves particularly in microscale systems in electronic devices. In this framework, the present study aims to investigate the influence of a horizontal magnetic field on the hydrodynamic and thermal performance of a T45-R microscale Tesla valve integrated into a microsystem. Using computational fluid dynamics (CFD), the effect of the magnetic field, modeled via the Hartmann number (Ha = 0–100), on a laminar (Re = 500) Fe<sub>3</sub>O<sub>4</sub>-water ferro-nanofluid flow has been analyzed under both forward and reverse flow conditions. The studied flow is governed by the mass, momentum, and energy equations, which has been solved numerically using the finite element method. The results indicate that the magnetic field significantly affects both flow directions, inducing a pressure difference that increases by nearly 150 % for moderate magnetic flux densities (Ha ≈ 25) compared to the non-magnetic case. In forward flow, increased magnetic flux density enhances flow intensity and heat transfer while partially blocking the curved part of the valve, yet it may inadvertently support reverse flow. Diodicity analysis has revealed that valve performance decreases for Hartmann numbers below Ha ≈ 17, independent of nanoparticle concentration, while it improves beyond this threshold. Nevertheless, optimal valve performance is still observed in the absence of a magnetic field.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 1","pages":"Article 103937"},"PeriodicalIF":5.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.asej.2025.103948
Mingyuan Hu , Lei Zhang , Ran Tao , Ping Wang , Yaqing Gu , Zia Ullah
Surface-mounted permanent magnet synchronous motors (SPMSMs) require advanced speed regulation strategies due to their nonlinear dynamics and sensitivity to disturbances. Conventional integral sliding mode control (ISMC), when applied to these drives, faces critical drawbacks such as saturation effects caused by large initial speed errors and adaptive gain overestimation in super-twisting algorithms. To address these challenges, this paper proposes a nonlinear integral sliding mode control scheme enhanced with a dual-layer adaptive super-twisting algorithm (NISMC-DASTA). A novel integral sliding surface with a dynamic anti-saturation gain mechanism is introduced to accelerate error convergence, enhance disturbance rejection, and mitigate integrator windup. Additionally, a dual-layer adaptive mechanism is embedded within the super-twisting controller to adjust its gains dynamically. This two-tier adaptation not only suppresses chattering but also alleviates the trade-off between rapid convergence and excessive gain amplification commonly observed in single-layer adaptive STA approaches. Extensive simulations and experimental results on a practical SPMSM drive platform validate the superior performance and robustness of the proposed NISMC-DASTA method.
{"title":"Nonlinear integral sliding mode control of SPMSMs using a dual-layer adaptive super-twisting algorithm","authors":"Mingyuan Hu , Lei Zhang , Ran Tao , Ping Wang , Yaqing Gu , Zia Ullah","doi":"10.1016/j.asej.2025.103948","DOIUrl":"10.1016/j.asej.2025.103948","url":null,"abstract":"<div><div>Surface-mounted permanent magnet synchronous motors (SPMSMs) require advanced speed regulation strategies due to their nonlinear dynamics and sensitivity to disturbances. Conventional integral sliding mode control (ISMC), when applied to these drives, faces critical drawbacks such as saturation effects caused by large initial speed errors and adaptive gain overestimation in super-twisting algorithms. To address these challenges, this paper proposes a nonlinear integral sliding mode control scheme enhanced with a dual-layer adaptive super-twisting algorithm (NISMC-DASTA). A novel integral sliding surface with a dynamic anti-saturation gain mechanism is introduced to accelerate error convergence, enhance disturbance rejection, and mitigate integrator windup. Additionally, a dual-layer adaptive mechanism is embedded within the super-twisting controller to adjust its gains dynamically. This two-tier adaptation not only suppresses chattering but also alleviates the trade-off between rapid convergence and excessive gain amplification commonly observed in single-layer adaptive STA approaches. Extensive simulations and experimental results on a practical SPMSM drive platform validate the superior performance and robustness of the proposed NISMC-DASTA method.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 1","pages":"Article 103948"},"PeriodicalIF":5.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.asej.2025.103956
Afnan M. Alhassan, Nouf I. Altmami
Skin cancer is a common type of cancer that emerges from the epidermis of the skin and spreads to other parts of the body. Among the types of skin cancer, non-melanoma skin cancer has fewer detection techniques and shows an increased case rate annually. Detecting the non-melanoma skin cancer remains a critical task as the existing methods struggle with the positional detection, potential of the tissues, and transparency and interpretability. In addition, the previous technologies faced difficulty with the large and poor-quality image dataset. To overcome these limitations, the proposed research designed a Multivariable Deep Convolutional Neural Network model for the accurate multiclass non-melanoma skin cancer. The model incorporates the Hybrid gradient boosting and the Hybrid attention module, which reduces the complexity and enhances the performance with accurate outcomes. The feature extraction process of the model includes two pre-trained models that are fused to achieve the best feature extraction, along with the shape and texture features. The ultimate goal of the model is to detect multiclass non-melanoma skin cancer with greater evaluation values, which achieves an accuracy of 96.8%, sensitivity of 97.56%, specificity of 96.03%, precision of 96.71% and F1-score of 97.13% with the Histopathological non-melanoma skin cancer segmentation dataset.
{"title":"Detection of multiclass non-melanoma skin cancer with multi-variable DCNN with hybrid gradient boosting optimizer","authors":"Afnan M. Alhassan, Nouf I. Altmami","doi":"10.1016/j.asej.2025.103956","DOIUrl":"10.1016/j.asej.2025.103956","url":null,"abstract":"<div><div>Skin cancer is a common type of cancer that emerges from the epidermis of the skin and spreads to other parts of the body. Among the types of skin cancer, non-melanoma skin cancer has fewer detection techniques and shows an increased case rate annually. Detecting the non-melanoma skin cancer remains a critical task as the existing methods struggle with the positional detection, potential of the tissues, and transparency and interpretability. In addition, the previous technologies faced difficulty with the large and poor-quality image dataset. To overcome these limitations, the proposed research designed a Multivariable Deep Convolutional Neural Network model for the accurate multiclass non-melanoma skin cancer. The model incorporates the Hybrid gradient boosting and the Hybrid attention module, which reduces the complexity and enhances the performance with accurate outcomes. The feature extraction process of the model includes two pre-trained models that are fused to achieve the best feature extraction, along with the shape and texture features. The ultimate goal of the model is to detect multiclass non-melanoma skin cancer with greater evaluation values, which achieves an accuracy of 96.8%, sensitivity of 97.56%, specificity of 96.03%, precision of 96.71% and F1-score of 97.13% with the Histopathological non-melanoma skin cancer segmentation dataset.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 1","pages":"Article 103956"},"PeriodicalIF":5.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study evaluates retrofit strategies that combine wall insulation and green wall systems in three typical UK residential buildings from the 1920s, 1970s, and 2010s. While both approaches have been individually explored, their combined thermal and economic impact across housing eras remains underexamined. Using 64 thermal simulation scenarios in DesignBuilder, the research analyzes effects on U-values, energy use intensity, and heating gas demand, alongside cost savings and payback periods. Rock Wool insulation achieved the highest energy savings, while green walls offered modest improvements and passive cooling. Hybrid strategies delivered the best overall performance but resulted in longer payback times. The most cost-effective measure was cavity fill insulation in the 1970s house. By integrating energy and economic assessments across varied building types and retrofit combinations, this study fills a critical gap and advocates for customized, cost-effective retrofit strategies, especially in heating-driven climates where green walls alone yield limited benefits. The insights also extend to international contexts with temperate climates and aging housing stocks, supporting renovation strategies aligned with global decarbonization targets.
{"title":"Integrated retrofit strategies for UK housing: simulation-based assessment of insulation and green wall combinations across construction eras","authors":"Aseel Hussien , Ameera Ghanim , Aref Maksoud , Shouib Nouh Ma’bdeh , Emad Mushtaha","doi":"10.1016/j.asej.2025.103951","DOIUrl":"10.1016/j.asej.2025.103951","url":null,"abstract":"<div><div>This study evaluates retrofit strategies that combine wall insulation and green wall systems in three typical UK residential buildings from the 1920s, 1970s, and 2010s. While both approaches have been individually explored, their combined thermal and economic impact across housing eras remains underexamined. Using 64 thermal simulation scenarios in DesignBuilder, the research analyzes effects on U-values, energy use intensity, and heating gas demand, alongside cost savings and payback periods. Rock Wool insulation achieved the highest energy savings, while green walls offered modest improvements and passive cooling. Hybrid strategies delivered the best overall performance but resulted in longer payback times. The most cost-effective measure was cavity fill insulation in the 1970s house. By integrating energy and economic assessments across varied building types and retrofit combinations, this study fills a critical gap and advocates for customized, cost-effective retrofit strategies, especially in heating-driven climates where green walls alone yield limited benefits. The insights also extend to international contexts with temperate climates and aging housing stocks, supporting renovation strategies aligned with global decarbonization targets.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 1","pages":"Article 103951"},"PeriodicalIF":5.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.asej.2025.103940
Muhammad Idrees Afridi
Nonlinear integrable systems play a crucial role in many areas of science, such as fluid dynamics, applied mathematics, nonlinear optics, and plasma physics. These models are particularly valuable for studying wave propagation and interaction effects. In this work, we examine the (1+1)-dimensional Aizhan-Gudekli-Nurshuak-Zhanbota model (), a new integrable model possessing significant nonlinear characteristics. Employing the N-fold Darboux Transformation () method for the associated Lax pair (LP), we construct analytic multi-soliton solutions of the . We also derive first and second order rogue wave solutions, emphasizing the equation’s ability to capture extreme localised wave phenomena. We support the analytical solutions with graphical presentations of their dynamical behaviour. This study enhances our understanding of nonlinear wave structures and contributes to the broader investigation of integrable systems in mathematical physics and computational modeling.
{"title":"Dynamical behaviours of the multi-solitons and rogue waves in the Aizhan-Gudekli-Nurshuak-Zhanbota model with the N-fold Darboux transformation in nonlinear sciences","authors":"Muhammad Idrees Afridi","doi":"10.1016/j.asej.2025.103940","DOIUrl":"10.1016/j.asej.2025.103940","url":null,"abstract":"<div><div>Nonlinear integrable systems play a crucial role in many areas of science, such as fluid dynamics, applied mathematics, nonlinear optics, and plasma physics. These models are particularly valuable for studying wave propagation and interaction effects. In this work, we examine the (1+1)-dimensional Aizhan-Gudekli-Nurshuak-Zhanbota model (<span><math><mrow><mi>AGNZM</mi></mrow></math></span>), a new integrable model possessing significant nonlinear characteristics. Employing the N-fold Darboux Transformation (<span><math><mrow><mi>DT</mi></mrow></math></span>) method for the associated Lax pair (LP), we construct analytic multi-soliton solutions of the <span><math><mrow><mi>AGNZM</mi></mrow></math></span>. We also derive first and second order rogue wave solutions, emphasizing the equation’s ability to capture extreme localised wave phenomena. We support the analytical solutions with graphical presentations of their dynamical behaviour. This study enhances our understanding of nonlinear wave structures and contributes to the broader investigation of integrable systems in mathematical physics and computational modeling.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 1","pages":"Article 103940"},"PeriodicalIF":5.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.asej.2025.103939
A. Meenakshi , J. Shivangi Mishra , Leo Mršić , Antonios Kalampakas , Sovan Samanta , Tofigh Allahviranloo
This paper explores the applications of Intuitionistic Fuzzy Graphs representing uncertainty and imprecision in complex systems through the analysis of correlation and regression coefficients with focus on the maximal product. The study examines the relationships between the edges of the graph by analysing the line graph derived from , facilitating a deeper understanding of the network’s dynamics. The construction of adjacency matrices that incorporate both membership and non-membership values enables the calculation of energy and weight scores, quantifying the strength and predictive correlations among variables. Furthermore, the study discusses the complement of Intuitionistic Fuzzy Line Graphs , using maximal product analysis to uncover concealed relationships within the network. MATLAB is used to generate heatmaps that visually represent the importance of correlation to critical network characteristics. The practical importance is demonstrated in a healthcare context, particularly in predicting diabetes risk by modelling factors of glucose levels, body mass index (BMI), and insulin. Heatmaps can be effectively visualized to show interrelationships between these features, aiding in the interpretation of network patterns.
{"title":"Maximal product-based intuitionistic fuzzy line graphs for healthcare predictive analysis","authors":"A. Meenakshi , J. Shivangi Mishra , Leo Mršić , Antonios Kalampakas , Sovan Samanta , Tofigh Allahviranloo","doi":"10.1016/j.asej.2025.103939","DOIUrl":"10.1016/j.asej.2025.103939","url":null,"abstract":"<div><div>This paper explores the applications of Intuitionistic Fuzzy Graphs <span><math><mrow><mo>(</mo><mi>IFG</mi><mo>)</mo></mrow></math></span> representing uncertainty and imprecision in complex systems through the analysis of correlation and regression coefficients <span><math><mrow><mo>(</mo><mi>CRCs</mi><mo>)</mo></mrow></math></span> with focus on the maximal product. The study examines the relationships between the edges of the graph by analysing the line graph derived from <span><math><mrow><mi>IFG</mi></mrow></math></span>, facilitating a deeper understanding of the network’s dynamics. The construction of adjacency matrices that incorporate both membership and non-membership values enables the calculation of energy and weight scores, quantifying the strength and predictive correlations among variables. Furthermore, the study discusses the complement of Intuitionistic Fuzzy Line Graphs <span><math><mrow><mo>(</mo><mi>IFLG</mi><mo>)</mo></mrow></math></span>, using maximal product analysis to uncover concealed relationships within the network. MATLAB is used to generate heatmaps that visually represent the importance of correlation to critical network characteristics. The practical importance is demonstrated in a healthcare context, particularly in predicting diabetes risk by modelling factors of glucose levels, body mass index (BMI), and insulin. Heatmaps can be effectively visualized to show interrelationships between these features, aiding in the interpretation of network patterns.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 1","pages":"Article 103939"},"PeriodicalIF":5.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146022453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.asej.2025.103942
Xing Li , Huan Hao , Lingying Chen , Fuqiang Zhao , Yuhui Liu
This study proposes a GNN-based multi-scale heat transfer path optimization method for magnetic-thermal coupling simulation of wound conductors. Key parameters like magnetic vector potential, flux density, and temperature distribution are identified. An adaptive graph network integrates these parameters to build a 3D conductor model. A multi-scale spatio-temporal graph convolution module captures heat transfer path characteristics, while the GraphSAGE algorithm aggregates thermal resistance and electromagnetic loss data from adjacent nodes to train the GNN.The trained GNN outputs optimized multi-scale heat transfer path results, including temperature distribution and magnetic field loss. Experiments show the method effectively simulates magnetic-thermal coupling, with ohmic losses in low-voltage and high-voltage windings at ∼600 W and ∼300 W, respectively, and peak eddy current losses reaching ∼1600 W and ∼1700 W. Temperatures mainly range between 320–340 K (low-voltage) and 300–320 K (high-voltage). The method’s optimization reduces magnetic losses and material usage.
{"title":"Multi-scale heat transfer path optimization in magnetic-thermal coupling simulation of winding conductors using graph neural networks","authors":"Xing Li , Huan Hao , Lingying Chen , Fuqiang Zhao , Yuhui Liu","doi":"10.1016/j.asej.2025.103942","DOIUrl":"10.1016/j.asej.2025.103942","url":null,"abstract":"<div><div>This study proposes a GNN-based multi-scale heat transfer path optimization method for magnetic-thermal coupling simulation of wound conductors. Key parameters like magnetic vector potential, flux density, and temperature distribution are identified. An adaptive graph network integrates these parameters to build a 3D conductor model. A multi-scale spatio-temporal graph convolution module captures heat transfer path characteristics, while the GraphSAGE algorithm aggregates thermal resistance and electromagnetic loss data from adjacent nodes to train the GNN.The trained GNN outputs optimized multi-scale heat transfer path results, including temperature distribution and magnetic field loss. Experiments show the method effectively simulates magnetic-thermal coupling, with ohmic losses in low-voltage and high-voltage windings at ∼600 W and ∼300 W, respectively, and peak eddy current losses reaching ∼1600 W and ∼1700 W. Temperatures mainly range between 320–340 K (low-voltage) and 300–320 K (high-voltage). The method’s optimization reduces magnetic losses and material usage.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 1","pages":"Article 103942"},"PeriodicalIF":5.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.asej.2025.103954
Mohammed Alghamdi, Salman Alhifthi, Naif Alsanabani, Khalid Al-Gahtani, Ayman Altuwaim, Abdullah AlSharef
Hospitals are mission-critical facilities where operational integrity is crucial for ensuring patient safety and delivering adequate healthcare. Reactive, fragmented approaches often undermine effective hospital facility management (FM). This study addresses this gap by developing and validating a system dynamics (SD) model to analyze the causal relationships and feedback loops among key performance factors. A multi-phase methodology was employed, integrating expert surveys using the Relative Importance Index (RII), the Analytic Hierarchy Process (AHP), and the DEMATEL technique to structure and quantify the model. The developed SD model was validated through sensitivity analysis. Study findings revealed that cumulative impacts hinder the system, resulting in a significant 26.38% budget overrun over twelve months. The model identifies ’Design Errors’ and ’System and Selection of Materials’ as the most destructive factors, causing severe performance degradation across the system. The implications are significant, providing a strategic blueprint for hospital managers to shift towards proactive interventions by focusing on these high-leverage points.
{"title":"Modeling the interdependencies of critical factors in hospital facility management: a system dynamics framework","authors":"Mohammed Alghamdi, Salman Alhifthi, Naif Alsanabani, Khalid Al-Gahtani, Ayman Altuwaim, Abdullah AlSharef","doi":"10.1016/j.asej.2025.103954","DOIUrl":"10.1016/j.asej.2025.103954","url":null,"abstract":"<div><div>Hospitals are mission-critical facilities where operational integrity is crucial for ensuring patient safety and delivering adequate healthcare. Reactive, fragmented approaches often undermine effective hospital facility management (FM). This study addresses this gap by developing and validating a system dynamics (SD) model to analyze the causal relationships and feedback loops among key performance factors. A multi-phase methodology was employed, integrating expert surveys using the Relative Importance Index (RII), the Analytic Hierarchy Process (AHP), and the DEMATEL technique to structure and quantify the model. The developed SD model was validated through sensitivity analysis. Study findings revealed that cumulative impacts hinder the system, resulting in a significant 26.38% budget overrun over twelve months. The model identifies ’Design Errors’ and ’System and Selection of Materials’ as the most destructive factors, causing severe performance degradation across the system. The implications are significant, providing a strategic blueprint for hospital managers to shift towards proactive interventions by focusing on these high-leverage points.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 1","pages":"Article 103954"},"PeriodicalIF":5.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.asej.2025.103941
Dengguo Wu , Jian Yang , Wenjie Cai , Wenzhong Xia , Dongfang Jiang , Shengyao Liu , Buting Xu , Haiyang Wang
Air quality in urban residential areas depends on the vehicles, celebrations, carbon emissions, etc. experienced around the day/ year. The effects of carbon emissions on residents’ thermal comfort are more important than control measures, for which measurements are mandatory. This article, therefore, introduces an ENVi-Met-based thermal structure assessment model to identify the air quality affected by carbon emissions. In the thermal structure assessment, the three-dimensional space of the urban Area, including the emitting and emission-conducted regions, is modeled to compute the air quality index (AQI). A stabilized assessment of the mean AQI that distinguishes between the worst and better thermal structures is estimated from continuous assessments. In this process, the change in AQI from the lowest to the highest is the boundary for the structural evaluation. The primary objective of this study is to develop an integrated framework that explains how carbon emissions affect the thermal structure and air quality in urban residential areas. The work employs the ENVI-met microclimate simulation system to model the spatial and temporal distribution of emissions, thereby facilitating a complex representation of pollutant dynamics within three-dimensional urban environments. It subsequently sets high and low AQI limits that reflect differing thermal conditions, making it easier to distinguish areas that are thermally strained from those that are well-ventilated. The model employs convergence-based transfer learning to maintain stable AQI forecasts over time, ensuring predictions remain consistent even as environmental variables change. Lastly, the framework examines thermal comfort by considering the combined effects of emission intensity, vegetation absorption, and microclimatic interactions. The boundary-based change differentiation is validated using converged transfer learning to identify the maximum changes in thermal structures. Learning converges for the AQI differentiation value for stabilization detection. Therefore, this stabilization value is used to train the learning network to maintain boundary consistency across different structural changes. The proposed model achieves an 11.39% high AQI analysis with a maximum Kappa of 12.58% between the convergence and stability for the time/day and stable variants under hot climatic conditions.
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