Pub Date : 2026-01-22DOI: 10.1016/j.asej.2026.103994
Jiafu Su , Hongyu Liu , Yijun Chen , Lianxin Jiang , Na Zhang
This paper proposes FUCOMSort, a novel consensus-based multi-criteria sorting method that utilizes the Full COnsistency Method (FUCOM) to categorize alternatives into predefined categories. By reducing pairwise comparisons, it significantly improves sorting efficiency and classification model consistency. Specifically, the LPHFSs Dombi Weighted Average (LPHFDWA) operator is introduced to effectively aggregate expert information. In addition, a redefined hybrid centrality measure, combining trust relationships with K-core decomposition, is proposed to evaluate their substantial impact on the classification outcomes. A consensus-reaching process is further constructed using trust networks and regret theory, addressing conflicts in expert evaluations. FUCOM is extended to the LPHFSs environment, incorporating both subjective and objective weights through linear equations. The proposed FUCOMSort method reduces pairwise comparisons to just n-1, thereby substantially improving efficiency in large-scale multi-criteria sorting problems. To validate the proposed method, we applied it to the classification of green patent values and conducted sensitivity analysis and comparative analysis. The analysis results demonstrate that the method possesses strong robustness and effectiveness.
{"title":"A novel multi-criteria sorting method based on the linguistic polyhedral hesitant fuzzy consensus-reaching model","authors":"Jiafu Su , Hongyu Liu , Yijun Chen , Lianxin Jiang , Na Zhang","doi":"10.1016/j.asej.2026.103994","DOIUrl":"10.1016/j.asej.2026.103994","url":null,"abstract":"<div><div>This paper proposes FUCOMSort, a novel consensus-based multi-criteria sorting method that utilizes the Full COnsistency Method (FUCOM) to categorize alternatives into predefined categories. By reducing pairwise comparisons, it significantly improves sorting efficiency and classification model consistency. Specifically, the LPHFSs Dombi Weighted Average (LPHFDWA) operator is introduced to effectively aggregate expert information. In addition, a redefined hybrid centrality measure, combining trust relationships with K-core decomposition, is proposed to evaluate their substantial impact on the classification outcomes. A consensus-reaching process is further constructed using trust networks and regret theory, addressing conflicts in expert evaluations. FUCOM is extended to the LPHFSs environment, incorporating both subjective and objective weights through linear equations. The proposed FUCOMSort method reduces pairwise comparisons to just n-1, thereby substantially improving efficiency in large-scale multi-criteria sorting problems. To validate the proposed method, we applied it to the classification of green patent values and conducted sensitivity analysis and comparative analysis. The analysis results demonstrate that the method possesses strong robustness and effectiveness.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 2","pages":"Article 103994"},"PeriodicalIF":5.9,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023810","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 : 2026-01-21DOI: 10.1016/j.asej.2026.104003
Ping Guo, Jiwei Zhu
The renovation of urban old residential areas (UORA) is a crucial measure in urban stock renewal for improving the quality of residents’ lives. Scientifically understanding the multidimensional vulnerability of UORA is a prerequisite for implementing stock renewal. However, existing vulnerability assessment methods for UORA suffer from limitations such as subjective weight assignment, and insufficient handling of uncertain information, leading to inadequate support for precise renewal decisions. To address these gaps, this study proposes a novel multidimensional vulnerability evaluation framework. A vulnerability evaluation index system is constructed from physical space, infrastructure, functional adaptation, ecological environment, and social governance. A comprehensive evaluation model is established by integrating the combined entropy weight method and the unascertained measure theory. This methodological innovation enhances the objectivity of weight determination while effectively addressing unstructured data and uncertain factors in vulnerability assessment. The empirical results show that the vulnerability evaluation results of the six projects are clearly polarised. High-risk clusters need to prioritise the initiation of engineering interventions and social governance reconstruction; for medium-risk projects, dynamic monitoring and adaptive management should be strengthened. This study provides a priority standard and scientific support for renewal decisions and promotes the transformation of vulnerability assessment from a single diagnosis to a systematic governance paradigm..
{"title":"Vulnerability analysis of urban old residential areas for stock renewal: an unascertained measure theory approach","authors":"Ping Guo, Jiwei Zhu","doi":"10.1016/j.asej.2026.104003","DOIUrl":"10.1016/j.asej.2026.104003","url":null,"abstract":"<div><div>The renovation of urban old residential areas (UORA) is a crucial measure in urban stock renewal for improving the quality of residents’ lives. Scientifically understanding the multidimensional vulnerability of UORA is a prerequisite for implementing stock renewal. However, existing vulnerability assessment methods for UORA suffer from limitations such as subjective weight assignment, and insufficient handling of uncertain information, leading to inadequate support for precise renewal decisions. To address these gaps, this study proposes a novel multidimensional vulnerability evaluation framework. A vulnerability evaluation index system is constructed from physical space, infrastructure, functional adaptation, ecological environment, and social governance. A comprehensive evaluation model is established by integrating the combined entropy weight method and the unascertained measure theory. This methodological innovation enhances the objectivity of weight determination while effectively addressing unstructured data and uncertain factors in vulnerability assessment. The empirical results show that the vulnerability evaluation results of the six projects are clearly polarised. High-risk clusters need to prioritise the initiation of engineering interventions and social governance reconstruction; for medium-risk projects, dynamic monitoring and adaptive management should be strengthened. This study provides a priority standard and scientific support for renewal decisions and promotes the transformation of vulnerability assessment from a single diagnosis to a systematic governance paradigm..</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 2","pages":"Article 104003"},"PeriodicalIF":5.9,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023814","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}
Pneumatic planters are well-known for precise seed placement and accurate singulation across the world. These planters are available in various designs and configurations but, plate-type seed metering mechanism with pneumatic suction are the most commonly adopted due to high precision, versatility and efficiency in seed placement with minimum seed damage. The design and operational parameters of these metering plates vary with seed type, and typically require extensive laboratory and field experiments, ultimately leading to lot of complexity, cost and wastage of precious time and input resources. To address this, a theoretical method was developed to calculate the key design parameters of seed metering unit of a planter. These parameters (orifice diameter, vacuum pressure, suction depth, diameter of seed metering plate, pitch circle diameter (PCD) of seed metering plate, pitch between orifice, and vacuum cut off angle) were calculated on the basis of seed properties and their interaction properties with seed metering plate material. A probabilistic approach established a minimum suction depth of six times the seed length which improved seed singulation to over 90%. A new equation was established interrelating orifice diameter, suction depth, vacuum pressure, and peripheral velocity, and was used for predicting optimal vacuum pressure for different varieties of cotton seed — Suraj, Ajeet 155, Ankur 3028, RCH 2, and RCH 659. This research also finds out the design space for optimization of key parameters— orifice size, vacuum pressure, and peripheral speed for conventional optimization. Considering above three independent parameters, central composite rotatable design (CCRD) in response surface method (RSM) was followed for establishment of prediction equations of miss, multiple, precision indices. The metering plate was designed to get a quality feed index of about 93.75% while the predicted quality feed index on the basis of developed polynomial equation using experimental result was 94.74%. This indicated that the developed theoretical method has potential for effective and efficient design of pneumatic seed metering plate for different seeds to achieve desired quality feed index. In field condition, quality feed index with developed planter along with optimized parameters was observed 5.2% less than the designed quality feed index. It showed that proposed approach for designing effective pneumatic metering system can save considerable cost involved in conducting laboratory and field experiments along with time and labour without compromising its performance quality. The application of this novel theoretical engineering design in precision pneumatic planter development enables accurate seed spacing in various crops and promotes precision agriculture.
{"title":"An analytical procedure in pneumatic seed meter design for enhanced performance validated through development and evaluation","authors":"Jyotirmay Mahapatra , Ramesh K. Sahni , Vikas Pagare , Jagjeet Singh , Prem Shanker Tiwari , Krishna Pratap Singh , Balaji Murhari Nandede","doi":"10.1016/j.asej.2026.104001","DOIUrl":"10.1016/j.asej.2026.104001","url":null,"abstract":"<div><div>Pneumatic planters are well-known for precise seed placement and accurate singulation across the world. These planters are available in various designs and configurations but, plate-type seed metering mechanism with pneumatic suction are the most commonly adopted due to high precision, versatility and efficiency in seed placement with minimum seed damage. The design and operational parameters of these metering plates vary with seed type, and typically require extensive laboratory and field experiments, ultimately leading to lot of complexity, cost and wastage of precious time and input resources. To address this, a theoretical method was developed to calculate the key design parameters of seed metering unit of a planter. These parameters (orifice diameter, vacuum pressure, suction depth, diameter of seed metering plate, pitch circle diameter (PCD) of seed metering plate, pitch between orifice, and vacuum cut off angle) were calculated on the basis of seed properties and their interaction properties with seed metering plate material. A probabilistic approach established a minimum suction depth of six times the seed length which improved seed singulation to over 90%. A new equation was established interrelating orifice diameter, suction depth, vacuum pressure, and peripheral velocity, and was used for predicting optimal vacuum pressure for different varieties of cotton seed — <em>Suraj</em>, <em>Ajeet 155</em>, <em>Ankur 3028</em>, <em>RCH 2</em>, and <em>RCH 659</em>. This research also finds out the design space for optimization of key parameters— orifice size, vacuum pressure, and peripheral speed for conventional optimization. Considering above three independent parameters, central composite rotatable design (CCRD) in response surface method (RSM) was followed for establishment of prediction equations of miss, multiple, precision indices. The metering plate was designed to get a quality feed index of about 93.75% while the predicted quality feed index on the basis of developed polynomial equation using experimental result was 94.74%. This indicated that the developed theoretical method has potential for effective and efficient design of pneumatic seed metering plate for different seeds to achieve desired quality feed index. In field condition, quality feed index with developed planter along with optimized parameters was observed 5.2% less than the designed quality feed index. It showed that proposed approach for designing effective pneumatic metering system can save considerable cost involved in conducting laboratory and field experiments along with time and labour without compromising its performance quality. The application of this novel theoretical engineering design in precision pneumatic planter development enables accurate seed spacing in various crops and promotes precision agriculture.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 2","pages":"Article 104001"},"PeriodicalIF":5.9,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023357","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}
Hip protectors are essential for mitigating hip fractures, particularly among elderly individuals at risk of falls. This study investigates the impact force attenuation of 3D-printed honeycomb structures in hip protectors, focusing on cell wall thickness, relative density, and orientation. The design integrates an EVA foam outer layer with a thermoplastic polyurethane (TPU) honeycomb core fabricated using fused-deposition modeling (FDM). Horizontal and vertical orientations were tested at relative densities of 12%, 20%, and 28%, with wall thicknesses of 0.4, 0.6, and 0.8 mm. Compression and impact tests showed that vertical structures offer superior impact reduction at equal relative densities. Higher densities enhanced energy absorption, while wall thickness had minimal effects within elastic and plateau regions. Notably, a vertical structure with 12% density matched a horizontal one with 28%, demonstrating effective force attenuation with reduced material and weight. These findings provide design guidance for developing lightweight, high-performance hip protectors based on 3D-printed honeycomb architectures.
{"title":"Experimental study on the design and modeling of honeycomb structures for impact force attenuation in hip protectors","authors":"Prawit Kaeonarong , Boonsin Tangtrakulwanich , Theerawat Petdee , Varah Yuenyongviwat , Wiriya Thongruang , Satta Srewaradachpisal","doi":"10.1016/j.asej.2026.103986","DOIUrl":"10.1016/j.asej.2026.103986","url":null,"abstract":"<div><div>Hip protectors are essential for mitigating hip fractures, particularly among elderly individuals at risk of falls. This study investigates the impact force attenuation of 3D-printed honeycomb structures in hip protectors, focusing on cell wall thickness, relative density, and orientation. The design integrates an EVA foam outer layer with a thermoplastic polyurethane (TPU) honeycomb core fabricated using fused-deposition modeling (FDM). Horizontal and vertical orientations were tested at relative densities of 12%, 20%, and 28%, with wall thicknesses of 0.4, 0.6, and 0.8 mm. Compression and impact tests showed that vertical structures offer superior impact reduction at equal relative densities. Higher densities enhanced energy absorption, while wall thickness had minimal effects within elastic and plateau regions. Notably, a vertical structure with 12% density matched a horizontal one with 28%, demonstrating effective force attenuation with reduced material and weight. These findings provide design guidance for developing lightweight, high-performance hip protectors based on 3D-printed honeycomb architectures.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 2","pages":"Article 103986"},"PeriodicalIF":5.9,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023811","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 : 2026-01-20DOI: 10.1016/j.asej.2025.103926
Etaf Alshawarbeh , I. Elbatal , Ehab M. Almetwally , Sule Omeiza Bashiru , Ibrahim Hassan Alkhairy , Lamis M. Alamoudi , Eslam Hussam , Ahmed M. Gemeay
Modern datasets often exhibit high skewness and non-monotonic hazard rate patterns. These features reveal a gap in many traditional distributions, which struggle to model such behavior accurately. This study introduces the inverse power Akshaya distribution (IPAkD) to address this limitation. The IPAkD is developed using the inverse power transformation and provides greater flexibility for modeling right-skewed data. It has closed-form probability density function and cumulative distribution function expressions, and its hazard rate can capture an upside-down bathtub-shaped pattern. Key properties such as moments, extropy, and order statistics are also presented. The model parameters were estimated using several methods. The IPAkD was applied to seven right-skewed real datasets and compared with twelve existing models using twelve evaluation measures. The findings show that the IPAkD offers a better fit and stronger practical performance, filling an important gap in modeling complex right-skewed datasets.
{"title":"Fitting right-skewed mechanical, medical, and geological data sets by a novel statistical model","authors":"Etaf Alshawarbeh , I. Elbatal , Ehab M. Almetwally , Sule Omeiza Bashiru , Ibrahim Hassan Alkhairy , Lamis M. Alamoudi , Eslam Hussam , Ahmed M. Gemeay","doi":"10.1016/j.asej.2025.103926","DOIUrl":"10.1016/j.asej.2025.103926","url":null,"abstract":"<div><div>Modern datasets often exhibit high skewness and non-monotonic hazard rate patterns. These features reveal a gap in many traditional distributions, which struggle to model such behavior accurately. This study introduces the inverse power Akshaya distribution (IPAkD) to address this limitation. The IPAkD is developed using the inverse power transformation and provides greater flexibility for modeling right-skewed data. It has closed-form probability density function and cumulative distribution function expressions, and its hazard rate can capture an upside-down bathtub-shaped pattern. Key properties such as moments, extropy, and order statistics are also presented. The model parameters were estimated using several methods. The IPAkD was applied to seven right-skewed real datasets and compared with twelve existing models using twelve evaluation measures. The findings show that the IPAkD offers a better fit and stronger practical performance, filling an important gap in modeling complex right-skewed datasets.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 2","pages":"Article 103926"},"PeriodicalIF":5.9,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023358","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}
Crest settlement is a key indicator of seismic deformation in rockfill dams. However, the absence of a dedicated seismic settlement database and the incomplete recording of key parameters hinder systematic assessments of seismic damage. To address these limitations, this study develops a comprehensive database documenting crest settlement and associated dam damage. A novel Data–Physics Hybrid-Driven (DPHD) imputation method is introduced to reconstruct missing parameters, and its accuracy is rigorously validated. Single-factor analyses elucidate the mechanisms governing crest settlement, whereas grey relational analysis identifies the dominant influencing factors—namely, dam resistance, seismic-acceleration intensity, near-field effects, and epicentral distance. Based on the database and analytical results, seismic-settlement control standards corresponding to different damage levels are further proposed. The results demonstrate that the DPHD method effectively resolves data gaps, and the derived settlement standards provide practical guidance for seismic design and settlement-mitigation strategies in rockfill dams.
{"title":"Safety analysis of rockfill dams based on crest seismic settlement with intelligent parameter imputation and grey relational analysis","authors":"Zhou Zheng , Jinjuan Li , Shixin Zhang , Mingcong Lv","doi":"10.1016/j.asej.2026.104006","DOIUrl":"10.1016/j.asej.2026.104006","url":null,"abstract":"<div><div>Crest settlement is a key indicator of seismic deformation in rockfill dams. However, the absence of a dedicated seismic settlement database and the incomplete recording of key parameters hinder systematic assessments of seismic damage. To address these limitations, this study develops a comprehensive database documenting crest settlement and associated dam damage. A novel Data–Physics Hybrid-Driven (DPHD) imputation method is introduced to reconstruct missing parameters, and its accuracy is rigorously validated. Single-factor analyses elucidate the mechanisms governing crest settlement, whereas grey relational analysis identifies the dominant influencing factors—namely, dam resistance, seismic-acceleration intensity, near-field effects, and epicentral distance. Based on the database and analytical results, seismic-settlement control standards corresponding to different damage levels are further proposed. The results demonstrate that the DPHD method effectively resolves data gaps, and the derived settlement standards provide practical guidance for seismic design and settlement-mitigation strategies in rockfill dams.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 2","pages":"Article 104006"},"PeriodicalIF":5.9,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023813","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 : 2026-01-20DOI: 10.1016/j.asej.2026.103993
Jun Zhou, Yajun Duan
Life Cycle Assessment (LCA) often faces challenges such as low data transparency, limited traceability, and poor data sharing among entities. To address these issues, this study develops a blockchain based life cycle information management system that adopts a front end and back end separation architecture and integrates on chain and off chain collaborative storage. The system supports version tracking, auditing, and secure data sharing through unique identifiers, permission control, and smart contracts. Using bogie frame as a case study, it was validated under real data scenarios, showing zero error rates and high consistency in integrity and transparency. Performance tests indicated average response times of 30–60 ms and on chain delays of about 2.8 s, with stable operation at medium scale. The proposed framework enhances transparency, reliability, and efficiency, providing a scalable digital solution for integrating blockchain with LCA in sustainable manufacturing.
{"title":"Blockchain-enabled product life cycle assessment information management system","authors":"Jun Zhou, Yajun Duan","doi":"10.1016/j.asej.2026.103993","DOIUrl":"10.1016/j.asej.2026.103993","url":null,"abstract":"<div><div>Life Cycle Assessment (LCA) often faces challenges such as low data transparency, limited traceability, and poor data sharing among entities. To address these issues, this study develops a blockchain based life cycle information management system that adopts a front end and back end separation architecture and integrates on chain and off chain collaborative storage. The system supports version tracking, auditing, and secure data sharing through unique identifiers, permission control, and smart contracts. Using bogie frame as a case study, it was validated under real data scenarios, showing zero error rates and high consistency in integrity and transparency. Performance tests indicated average response times of 30–60 ms and on chain delays of about 2.8 s, with stable operation at medium scale. The proposed framework enhances transparency, reliability, and efficiency, providing a scalable digital solution for integrating blockchain with LCA in sustainable manufacturing.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 2","pages":"Article 103993"},"PeriodicalIF":5.9,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023809","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 : 2026-01-19DOI: 10.1016/j.asej.2026.103985
G Divya Deepak, Pavan Hiremath, Subraya Krishna Bhat
Semantic segmentation is a critical perception task in autonomous vehicles, enabling pixel-wise classification of road scenes. In this study, we propose a systematic optimization of DeepLabV3+ semantic segmentation model using Taguchi Design of Experiments (DoE) technique to enhance its performance for real-time deployment in autonomous driving. We explore the influence of key hyperparameters. solver type (Adam, RMSProp, SGDM), learning rate (10−5, 10−4, 10−3) batch size (1, 2, 3), and L2 regularization (10−5, 10−4, 10−3), across three backbone networks: ResNet-18, ResNet-50, and MobileNetV2. Experiments were conducted on the Cambridge-driving Labeled Video Database (CamVid), a widely used benchmark for road scene understanding. The DoE approach efficiently reduced the number of training configurations while maximizing segmentation performance. The best-performing model, DeepLabV3+ with a ResNet-50 backbone, achieved a Mean Intersection over Union (IoU) of 76.23%, surpassing recent approaches. The proposed framework offers a practical strategy for deploying semantic segmentation models in autonomous vehicle systems.
语义分割是自动驾驶汽车的一项关键感知任务，可以实现道路场景的逐像素分类。本研究采用田口实验设计（Taguchi Design of Experiments, DoE）技术对DeepLabV3+语义分割模型进行了系统优化，以提高其在自动驾驶中实时部署的性能。我们探讨了关键超参数的影响。求解器类型（Adam, RMSProp， SGDM），学习率（10−5,10−4,10−3），批大小（1,2,3）和L2正则化（10−5,10−4,10−3），跨越三个骨干网：ResNet-18， ResNet-50和MobileNetV2。实验是在剑桥驾驶标记视频数据库（CamVid）上进行的，CamVid是一种广泛使用的道路场景理解基准。DoE方法有效地减少了训练配置的数量，同时最大限度地提高了分割性能。性能最好的DeepLabV3+模型采用ResNet-50骨干网，实现了76.23%的平均联交（IoU），超过了最近的方法。该框架为在自动驾驶汽车系统中部署语义分割模型提供了一种实用的策略。
{"title":"Taguchi-optimized DeepLabV3+ for semantic segmentation in autonomous driving applications","authors":"G Divya Deepak, Pavan Hiremath, Subraya Krishna Bhat","doi":"10.1016/j.asej.2026.103985","DOIUrl":"10.1016/j.asej.2026.103985","url":null,"abstract":"<div><div>Semantic segmentation is a critical perception task in autonomous vehicles, enabling pixel-wise classification of road scenes. In this study, we propose a systematic optimization of DeepLabV3+ semantic segmentation model using Taguchi Design of Experiments (DoE) technique to enhance its performance for real-time deployment in autonomous driving. We explore the influence of key hyperparameters. solver type (Adam, RMSProp, SGDM), learning rate (10<sup>−5</sup>, 10<sup>−4</sup>, 10<sup>−3</sup>) batch size (1, 2, 3), and L2 regularization (10<sup>−5</sup>, 10<sup>−4</sup>, 10<sup>−3</sup>), across three backbone networks: ResNet-18, ResNet-50, and MobileNetV2. Experiments were conducted on the Cambridge-driving Labeled Video Database (CamVid), a widely used benchmark for road scene understanding. The DoE approach efficiently reduced the number of training configurations while maximizing segmentation performance. The best-performing model, DeepLabV3+ with a ResNet-50 backbone, achieved a Mean Intersection over Union (IoU) of 76.23%, surpassing recent approaches. The proposed framework offers a practical strategy for deploying semantic segmentation models in autonomous vehicle systems.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 2","pages":"Article 103985"},"PeriodicalIF":5.9,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023356","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}
Predictive maintenance (PdM) relies on accurate estimation of the remaining useful life (RUL) to support efficient industrial maintenance. However, most RUL models overlook uncertainty quantification (UQ), which is essential for safety–critical decision-making. This study presents a hybrid uncertainty-aware framework that combines a Transformer backbone with Monte Carlo Dropout (MC Dropout) and Conformal Prediction (CP). The Transformer architecture effectively learns long-range temporal dependencies in sensor data, while MC Dropout approximates epistemic uncertainty arising from model limitations. CP complements this by producing prediction intervals that capture aleatoric variability caused by noise and operating conditions. The framework is validated using NASA’s C-MAPSS FD001 and FD003 datasets. It achieves strong performance on FD001, with MAE 8.11, RMSE 11.71, and a predictive score of 193.6, and on FD003, with MAE 7.21, RMSE 10.50, and R2 0.926. By jointly addressing both uncertainty types, the method yields well-calibrated confidence intervals, enhancing reliability and interpretability in PdM applications.
{"title":"Uncertainty aware predictive maintenance using a hybrid Transformer with Monte Carlo Dropout and conformal prediction","authors":"Chao-Lung Yang, Tamrat Yifter Meles, Atinkut Atinafu Yilma, Melkamu Mengstnew Teshome","doi":"10.1016/j.asej.2026.103992","DOIUrl":"10.1016/j.asej.2026.103992","url":null,"abstract":"<div><div>Predictive maintenance (PdM) relies on accurate estimation of the remaining useful life (RUL) to support efficient industrial maintenance. However, most RUL models overlook uncertainty quantification (UQ), which is essential for safety–critical decision-making. This study presents a hybrid uncertainty-aware framework that combines a Transformer backbone with Monte Carlo Dropout (MC Dropout) and Conformal Prediction (CP). The Transformer architecture effectively learns long-range temporal dependencies in sensor data, while MC Dropout approximates epistemic uncertainty arising from model limitations. CP complements this by producing prediction intervals that capture aleatoric variability caused by noise and operating conditions. The framework is validated using NASA’s C-MAPSS FD001 and FD003 datasets. It achieves strong performance on FD001, with MAE 8.11, RMSE 11.71, and a predictive score of 193.6, and on FD003, with MAE 7.21, RMSE 10.50, and R2 0.926. By jointly addressing both uncertainty types, the method yields well-calibrated confidence intervals, enhancing reliability and interpretability in PdM applications.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 2","pages":"Article 103992"},"PeriodicalIF":5.9,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023359","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 : 2026-01-17DOI: 10.1016/j.asej.2025.103953
Selman Ogras, Fevzi Onen
Hydropower structures have approved significant progress and innovation in the development of water resources over the last 30 years, leading to the construction of large hydroelectric projects. Dissipation the enormous energy generated is a significant zone of dam engineering. Effective project design, which addresses the hydraulic characteristics of dam discharge structures and the safe and economical distribution of the resulting energy, requires a comprehensive evaluation of physical modeling, prototype experiments, and numerical modeling results. In this study, the hydraulic characteristics of the Ilısu Dam spillway structure, determined by physical modeling studies, and the effectiveness of the energy dissipation structures were numerically investigated using Computational Fluid Dynamics (Flow3D). Evaluations were accomplished by comparing the 1/100 scale model of the spillway structure and the 1/30 scale of the discharge channel. The numerical analyses employed the RNG and standard k-ε turbulence models, separately. Thus, the effectiveness of turbulence models across the entire spillway structure was determined. Moreover,16 different thresholds were designed with different deflector angles and radii of the flip bucket, which is one of the effective structures in terms of energy dissipation, and these designs were numerically analyzed and compared with the results obtained both in our current study and previous studies in the literature.
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