Ain Shams Engineering Journal最新文献

{"title":"Corrigendum to “The utilization of novel deep eutectic solvents in cement production and their impact on the physical and the mechanical properties of Portland cement” [Ain Shams Eng. J. 17(1) (2026) 103861]","authors":"Ali Tugrul Albayrak","doi":"10.1016/j.asej.2026.104025","DOIUrl":"10.1016/j.asej.2026.104025","url":null,"abstract":"","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 3","pages":"Article 104025"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147539233","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}

{"title":"Design of speed-control system for an autonomous vehicle based on dual BLDC-motor steering and CAN communication, applying adaptive fuzzy logic control","authors":"Sayyed Haleem Shah ,&nbsp;Sadiq Ur Rahman ,&nbsp;Omer Mohammed Elbabo Mohammed ,&nbsp;Hui Cai","doi":"10.1016/j.asej.2026.104057","DOIUrl":"10.1016/j.asej.2026.104057","url":null,"abstract":"<div><div>The article presents a speed-controlled driving mechanism designed for an electric vehicle, utilizing a dual Brushless Direct Current (BLDC) motor autonomous steering configuration. To achieve accurate control of the speed in motor control applications, it is desirable to ensure that the system operates with high efficiency and robustness for optimal performance. Traditional approaches to motor control, such as Integral-Derivative (PID) control, are often severely limited by the dynamic requirements of changing speeds and the effects of sensor noise, hence requiring new solutions. In response to these challenges, this work presents the combined usage of adaptive PID control techniques, fuzzy logic algorithms, and Controller Area Network (CAN) bus communication protocols to improve the speed and directional orientation of a dual-motor autonomous vehicle steering design, thereby guaranteeing both real-time response and high-performance control capabilities. The proposed approach of adaptive fuzzy-PID, which is based on the real-time analysis of motor behavior, empowers the system to dynamically adjust to the varying commands pertaining to motor speed and direction, thereby ensuring that optimal performance is consistently achieved across a spectrum of operational conditions. Furthermore, CAN communication facilitates both the effective control of the motors and the acquisition of diagnostic feedback, thus enabling the system to function efficiently in real-time environments while simultaneously monitoring critical safety features to assure reliable operational integrity. The proposed system has been experimentally validated and is designed to enable the independent control of dual motors with synchronized speed regulation, thereby rendering its application particularly suitable for various domains, including electric vehicles, robotic systems, and any other applications wherein coordinated motor movement is of utmost significance.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 3","pages":"Article 104057"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147422180","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}

{"title":"Input attention, squeeze and excitation, and spatial transformer of YOLO for fault detection using UAV","authors":"João Pedro Matos Carvalho ,&nbsp;Stefano Frizzo Stefenon ,&nbsp;Valderi Reis Quietinho Leithardt ,&nbsp;Laio Oriel Seman ,&nbsp;Kin-Choong Yow ,&nbsp;Juan Francisco De Paz Santana","doi":"10.1016/j.asej.2026.104067","DOIUrl":"10.1016/j.asej.2026.104067","url":null,"abstract":"<div><div>The detection of faults in insulators is important to guarantee the continuous supply of electricity. To identify faults in these components, various object detection methods based on deep learning have been explored. This paper investigates architectural enhancements to the You Only Look Once (YOLO) framework for fault detection in electrical power grid insulators. Three structural variants are proposed: the Input Attention Transformer (IAT-YOLO) for spatial feature refinement, Squeeze-and-Excitation (SAE-YOLO) modules for channel recalibration, and Spatial Transformer Networks (STN-YOLO) for geometric alignment. Experiments were conducted on a publicly available insulator dataset from Unmanned Aerial Vehicles (UAVs), comprising seven defect categories, including pollution, breakage, and flashover damage. Results demonstrate that STN-YOLO and SAE-YOLO consistently improve generalization and robustness, achieving mAP values of up to 0.995 for specific classes. The findings highlight the effectiveness of integrating attention mechanisms and spatial transformations to enhance YOLO-based detection, contributing to improved automated inspection of the power grid.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 3","pages":"Article 104067"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147422176","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}

{"title":"The evolving landscape of AI-powered antenna design, optimization, and control: A comprehensive review","authors":"Wei Xu ,&nbsp;Jing Liu ,&nbsp;Tian-qi Bai ,&nbsp;Hong Wu ,&nbsp;Qing-song Yang","doi":"10.1016/j.asej.2026.104052","DOIUrl":"10.1016/j.asej.2026.104052","url":null,"abstract":"<div><div>The rapid evolution of wireless communication systems, including 5G/6G networks, IoT ecosystems, satellite communications, and joint sensing applications, has imposed unprecedented demands on antenna performance, necessitating innovations in design, optimization, and control. This comprehensive review synthesizes the transformative role of artificial intelligence (AI) in antenna engineering, addressing traditional challenges such as high computational costs, complex multi-objective trade-offs, and real-time adaptability. We systematically survey AI paradigms—evolutionary algorithms (EAs), machine learning (ML), and deep learning (DL)—across key lifecycle stages: generative design via EAs and GANs for novel topologies; surrogate-assisted optimization using SMA-EA and Bayesian methods for parameter refinement; RL-driven control for adaptive beamforming, reconfigurable antennas, and impedance matching; and hybrid approaches integrating AI with physics-informed neural networks (PINNs) for inverse problems. Case studies illustrate significant advancements, including up to 90% reduction in simulation time and discovery of non-intuitive structures surpassing conventional designs. Critical challenges, such as data scarcity, generalizability, interpretability, and edge deployment, are critically analyzed. Promising future directions emphasize advanced architectures (e.g., GNNs and Transformers), transfer learning for sim-to-real gaps, multi-physics integration, explainable AI (XAI), and open-source ecosystems. This review consolidates fragmented knowledge, identifies research gaps, and provides a roadmap for developing intelligent, autonomous antenna systems essential for next-generation technologies, fostering interdisciplinary collaboration between AI and electromagnetics experts.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 3","pages":"Article 104052"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147422179","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}

{"title":"Exploration of exergoeconomic evaluation through solar collector in magnetohydrodynamic Williamson hybrid nanofluid flow based on machine learning technique","authors":"Attia Khushi ,&nbsp;Mushtaq K. Abdalrahem ,&nbsp;Muhammad Habib Ullah Khan ,&nbsp;Waqar Azeem Khan ,&nbsp;Zohaib Arshad ,&nbsp;Taseer Muhammad ,&nbsp;Muhammad Waqas","doi":"10.1016/j.asej.2026.104013","DOIUrl":"10.1016/j.asej.2026.104013","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Efficient heat management is essential for improving the performance of renewable energy systems, particularly in solar-based thermal technologies. To address this challenge, the present study investigates the exergoeconomic performance and thermophysical behavior of a magnetohydrodynamic Williamson hybrid nanofluid (WHNF) flowing over a continuously moving thin needle under the influence of a magnetic field, porosity, and non-uniform heat flux. The hybrid nanofluid, composed of AA7075–AA7072 nanoparticles dispersed in methanol, is analyzed to enhance heat transfer and energy conversion efficiency. The governing partial differential equations are transformed into ordinary differential equations using similarity variables and solved parametrically to examine variations in velocity, temperature, and entropy generation profiles. A machine learning framework based on Artificial Neural Networks (ANNs) is integrated to predict and optimize the thermophysical properties and exergy efficiency of the WHNF system. The graphical results are obtained by varying number of parameters like; &lt;span&gt;&lt;math&gt;&lt;mi&gt;M&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt;, &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;mi&gt;e&lt;/mi&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;, &lt;span&gt;&lt;math&gt;&lt;mi&gt;C&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt;, &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;Pr&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;, and &lt;span&gt;&lt;math&gt;&lt;mi&gt;B&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt;, for discussions of numerical results on &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msup&gt;&lt;mi&gt;f&lt;/mi&gt;&lt;mo&gt;′&lt;/mo&gt;&lt;/msup&gt;&lt;mfenced&gt;&lt;mrow&gt;&lt;mi&gt;η&lt;/mi&gt;&lt;/mrow&gt;&lt;/mfenced&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; and &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;mfenced&gt;&lt;mrow&gt;&lt;mi&gt;η&lt;/mi&gt;&lt;/mrow&gt;&lt;/mfenced&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; profile. A total of 76 datasets were generated, with 54 used for training, 11 for testing, and 11 for validation. The ANN results show strong predictive accuracy, with mean square error (MSE) values and absolute error (AE) within acceptable limits. The analysis reveals that increasing the magnetic parameter and porosity tends to reduce velocity while enhancing temperature gradients and entropy generation. Moreover, The &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msup&gt;&lt;mi&gt;f&lt;/mi&gt;&lt;mo&gt;′&lt;/mo&gt;&lt;/msup&gt;&lt;mfenced&gt;&lt;mrow&gt;&lt;mi&gt;η&lt;/mi&gt;&lt;/mrow&gt;&lt;/mfenced&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; profile declines with growing differences of &lt;span&gt;&lt;math&gt;&lt;mi&gt;M&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt; and &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;mi&gt;e&lt;/mi&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; while &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msup&gt;&lt;mi&gt;f&lt;/mi&gt;&lt;mo&gt;′&lt;/mo&gt;&lt;/msup&gt;&lt;mfenced&gt;&lt;mrow&gt;&lt;mi&gt;η&lt;/mi&gt;&lt;/mrow&gt;&lt;/mfenced&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; increases growing differences of &lt;span&gt;&lt;math&gt;&lt;mi&gt;C&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt;. &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;mfenced&gt;&lt;mrow&gt;&lt;mi&gt;η&lt;/mi&gt;&lt;/mrow&gt;&lt;/mfenced&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; profile declines with raising values of &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mi&gt;r&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; and AE noted between &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mo&gt;-&lt;/mo&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mi&gt;o&lt;/mi&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mn&gt;3&lt;/mn&gt;&lt;mo&gt;×&lt;/mo&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;msup&gt;&lt;mn&gt;10&lt;/mn&gt;&lt;mrow&gt;&lt;mo&gt;-&lt;/mo&gt;&lt;mn&gt;4&lt;/mn&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;. Moreover, &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 3","pages":"Article 104013"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190858","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}

{"title":"Real wind data clustering for optimal design of a 12-slot/10-pole PMSG in wind power applications","authors":"Ahmed T. Abdel-Wahed ,&nbsp;Wael A. Taha ,&nbsp;Mohamed G. Abdel-Moneim ,&nbsp;Ayman S. Abdel-Khalik ,&nbsp;Majdi Mansouri ,&nbsp;Shehab Ahmed","doi":"10.1016/j.asej.2026.104018","DOIUrl":"10.1016/j.asej.2026.104018","url":null,"abstract":"<div><div>The growing demand for renewable energy highlights wind power as a key source of sustainable electricity. However, the fluctuating nature of wind poses challenges for turbine operation and generator design, impacting system efficiency. To address this, extensive wind datasets combined with modern analysis methods offer practical solutions. In particular, artificial intelligence (AI) techniques such as machine learning and clustering can model real wind conditions and support improved design strategies. This paper introduces a data-driven approach to wind generator design, moving beyond the traditional single operating point by integrating real-world wind profiles at the early design stage. Several clustering methods are evaluated statistically to determine the most effective representation of wind variability. The chosen method is applied to a 25-kW surface-mounted permanent magnet synchronous generator (PMSG), optimized using surrogate modeling and finite element analysis (FEA). The design is further validated with FEA simulations and experimental tests on a 2-kW prototype.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 3","pages":"Article 104018"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190843","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}

{"title":"Auxiliary diagnosis of liver cancer using multimodal CT and MRI with deep learning and radiological feature fusion approach","authors":"Yan Wang ,&nbsp;Shi Wang ,&nbsp;Wenjuan Pan ,&nbsp;Shiping Ye ,&nbsp;Jinming Wang ,&nbsp;Ghulam Abbas ,&nbsp;Amr Yousef ,&nbsp;Ezzeddine Touti","doi":"10.1016/j.asej.2026.104014","DOIUrl":"10.1016/j.asej.2026.104014","url":null,"abstract":"<div><div>Liver cancer, particularly Hepatocellular carcinoma (HCC), is a significant cause of cancer-related deaths worldwide due to its asymptomatic nature and challenges in early detection. In clinical practice, radiologists often rely on multiphase Computed Tomography (CT) and multi-sequence Magnetic Resonance Imaging (MRI) to detect and evaluate liver lesions. However, accurately interpreting across these modalities is complex and subject to diagnostic variability, particularly in early-stage cases. Additionally, conventional methods that rely on single-modality CT or MRI often overlook subtle yet critical diagnostic features and fail to integrate cross-modal dependencies effectively. This research presents a Residual Dense-based Multimodal Fusion Network (RD-MFNet) to assist radiologists by providing accurate and consistent auxiliary diagnosis of liver cancer through the combined analysis of CT and MRI scans. The model integrates ResNet3D for modality-specific encoding of CT phases, capturing structural and vascular analysis, and EfficientNet3D with Squeeze-and-Excitation (SE) modules for extracting contrast-enhanced features from image sequences. A residual dense feature fusion using conditional masking handles missing modalities and fuses hierarchical representation across feature phases. The RD-MFNet model enhances liver cancer diagnosis, yielding a 12% increase in Dice Similarity Coefficient (DSC) and a decrease in Hausdorff distance, and achieves a DSC of 92.3% and an area under the curve of 97.5%, demonstrating its reliability in auxiliary diagnosis.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 3","pages":"Article 104014"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191328","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}

{"title":"Quintic Hermite Spline Collocation Approach to the Time Fractional RLW and MRLW equations","authors":"Murat Arı","doi":"10.1016/j.asej.2026.104011","DOIUrl":"10.1016/j.asej.2026.104011","url":null,"abstract":"<div><div>This study presents a quintic Hermite spline-based collocation scheme for solving the Regularized Long-Wave (RLW) and Modified RLW equations in both integer-order and Caputo time-fractional settings. To the best of our knowledge, this represents the first application of this technique to these specific equations. Using Legendre and Chebyshev collocation points, the method is rigorously assessed through benchmark problems. A von Neumann analysis confirms the unconditional stability of the linearized scheme. Numerical results demonstrate that the proposed approach yields superior accuracy compared to existing methods, achieving high precision even on coarse spatial meshes. Additionally, the algorithm’s conservative nature is verified by the preservation of mass, momentum, and energy invariants. The findings establish the method as a robust and efficient framework for simulating complex fractional wave dynamics.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 3","pages":"Article 104011"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191325","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}

{"title":"Theoretical and computational analysis of a novel fractional-order mathematical model for HIV transmission dynamics","authors":"Zakir Ullah ,&nbsp;Kamal Shah ,&nbsp;M. Motawi Khashan ,&nbsp;Bahaaeldin Abdalla ,&nbsp;Thabet Abdeljawad","doi":"10.1016/j.asej.2026.104019","DOIUrl":"10.1016/j.asej.2026.104019","url":null,"abstract":"<div><div>We develop a five-class fractional mathematical model to investigate HIV transmission using the Caputo–Fabrizio (CF) derivative. The population is divided into susceptible, acute, chronic, treated and AIDS classes to capture the key stages of HIV progression and the effects of antiretroviral therapy. Existence and uniqueness of solutions are established using the fixed point theorem, a bounded invariant region is identified, and the basic reproduction threshold <span><math><msub><mi>R</mi><mrow><mn>0</mn></mrow></msub></math></span> is derived using the next-generation matrix. Analytical results demonstrate the local and global stability of both the infection-free equilibrium and the endemic equilibrium. Lower fractional orders are shown to slow convergence to equilibrium, reflecting the memory effects inherent in fractional dynamics. The CF operator therefore provides a flexible and realistic framework for understanding HIV transmission and assessing the influence of treatment, disease progression, and memory effects on long-term epidemic outcomes. The Ulam–Hyers (UH) stability of the considered HIV model under CF derivative is proved. In addition, numerical solutions are obtained by using the Adams–Bashforth method corresponding to the CF derivative. Simulations show that early initiation of antiretroviral therapy, reduced treatment dropout, and improved viral suppression substantially decrease HIV prevalence.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 3","pages":"Article 104019"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190859","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}

{"title":"Investigation of long-term performance monitoring of cementitious mixes modified with healing agents and polymeric additives of self-healing polymer modified mortar (SHPMM)","authors":"Humaira Kanwal ,&nbsp;Ziping Wang ,&nbsp;Wenfeng Hao ,&nbsp;Kamran Javed ,&nbsp;Muhammad Asim ,&nbsp;Kennedy C. Onyelowe ,&nbsp;Viroon Kamchoom ,&nbsp;Krishna Prakash Arunachalam","doi":"10.1016/j.asej.2026.104038","DOIUrl":"10.1016/j.asej.2026.104038","url":null,"abstract":"<div><div>Concrete and mortar exhibit durability limitations in aggressive environments due to cracking, high permeability, and construction defects. Polymer-modified and self-healing cementitious materials have emerged as sustainable solutions; however, the synergistic use of polymer modifiers with chemical–biological healing agents remains underexplored.</div><div>This study investigates self-healing polymer-modified mortar (SHPMM) incorporating styrene butadiene rubber (SBR) and ethylene vinyl acetate (EVA) as partial cement replacements at 0%,4%,8%,12% &amp; 16%. A healing system consisting of 5% calcium lactate, 5% sodium silicate, 1% sodium carbonate. Also 1% effective microorganisms was added to all mixes. Workability, mechanical performance, durability, and microstructural characteristics were evaluated through slump, ultrasonic pulse velocity, strength tests, rapid chloride permeability, SEM, and EDX analyses.</div><div>The results indicate that polymer addition significantly improves workability, strength, and durability. Slump values increased steadily with increasing polymer content. Optimum performance was observed at 4% and 8% polymer replacement, where permeability was markedly reduced. Compared to the control mix, compressive strength increased by 7–11%, split tensile strength by 12–17%, and flexural strength by 31–33%. RCPT values decreased substantially, with reductions of 32% and 45% for 4% and 8% SBR, and 22% and 58% for 4% and 8% EVA, respectively. Microstructural analysis confirmed improved matrix densification and crack-healing efficiency. EVA demonstrated superior performance compared to SBR, attributed to its powdered form and enhanced bonding characteristics.</div><div>Overall, the combined application of polymer modifiers and healing agents effectively improves the mechanical performance, durability, and self-healing efficiency of cementitious composites, offering a viable solution for sustainable infrastructure in aggressive environments.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"17 3","pages":"Article 104038"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190844","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}