alexandria engineering journal最新文献

{"title":"Remediation of cadmium-contaminated soil with iron-modified montmorillonite: Insight for cadmium bioavailability and rhizosphere soil bacterial community","authors":"Chenchen Zhao ,&nbsp;Jihai Gu ,&nbsp;Yuming Zhang ,&nbsp;Jie Zhang ,&nbsp;Jingqi Zhao ,&nbsp;Fengsong Liu","doi":"10.1016/j.aej.2025.09.024","DOIUrl":"10.1016/j.aej.2025.09.024","url":null,"abstract":"<div><div>Cadmium (Cd) contamination in agricultural soils poses serious environmental and food safety risks. This study evaluated the remediation potential of iron-modified montmorillonite (GMt) for Cd contamination in rhizosphere soils through pot experiments using perennial ryegrass (<em>Lolium perenne</em> L.). The results showed that the application of GMt improved the physical and chemical properties of the soil (pH, total nitrogen, available nitrogen, and available potassium). GMt significantly reduced Cd bioavailability by 53.48 %-87.04 % (p &lt; 0.05), accompanied by a decrease in acid-soluble and reducible Cd fractions and an increase in oxidizable and residual fractions. GMt also enhanced soil urease and catalase activity (p &lt; 0.05), optimized rhizosphere bacterial community structure, particularly enriching genera associated with nutrient cycling and heavy metal tolerance. GMt reduced Cd accumulation in ryegrass by 23.54 %-27.03 %, lowering the risk of Cd entering the food chain. These findings highlight that GMt is a promising amendment for immobilizing Cd and has broad application prospects in improving soil health and ensuring food security.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 483-493"},"PeriodicalIF":6.8,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118997","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":"Boosting expertise and efficiency in LLM: A knowledge-enhanced framework for construction support","authors":"Bin Yang ,&nbsp;Hongru Xiao ,&nbsp;Zixuan Zeng ,&nbsp;Songning Lai ,&nbsp;Jiale Han ,&nbsp;Yanke Tan ,&nbsp;Yiqing Ni","doi":"10.1016/j.aej.2025.09.029","DOIUrl":"10.1016/j.aej.2025.09.029","url":null,"abstract":"<div><div>Current research on question answering in construction management faces multiple challenges, including insufficient construction knowledge in general large language models (LLMs) and the challenge for traditional LLM-based Q&amp;A systems to balance response accuracy with computational cost. To address these issues, this study proposes a knowledge-enhanced framework that incorporates two key components: (i) a Collaborative Expert Module (CEM), which enhances generation reliability while preserving efficiency through coordinated learning in a sparse network, and (ii) a Knowledge-Injected (KI) training strategy that dynamically augments model training with relevant domain knowledge. Experimental evaluations demonstrate that the proposed method not only outperforms the baseline Qwen1.5-MoE by 8.2% in ROUGE-L and 9.0% in semantic similarity, but also surpasses state-of-the-art models such as GPT-4 Turbo and DeepSeek V3, while operating with only 2.7B activated parameters. This work contributes a data-driven approach that strengthens LLMs with construction-specific knowledge, offering a more reliable and efficient foundation for domain-specific question answering.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 525-542"},"PeriodicalIF":6.8,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145119001","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":"An attention-enhanced TimesNet time series model for predicting the commodity price","authors":"Xuesen Cai","doi":"10.1016/j.aej.2025.09.018","DOIUrl":"10.1016/j.aej.2025.09.018","url":null,"abstract":"<div><div>Commodity price prediction is a critical task in economic management, financial investment, and market regulation. Traditional prediction models, such as ARIMA and GARCH, often encounter limitations in capturing the complex nonlinear dynamics and time-dependent nature of price fluctuations. In this study, we present an enhanced TimesNet model that integrates self-attention mechanisms with two-dimensional time–frequency transformations. This combination improves the model’s ability to effectively capture both long-term trends and short-term cyclical fluctuations in commodity prices. The model was evaluated using data from a wide range of agricultural commodities, including potatoes, cucumbers, soybeans, corn, wheat, rapeseed, eggs, bananas, apples, oil, and watermelons. Experimental results demonstrate that the improved model significantly outperforms existing models. Specifically, with a sequence length of 512, the model achieves an average absolute error (MAE) of 0.129, compared to 0.134 for the original TimesNet model. These results confirm the enhanced model’s superior capacity for capturing long-term dependencies and cyclical fluctuations. The proposed TimesNet model, by combining self-attention and 2D time–frequency transformations, offers a robust, accurate, and computationally efficient solution for commodity price prediction, making it highly applicable to real-world agricultural markets.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 447-458"},"PeriodicalIF":6.8,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099982","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":"Atomistic insights into catalytic role of platinum-graphene nanostructures in decomposition of high-energy-density fuels","authors":"Eungyo Choi ,&nbsp;Sungwook Leo Hong ,&nbsp;Chang-Min Yoon ,&nbsp;Hyung Sub Sim","doi":"10.1016/j.aej.2025.09.007","DOIUrl":"10.1016/j.aej.2025.09.007","url":null,"abstract":"<div><div>To advance the cooling performance critical for hypersonic vehicles, high-energy-density fuels have emerged as promising candidates, with platinum-graphene (Pt@FGS) nanocatalysts demonstrating significant potential for enhancing their regenerative cooling efficiency. However, the underlying catalytic mechanisms of these nanocatalysts, particularly their influence on reaction pathways and carbonization processes, remain insufficiently understood. This study employs a ReaxFF-based hybrid simulation approach to investigate the effects of Pt@FGS nanocatalysts on the decomposition of exo-tetrahydrodicyclopentadiene (exo-THDCPD) across a broad temperature range (900–2000 K). The Pt@FGS nanocatalysts were modeled as a partially oxidized graphene structure with six platinum atoms anchored at defect sites. ReaxFF molecular dynamics (MD) simulations were performed to capture real-time pyrolysis pathways and nanocatalyst-fuel interactions at the atomic scale. To extend the timescale and observe low-temperature pyrolysis relevant to experimental conditions, the collective variable-driven hyperdynamics (CVHD) method was employed. Nudged elastic band (NEB) calculations quantified key bond dissociation energy barriers, providing insight into catalytic dehydrogenation mechanisms. The MD results revealed that Pt@FGS nanocatalysts reduce the activation energy by approximately 33 % compared to neat fuel, significantly enhancing fuel conversion rates by up to a factor of four through catalytic dehydrogenation. Heat sink capacity improvements were observed at lower temperature ranges, attributed to nanocatalyst-promoted dehydrogenation, as confirmed by NEB analysis. The CVHD approach enabled pyrolysis simulations under experimentally relevant conditions, yielding activation energies and product distributions consistent with those obtained from high-temperature MD simulations. Interestingly, additional MD simulations demonstrated Pt@FGS nanocatalysts can delay carbonization onset effectively suppressing the formation of carbon deposits. By combining MD, CVHD, and NEB analyses, we elucidated the reaction mechanisms of exo-THDCPD decomposition over Pt@FGS nanocatalysts. The results demonstrate at the atomistic scale that Pt suppresses coke formation by interacting with intermediates and hindering aromatic ring closure, providing insights into the design of fuel-dispersible catalysts for regenerative fuel cooling.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 420-436"},"PeriodicalIF":6.8,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099980","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":"BiTCSAtt-TCN: A hybrid model for efficient electricity load forecasting in smart grids","authors":"Yuxuan Sun ,&nbsp;Yan Zhou","doi":"10.1016/j.aej.2025.09.002","DOIUrl":"10.1016/j.aej.2025.09.002","url":null,"abstract":"<div><div>With the rapid development of smart grids, electricity load forecasting and anomaly detection have become essential tasks for ensuring the stable operation of the grid and optimizing energy management. The large-scale time-series data generated by smart grids contain complex patterns and various dependencies, which pose challenges for traditional forecasting methods, especially in handling long-term dependencies and high-dimensional data. This paper proposes the BiTCSAtt-TCN model, which cleverly combines Temporal Convolutional Networks (TCN), Bidirectional Long Short-Term Memory networks (BiLSTM), and the self-attention mechanism to leverage the advantages of each component. TCN effectively extracts local time features, BiLSTM enhances the modeling of bidirectional dependencies within the sequence, and the self-attention mechanism dynamically focuses on critical time steps. This combination not only compensates for the shortcomings of individual models but also provides significant advantages in handling long-term dependencies and improving prediction accuracy. Extensive experiments were conducted on the SGRT-LMD, ELF, NREL, and EIA datasets, and the results show that BiTCSAtt-TCN outperforms existing models across multiple evaluation metrics, such as MSE, RMSE, R<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>, and MAE.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 437-446"},"PeriodicalIF":6.8,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099981","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":"MONRBO: A multi-objective Newton-Raphson-based optimizer with dynamic elimination-based crowding distance for numerical benchmark and engineering design problems","authors":"Premkumar Manoharan ,&nbsp;Sowmya Ravichandran ,&nbsp;Garima Sinha ,&nbsp;Tan Ching Sin ,&nbsp;Ahmad O. Hourani ,&nbsp;Tengku Juhana Tengku Hashim","doi":"10.1016/j.aej.2025.09.015","DOIUrl":"10.1016/j.aej.2025.09.015","url":null,"abstract":"<div><div>In the multi-objective optimization domain, where the aim is to handle multiple conflicting objectives simultaneously, the effectiveness of the optimization algorithm plays a critical role. The Newton-Raphson-Based Optimizer (NRBO) is initially developed for single-objective problems employs a Newton-Raphson-based search rule to navigate complex solution spaces. This study introduces a new extension of this approach, termed Multi-Objective NRBO (MONRBO), to solve multi-objective optimization problems. The proposed MONRBO incorporates non-dominated sorting and a dynamic elimination-based crowding distance mechanism to maintain solution diversity and improve convergence toward the true Pareto front. The performance of MONRBO is evaluated in three phases. First, it is tested on five standard bi-objective problems from the ZDT benchmark suite. Second, its capability is assessed on seven scalable tri-objective problems from the DTLZ test suite. Finally, its practical applicability is validated on six real-world constrained engineering design problems. MONRBO is compared with state-of-the-art algorithms using comprehensive performance metrics, including GD, IGD, HV, Spread, and Spacing in all phases. The results consistently demonstrate that MONRBO achieves competitive performance across test problems and real-world applications, highlighting its robustness, scalability, and effectiveness for solving complex multi-objective optimization problems.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 374-402"},"PeriodicalIF":6.8,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099978","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":"MDEformer: A spatio-temporal decoupling transformer with the multidimensional information encoding for certain traffic flow prediction","authors":"Yudong Lu ,&nbsp;Tao Cui ,&nbsp;Di Dong ,&nbsp;Chongguang Ren ,&nbsp;Zhijian Qu ,&nbsp;Xianwei Zhang","doi":"10.1016/j.aej.2025.09.037","DOIUrl":"10.1016/j.aej.2025.09.037","url":null,"abstract":"<div><div>With the rapid advancement of Intelligent Transportation Systems (ITS), accurate traffic flow prediction has become a critical challenge. Although existing deep learning models are capable of capturing the spatio-temporal dependencies in traffic data to some extent, they still face limitations in modeling spatio-temporal features, long-term and short-term temporal dependencies, and the dynamic-static spatial relationships at local and global scales. This paper proposes a Spatio-Temporal Decoupling Transformer with Multidimensional Information Encoding (MDEformer) to address these issues. MDEformer effectively captures spatio-temporal features through the integration of multidimensional information encoding. Moreover, the model adopts a decoupled design of temporal and spatial encoder layers. In the temporal encoder layer, a GRU is employed to replace the linear mapping in the multi-head self-attention mechanism, thereby facilitating improved capture of short-term fluctuations and long-term trends. In the spatial encoder layer, we integrate the graph fusion module with Chebyshev graph convolution to replace the conventional mapping in the multi-head self-attention mechanism, thereby enhancing the capability to model local and global dynamic-static spatial dependencies. Experiments on four real-world traffic datasets demonstrate that MDEformer significantly outperforms other baseline methods in terms of prediction accuracy.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 403-419"},"PeriodicalIF":6.8,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099979","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":"Correlations among microstructure, crystallographic texture and mechanical properties of AA7475-T7/SiC/Al2O3 surface composite fabricated via FSP","authors":"Md Saquib Bin Reyaz ,&nbsp;Murshid Imam ,&nbsp;Md Anwar Ali Anshari ,&nbsp;K.P. Vineesh","doi":"10.1016/j.aej.2025.09.031","DOIUrl":"10.1016/j.aej.2025.09.031","url":null,"abstract":"<div><div>In this study, AA7475-T7/SiC/Al₂O₃ hybrid surface composites (HSCs) were fabricated via friction stir processing (FSP) by using different rotational speeds of 900 rpm, 1100 rpm and 1300 rpm, and different reinforcement combinations of SiC and Al₂O₃ by vol%. These composites are recognized as S1 (900 rpm, 7 % SiC and 13 % Al₂O₃), S2 (1100 rpm, 13 % SiC and 7 % Al₂O₃) and S3 (1300 rpm 10 % SiC and 10 % Al₂O₃). Composite (S3) emerged as the best composite, achieving the highest ultimate tensile strength (UTS) of 656 ± 5.81 MPa, a highest microhardness of 281 ± 2.93 Hv with a minimum residual stress of −80 ± 5.0 MPa as supported by tensile test, Vickers hardness test and Chromium X-ray tube test respectively. The microscopic observations revealed that S3 consisted of highly refined grains with an average grain size (AGS) of 3.17 ± 0.09 µm, a high fraction (90.20 %) of the high-angle grain boundaries along with B and C major shear texture components as evident by scanning electron microscopy (SEM) and electron backscattered diffraction (EBSD) analyses. Overall, the study demonstrates the strategy of selection of FSP rotational speed and reinforcement combination to develop the desired mechanical properties in AA7475-T7 based hybrid composite.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 355-373"},"PeriodicalIF":6.8,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099977","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":"Generalized class of estimators for population distribution function in the presence of non-response","authors":"Abdulaziz S. Alghamdi ,&nbsp;Fatimah A. Almulhim","doi":"10.1016/j.aej.2025.08.052","DOIUrl":"10.1016/j.aej.2025.08.052","url":null,"abstract":"<div><div>The nature of non-response in surveys is a very big challenge and the results obtained are often biased and may misguide research and policy conclusions. To resolve this we suggest flexible and generalized estimator that should be in place to correct the non-response and improve the precision of the estimations of population distribution function (DF). Their main contribution is associated with the creation of a purification process which is useful to rectify productivity-related distributions distortions brought about non-response. Our valid sample of the suggested approach is based on real survey data, which shows significant increases in reliability and representativeness of estimates of the productivity DF. A first-order approximation will help to evaluate recommended and existing estimators regarding their bias and MSE characteristics. The proposed estimators receive a numerical evaluation against current operational estimators. Multiple Specific estimators were developed to enlarge the generalized class of estimators. This research uses authentic data to check the precision of the estimators. The proposed estimators provide superior performance for population DF under non-response compared to initial estimators as indicated by our data. The estimation method reveals substantial efficiency superiority of the proposed MSE-based estimators. These findings highlight the practical applications of our method in real-life situations especially by the researchers and policymakers that require good data on economic and social analysis. In general, this works closing one of the major gaps in statistical methodology that exists by providing a powerful solution to the problem of population non-response.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 343-354"},"PeriodicalIF":6.8,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099976","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 backstepping command-filtered adaptive sliding mode disturbance observer for finite-time tracking of wheelchair upper-limb exoskeleton robots","authors":"Huan-Chung Li ,&nbsp;Omid Mofid ,&nbsp;Saleh Mobayen ,&nbsp;Telung Pan ,&nbsp;Anton Zhilenkov ,&nbsp;Hung-Wen Chiu","doi":"10.1016/j.aej.2025.09.025","DOIUrl":"10.1016/j.aej.2025.09.025","url":null,"abstract":"<div><div>In this paper, the main objective is to design a high-performance trajectory tracking control method for the wheelchair upper-limb exoskeleton robot system operating under significant uncertainty and external disturbances utilizing integrated command-filtered backstepping sliding mode control with an adaptive sliding mode disturbance observer. To this end, a general form of the dynamical model of the wheelchair upper-limb exoskeleton system under uncertainties and disturbances is first developed. The proposed approach overcomes chattering, computational complexity, or lack of robustness to uncertainties through adaptive compensation and command filtering techniques. Specifically, the command-filtered backstepping control reduces the computational burden associated with traditional backstepping, while the adaptive sliding mode disturbance observer effectively compensates for unknown dynamics and external perturbations in real time, enabling smooth and accurate control without chattering. Additionally, an asymmetric Lyapunov function is incorporated into the control design to ensure finite-time convergence of the tracking error and enhance system stability. The effectiveness of the proposed method is validated through both numerical and real-time simulations. Quantitative results from numerical simulations demonstrate that the proposed controller achieves less than 1 % steady-state tracking error and a 35 % improvement in convergence time compared to conventional sliding mode controllers. Moreover, real-time experiments using the Speedgoat real-time target system—interfaced with MATLAB/ Simulink for hardware-in-the-loop testing—confirm the practical implementation viability of the controller.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 241-259"},"PeriodicalIF":6.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099515","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}