Asian Journal of Civil Engineering最新文献

Correlation analysis of ground motion intensity measures for seismic damage assessment: insights from near and far field records 地震损害评估中地面运动强度测量的相关分析：来自近场和远场记录的见解

Asian Journal of Civil Engineering Pub Date : 2025-04-12 DOI: 10.1007/s42107-025-01289-9

Manish Sharma, Srishti Singh, Prahlad Prasad, Vishwajit Anand, Nazrul Islam

{"title":"Correlation analysis of ground motion intensity measures for seismic damage assessment: insights from near and far field records","authors":"Manish Sharma, Srishti Singh, Prahlad Prasad, Vishwajit Anand, Nazrul Islam","doi":"10.1007/s42107-025-01289-9","DOIUrl":"10.1007/s42107-025-01289-9","url":null,"abstract":"<div><p>This study examines the relationship between various earthquake ground motion parameters, offering valuable insights into structural behaviour. The analysis utilizes the horizontal components of motion from 71 pairs of far-field and 98 pairs of near-field ground motion records sourced from the PEER NGA West-2 Database. Factors such as event magnitude, source-to-site distance, and geological conditions at recording sites are carefully taken into account. Seism Signal software is employed to determine the ground motion parameters. A particular focus is placed on investigating the correlation between different ground motion parameters, especially the ratio of peak ground acceleration (PGA) to peak ground velocity (PGV), which is a critical parameter for classifying ground motion suites in nonlinear time history analyses of structures. Using Pearson correlation, the study highlights that mean time exhibits the strongest correlation with the PGA/PGV ratio for far-source earthquakes. Additionally, it identifies a more pronounced correlation between the PGA/PGV ratio and specific ground motion parameters in near-source earthquakes compared to far-source events.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 5","pages":"1973 - 2004"},"PeriodicalIF":0.0,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Vulnerability assessment of vertical irregularities in medium-rise reinforced concrete structures using lead rubber bearing 铅橡胶支座中高层钢筋混凝土结构竖向不规则性易损性评价

Asian Journal of Civil Engineering Pub Date : 2025-04-07 DOI: 10.1007/s42107-024-01260-0

Sonal A. Chavan, Nilesh U. Mate

{"title":"Vulnerability assessment of vertical irregularities in medium-rise reinforced concrete structures using lead rubber bearing","authors":"Sonal A. Chavan, Nilesh U. Mate","doi":"10.1007/s42107-024-01260-0","DOIUrl":"10.1007/s42107-024-01260-0","url":null,"abstract":"<div><p>Medium-rise reinforced concrete structures with vertical irregularities experience vulnerable behavior during seismic forces. To mitigate this vulnerable behavior, the base isolation technique is more effective than the strategies used to protect the civil structure against seismic excitation, as Iuliis (2008) stated. Base isolation is a technique to separate the structure from the seismic effect developed in the form of ground acceleration. The acceleration parameter, base shear, story displacement at the top and ground floors, story drift ratios, and target periods are considered for parametric study. The results demonstrate that the base isolator with stiffness coefficient reduces the structure's base shear and top floor displacement.</p><p>Similarly, the combined effects of base isolation and SSI create a more complex system that does not behave straightforwardly compared to simpler models. The use of LRB shows results similar to those of medium-stiff soil strata during building analysis. The LRB reduces the sudden increase in the inter-story drift at the stiffness irregularity location.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 5","pages":"2255 - 2273"},"PeriodicalIF":0.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing structural health monitoring with AI-ML algorithms: a focus on crack detection and prediction 用AI-ML算法加强结构健康监测：关注裂缝检测和预测

Asian Journal of Civil Engineering Pub Date : 2025-04-04 DOI: 10.1007/s42107-024-01261-z

Ahmad Bader, Amir Shtayat, Bara’ Al-Mistarehi

{"title":"Enhancing structural health monitoring with AI-ML algorithms: a focus on crack detection and prediction","authors":"Ahmad Bader, Amir Shtayat, Bara’ Al-Mistarehi","doi":"10.1007/s42107-024-01261-z","DOIUrl":"10.1007/s42107-024-01261-z","url":null,"abstract":"<div><p>SHM is a very important process in terms of the safety and durability of infrastructure. Traditional SHM often faces problems detecting minor structural defects and handling large datasets. Therefore, certain more advanced approaches are called for. The paper discussed the applications of AI and ML algorithms, such as CatBoost and the African Vultures Optimization Algorithm, for such challenges. The research is based on a unique dataset of 8,541 rows and diverse features, developing a predictive framework that enhances crack detection and forecast capabilities. The approach mainly deals with heterogeneous data using the CatBoost algorithm, given its capability for high-accuracy predictions, while AVOA optimizes feature selection, reduces the computational cost, and guarantees no loss in model performance. This methodology has resulted in a significant enhancement of the prediction accuracy, which states the importance of AI-ML integration in SHM. The key results demonstrate the effectiveness of the model in detecting structural anomalies and crack propagation to enable proactive maintenance strategies. This study’s contributions have gone toward advancing SHM with scalable and efficient AI-ML frameworks, enabling real-time monitoring for better infrastructure management. Such development might have a transforming potential to cut down on maintenance costs and enhance operational safety, thus further encouraging sustainable infrastructure systems.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 5","pages":"1907 - 1918"},"PeriodicalIF":0.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of compressive strength, static modulus and wenner resistivity for normal concrete using different percentages of recycled concrete as a coarse aggregate 用不同比例的再生混凝土作为粗骨料预测普通混凝土的抗压强度、静模量和温纳电阻率

Asian Journal of Civil Engineering Pub Date : 2025-04-01 DOI: 10.1007/s42107-025-01303-0

Sheetal Thapa, Nagondanahalli Raju Asha Rani, Richi Prasad Sharma

{"title":"Prediction of compressive strength, static modulus and wenner resistivity for normal concrete using different percentages of recycled concrete as a coarse aggregate","authors":"Sheetal Thapa, Nagondanahalli Raju Asha Rani, Richi Prasad Sharma","doi":"10.1007/s42107-025-01303-0","DOIUrl":"10.1007/s42107-025-01303-0","url":null,"abstract":"<div><p>The two most important mechanical properties for concrete are compressive strength and static modulus. Likewise, Wenner resistivity is a crucial durability parameter to be taken into consideration while monitoring the performance of any concrete members. This paper presents novel prediction models for normal concrete’s compressive strength, static modulus, and Wenner resistivity based on linear regression models and artificial neural networks (ANN). Due to the quicker rate of output convergence, the study used the Levenberg–Marquardt learning algorithm for the ANN model to forecast the aforementioned parameters. The prediction strength (R2) of the ANN technique is 14–20% higher than that of the normal regression model, 11–14% higher than that of the static modulus model, and 10–12.5% higher than that of the Wenner resistivity model. For both ANN and linear regression models, the input parameters considered were the rebound number and pulse velocity. The sample was evaluated by substituting normal stone aggregate (NSA) with varying amounts of recycled concrete aggregate (i.e., 0%, 25%, 50%, 75%, and 100% RCA) as a coarse aggregate. This study considered age (14, 28, and 90 days) and grade (M20, M25, and M30) into consideration while developing the models. Furthermore, by comparing the developed compressive strength model with earlier models created by other authors, the study found that the generated model performed better for RCA specimens. The findings of this investigation will support the application of RCA in the Indian construction sector and promote utilization of natural coarse aggregate more sustainably.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 5","pages":"2135 - 2152"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influence of the size of the coarse and fine aggregates on the compressive strength of concrete 粗、细骨料粒径对混凝土抗压强度的影响

Asian Journal of Civil Engineering Pub Date : 2025-03-29 DOI: 10.1007/s42107-025-01297-9

Pritam Dey, Sneha Singh, Ramagopal Uppaluri

{"title":"Influence of the size of the coarse and fine aggregates on the compressive strength of concrete","authors":"Pritam Dey, Sneha Singh, Ramagopal Uppaluri","doi":"10.1007/s42107-025-01297-9","DOIUrl":"10.1007/s42107-025-01297-9","url":null,"abstract":"<div><p>In this study, the influence of aggregate sizes on the compressive strength (CS) of concrete system has been assessed. Accordingly, the fine aggregates (FA) and coarse aggregates (CA) with fixed gradation sizes were considered and the prepared conventional concrete samples were assessed for their 7th and 28th day compressive strength. Thereby, three different types of FA were selected for FA particle size gradation. Striking variations in the CS values were noted for the concrete samples with a particular combination of FA and CA sizes, and for a fixed choice of the water-to-cement ratio. Further investigations for the CS modelling are conducted with the response surface methodology (RSM). Considering overall specific gravity (FA Sp.Gr.) as a parameter but not a factor, the experimental design considered the FA size (in µm) and CA size (in mm) as independent variables. The best-fit RSM model analysis inferred the quadratic model with good relevance (<i>p</i> < 0.001) for the prediction CS in the defined factor space and for three alternate FA types. The Pareto plots revealed that while the FA size was the influential factor for both responses for the case of the FA Sp.Gr. value of 2.59, while CA size was the highest contributor for the other two FA Sp.Gr. types. Thereby, the role of the type of FA and the aggregate sizes were assessed to be very important to achieve the high CS. The adopted methodology is generic for selecting the best-fit control sample for further research into advanced concrete composite materials.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 5","pages":"2053 - 2070"},"PeriodicalIF":0.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Boosting multi-objective aquila optimizer with opposition-based learning for large-scale time–cost trade-off problems 基于对立学习的大规模时间成本权衡问题多目标aquila优化器

Asian Journal of Civil Engineering Pub Date : 2025-03-26 DOI: 10.1007/s42107-025-01306-x

Yusuf Baltaci

{"title":"Boosting multi-objective aquila optimizer with opposition-based learning for large-scale time–cost trade-off problems","authors":"Yusuf Baltaci","doi":"10.1007/s42107-025-01306-x","DOIUrl":"10.1007/s42107-025-01306-x","url":null,"abstract":"<div><p>This study presents an enhanced version of the Aquila optimizer (AO), known as the opposition-based aquila optimizer (OBAO), which incorporates opposition-based learning (OBL) to enhance performance. By considering both current solutions and their opposites, OBL expands the search space, increasing the chances of avoiding local optima and identifying superior solutions. Additionally, OBL replaces the expanded and narrowed exploitation methods of the original AO, reducing computational complexity and enhancing the efficiency of the proposed model. The proposed OBAO is applied to a large-scale time–cost trade-off problems (TCTP) with 630 activities, demonstrating its capability to efficiently achieve optimal or near-optimal solutions. Comparative assessments against advanced optimization algorithms, including teaching learning-based optimization (TLBO), genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), and plain AO indicate that OBAO achieves better solutions in terms of number of objective function evaluations (NFE) and hypervolume (HV) indicator. The findings suggest that OBAO is a promising alternative for optimizing large-scale construction projects in construction management field.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 5","pages":"2179 - 2188"},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flexural behavior of composite beam with different shear connectors 不同剪力连接件组合梁的受弯性能

Asian Journal of Civil Engineering Pub Date : 2025-03-25 DOI: 10.1007/s42107-025-01274-2

Mohammad Osman Ghone, Md. Khasro Miah, Md. Rakibul Hasan, Noor Md. Sadiqul Hasan, Md Jihad Miah

{"title":"Flexural behavior of composite beam with different shear connectors","authors":"Mohammad Osman Ghone, Md. Khasro Miah, Md. Rakibul Hasan, Noor Md. Sadiqul Hasan, Md Jihad Miah","doi":"10.1007/s42107-025-01274-2","DOIUrl":"10.1007/s42107-025-01274-2","url":null,"abstract":"<div><p>This study aims to evaluate the flexural performance, crack resistance, and mechanical properties of composite beams. It specifically focuses on the performance characteristics of locally available inverted L-type shear connectors, headed shear connectors, and concrete made with brick aggregates and stone aggregates. This study examined how headed and inverted L-type shear connectors affect the steel–concrete composite beam’s flexural and mechanical performance. Thus, the experiment maintained the concrete mix design and reinforcement ratio while varying headed and inverted L-type connectors. The impact of shear connections improves the structural performance of composite beams compared to non-composite beams without them. The ultimate load capacity, corresponding deflection, and midspan deflection curve were examined in relation to the experimental data. The test specimens' failure behaviour was also investigated. The concrete slab’s flexural shear cracking and the steel flange's local buckling caused the composite beams to fail. The CBHS specimen improves in load-bearing (46.84%) and deflection reduction (61.30%), while CBIB demonstrates consistency, CBIS variability, and moment capacity increases are minor, demonstrating CBHS's efficiency and optimization possibilities. The test results show specimens with headed shear connectors function better than those with inverted L-type shear connectors.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 5","pages":"1919 - 1938"},"PeriodicalIF":0.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prioritizing passive envelope design features for integration into the building energy codes: a case of India 优先考虑被动式围护结构设计特征以融入建筑能源规范：以印度为例

Asian Journal of Civil Engineering Pub Date : 2025-03-25 DOI: 10.1007/s42107-025-01275-1

Kuladeep Kumar Sadevi, Avlokita Agrawal

{"title":"Prioritizing passive envelope design features for integration into the building energy codes: a case of India","authors":"Kuladeep Kumar Sadevi, Avlokita Agrawal","doi":"10.1007/s42107-025-01275-1","DOIUrl":"10.1007/s42107-025-01275-1","url":null,"abstract":"<div><p>Energy efficiency in buildings is a key area of focus in the path towards net zero energy goals and mitigating climate change. Among various passive strategies for energy efficiency in buildings, building envelope shading is considered a key strategy to control solar heat gain and reduce the cooling loads in buildings. While significant focus has been given to shading glazing components of buildings, this paper addresses a critical gap by investigating the potential of shading the opaque envelope components (OECs), which include opaque walls and roofs. OECs can reduce cooling load by managing the heat ingress into the buildings. Although OECs are not widely used in energy-efficient building strategies, the passive strategies in OECS help control heat gains and decrease cooling loads, especially in hot climates. This study investigates the shading strategies of opaque OECs in a two-stage review, initially reviewing the global building energy codes to assess the inclusion of OEC shading strategies and then identifying effective shading techniques for walls and roofs through a systematic literature review. The review of energy codes reveals that very few energy codes explicitly address OEC shading with a single instance mentioned in the energy codes of Australia and India. In contrast, all the codes explicitly specify window shading as a passive strategy. The SLR further demonstrates that the shading OECs can significantly reduce cooling demands, with strategies such as overhangs, green facades, double-skin roofs, and photovoltaic panels showing up to 77% energy savings. The shading potential provides considerable scope for integrating the shading of OECs as a passive strategy that can be incorporated into the energy for better adoption in the buildings.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 5","pages":"1865 - 1879"},"PeriodicalIF":0.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sustainable development factors in building engineering systems: do demographic factors matter? 建筑工程系统中的可持续发展因素：人口因素重要吗？

Asian Journal of Civil Engineering Pub Date : 2025-03-25 DOI: 10.1007/s42107-025-01301-2

Priji Biju, Nahia Mourad, Ahmed Mohamed Habib

{"title":"Sustainable development factors in building engineering systems: do demographic factors matter?","authors":"Priji Biju, Nahia Mourad, Ahmed Mohamed Habib","doi":"10.1007/s42107-025-01301-2","DOIUrl":"10.1007/s42107-025-01301-2","url":null,"abstract":"<div><p>Sustainable engineering builds systems, products, and processes that are socially, environmentally, and economically viable to fulfil the promise of a balanced approach to achieve the net zero emission targets of the world to mitigate climate change impacts. Owing to the multidisciplinary nature of sustainable development, sustainability efforts involve concepts, principles, and methods from engineering, social sciences, economics, social psychology, biological sciences, ecology, and physical sciences. Hence, scientific analysis is required to define inter-item relationships and identify differences based on the demographic features of professionals. The lack of such studies in the literature represents the main gap covered by this study. In this context, a methodology was designed and applied by surveying 101 professionals from various engineering disciplines in the UAE’s construction sector. The results confirmed a significant correlation among sociocultural (SOC), economic (ECO), and environmental (ENV) sustainability factors. The findings revealed that the distributions of SOC, ECO, and ENV were the same across gender, specialisation, and experience categories. Moreover, the distributions of ECO and ENV were the same across age categories, except for the distribution of SOC, which differed across age categories, favouring groups over 25 years of age. These findings would support stakeholders in the construction sector in developing sustainable engineering building systems. The proposed methodology can be used in other areas to help stakeholders establish sustainable systems based on the SOC, ECO, and ENV factors.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 5","pages":"2101 - 2116"},"PeriodicalIF":0.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting compressive strength of sustainable concrete using advanced AI models: DLNN, RF, and MARS 使用先进的人工智能模型预测可持续混凝土的抗压强度：DLNN， RF和MARS

Asian Journal of Civil Engineering Pub Date : 2025-03-24 DOI: 10.1007/s42107-025-01278-y

Monali Wagh, Charuta Waghmare, Amit Gudadhe, Nisha Thakur, Salah J. Mohammed, Sameer Algburi, Hasan Sh. Majdi, Khalid Ansari

{"title":"Predicting compressive strength of sustainable concrete using advanced AI models: DLNN, RF, and MARS","authors":"Monali Wagh, Charuta Waghmare, Amit Gudadhe, Nisha Thakur, Salah J. Mohammed, Sameer Algburi, Hasan Sh. Majdi, Khalid Ansari","doi":"10.1007/s42107-025-01278-y","DOIUrl":"10.1007/s42107-025-01278-y","url":null,"abstract":"<div><p>Recycled aggregate is becoming a sustainable construction resource that minimizes the carbon footprint in concrete structures. To predict the behavior of environmentally friendly (EnF) concrete in sustainable construction, it is necessary to predict the compressive strength using recycled materials accurately. The current research highlights the performance of the Deep Learning Neural Network (DLNN), Random Forests (RFs), and Multivariate Adaptive Regression Splines (MARS) are evaluated and extensive analysis of data segmentation was performed by splitting the dataset used in this study into 75–25% as well as 80–20% training/testing scenarios using Extreme Gradient Boosting (XG Boost), a quantitative measurement of the effect of data segmentation on model efficiency. The combination of AI models with Extreme Gradient Boosting (XG Boost) was employed to ascertain the governing variables on the CS prediction. Numerous statistical models developed were used to compare the effectiveness of these given models showing the best performance of the DLNN model based on the least RMSE (2.93). The results found that more variables should be added to the prediction problem for better prediction accuracy and the data split of 80–20% was the best choice. Based on the high accuracy of models, the results demonstrated that over the other established models, the DLNN model surpasses them in the analysis of concrete behavior and is useful for future applications.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 5","pages":"1939 - 1954"},"PeriodicalIF":0.0,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0