Engineering Structures最新文献_第3页

Mitigating damages to infill walls under combined in-plane and out-of-plane loadings using a spider web-inspired strengthening strategy: Numerical analyses 利用受蜘蛛网启发的加固策略减轻填充墙在平面内和平面外联合荷载作用下的损坏：数值分析

IF 5.6 1区工程技术

Engineering Structures Pub Date : 2024-11-12 DOI: 10.1016/j.engstruct.2024.119297

Mohammad Asad , Julian Thamboo , Tatheer Zahra , David P. Thambiratnam

{"title":"Mitigating damages to infill walls under combined in-plane and out-of-plane loadings using a spider web-inspired strengthening strategy: Numerical analyses","authors":"Mohammad Asad , Julian Thamboo , Tatheer Zahra , David P. Thambiratnam","doi":"10.1016/j.engstruct.2024.119297","DOIUrl":"10.1016/j.engstruct.2024.119297","url":null,"abstract":"<div><div>Unreinforced masonry walls (IMW) are commonly used as infills to envelop and partition reinforced concrete (RC) frame buildings. These IMWs are non-loadbearing, however they contribute to the in-plane (IP) load resisting mechanism of the RC frames and are prone to out-of-plane (OOP) failure during lateral actions, such as earthquakes, impacts, tsunamis, and high winds. The OOP failure of IMWs is influenced by prior IP damage, and therefore the characteristics of bi-directional interaction (IP and OOP) should be accounted to assess the appropriate OOP capacity of IMWs in RC frames. However, limited studies have been reported on the bi-directional failure characteristics of IMWs, especially mitigation of this failure and increasing the OOP capacity of the walls without increasing the stiffness in the IP direction. In this research study, finite element (FE) based numerical models of IMWs under bi-directional loadings has been developed and validated using existing experimental data. Numerical and experimental results show good agreement of failure modes and both IP and OOP load-displacement characteristics. To mitigate their failure, a nature inspired spider-web grid (as a surface rending strengthening system) was applied to the IMWs and their IP and OOP responses were evaluated numerically. Using spider-web-inspired reinforcement on the rear face of the IMWs yielded a 31 % increase in their out-of-plane capacity with an increase in out-of-plane displacement by 2.7 times compared to the unreinforced IMW configuration. Findings of this paper will help to improve the designs of IMWs vulnerable to combined IP and OOP loadings.</div></div>","PeriodicalId":11763,"journal":{"name":"Engineering Structures","volume":"323 ","pages":"Article 119297"},"PeriodicalIF":5.6,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of incorporating parallel-threaded mechanical coupler splices on the seismic behaviour of reinforced concrete columns 采用平行螺纹机械耦合器拼接对钢筋混凝土柱抗震性能的影响

IF 5.6 1区工程技术

Engineering Structures Pub Date : 2024-11-12 DOI: 10.1016/j.engstruct.2024.119289

Nasser Mohamed , Michel Laurent , Ferrier Emmanuel , Gabor Aron , Gardes Rémi , Boisson Richard , Huet Philippe , Clément Poissonnet , Dolo jean-marie

{"title":"Impact of incorporating parallel-threaded mechanical coupler splices on the seismic behaviour of reinforced concrete columns","authors":"Nasser Mohamed , Michel Laurent , Ferrier Emmanuel , Gabor Aron , Gardes Rémi , Boisson Richard , Huet Philippe , Clément Poissonnet , Dolo jean-marie","doi":"10.1016/j.engstruct.2024.119289","DOIUrl":"10.1016/j.engstruct.2024.119289","url":null,"abstract":"<div><div>This study compared the performance of reinforced concrete (RC) columns using mechanical couplers with that of traditional overlapping splices under axial and cyclic loading conditions. Splicing methods incorporating larger diameters are critical for ensuring the structural integrity of large structures, for which safety is of paramount importance. Overlapping splices often result in congestion and poor construction quality owing to the complex RC detailing in the joints. Mechanical couplers enable efficient installation and provide economic benefits. In this study, RC columns with different splicing configurations were tested using quasistatic cyclic lateral loading. The coupler properties, geometry, and position were analysed. The results demonstrate that mechanical couplers can maintain or slightly enhance the ductility, energy dissipation, and self-centring capacity while effectively maintaining the stiffness and strength. These findings suggest that mechanical couplers are superior alternatives to traditional rebar splicing methods for improving the overall performance and reliability of RC structures in large-scale construction projects.</div></div>","PeriodicalId":11763,"journal":{"name":"Engineering Structures","volume":"323 ","pages":"Article 119289"},"PeriodicalIF":5.6,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Experimental characterization of prefabricated link slabs with randomly oriented and oriented-fibres UHPC under multiple geometric configurations 在多种几何构型下使用随机取向和取向纤维超高性能混凝土预制连接板的实验表征

IF 5.6 1区工程技术

Engineering Structures Pub Date : 2024-11-11 DOI: 10.1016/j.engstruct.2024.119253

Junqing Xue , Shengrong Mao , Wei Xu , Angelo Aloisio , Yang Zhengxian , Alessandro Contento , Bruno Briseghella

{"title":"Experimental characterization of prefabricated link slabs with randomly oriented and oriented-fibres UHPC under multiple geometric configurations","authors":"Junqing Xue , Shengrong Mao , Wei Xu , Angelo Aloisio , Yang Zhengxian , Alessandro Contento , Bruno Briseghella","doi":"10.1016/j.engstruct.2024.119253","DOIUrl":"10.1016/j.engstruct.2024.119253","url":null,"abstract":"<div><div>The link slabs are structural elements connecting two bridge decks, ensuring structural continuity without altering the simple support scheme of the deck. These elements provide the durability benefits of integral bridges by eliminating expansion joints between beams, which are prone to water infiltration and exposure to degrading agents. The development of link slabs is closely connected to the progress in composite materials. Ultra-High Performance Concrete (UHPC) is a cementitious material capable of ensuring the mechanical performance of link slabs under operational loads, thanks to high resistance and durability. This work presents an extensive experimental characterization of prefabricated link slabs, considering an experimental setup representative of operational conditions. The authors examined nine experimental configurations, varying both the geometry and the material. For geometry, they varied the bolts’ edge distance and the thickness of the unbonded layer. For material, they studied link slabs made of Reinforced Concrete (RC), UHPC with randomly oriented fibres, and UHPC with oriented fibres. The effect of the volumetric fraction of fibres was assessed in the slabs with oriented fibres. The results provide practical recommendations for selecting the combination of geometric properties and materials to maximize the mechanical performance of prefabricated UHPC link slabs.</div></div>","PeriodicalId":11763,"journal":{"name":"Engineering Structures","volume":"323 ","pages":"Article 119253"},"PeriodicalIF":5.6,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Parallel wires steel-reinforced polymer and mortar for structural strengthening: Introducing and bond properties 用于结构加固的平行钢丝钢筋聚合物和砂浆：介绍和粘结性能

IF 5.6 1区工程技术

Engineering Structures Pub Date : 2024-11-11 DOI: 10.1016/j.engstruct.2024.119249

Ali Raji, Reza Zamani Ghaleh, Davood Mostofinejad

{"title":"Parallel wires steel-reinforced polymer and mortar for structural strengthening: Introducing and bond properties","authors":"Ali Raji, Reza Zamani Ghaleh, Davood Mostofinejad","doi":"10.1016/j.engstruct.2024.119249","DOIUrl":"10.1016/j.engstruct.2024.119249","url":null,"abstract":"<div><div>This study aims to introduce a cost-effective composite for strengthening/retrofitting concrete elements in bond-critical applications. It comprises a polymeric or cementitious matrix reinforced with parallel high-tensile strength steel wires. 14 concrete prisms were first strengthened with such composites as carbon fiber-reinforced polymer sheets (CFRP), parallel wires steel-reinforced polymer (PW-SRP), and parallel wires steel-reinforced mortar (PW-SRM), and then tested under a direct single lap-shear setup. The study also assesses the efficacy of two surface preparation methods, externally-bonded reinforcement (EBR) and externally-bonded reinforcement on grooves (EBROG), on the bond features of the composites above. In the EBR group, the bond capacity of PW-SRP is 46 % and 85 % higher than that of CFRP and PW-SRM, respectively, while EBROG-CFRP held the first rank in the EBROG group, recording a capacity of 8 % and 54 % higher than the PW-SRP and the PW-SRM. Such results demonstrate the importance and priority of PW-SRP and PW-SRM composites from both resistive and economical considerations. Despite the PW-SRM's low capacity, its cheaper matrix justifies its use. Although the CFRP- and PW-SRM-strengthened samples debonded, the PW-SRP hit the peak failure strain and reached the wire rupture in both surface preparation methods. Moreover, the EBROG kept its superiority over the EBR in the bond capacities of PW-SRP and PW-SRM samples, reaching a capacity of up to 69 % higher than the EBR ones.</div></div>","PeriodicalId":11763,"journal":{"name":"Engineering Structures","volume":"323 ","pages":"Article 119249"},"PeriodicalIF":5.6,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy absorption characteristics and auxetic effect of novel elliptic-arc re-entrant honeycomb structures 新型椭圆弧形重入角蜂窝结构的能量吸收特性和辅助效应

IF 5.6 1区工程技术

Engineering Structures Pub Date : 2024-11-11 DOI: 10.1016/j.engstruct.2024.119260

Tang Yuxin , Zhong Yifeng , Zhu Yilin , Liu Rong

{"title":"Energy absorption characteristics and auxetic effect of novel elliptic-arc re-entrant honeycomb structures","authors":"Tang Yuxin , Zhong Yifeng , Zhu Yilin , Liu Rong","doi":"10.1016/j.engstruct.2024.119260","DOIUrl":"10.1016/j.engstruct.2024.119260","url":null,"abstract":"<div><div>The novel elliptical-arc re-entrant honeycomb (ERH) is designed by substituting the straight inclined struts within the re-entrant honeycomb with elliptical-arc struts. To assess its performance effectively, the study established the 3D equivalent Cauchy model (3D-ECM) and 2D equivalent Kirchhoff–Love model (2D-EKM) using the variational asymptotic method. The equivalent properties derived from the unit-cell constitutive model were integrated into the equivalent models for macroscopic analysis. Through 3D printing experiments and numerical simulations, the model’s accuracy in predicting the compression behaviors and auxetic effects of various uni- and multi-cellular ERHs under uniaxial compression, as well as the three-point bending behaviors of ERH panels were confirmed. In addition, this model substantially simplifies the modeling process, leading to a 8-fold increase in computational efficiency. Parametric analyses demonstrated that the ERH structure can uphold a beneficial auxetic effect while achieving lightweight and high strength characteristics when the axial ratio of the ellipse equals 1.25. Furthermore, ERH structures outperform arc-shaped re-entrant and regular re-entrant honeycombs in energy absorption and specific energy absorption capacity. These findings offer valuable insights for the preliminary design and optimization of ERH structures.</div></div>","PeriodicalId":11763,"journal":{"name":"Engineering Structures","volume":"323 ","pages":"Article 119260"},"PeriodicalIF":5.6,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A real-time structural seismic response prediction framework based on transfer learning and unsupervised learning 基于迁移学习和无监督学习的结构地震响应实时预测框架

IF 5.6 1区工程技术

Engineering Structures Pub Date : 2024-11-10 DOI: 10.1016/j.engstruct.2024.119227

Hongrak Pak, Stephanie German Paal

{"title":"A real-time structural seismic response prediction framework based on transfer learning and unsupervised learning","authors":"Hongrak Pak, Stephanie German Paal","doi":"10.1016/j.engstruct.2024.119227","DOIUrl":"10.1016/j.engstruct.2024.119227","url":null,"abstract":"<div><div>Conventional data-driven methods for predicting the seismic response of structures often require extensive data and computational resources. To address these challenges, a novel deep learning framework that can efficiently and accurately predict the structural seismic responses is proposed. The proposed framework overcomes the limitations of the conventional data-driven methods, by utilizing transfer learning based on the most relevant knowledge determined via the unsupervised learning technique. The framework leverages the seismic information history database to identify the most similar previous earthquake, and subsequently transfers the corresponding knowledge from the Structural Seismic Response network (SSR net) to predict structural responses caused by a new earthquake. This innovative method significantly reduces the need for extensive data collection and provides efficient predictions. Case studies demonstrate the framework’s ability to predict seismic structural responses without extensive training or data collection. The framework can reliably capture the complex nonlinear dynamics of structures under seismic loads and offer significant potential for advancing seismic fragility analyses and reliability assessments. Future research will focus on expanding the framework’s applicability to various structural types and further refining its prediction capabilities.</div></div>","PeriodicalId":11763,"journal":{"name":"Engineering Structures","volume":"323 ","pages":"Article 119227"},"PeriodicalIF":5.6,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A deep kernel regression-based forecasting framework for temperature-induced strain in large-span bridges 基于深度核回归的大跨度桥梁温度诱发应变预测框架

IF 5.6 1区工程技术

Engineering Structures Pub Date : 2024-11-09 DOI: 10.1016/j.engstruct.2024.119259

Boqiang Xu , Chao Liu

{"title":"A deep kernel regression-based forecasting framework for temperature-induced strain in large-span bridges","authors":"Boqiang Xu , Chao Liu","doi":"10.1016/j.engstruct.2024.119259","DOIUrl":"10.1016/j.engstruct.2024.119259","url":null,"abstract":"<div><div>The strain data from health monitoring systems of large-span bridges is influenced by various load effects, with the extraction and forecasting of temperature-induced strain being particularly significant for precise analysis and early warning of monitoring data. This paper presents a forecasting framework for temperature-induced strain in large-span bridges, employing a deep kernel regression (DKR) approach that integrates deep learning with Bayesian regression to enhance accuracy and certainty. Initially, this paper addresses the influence of additional response increment induced by vehicle strain effects and employs a robust data smoothing algorithm to extract temperature-induced effect components from measured strain data offline. Subsequently, a DKR model is proposed, integrating a long short-term memory (LSTM) layer with a fully connected layer. The output of the deep learning module serves as the kernel function parameter for the Gaussian process regression (GPR) module, and the GPR module with updated hyperparameters is used for time series forecasting. This method effectively extracts and utilizes time series features from historical data alongside key environmental factors, enabling real-time forecasting of strain effects and significantly improving the performance and utility of health monitoring systems in large-span bridges. Compared to commonly used time series forecasting algorithms, the algorithm proposed in this paper exhibits significantly improved accuracy, stability, and certainty. Through comparing the inference time, it was verified that the algorithm can meet the performance requirements of real-time inference, which underscores the model's potential as a robust tool in bridge structural health monitoring.</div></div>","PeriodicalId":11763,"journal":{"name":"Engineering Structures","volume":"323 ","pages":"Article 119259"},"PeriodicalIF":5.6,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of model architecture and input parameters to improve performance of artificial intelligence models for estimating concrete strength using SonReb 模型结构和输入参数对提高利用 SonReb 估算混凝土强度的人工智能模型性能的影响

IF 5.6 1区工程技术

Engineering Structures Pub Date : 2024-11-09 DOI: 10.1016/j.engstruct.2024.119285

Seyed Alireza Alavi, Martin Noel

{"title":"Effect of model architecture and input parameters to improve performance of artificial intelligence models for estimating concrete strength using SonReb","authors":"Seyed Alireza Alavi, Martin Noel","doi":"10.1016/j.engstruct.2024.119285","DOIUrl":"10.1016/j.engstruct.2024.119285","url":null,"abstract":"<div><div>The use of Artificial Intelligence (AI) with the non-intrusive SonReb method, which combines Ultrasonic Pulse Velocity (UPV) and Rebound Number (RN) to predict concrete compressive strength, has attracted increasing attention in recent years. This study introduces a novel approach to improve AI models for predicting concrete strength, making them more suitable for future practical applications. One of the key challenge in AI models is the number of input parameters; while more inputs often improve accuracy, they are typically impractical for most applications dealing with existing structures (e.g., requiring detailed concrete mix design information that is often unavailable). SonReb AI-based models which use only two input parameters (UPV and RN) have shown reasonable accuracy, but their general use is limited by adoption of different testing standards which precludes the development of large databases. This study aims to improve two-parameter SonReb-based AI models through the addition of a binary input variable that represents the type of the specimen geometry (cube or cylinder) and investigates the effect of model architecture by comparing three different AI algorithms: Artificial Neural Networks (ANN), Deep Neural Networks (DNN), and Adaptive Neuro-Fuzzy Inference Systems (ANFIS). Six AI models were developed using 514 data points from experimental tests and collected data, and an unbiased data splitting method was applied for training and testing. The results showed that including specimen geometry improved model accuracy across all AI algorithms. The results of this study show that regardless of AI architecture, the proposed novel approach not only improves the accuracy of models, but also enables the use of larger databases containing both cubic and cylindrical specimens.</div></div>","PeriodicalId":11763,"journal":{"name":"Engineering Structures","volume":"323 ","pages":"Article 119285"},"PeriodicalIF":5.6,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mechanical properties of short rebar connectors in ultra-thin lightweight composite decks 超薄轻质复合材料甲板中短钢筋连接件的机械特性

IF 5.6 1区工程技术

Engineering Structures Pub Date : 2024-11-09 DOI: 10.1016/j.engstruct.2024.119272

Shuwen Deng , Yingzhuo Liu , Xudong Shao , Hanwen Zhang , Lian Shen , Junhui Cao

引用次数: 0

A novel approach to model differential settlements and crack patterns in masonry structures 建立砌体结构差异沉降和裂缝模式模型的新方法

IF 5.6 1区工程技术

Engineering Structures Pub Date : 2024-11-09 DOI: 10.1016/j.engstruct.2024.119220

Antonino Iannuzzo , Vincenzo Mallardo

引用次数: 0