Computer-Aided Civil and Infrastructure Engineering最新文献

UAV-based pavement distress segmentation via controllable synthetic data augmentation and a lightweight selective fusion network under limited annotations 基于可控合成数据增强和有限标注的轻型选择性融合网络的无人机路面破损分割

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2026-10-01 DOI: 10.1016/j.cacaie.2026.100204

Jinfeng Yan,Cheng Fang,Yifan Wang,Yuhui Zhang,Fujiao Tang,Dawei Wang,Zepeng Fan

引用次数: 0

Polynomial-to-linear reduction of computational complexity via tensor-train dynamic mode decomposition for predicting chloride diffusion in concrete 通过张量-列动态模态分解预测混凝土中氯离子扩散的计算复杂度的多项式-线性降低

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2026-10-01 DOI: 10.1016/j.cacaie.2026.100195

Yue Li,Miroslav Vořechovský

引用次数: 0

Heterogeneous acceleration-vision fusion within finite element model updating for damage identification in frame structures 基于有限元模型更新的非均匀加速视觉融合框架结构损伤识别

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2026-10-01 DOI: 10.1016/j.cacaie.2026.100194

Shengfei Zhang,Xiaogang Liu,Pinghe Ni,Qiang Han,Qingrui Yue

引用次数: 0

Probabilistic Gaussian Grouping: Uncertainty-Aware 3D Scene Understanding for Robotics in Construction 概率高斯分组：建筑机器人的不确定性感知三维场景理解

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2026-10-01 DOI: 10.1016/j.cacaie.2026.100198

Gan Zhang,Qi Liu,Peter E.D. Love,Wei Zhou,Weili Fang

引用次数: 0

RockViT: image-based rockfill compaction-state recognition for compaction control and decision support RockViT：用于压实控制和决策支持的基于图像的堆石料压实状态识别

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2026-10-01 DOI: 10.1016/j.cacaie.2026.100197

Chen-Geng Liu,Hui-Li Huang,Chao-Min Shen,Si-Hong Liu,J. David Frost

引用次数: 0

Surrogate-assisted multi-objective seismic design optimisation of diagrid tall buildings 网格高层建筑多目标抗震设计优化

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2026-10-01 DOI: 10.1016/j.cacaie.2026.100181

Pooyan Kazemi,Michela Turrin,Charalampos Andriotis,Alireza Entezami,Stefano Mariani,Aldo Ghisi

引用次数: 0

Physics-Informed Graph Neural Networks for Minimal Mass Design of Cable-Strut Structures 索杆结构最小质量设计的物理信息图神经网络

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2026-09-02 DOI: 10.1016/j.cacaie.2026.100210

Yan Zhou, Yafeng Wang, Yaozhi Luo

{"title":"Physics-Informed Graph Neural Networks for Minimal Mass Design of Cable-Strut Structures","authors":"Yan Zhou, Yafeng Wang, Yaozhi Luo","doi":"10.1016/j.cacaie.2026.100210","DOIUrl":"https://doi.org/10.1016/j.cacaie.2026.100210","url":null,"abstract":"This paper presents a topology-adaptive physics-informed graph-to-design neural network (PI-GNN) framework for rapid nonlinear minimal-mass design of cable-strut structures. Although direct nonlinear optimization can yield rigorous solutions for individual feasible designs, repeated case-by-case optimization becomes computationally expensive in topology-level exploration, where numerous candidate structures must be evaluated and infeasible layouts or poor initial guesses often lead to failed or slow convergence. To address this challenge, the proposed framework reformulates repeated nonlinear optimization as a reusable graph-to-design learning problem that directly maps candidate structural graphs to preliminary prestress and member-level sectional designs. Variable-size graph modeling enables a unified network to accommodate different structural configurations. A feasibility screening network first evaluates candidate structures, after which the design network predicts prestress levels and member-level cross-sectional variables. An auxiliary displacement network estimates structural responses under multiple load cases, enabling a differentiable mechanics evaluator to quantify engineering-constraint violations. These violations are incorporated into augmented-Lagrangian physics losses and backpropagated to guide the design network toward lightweight and mechanically admissible solutions. Numerical studies on a planar photovoltaic cable truss and a spatial Levy cable dome demonstrate the accuracy, physical consistency, and computational efficiency of the proposed method for topology-level design exploration.","PeriodicalId":156,"journal":{"name":"Computer-Aided Civil and Infrastructure Engineering","volume":"24 1","pages":""},"PeriodicalIF":11.775,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148884451","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 motion-region-based center frequency optimization method for Gabor wavelets in phase-based displacement measurement 基于运动区域的Gabor小波相位位移测量中心频率优化方法

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2026-09-02 DOI: 10.1016/j.cacaie.2026.100205

Sida Ai, Zhenkun Li

{"title":"A motion-region-based center frequency optimization method for Gabor wavelets in phase-based displacement measurement","authors":"Sida Ai, Zhenkun Li","doi":"10.1016/j.cacaie.2026.100205","DOIUrl":"https://doi.org/10.1016/j.cacaie.2026.100205","url":null,"abstract":"Phase-based displacement measurement has attracted increasing attention in structural vibration monitoring because of its robustness to illumination variations and high subpixel accuracy. The Gabor wavelet is one of the earliest and most widely used phase extraction methods for phase-based displacement measurement. When Gabor wavelets are used for phase extraction, measurement performance is highly sensitive to the center frequency, while its selection in most previous studies relies on comparison with ground truth. To overcome this limitation, this study proposes a motion-region-based center frequency optimization method for Gabor wavelets in phase-based displacement measurement. Numerical experiments on numerical videos with different target motion characteristics show that the optimal center frequency varies systematically with these characteristics. In particular, the results reveal a clear relationship between the optimal center frequency and the target motion region, with larger motion regions generally requiring lower center frequencies for accurate displacement measurement. Based on this finding and the physical interpretation of the Gabor wavelet, a physics-inspired relationship between the optimal center frequency and the motion region is established, and an iterative center frequency optimization method is developed accordingly. The proposed optimization method is validated through a laboratory shaker test and an outdoor seismic response measurement of a cold-formed steel wall structure.","PeriodicalId":156,"journal":{"name":"Computer-Aided Civil and Infrastructure Engineering","volume":"35 1","pages":""},"PeriodicalIF":11.775,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148884454","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 Hybrid-Driven Method Based on Dynamic and Static Responses for Dynamic Girder Strain Reconstruction of Long-Span Suspension Bridges 基于动静响应的大跨度悬索桥动梁应变重建混合驱动方法

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2026-09-01 DOI: 10.1016/j.cacaie.2026.100213

Zaiyang Jiang, Qianen Xu, Qingfei Gao, Yang Liu

{"title":"A Hybrid-Driven Method Based on Dynamic and Static Responses for Dynamic Girder Strain Reconstruction of Long-Span Suspension Bridges","authors":"Zaiyang Jiang, Qianen Xu, Qingfei Gao, Yang Liu","doi":"10.1016/j.cacaie.2026.100213","DOIUrl":"https://doi.org/10.1016/j.cacaie.2026.100213","url":null,"abstract":"In structural health monitoring (SHM) of long-span bridges, distributed optical fiber sensing technology can provide strain information with high spatial resolution. However, due to the inherently low sampling frequency of the system, it is difficult to capture the high-frequency dynamic strain responses of bridges under complex operational environments. To address this hardware bottleneck, a hybrid-driven method based on dynamic and static responses for dynamic girder strain reconstruction of long-span suspension bridges is proposed. First, a joint state estimation framework based on variational mode decomposition (VMD) and a Kalman filter is established. This framework utilizes high-frequency acceleration as a dynamic prior while treating low-frequency deflection measurements as absolute constraints, effectively resolving the persistent issue of low-frequency drift caused by uncertain initial conditions in double integration. Second, a multi-task BP neural network is introduced to decode the complex, non-linear spatiotemporal mapping between global girder deflection and localized strain fields, thereby mapping the reconstructed dynamic deflection field to high-frequency dynamic strains at multiple cross-sections of the entire bridge.. The proposed method is validated using numerical simulation and actual monitoring data of a long-span suspension bridge. Results demonstrate that compared to conventional identification methods relying solely on acceleration integration, the proposed approach reduces the maximum root-mean-square error (RMSE) and mean absolute error (MAE) of the reconstructed dynamic strains by up to 50% and 51%, respectively. Furthermore, under Gaussian white noise interference as high as 15%, the method still maintains highly consistent strain reconstruction trends, demonstrating excellent noise robustness.","PeriodicalId":156,"journal":{"name":"Computer-Aided Civil and Infrastructure Engineering","volume":"6 1","pages":""},"PeriodicalIF":11.775,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148884903","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

AdvSerial: Physical adversarial attacks on infrastructure-mounted pedestrian detectors via semantic feature suppression AdvSerial：通过语义特征抑制对安装在基础设施上的行人检测器进行物理对抗性攻击

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2026-09-01 DOI: 10.1016/j.cacaie.2026.100215

Yuanhao Huang,Yilong Ren,Jinlei Wang,Xuesong Bai,Jinchuan Zhang,Haiyang Yu

引用次数: 0