Computer-Aided Civil and Infrastructure Engineering最新文献

Cover Image, Volume 40, Issue 1

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-22 DOI: 10.1111/mice.13404

引用次数: 0

Research on autonomous path planning and tracking control methods for unmanned electric shovels

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-21 DOI: 10.1111/mice.13402

Xiaodan Tan, Guoqiang Wang, Guohua Wu, Zongwei Yao, Yongpeng Wang, Qingxue Huang

引用次数: 0

Uncertainty-informed regional deformation diagnosis of arch dams

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-20 DOI: 10.1111/mice.13395

Xudong Chen, Wenhao Sun, Shaowei Hu, Liuyang Li, Chongshi Gu, Jinjun Guo, Bowen Wei, Bo Xu

引用次数: 0

Two-step rapid inspection of underwater concrete bridge structures combining sonar, camera, and deep learning

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-16 DOI: 10.1111/mice.13401

Weihao Sun, Shitong Hou, Gang Wu, Yujie Zhang, Luchang Zhao

引用次数: 0

A semi-supervised approach for building wall layout segmentation based on transformers and limited data

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-14 DOI: 10.1111/mice.13397

Hao Xie, Xiao Ma, Qipei Mei, Ying Hei Chui

引用次数: 0

Training of construction robots using imitation learning and environmental rewards

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-13 DOI: 10.1111/mice.13394

Kangkang Duan, Zhengbo Zou, T. Y. Yang

引用次数: 0

Genetic algorithm optimized frequency‐domain convolutional blind source separation for multiple leakage locations in water supply pipeline

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-13 DOI: 10.1111/mice.13392

Hongjin Liu, Hongyuan Fang, Xiang Yu, Yangyang Xia

{"title":"Genetic algorithm optimized frequency‐domain convolutional blind source separation for multiple leakage locations in water supply pipeline","authors":"Hongjin Liu, Hongyuan Fang, Xiang Yu, Yangyang Xia","doi":"10.1111/mice.13392","DOIUrl":"https://doi.org/10.1111/mice.13392","url":null,"abstract":"In the realm of using acoustic methods for locating leakages in water supply pipelines, existing research predominantly focuses on single leak localization, with limited exploration into the challenges posed by multiple leak scenarios. To address this gap, a genetic algorithm‐optimized frequency‐domain convolutional blind source separation algorithm is proposed for the precise localization of multiple leaks. This algorithm effectively separates mixed leak sources and accurately estimates the delays of source propagation. Signal simulations confirm the algorithm's effectiveness, revealing that the distribution of leak positions, signal‐to‐noise ratio, and frequency characteristics of the leakage source all influence the algorithm's performance. Comparative analysis demonstrates the algorithm's capability to eliminate signal interactions, facilitating the localization of multiple leaks. The algorithm's efficacy is further validated through extensive full‐scale experiments, underscoring its potential as a novel and practical solution to the complex challenge of multiple leakage localization in water supply pipelines.","PeriodicalId":156,"journal":{"name":"Computer-Aided Civil and Infrastructure Engineering","volume":"119 1","pages":""},"PeriodicalIF":11.775,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142815749","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

Integrating spatial and channel attention mechanisms with domain knowledge in convolutional neural networks for friction coefficient prediction

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-10 DOI: 10.1111/mice.13391

Zihang Weng, Chenglong Liu, Yuchuan Du, Difei Wu, Zhen Leng

{"title":"Integrating spatial and channel attention mechanisms with domain knowledge in convolutional neural networks for friction coefficient prediction","authors":"Zihang Weng, Chenglong Liu, Yuchuan Du, Difei Wu, Zhen Leng","doi":"10.1111/mice.13391","DOIUrl":"https://doi.org/10.1111/mice.13391","url":null,"abstract":"The pavement skid resistance is crucial for ensuring driving safety. However, the reproducibility and comparability of field measurements are constrained by various influencing factors. One solution to these constraints is utilizing laser‐based 3D pavement data, which are notably stable and can be employed to estimate pavement skid resistance indirectly. However, the integration of tire–road friction mechanisms and deep neural networks has not been fully studied. This study employed spatial‐channel attention mechanisms to integrate frictional domain knowledge and convolutional neural networks (CNNs) that predict the friction coefficient as the output. The models’ inputs include 3D texture data, corresponding finite element (FE) simulation outcomes, and 2D wavelet decomposition outcomes. An additional spatial attention (ASA) mechanism guided the CNNs to focus on the tire–road contact region, using tire–road contact stress from FE simulation as domain knowledge. Multi‐scale channel attention (MSCA) mechanisms enabled the CNNs to learn the channel weights of 2D‐wavelet‐based multi‐scale inputs, thereby assessing the contribution of different texture scales to tire–road friction. A multi‐attention and feature fusion mechanism was designed, and the performances of various combinations were compared. The results showed that the fusion of ASA and MSCA achieved the best performance, with a regression R2 of 0.8470, which was a 20.25% improvement over the baseline model.","PeriodicalId":156,"journal":{"name":"Computer-Aided Civil and Infrastructure Engineering","volume":"36 1","pages":""},"PeriodicalIF":11.775,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142797166","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 K‐Net‐based deep learning framework for automatic rock quality designation estimation

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-10 DOI: 10.1111/mice.13386

Sihao Yu, Louis Ngai Yuen Wong

引用次数: 0

Event-based supervisor control for a cyber-physical waterway lock system

IF 11.775 1区工程技术

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-08 DOI: 10.1111/mice.13393

D. G. Fragkoulis, F. N. Koumboulis, M. P. Tzamtzi, P. G. Totomis

{"title":"Event-based supervisor control for a cyber-physical waterway lock system","authors":"D. G. Fragkoulis, F. N. Koumboulis, M. P. Tzamtzi, P. G. Totomis","doi":"10.1111/mice.13393","DOIUrl":"https://doi.org/10.1111/mice.13393","url":null,"abstract":"An event-based supervisory control scheme, in the Ramdage–Wonham framework, will be proposed for the cyber-physical Waterway Lock system, known as Lock III, in Tilburg, the Netherlands. The proposed control scheme imposes desired behavior, by appropriately disabling controllable events, so as to avoid activation of actuator commands that may lead to undesired and potentially hazardous operating states. The discrete event model of the total Waterway Lock system, comprising 54 actuator and sensor automata, will be presented in analytic 6-tuple forms of its subsystems. The system's desired behavior, which is expressed using six rules, will be formulated as 84 regular and prefix closed languages that will be realized as appropriate supervisor automata. All supervisors are developed by a general two-state supervisor form, which facilitates their implementation. A distributed control architecture will be proposed, which organizes all supervisors in distinct groups, each of which controls one and only one distinct command event. The complexity of the proposed control scheme will be computed to be equal to (168,324,564), being reasonable, as compared to the large number of subsystems and the restrictive design requirements. The physical realizability of the 84 supervisors, with respect to the 54 subsystems of the waterway lock system, will be proved analytically. Also, it will be proved analytically that the proposed supervisor architecture guarantees the nonblocking property of the controlled automaton, including all subsystems. The establishment of these analytic proofs supports the extendibility of the results to other applications. To demonstrate the resulting large-scale controlled automaton's good performance, its marked behavior and simulation results will be presented.","PeriodicalId":156,"journal":{"name":"Computer-Aided Civil and Infrastructure Engineering","volume":"14 1","pages":""},"PeriodicalIF":11.775,"publicationDate":"2024-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142793159","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