Automation in Construction最新文献_第4页

Automated BIM generation for MEP systems from CAD data using multi-drawing graph integration 使用多图图形集成从CAD数据自动生成MEP系统的BIM

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-19 DOI: 10.1016/j.autcon.2025.106542

Qian Zhao , Hao Shi , Liangchen Zhou , Guonian Lv

{"title":"Automated BIM generation for MEP systems from CAD data using multi-drawing graph integration","authors":"Qian Zhao , Hao Shi , Liangchen Zhou , Guonian Lv","doi":"10.1016/j.autcon.2025.106542","DOIUrl":"10.1016/j.autcon.2025.106542","url":null,"abstract":"<div><div>Building information modeling (BIM) of mechanical, electrical, and plumbing (MEP) systems is essential for building facility management. Computer-aided-design (CAD) data are detailed sources for MEP BIM modeling. However, existing methods for MEP BIM are complex, leading to heavy reliance on manual intervention. This paper addresses this challenge by proposing an approach for generating MEP BIM models from CAD data. Graph structures are introduced to represent MEP systems, and multiple graph structures converted from CAD drawings are utilized to match pipeline components and aggregate dispersed information across various drawings. Based on the integrated pipeline graph, missing information is inferred and completed considering the relationships between components, ensuring detailed and accurate modeling results. Experiments on an actual factory case demonstrate the reliability and efficiency of this approach. This paper contributes to the MEP BIM theory by providing a perspective on interpreting MEP CAD data and a robust technical route of CAD-to-BIM conversion for MEP systems.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"180 ","pages":"Article 106542"},"PeriodicalIF":11.5,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145093962","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

Advancing graph-supported machine learning in generative design for architectural engineering 推进建筑工程生成设计中图形支持的机器学习

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-19 DOI: 10.1016/j.autcon.2025.106530

Hanmo Wang , Zhuyin Lu , Shawn Owyong , Huan Ting Chen , Cai Wu , Tam H. Nguyen , Alexander Lin

{"title":"Advancing graph-supported machine learning in generative design for architectural engineering","authors":"Hanmo Wang , Zhuyin Lu , Shawn Owyong , Huan Ting Chen , Cai Wu , Tam H. Nguyen , Alexander Lin","doi":"10.1016/j.autcon.2025.106530","DOIUrl":"10.1016/j.autcon.2025.106530","url":null,"abstract":"<div><div>Graph-Supported Machine Learning (GML), including Graph Neural Networks (GNNs) and Probabilistic Graphical Models (PGMs), shows promise for tackling Generative Design (GD) challenges in architectural engineering. However, a systematic review of its use, limitations, and future potential is still lacking. This paper addresses that gap by analyzing 70 peer-reviewed papers, mapping their applications, data sources, and model types. A two-tier analysis identifies key limitations, including small datasets, narrow generalization, and limited integration of physical laws or expert feedback. To overcome these challenges, five strategic directions are proposed: co-evolving data and algorithms, hybrid modeling with Bayesian Networks and GNNs, graph sparsification, human-in-the-loop design refinement, and physics-informed learning. These directions guide the development of more versatile and practical GML models, able to adapt across scales, reduce computational cost, and align with design intent and engineering principles. The findings are intended to foster innovative design practices and advance automation in construction through enhanced computer-aided design.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"180 ","pages":"Article 106530"},"PeriodicalIF":11.5,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094179","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

Autonomous launching gantry: Improved monocular vision approach for real-time pose estimation of precast concrete girders 自主发射龙门：用于预制混凝土梁实时姿态估计的改进单目视觉方法

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-19 DOI: 10.1016/j.autcon.2025.106534

Weili Fang , Guanghui Geng , Gan Zhang , Peter E.D. Love

{"title":"Autonomous launching gantry: Improved monocular vision approach for real-time pose estimation of precast concrete girders","authors":"Weili Fang , Guanghui Geng , Gan Zhang , Peter E.D. Love","doi":"10.1016/j.autcon.2025.106534","DOIUrl":"10.1016/j.autcon.2025.106534","url":null,"abstract":"<div><div>The absence of accurate and real-time 6-DoF pose data for precast concrete girders renders launching gantry operations predominantly manual, thereby impeding further automation. Such limitations pose a critical question: <em>How can we accurately and robustly estimate the pose of precast concrete girders in real-time during launching gantry operations?</em> To address that question, our paper proposes a monocular vision-based approach to estimate the 6-DoF pose of the precast concrete girder in launching gantry operations. The approach detects the ChArUco board regions using the YOLOv11n model, applies GAN-based image deblurring. The 6-DoF pose is then estimated using a Perspective-n-Point solver and transformed to the gantry coordinate system. Field tests demonstrate robust performance, achieving a mean reprojection error of 0.113 pixels and a processing latency of 60 ms per frame. The results validate the approach's robustness and real-time performance, highlighting monocular vision as a cost-effective alternative to LiDAR–IMU fusion for large-scale automation in construction.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"180 ","pages":"Article 106534"},"PeriodicalIF":11.5,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094163","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

LLM-based framework for automated and customized floor plan design 基于llm的自动化和定制平面图设计框架

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-18 DOI: 10.1016/j.autcon.2025.106512

Zijin Qiu , Jiepeng Liu , Yantao Wu , Pengkun Liu , Hongtuo Qi , Haobo Liang , Yi Xia

{"title":"LLM-based framework for automated and customized floor plan design","authors":"Zijin Qiu , Jiepeng Liu , Yantao Wu , Pengkun Liu , Hongtuo Qi , Haobo Liang , Yi Xia","doi":"10.1016/j.autcon.2025.106512","DOIUrl":"10.1016/j.autcon.2025.106512","url":null,"abstract":"<div><div>Interpreting diverse and ambiguous natural language (NL) user requirements into precise floor plans poses significant challenges for design automation. This paper presents a large language model (LLM)-based framework to automate and customize vectorized floor plan design. This framework utilizes a syntax tree for NL parsing and automated dataset enrichment. A dual LLM approach involves using a recognition model for automated dataset augmentation, while a generation model interprets user inputs to create diverse, geometrically precise vectorized floor plans that align with complex semantic preferences. Experimental results demonstrate the proposed LLM-based models' effectiveness, achieving high accuracy in interpreting user requirements and high quality in generating corresponding vectorized floor plans. Additionally, a large-scale NL-based dataset is generated through the automatic recognition of existing floor plans. The proposed method can advance automated and user-centric floor plan design by enabling direct NL interaction and generating readily usable vectorized outputs.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"180 ","pages":"Article 106512"},"PeriodicalIF":11.5,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094176","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

Vision-guided autonomous drone construction system for standardized bricklaying 用于标准化砌砖的视觉引导自主无人机施工系统

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-18 DOI: 10.1016/j.autcon.2025.106525

Xingjie Xie, Sijia Gu, Xiaofan Gao, Yilei Xu, Philip F. Yuan

引用次数: 0

Integrated weatherability optimization design tools for ice-shell architecture based on explainable surrogate models 基于可解释代理模型的冰壳建筑综合耐候性优化设计工具

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-18 DOI: 10.1016/j.autcon.2025.106539

Shuoyong Yang , Peng Luo , Xiaoping Liu

{"title":"Integrated weatherability optimization design tools for ice-shell architecture based on explainable surrogate models","authors":"Shuoyong Yang , Peng Luo , Xiaoping Liu","doi":"10.1016/j.autcon.2025.106539","DOIUrl":"10.1016/j.autcon.2025.106539","url":null,"abstract":"<div><div>The weatherability of ice-shell architecture directly affects both structural safety and industrial value. However, cost-effective solutions to improve weatherability remain limited. This paper proposes an efficient early-stage design optimization using surrogate models integrated with design tools. The degree of elastic energy degradation is introduced as a quantitative evaluation index. Generalizable spatial and shape features are extracted, and surrogate models are refined through Shapley Additive Explanations (SHAP) interpretation and validation with two engineering cases. The method reduces the data acquisition complexity and reliance on experience in the design process, thereby improving automation in the design workflow. Its universality makes it broadly applicable to airbag mold ice-shell buildings in northeastern China. Applied to a representative combined shuttle-shaped ice-shell architecture, the method reveals climatic coupling relationships and dominant design parameters, including long-axis length, support length, and orientation. Results indicate that the weatherability index can be reduced to 30–40 % through optimization.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"180 ","pages":"Article 106539"},"PeriodicalIF":11.5,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145093966","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

Graph neural network–based framework for predicting seismic damage in shield tunnels with contact loss defects 基于图神经网络的盾构隧道接触损失震害预测框架

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-16 DOI: 10.1016/j.autcon.2025.106535

Xianlong Wu , Xiaohua Bao , Jun Shen , Xiangsheng Chen

引用次数: 0

LiDAR-based temporal surface damage assessment of bridge infrastructure using efficient scan area planning 基于激光雷达的高效扫描区域规划桥梁基础设施时间面损伤评估

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-16 DOI: 10.1016/j.autcon.2025.106526

Vignesh Vijayalakshmi Palanisamy, Senthilkumar Venkatachalam

{"title":"LiDAR-based temporal surface damage assessment of bridge infrastructure using efficient scan area planning","authors":"Vignesh Vijayalakshmi Palanisamy, Senthilkumar Venkatachalam","doi":"10.1016/j.autcon.2025.106526","DOIUrl":"10.1016/j.autcon.2025.106526","url":null,"abstract":"<div><div>Aging bridges pose significant risks to public safety and economic stability, and traditional inspection methods lack accuracy and historical data. LiDAR-based damage assessment has gained prominence in recent years because of its precision and automation capabilities. However, optimal scanner placement for efficient and comprehensive, accurate data collection remains a challenge. This paper demonstrates and validates a scan area planning method that minimizes differences between planned and measured interpoint spacings, achieving sub-millimeter accuracy. Using this approach, point clouds of bridge pier infrastructure were collected over two years to track cracks, spalling, and reinforcement corrosion. The results revealed a 47.2% reduction in the diameter of the exposed reinforcement and a 37.1% increase in the vertical crack width, indicating significant structural deterioration. The proposed method provides valuable insights into the condition of the bridge components and their surrounding environment, supporting proactive maintenance planning and more efficient resource allocation.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"180 ","pages":"Article 106526"},"PeriodicalIF":11.5,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094178","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

Precision UAV image-to-BIM registration through contour-based matching for concrete dam structural health monitoring 基于等高线匹配的高精度无人机图像与bim配准用于混凝土坝结构健康监测

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-15 DOI: 10.1016/j.autcon.2025.106536

Sizeng Zhao , Fei Kang , Junjie Li , Jin Gong , Maosong Yang , Liangchong Xie

{"title":"Precision UAV image-to-BIM registration through contour-based matching for concrete dam structural health monitoring","authors":"Sizeng Zhao , Fei Kang , Junjie Li , Jin Gong , Maosong Yang , Liangchong Xie","doi":"10.1016/j.autcon.2025.106536","DOIUrl":"10.1016/j.autcon.2025.106536","url":null,"abstract":"<div><div>The accurate mapping of UAV images to BIM is critical for long-term structural health monitoring. However, the complexity of concrete dams introduce positioning deviations, making it challenging to precisely localize defects. This paper proposes a precise image-to-BIM method based on contour matching. After point cloud registration establishes global coordinate transformation, the structural contour templates are extracted for UAV viewpoints. The concrete dam contours are classified as outer or inner, and the UAV images are matched with templates using different algorithms. 2D pixel variations are then converted into 3D spatial displacements, and the UAV coordinates are iteratively refined for accurate contour alignment. The corrected coordinates map the detected defects onto the BIM surface to ensure precise image-to-BIM registration. The proposed method is validated on a real concrete dam. After coordinate correction, cracks detected in the UAV images are accurately mapped to the BIM surface, with consistent localization across different viewing angles.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"180 ","pages":"Article 106536"},"PeriodicalIF":11.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060860","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

Multistage cognitive dynamics for team-based teleoperation in challenging environments 挑战性环境下基于团队的远程操作的多阶段认知动力学

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-15 DOI: 10.1016/j.autcon.2025.106537

Di Liu , Youngjib Ham

{"title":"Multistage cognitive dynamics for team-based teleoperation in challenging environments","authors":"Di Liu , Youngjib Ham","doi":"10.1016/j.autcon.2025.106537","DOIUrl":"10.1016/j.autcon.2025.106537","url":null,"abstract":"<div><div>Excavation in urban areas presents high risks, particularly underground utility strikes, which can lead to significant disruptions and safety hazards. This paper investigates the cognitive dynamics of teleoperated excavation, focusing on how operator-spotter communication and environmental complexity impact cognitive load, attention allocation, and task performance in high-stress settings. Excavation scenarios are simulated in baseline and challenging urban environments, involving 56 subjects examined key metrics, including attention resources, cognitive workload, situational awareness, and unsafe behaviors. Findings show high perceptual and cognitive-control loads in a complex environment impair situational awareness, extend task completion times, and increase communication error rates. Results also highlight hand signals reduce cognitive load, enhancing focus on peripheral cues, whereas verbal signals help operators concentrate on task-critical elements, lowering collision risks. This paper advances the understanding of human-machine collaboration by building on a multistage cognitive framework that provides insights into team communication and safety for teleoperation in challenging environments.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"180 ","pages":"Article 106537"},"PeriodicalIF":11.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060859","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