Civil Engineering Design最新文献

Practical assessment of masonry tunnel joint segmentation using topological machine learning 基于拓扑机器学习的砌体隧道接缝分割的实用评价

Civil Engineering Design Pub Date : 2025-05-01 DOI: 10.1002/cend.202400049

Jack Smith, Chrysothemis Paraskevopoulou

{"title":"Practical assessment of masonry tunnel joint segmentation using topological machine learning","authors":"Jack Smith, Chrysothemis Paraskevopoulou","doi":"10.1002/cend.202400049","DOIUrl":"https://doi.org/10.1002/cend.202400049","url":null,"abstract":"Condition assessment of masonry lined tunnels is time consuming and labor intensive. Recently developed digital workflows enable structural models to be created automatically, reducing analysis time. As part of these procedures, it is important to be able to identify the location of each masonry block. Masonry joints can be segmented by applying deep learning to 3D point clouds obtained by lidar. However, these models often fail to separate block instances, reducing the effectiveness of subsequent analysis. Recent developments in topological loss functions enable models to more accurately connect detected structures. While these can be applied to better isolate individual masonry blocks, their performance depends on the selected training data, and so further investigation is required to enable the method to be applied effectively to different structures. This study investigates the ability of topological loss functions to enable deep learning models to operate on different tunnels with varying lining properties. By focusing on possible workflows for real world application of these methods, the study shows how training data type and origin impact performance. Block instance segmentation performance is evaluated directly using a new Blockwise Intersection Over Union metric. With this metric, training data volume and variety is shown to be a bigger driver of segmentation performance than either similarity between training and testing datasets or choice of loss function.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"7 2","pages":"93-110"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.202400049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Photogrammetric documentation in tunneling 隧道工程中的摄影测量文件

Civil Engineering Design Pub Date : 2025-02-25 DOI: 10.1002/cend.202400040

Andreas Zani, Ines Metzler, Thomas Marcher

引用次数: 0

Generalization challenges and strategies in tunnel boring machine performance prediction 隧道掘进机性能预测的泛化挑战与策略

Civil Engineering Design Pub Date : 2025-02-10 DOI: 10.1002/cend.202400047

Shengfeng Huang, George Korfiatis, Rita Sousa

{"title":"Generalization challenges and strategies in tunnel boring machine performance prediction","authors":"Shengfeng Huang, George Korfiatis, Rita Sousa","doi":"10.1002/cend.202400047","DOIUrl":"https://doi.org/10.1002/cend.202400047","url":null,"abstract":"Achieving robust generalization in machine learning for tunnel boring machine performance prediction is challenging, particularly when models are developed on data from different projects. This study assesses the generalization abilities of K-nearest neighbors, support vector regression, artificial neural networks, random forest, classification and regression trees, and extreme gradient boosting (XGBoost) for predicting penetration rate (PR) and explores the potential of incremental learning to enhance it. The datasets were collected from two tunnels (Line C and Line S) that were constructed in similar geological formation, with similar technology, in Porto, Portugal. In the first part, these models are trained using Line C data and applied to Line S for generalization assess under different splitting and scaling methods. XGBoost demonstrated superior performance in both accuracy and generalization, making it the base model for incremental learning. In the second part, the incremental learning, applied by continually updating the XGBoost model when new data becomes available, was evaluated across different PR ranges and different incremental sizes. Finally, the model trained using Line C data plus Line S data was compared to the model using Line S only to investigate the impact of including Line C data on generalization. Our findings show that for the imbalanced data of PR <125 mm/rpm, incremental learning show unstable generalization but exhibited improved generalization on PR < 25 mm/rpm. For the balanced data of PR <25 mm/rpm, incremental learning showed more stable and gradually improved generalization. Combining Line C data with Line S data for training improved generalization significantly. The study results provide important insights into developing generalization strategies, highlighting the benefits of pre-training with similar data and the challenges of dealing with imbalanced data in real-life projects.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"7 2","pages":"63-84"},"PeriodicalIF":0.0,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.202400047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hyperledger Fabric for the (digitalized) lifecycle of construction products: Applied review on fastening technology 建筑产品（数字化）生命周期的超级分类织物：紧固技术的应用综述

Civil Engineering Design Pub Date : 2025-02-03 DOI: 10.1002/cend.202400027

Aileen Pfeil, Dimosthenis Kifokeris, Panagiotis Spyridis

{"title":"Hyperledger Fabric for the (digitalized) lifecycle of construction products: Applied review on fastening technology","authors":"Aileen Pfeil, Dimosthenis Kifokeris, Panagiotis Spyridis","doi":"10.1002/cend.202400027","DOIUrl":"https://doi.org/10.1002/cend.202400027","url":null,"abstract":"Blockchain technology is a digital decentralized data ledger recording transactions in an encrypted format. Its implementation can potentially hold significant advantages for the built environment, particularly in manufacturing and building product usage aligned with Building Information Modeling (BIM). This paradigm shift toward decentralized transactions can foster security, reliability, and accountability. Hyperledger Fabric (HLF), an enterprise-grade distributed ledger, offers a modular, scalable, and confidential digital framework. This article introduces HLF-based workflows to address inefficiencies in BIM and fastener product lifecycle management, such as fragmented data handling and limited process automation. Leveraging chaincodes linked to BIM models, HLF simplifies, enhances transparency, and automates construction product lifecycle processes. Contract data and execution details are managed through a blockchain stored in a common data environment (CDE) and linked to chaincodes. The article presents the conceptualization and implementation of automated workflows, emphasizing efficiency and transparency. While showcasing successful deployments, it also highlights areas for future improvement and development. The proposed framework represents a pioneering step toward a decentralized cooperative environment in the construction industry, aligning with the transformative potential of blockchain technology.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"7 1","pages":"9-22"},"PeriodicalIF":0.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.202400027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143638577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advanced computational strategy for damage identification of offshore jacket platforms 海上导管架平台损伤识别的先进计算策略

Civil Engineering Design Pub Date : 2025-01-24 DOI: 10.1002/cend.202400032

Jafar Jafari-Asl, You Dong, Yaohan Li

{"title":"Advanced computational strategy for damage identification of offshore jacket platforms","authors":"Jafar Jafari-Asl, You Dong, Yaohan Li","doi":"10.1002/cend.202400032","DOIUrl":"https://doi.org/10.1002/cend.202400032","url":null,"abstract":"In this study, an efficient surrogate-assisted grey wolf optimizer (GWO) is presented by combining Kriging-based active learning to identify damages in jacketed platforms based on modal analysis. The use of active learning in parallel with GWO significantly reduced the number of calls to the objective function and increased the accuracy of the algorithm's search in the problem space. The proposed approach was first evaluated on four benchmark problems, and its performance was validated against original GWO, particle swarm optimization (PSO), and genetic algorithm (GA) techniques. Then, by generating artificial damage scenarios on a real jacket platform in ABAQUS software, it was evaluated for the identification of damaged members. The results indicated high accuracy in estimation and an appropriate convergence rate in solving the high-dimensional and complicated problem of damage detection of jacketed platforms. In such a way that the error rate of damage severity estimation in scenarios 1 and 2 was, on average, 3% and 5%, respectively. Meanwhile, the damage position was correctly estimated, and the call rate of the function was reduced by 50%. The efficiency of the proposed approach shows that it can be used for further works on the reliability-based design of jacket structures.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"7 1","pages":"36-48"},"PeriodicalIF":0.0,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.202400032","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143639218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital documentation of railway tunnel inspection in Austria 奥地利铁路隧道检查的数字文档

Civil Engineering Design Pub Date : 2025-01-09 DOI: 10.1002/cend.202400029

Matthias J. Rebhan, Stefan S. Grubinger, Andreas Schüppel, Simona Deutinger, Gernot Schwarzenberger

{"title":"Digital documentation of railway tunnel inspection in Austria","authors":"Matthias J. Rebhan, Stefan S. Grubinger, Andreas Schüppel, Simona Deutinger, Gernot Schwarzenberger","doi":"10.1002/cend.202400029","DOIUrl":"https://doi.org/10.1002/cend.202400029","url":null,"abstract":"Infrastructure, especially railway tunnels, require continuous inspection to ensure their safety. Furthermore, the detection of damages at an early stage can improve their service life. These tasks represent a major challenge for those involved and the tunnel down time is a disruption in operation. In rail networks, comprehensive preparations are necessary to be able to plan closures and required compensation measures. To optimize this process, a workflow for a digital inspection was generated to allow a rapid localization and a corresponding time advantage when conducting the activities on site. In doing so, a multitude of bases can be used, a standardization of damage patterns is carried out and a collaborative cooperation of multiple inspection personnel is possible. Depending on the data stock, digitized as-built models in the form of a plan, digital plan documents and existing or generated digital twins can be used. Making it possible to locate a damage already during the inspection and thus enable a comprehensible documentation and an automated generation of reports. The pre-set options for attribution of damages enables a time-optimized inspection on site—which enables a reduction of the required time, the associated restrictions on traffic routing and at the same time reduces the susceptibility to errors. Within this paper, results of a first series of field tests along the Tauern Line of ÖBB, using a digital inspection workflow, are presented.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"7 1","pages":"3-8"},"PeriodicalIF":0.0,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.202400029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143638849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-destructive testing in civil engineering—A memorandum for teaching NDTCE at universities 土木工程无损检测——高校无损检测教学备忘录

Civil Engineering Design Pub Date : 2025-01-06 DOI: 10.1002/cend.202400041

Ralf W. Arndt, Christian U. Grosse, Ernst Niederleithinger, Dietmar Mähner, Alexander Taffe, Daniel Algernon

{"title":"Non-destructive testing in civil engineering—A memorandum for teaching NDTCE at universities","authors":"Ralf W. Arndt, Christian U. Grosse, Ernst Niederleithinger, Dietmar Mähner, Alexander Taffe, Daniel Algernon","doi":"10.1002/cend.202400041","DOIUrl":"https://doi.org/10.1002/cend.202400041","url":null,"abstract":"This paper summarizes current developments and outlines essential teaching content in the field of non-destructive testing in civil engineering for academic education at German-speaking universities. This first memorandum on teaching and research in non-destructive testing in civil engineering (NDT-CE) at German-speaking universities provides an overview of academic education and identifies focal points in teaching and important developments and topics in NDT-CE research. Suggestions are given for the development and advancement of teaching curricula with regard to a comprehensive and sound professional education of students of civil engineering and related disciplines. In terms of content and form, the contribution deliberately borrows from the memorandum of university teachers in the adjacent subject “Building Materials” (Breit et al. Hochschullehrer-Memorandum Werkstoffe im Bauwesen—universitäre Lehre und Forschung, Bauingenieur, 87, 72–80, 2012).","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"7 1","pages":"49-60"},"PeriodicalIF":0.0,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.202400041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143638856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ensemble-based soil liquefaction assessment: Leveraging CPT data for enhanced predictions 基于集合的土壤液化评估：利用 CPT 数据加强预测

Civil Engineering Design Pub Date : 2025-01-02 DOI: 10.1002/cend.202400024

Arsham Moayedi Far, Masoud Zare

{"title":"Ensemble-based soil liquefaction assessment: Leveraging CPT data for enhanced predictions","authors":"Arsham Moayedi Far, Masoud Zare","doi":"10.1002/cend.202400024","DOIUrl":"https://doi.org/10.1002/cend.202400024","url":null,"abstract":"This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk of catastrophic failures. To enhance the accuracy of classification problems associated with liquefaction, we employ ensemble methods, leveraging diverse machine learning techniques such as support vector machines, stochastic gradient descent, multi-layer perceptron neural networks, K-nearest neighbors, and decision trees. The research encompasses data exploration and a subsequent division for performance assessment, followed by hyperparameter tuning through GridSearchCV to optimize model effectiveness. Among the ensemble methods employed, AdaBoost stands out as the most accurate, achieving precision of 85%, recall of 84%, F1 score of 83%, Jaccard index of 72%, and overall accuracy of 84%. However, K-nearest neighbors and decision trees exhibit higher false negative values compared to other methods. Notably, both ensemble approaches provide acceptable estimations, with false negative values ranging from 0 to 1 and false positive values between 7 and 10. The decision tree, while predicting the lowest false positive rate, has a higher false negative count, rendering it less favorable for practical applications.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"7 1","pages":"23-35"},"PeriodicalIF":0.0,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.202400024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143638852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

BIM tunneling documentation in Rohbaustollen Angath Rohbaustollen Angath的BIM隧道文件

Civil Engineering Design Pub Date : 2024-12-26 DOI: 10.1002/cend.202400039

Jaka Senekovic, Dario Gaudart, Mag. Frédéric Heil, Roland Arnold, Johannes Krasa

{"title":"BIM tunneling documentation in Rohbaustollen Angath","authors":"Jaka Senekovic, Dario Gaudart, Mag. Frédéric Heil, Roland Arnold, Johannes Krasa","doi":"10.1002/cend.202400039","DOIUrl":"https://doi.org/10.1002/cend.202400039","url":null,"abstract":"Since 2023, Austrian Federal Railways (ÖBB), with BEMO-ÖSTU STETTIN, has been constructing the 2.6 km raw construction tunnel Angath (Rohbaustollen Angath) along the Angerberg. It will support geological investigations, logistics for the future main railway tunnel Angerberg, and act as a rescue tunnel, ensuring safety. The project includes a pre-cut, tunnel excavation, and a 110-meter section of the main railway tunnel, with turning niches and cross adits. Building information modeling (BIM) is used for design, tendering, control, and documentation. The integrated project delivery (IPD) model ensures shared responsibility for risks and costs. BIM optimizes data flow and transparency, with tunneling documentation collected on-site, verified in ÖBB's Common Data Environment (MSP), and used for parametric modeling. Cost and progress monitoring occur via software RIB iTWO (Version 2023, 2023). Project documentation and the linking of the documentation into a 3D BIM model of a tunnel enables early detection of deviations and appropriate action to be taken, with transparency and traceability being critical to the success of the IPD project.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"6 4","pages":"150-157"},"PeriodicalIF":0.0,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.202400039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Navigating challenges in alpine tunneling 在高山隧道中导航挑战

Civil Engineering Design Pub Date : 2024-12-18 DOI: 10.1002/cend.202410012

Matthias Flora

引用次数: 0