Civil Engineering Design最新文献

TUM bond database with full-scale beam tests on anchorages and laps in tension TUM粘结数据库与全尺寸梁测试的锚固和圈在张力

Civil Engineering Design Pub Date : 2026-03-19 Epub Date: 2026-01-07 DOI: 10.1002/cend.70025

Johannes Fröse, Leopold Staller, Oliver Fischer

{"title":"TUM bond database with full-scale beam tests on anchorages and laps in tension","authors":"Johannes Fröse, Leopold Staller, Oliver Fischer","doi":"10.1002/cend.70025","DOIUrl":"https://doi.org/10.1002/cend.70025","url":null,"abstract":"Reliable experimental data is essential for the development and validation of structural design models. However, existing bond databases often lack consistency, traceability, and overall data quality. To address this, the Technical University of Munich (TUM) developed the TUM Bond Database (TUMBD), a curated collection of experimental test data focusing on lap splices and anchorages under tensile loading. TUMBD includes a variety of full-scale beam tests from the primary literature and tests conducted at TUM. The TUMBD currently comprises 1033 lap splice and 189 anchorage tests, with detailed information on geometry, test setup, materials, and experimental results. This paper discusses the database's origin and development, its structure and content, and presents a statistical analysis of the distribution of key parameters. The open-access database supports model calibration and data-driven research, including the use of artificial intelligence and advanced computational methods. Given the complexity of bond behavior, the emergence of new resource-efficient materials, and the potential of such advanced statistical techniques, TUMBD enhances the reliability, sustainability, and efficiency of reinforced concrete construction. Ongoing updates and strict criteria ensure data quality.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"8 1","pages":"3-10"},"PeriodicalIF":0.0,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147563895","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

TUM bond database with full-scale beam tests on anchorages and laps in tension TUM粘结数据库与全尺寸梁测试的锚固和圈在张力

Civil Engineering Design Pub Date : 2026-03-19 Epub Date: 2026-01-07 DOI: 10.1002/cend.70025

Johannes Fröse, Leopold Staller, Oliver Fischer

{"title":"TUM bond database with full-scale beam tests on anchorages and laps in tension","authors":"Johannes Fröse, Leopold Staller, Oliver Fischer","doi":"10.1002/cend.70025","DOIUrl":"https://doi.org/10.1002/cend.70025","url":null,"abstract":"Reliable experimental data is essential for the development and validation of structural design models. However, existing bond databases often lack consistency, traceability, and overall data quality. To address this, the Technical University of Munich (TUM) developed the TUM Bond Database (TUMBD), a curated collection of experimental test data focusing on lap splices and anchorages under tensile loading. TUMBD includes a variety of full-scale beam tests from the primary literature and tests conducted at TUM. The TUMBD currently comprises 1033 lap splice and 189 anchorage tests, with detailed information on geometry, test setup, materials, and experimental results. This paper discusses the database's origin and development, its structure and content, and presents a statistical analysis of the distribution of key parameters. The open-access database supports model calibration and data-driven research, including the use of artificial intelligence and advanced computational methods. Given the complexity of bond behavior, the emergence of new resource-efficient materials, and the potential of such advanced statistical techniques, TUMBD enhances the reliability, sustainability, and efficiency of reinforced concrete construction. Ongoing updates and strict criteria ensure data quality.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"8 1","pages":"3-10"},"PeriodicalIF":0.0,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147563875","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

In-situ installation safety of post-installed anchorages—Investigations on construction sites 后安装锚的原位安装安全施工现场调查

Civil Engineering Design Pub Date : 2025-10-28 DOI: 10.1002/cend.70003

Oliver Zeman, Elisabeth Stierschneider, Michael Schwenn, Konrad Bergmeister

{"title":"In-situ installation safety of post-installed anchorages—Investigations on construction sites","authors":"Oliver Zeman, Elisabeth Stierschneider, Michael Schwenn, Konrad Bergmeister","doi":"10.1002/cend.70003","DOIUrl":"https://doi.org/10.1002/cend.70003","url":null,"abstract":"The sensitivity to reduced installation effort of post-installed fastening systems is determined during the product qualification through robustness tests conducted under controlled laboratory conditions. Using the concept of required α-factors, the installation safety factor γinst is determined and provided as an essential characteristic in the corresponding European Technical Assessment (ETA) of the fastener. The purpose of robustness tests is to simulate reduced installation conditions. To gain more insight on the variability of the installation conditions in practice, an in-situ verification of the installation safety factor is carried out on four different construction sites in Austria using four anchorage types to cover all working principles. For this in-situ verification, the obtained ultimate loads from unconfined pull-out tests on-site are compared with corresponding ultimate loads from reference tests under laboratory conditions. Based on the in-situ tests, it is verified if the designed robustness tests are sufficiently appropriate to cover in-situ variations during the installation. The investigation shows that for all tested fastening products, the specified installation safety factor from the ETA could be confirmed with the in-situ tests based on mean values. As expected, the coefficient of variation of the in-situ tests is for torque-controlled mechanical fasteners around two to three times higher than in the laboratory tests, for concrete screws and bonded anchors, the value 1.5 applies.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"7 4","pages":"202-210"},"PeriodicalIF":0.0,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.70003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145751027","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-driven productivity and risk management of workspaces for manual and robotic installations bim驱动的生产力和手动和机器人安装的工作空间风险管理

Civil Engineering Design Pub Date : 2025-10-09 DOI: 10.1002/cend.70002

Aileen Pfeil, Cynthia Brosque, Yiannis Xenidis, Panagiotis Spyridis

引用次数: 0

Automatic inventory of retaining walls from aerial lidar data using 3D deep learning 使用3D深度学习从空中激光雷达数据自动清点挡土墙

Civil Engineering Design Pub Date : 2025-10-06 DOI: 10.1002/cend.70001

Ivo Gasparini, Souhir Ben Souissi, Dirk Proske

{"title":"Automatic inventory of retaining walls from aerial lidar data using 3D deep learning","authors":"Ivo Gasparini, Souhir Ben Souissi, Dirk Proske","doi":"10.1002/cend.70001","DOIUrl":"https://doi.org/10.1002/cend.70001","url":null,"abstract":"Infrastructure management along highways and railways requires inventories of critical structures like retaining walls, which traditionally rely on manual inspection and documentation. Unfortunately, data in infrastructure databases is often incomplete. This study investigates the feasibility of automating retaining wall inventories using public aerial lidar data from the Swiss Federal Office of Topography (Swisstopo) combined with deep learning. We develop a pipeline for data processing and apply the state-of-the-art Superpoint Transformer architecture with SuperCluster for panoptic segmentation. Three distinct approaches are evaluated: transfer learning from general Swisstopo lidar data, transfer learning from the DALES aerial lidar dataset, and training a specialized model from scratch. The specialized model achieves the best performance with 44% Intersection over Union (IoU) for semantic segmentation and 24% panoptic quality on test data. Our findings reveal that the primary challenges stem from data characteristics—like sparse sampling of vertical surfaces due to oblique scanning angles—rather than model architecture limitations. This work provides insights into the development of automated infrastructure inventories and identifies areas for improvement, including the need for expanded training data and robust augmentation techniques.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"7 4","pages":"178-189"},"PeriodicalIF":0.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145750721","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

Rock Mass Anomaly Detection with a Variational Autoencoder in Tunnel Boring Machine Data 基于变分自编码器的隧道掘进机数据岩体异常检测

Civil Engineering Design Pub Date : 2025-07-27 DOI: 10.1002/cend.202400053

Mario Wölflingseder, Paul J. Unterlass, Thomas Marcher

{"title":"Rock Mass Anomaly Detection with a Variational Autoencoder in Tunnel Boring Machine Data","authors":"Mario Wölflingseder, Paul J. Unterlass, Thomas Marcher","doi":"10.1002/cend.202400053","DOIUrl":"https://doi.org/10.1002/cend.202400053","url":null,"abstract":"This study presents an unsupervised machine learning approach to rock mass anomaly detection in tunnel boring machine operational data using a Variational Autoencoder combined with bidirectional Long Short-Term Memory cells. The model was trained on TBM data from the Brenner Base Tunnel project, with minor faults and geotechnically relevant fault zones removed to ensure a rock mass anomaly-free training set. By reconstructing input data from a compressed latent space, the Variational Autoencoder distinguishes between normal and abnormal patterns based on reconstruction errors. Anomalies, such as significant changes in rock mass conditions, are identified when reconstruction errors exceed a threshold based on a skewness-adjusted boxplot. Testing on three distinct sections of TBM data demonstrated the model's effectiveness in reliably detecting minor faults and major fault zones, though occasional delays in detection were noted. This approach underscores the potential of Variational Autoencoder-based rock mass anomaly detection in mechanized tunneling and paves the way for real-time, data-driven decision-making in future TBM tunneling projects.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"7 4","pages":"169-177"},"PeriodicalIF":0.0,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.202400053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145751255","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

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

Analysis of the opportunities for reducing energy intensity in construction site operations in Germany 分析德国建筑工地降低能源强度的机会

Civil Engineering Design Pub Date : 2025-03-19 DOI: 10.1002/cend.202400035

Štefan Krištofič, Thomas Harborth, Naďa Antošová, Jana Kalická

引用次数: 0

Experimental studies on multi-scale data-driven methods within the framework of structural health monitoring 结构健康监测框架下多尺度数据驱动方法的实验研究

Civil Engineering Design Pub Date : 2025-02-27 DOI: 10.1002/cend.202400036

Maximilian Rohrer MSc, Jan Backhaus MSc, Ulf Bestmann Dr.-Ing, Vanessa De Arriba López MSc, Pedro Achanccaray Diaz Dr, Markus Gerke Dr.-Ing, Carsten Könke Dr.-Ing, Armin Lenzen Dr.-Ing, Lukas Lippold MSc, Mehdi Maboudi MSc, Max Moeller MSc, Carlos Luis Paz Villegas MSc, Paul Winkler Dr.-Ing, Volkmar Zabel Dr.-Ing

{"title":"Experimental studies on multi-scale data-driven methods within the framework of structural health monitoring","authors":"Maximilian Rohrer MSc, Jan Backhaus MSc, Ulf Bestmann Dr.-Ing, Vanessa De Arriba López MSc, Pedro Achanccaray Diaz Dr, Markus Gerke Dr.-Ing, Carsten Könke Dr.-Ing, Armin Lenzen Dr.-Ing, Lukas Lippold MSc, Mehdi Maboudi MSc, Max Moeller MSc, Carlos Luis Paz Villegas MSc, Paul Winkler Dr.-Ing, Volkmar Zabel Dr.-Ing","doi":"10.1002/cend.202400036","DOIUrl":"https://doi.org/10.1002/cend.202400036","url":null,"abstract":"The German Research Foundation has established the priority program SPP 100+. Its subject is monitoring bridge structures in civil engineering. The data-driven methods cluster deals with the use of measurements and their special global and local analysis methods, which complement each other in an overall multi-scale concept in order to realize condition monitoring. The presented methods aim for damage detection, localization, and quantification of the monitored structure. Static and dynamic investigations based on mechanical multi-scale models were carried out, and process-oriented models combined with image processing methods and machine learning were created. The methods are tested on several laboratory and real-life experimental mechanical structures. The underlying theoretical concept and first experimental results of the research group are presented in this article. This study successfully employs a series of multi-scale experiments, integrating mechanical models and advanced image processing to effectively detect, localize, and quantify damage in bridge structures for enhanced structural health monitoring.","PeriodicalId":100248,"journal":{"name":"Civil Engineering Design","volume":"7 4","pages":"147-168"},"PeriodicalIF":0.0,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cend.202400036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145751254","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