Article
Computer Science, Interdisciplinary Applications
Bartosz Sobczyk, Lukasz Pyrzowski, Mikolaj Miskiewicz
Summary: This paper describes the problems encountered during the analysis of the structural response of historic masonry railroad arch bridges. It focuses on the stiffness of the masonry arches, their strengths, and the estimation of railroad load intensity. The paper presents computational models created to efficiently describe the responses of the bridges under typical loading conditions and discusses the outcomes of nonlinear static analyses. The possible causes of the deterioration of the bridges' condition were identified through these analyses.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
S. Grosman, L. Macorini, B. A. Izzuddin
Summary: This paper introduces a novel parametric model design tool for generating detailed 3D finite element meshes of realistic masonry arch bridges and viaducts. The tool allows for modular design of key viaduct parts and seamless introduction of new parts. The strategy enables variable fidelity model generation and consideration of initial damage in masonry structures.
ADVANCES IN ENGINEERING SOFTWARE
(2023)
Article
Chemistry, Multidisciplinary
Memduh Karalar, Mustafa Yesil
Summary: This study investigated the effect of arch height on the behavior of a single-span ancient masonry arch bridge. It was found that increasing the arch height can reduce the maximum motion during earthquakes, thus increasing the safety of the bridge.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Civil
Ozden Saygili, Jose Lemos
Summary: The study reveals that a shorter span bridge tends to withstand seismic actions with less damage, while a longer span bridge is more vulnerable to earthquake impacts. Rigid block models are effective in simulating the dynamic response of bridges and can be calibrated through vibration measurements.
Article
Engineering, Mechanical
Jofin George, Arun Menon
Summary: Scour-induced bridge collapse is a significant cause of failure for brick or stone masonry arch bridges in the existing rail and road infrastructure worldwide. This research develops a novel quantitative procedure based on limit analysis to assess the collapse behavior of masonry arch bridges subjected to scouring, enabling the formulation of suitable mitigation strategies.
ENGINEERING FAILURE ANALYSIS
(2022)
Review
Forestry
Brunela Pollastrelli Rodrigues, Christopher Adam Senalik, Xi Wu, James Wacker
Summary: This paper is a review of studies on the use of ground penetrating radar (GPR) for wood structures, highlighting its advantages as an inspection tool and the gaps in knowledge for its practical application. Despite laboratory studies, the use of GPR on large wood structures remains limited. Key knowledge gaps include distinguishing internal feature types and identifying internal decay.
Article
Construction & Building Technology
Federico Lombardi, Maurizio Lualdi, Elsa Garavaglia
Summary: This study evaluates the use of Ground Penetrating Radar for masonry texture identification and geometrical reconstruction, assessing its operational advantages and weaknesses for seismic assessment purposes. High frequency 3D GPR data collection on a plastered masonry wall successfully reconstructs the wall texture, providing detailed information on the masonry quality.
CONSTRUCTION AND BUILDING MATERIALS
(2021)
Article
Environmental Sciences
Ruiqing Shen, Yonghui Zhao, Shufan Hu, Bo Li, Wenda Bi
Summary: This study validated the effectiveness of ground-penetrating radar (GPR) combined with reverse time migration (RTM) algorithm in detecting and localizing rebars through experimental activities. GPR can accurately identify the quantity and positions of rebars, while RTM algorithm can assist in localizing and shaping rebars.
Article
Environmental Sciences
Vivek Kumar, Isabel M. Morris, Santiago A. Lopez, Branko Glisic
Summary: Estimating variations in material properties over space and time is crucial for structural health monitoring of civil infrastructure. Nondestructive methods like ground penetrating radar (GPR) are being used to assess in situ material properties of concrete, with a focus on compressive strength. The study shows that GPR attributes can successfully identify spatial and temporal variations in concrete properties, providing valuable insights for field applications.
Article
Engineering, Civil
Tamas Forgacs, Vasilis Sarhosis, Sandor Adany
Summary: This study investigates the stability and dynamic behavior of railway masonry arch bridges under traffic load conditions using a nonlinear mixed discrete-finite element numerical model, exploring the effects of moving traffic loads and train to bridge interaction. It is shown that the external load passing through the bridge causes plastic deformations and residual stresses, with dynamic amplification factors depending on the magnitude of the external load. The presence of nonlinearity in the structure with increased load decreases the natural frequency of the bridge, ultimately impacting the critical speed.
ENGINEERING STRUCTURES
(2021)
Article
Construction & Building Technology
Ismail Ozan Demirel, Alper Aldemir
Summary: This study proposes a hybrid methodology for assessing the seismic performance of dry-joint masonry arches, combining a simple finite element micro model with principles of limit analysis method. Kinematic conditions leading to possible collapse mechanisms were traced and applied to evaluate seismic risk of an ancient Roman arch bridge in close proximity to a fault line.
Article
Engineering, Civil
Baran Bozyigit, Sinan Acikgoz
Summary: The dynamic amplification of loads in masonry arch railway bridges is not well understood. This paper explores the problem through simple 2D and higher fidelity 3D models, revealing a complex relationship between train speed, bridge geometry, and axle spacing. The results highlight deficiencies in existing code provisions and demonstrate the potential of efficient numerical models to replace them.
Article
Engineering, Multidisciplinary
Zhengfang Wang, Ming Lei, Jing Wang, Bo Li, Jing Xu, Yuchen Jiang, Qingmei Sui, Yao Li
Summary: This paper proposes an unsupervised deep learning method for translating real ground penetrating radar (GPR) images to simulated ones. The method introduces geometry-consistency constraints to prevent semantic distortion in translation. It was validated using GPR data collected in various scenarios, and the findings demonstrate accurate identification of internal defects in translated GPR images.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Engineering, Civil
Ladislav Klusacek, Radim Necas, Michal Pozar, Robin Peknik, Adam Svoboda
Summary: This paper explores methods for strengthening and restoring aged masonry arch bridges, with a focus on using new reinforced concrete spandrel walls stabilized by transverse prestressed cables. The effectiveness of the method is demonstrated through case examples and data from prestressing and load tests.
ENGINEERING STRUCTURES
(2021)
Article
Chemistry, Multidisciplinary
Che-Way Chang, Che-An Tsai, Yan-Chyuan Shiau
Summary: This study compared the degree of corrosion of steel reinforcement using the reflected voltage of electromagnetic waves and ASTM C876 specification. It established a reference standard based on ASTM C876 for the degree of corrosion of steel bars and calculated the quantitative state of corroded steel bars.
APPLIED SCIENCES-BASEL
(2022)
Article
Construction & Building Technology
Mezgeen A. Rasol, Vega Perez-Gracia, Francisco M. Fernandes, Jorge C. Pais, Mercedes Solla, Caio Santos
Summary: This article introduces the ability of Ground Penetrating Radar (GPR) to assess cracks in rigid pavements, with laboratory and field tests conducted. The results show that GPR can accurately evaluate cracks of different sizes and materials.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2022)
Article
Computer Science, Information Systems
Miguel R. Luaces, Jesus A. Fisteus, Luis Sanchez-Fernandez, Mario Munoz-Organero, Jesus Balado, Lucia Diaz-Vilarino, Henrique Lorenzo
Summary: This paper introduces an architecture of an information system that creates an accessibility data model for cities by ingesting data from different sources and provides an application for computing accessible routes for people with different abilities. The system collects and integrates various information sources, including data extracted from maps and mobile sensing, as well as information collected from citizens' mobile devices sensors, in order to detect accessibility problems in the city.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2021)
Review
Environmental Sciences
Mercedes Solla, Vega Perez-Gracia, Simona Fontul
Summary: This paper introduces the use of ground penetrating radar (GPR) in the inspection of transportation infrastructures, highlighting its importance in assessing structural health conditions and its advantages and disadvantages. Through a review of the literature, the potential of using GPR is demonstrated, while some practical recommendations are made.
Article
Chemistry, Analytical
Lino Comesana-Cebral, Joaquin Martinez-Sanchez, Henrique Lorenzo, Pedro Arias
Summary: Individual tree segmentation is important for forest management, and LiDAR technology has shown to be superior in this area. Using DBSCAN clustering and cylinder voxelization can improve the detection rate and accuracy of tree location identification.
Article
Environmental Sciences
Jesus Balado, Pedro Arias, Henrique Lorenzo, Adrian Meijide-Rodriguez
Summary: This paper analyzes the impact of three disturbances (point density variation, ambient noise, and occlusions) on the classification of urban objects in point clouds. The results showed different behaviors for each disturbance: density reduction affected objects depending on the object shape and dimensions, ambient noise depending on the volume of the object, while occlusions depended on their size and location. Training the Convolutional Neural Network (CNN) with synthetic samples with disturbances resulted in improved performance, except for occlusions with a radius larger than 1 m.
Article
Construction & Building Technology
Mercedes Solla, Norberto Fernandez
Summary: Subsidence seriously affects the stability and safety of pavements and foundation soils, and efficient detection methods are needed. This study proposes using ground penetrating radar as a solution for non-invasive inspection of subsoil and explores different imaging techniques to improve the interpretability and detection of subsidence and settlement phenomena.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2023)
Review
Construction & Building Technology
Mezgeen Rasol, Jorge C. Pais, Vega Perez-Gracia, Mercedes Solla, Francisco M. Fernandes, Simona Fontul, David Ayala-Cabrera, Franziska Schmidt, Hossein Assadollahi
Summary: Suitable road pavements assessment is crucial for safe traffic movements and economic growth. Various factors can impact road pavements, reducing their lifespan and decreasing vehicle comfort. The use of non-destructive techniques like Ground Penetrating Radar (GPR) provides accurate and valuable information for optimizing maintenance and repairs, thereby increasing the longevity of road pavements.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Environmental Sciences
Mercedes Solla, Cristina Saez Blazquez, Ignacio Martin Nieto, Juan Luis Rodriguez, Miguel Angel Mate-Gonzalez
Summary: This research presents a review of the potential application of ground-penetrating radar (GPR) in studying geothermal resources and highlights its contribution to improving energy use. The specific case of investigating the San Xusto thermal baths in Spain is included, wherein GPR surveys and chemical analyses detected the presence of a hot spring, providing a basis for more efficient utilization of the geothermal resources in the area.
Article
Geochemistry & Geophysics
Mercedes Solla, Gonzalo Buceta-Bruneti, Ahmed Elseicy, Breogan Nieto-Muniz
Summary: This paper discusses the application of Ground Penetrating Radar (GPR) in the assessment of stone monuments. It compiles published works and presents a case study to demonstrate the potential of the method. The study introduces new imaging strategies and digitization techniques to improve damage detection and visualization. The paper also explores the potential of using GPR tests for the assessment of the conservation state of monumental stone structures.
SURVEYS IN GEOPHYSICS
(2022)
Review
Environmental Sciences
Federico Lombardi, Frank Podd, Mercedes Solla
Summary: Thanks to its non-destructive, high-resolution imaging possibilities and its sensitivity to both conductive and dielectric subsurface structures, Ground-Penetrating Radar (GPR) has become a widely recognized near-surface geophysical tool, routinely adopted in a wide variety of disciplines. Since its first development almost 100 years ago, the domain in which the methodology has been successfully deployed has significantly expanded from ice sounding and environmental studies to precision agriculture and infrastructure monitoring.
Article
Geography, Physical
Ernesto Frias, Mattia Previtali, Lucia Diaz-Vilarino, Marco Scaioni, Henrique Lorenzo
Summary: The use of laser scanners for generating accurate and dense 3D models has grown rapidly in the last two decades. Despite the development of optimized and automated scan planning strategies, most of the methods have focused on static scanning using terrestrial laser scanners (TLS). However, with the increasing use of portable mobile laser scanning systems (MLS), there is a need for dynamic scan planning to optimize scan trajectories. This study proposes a novel method that addresses the absence of dynamic scan planning by considering specific MLS constraints and evaluates the method's performance in real case studies.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Review
Environmental Sciences
Ahmed Elseicy, Alex Alonso-Diaz, Mercedes Solla, Mezgeen Rasol, Sonia Santos-Assuncao
Summary: Roads are crucial for transportation and require regular inspections and maintenance. Ground-penetrating radar (GPR) is a widely used non-destructive testing method to assess the condition of road pavements. Recent studies have combined GPR with other non-destructive testing methods to enhance its capabilities and detect potential pavement issues. Intelligent data analysis has the potential to improve the application of non-destructive testing techniques in the future.
Review
Construction & Building Technology
Ivan Garrido, Mercedes Solla, Susana Laguela, Mezgeen Rasol
Summary: This study presents a comprehensive review of the application of Infrared Thermography (IRT) and Ground-Penetrating Radar (GPR) in building inspection. The combined use of these two technologies in the building sector has great potential for applications in structural safety, energy efficiency, and heritage preservation.
ADVANCES IN CIVIL ENGINEERING
(2022)
Article
Architecture
Mercedes Solla, Jose Manuel Lopez-Leira, Alex Alonso-Diaz, Juan Luis Rodriguez
Summary: This study uses GPR technology to investigate settlement problems in an Indiana-style house built in 1933-1936. The GPR data is validated with geotechnical prospection results, providing engineers and architects with a better understanding for conservation activities.
INTERNATIONAL JOURNAL OF ARCHITECTURAL HERITAGE
(2022)
Article
Architecture
Vega Perez-Gracia, Mercedes Solla, Simona Fontul
Summary: This article summarizes different signal analysis techniques used to detect moisture from ground-penetrating radar (GPR) data. Four case studies are included, providing descriptions of the problems, results, methodologies, and limitations and advantages.
INTERNATIONAL JOURNAL OF ARCHITECTURAL HERITAGE
(2022)
Article
Construction & Building Technology
Jia Liang, Qipeng Zhang, Xingyu Gu
Summary: A lightweight PCSNet-based segmentation model is developed to address the issues of insufficient performance in feature extraction and boundary loss information. The introduction of generalized Dice loss improves prediction performance, and the visualization of class activation mapping enhances model interpretability.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Gilsu Jeong, Minhyuk Jung, Seongeun Park, Moonseo Park, Changbum Ryan Ahn
Summary: This study introduces a contextual audio-visual approach to recognize multi-equipment activities in tunnel construction sites, improving monitoring effectiveness. Tested against real-world operation data, the model achieved remarkable results, emphasizing the potential of contextual multimodal models in enhancing operational efficiency in complex construction sites.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Jin Wang, Zhigao Zeng, Pradip Kumar Sharma, Osama Alfarraj, Amr Tolba, Jianming Zhang, Lei Wang
Summary: This study presents a dual-path network for pavement crack segmentation, combining Convolutional Neural Network (CNN) and transformer. A lightweight CNN encoder is used for local feature extraction, while a novel transformer encoder integrates high-low frequency attention mechanism and efficient feedforward network for global feature extraction. Additionally, a complementary fusion module is introduced to aggregate intermediate features extracted from both encoders. Evaluation on three datasets confirms the superior performance of the proposed network.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Pierre Gilibert, Romain Mesnil, Olivier Baverel
Summary: This paper introduces a flexible method for crafting 2D assemblies adaptable to various geometric assumptions in the realm of sustainable construction. By utilizing digital fabrication technologies and optimization approaches, precise control over demountable buildings can be achieved, improving mechanical performance and sustainability.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Jorge Loy-Benitez, Myung Kyu Song, Yo-Hyun Choi, Je-Kyum Lee, Sean Seungwon Lee
Summary: This paper discusses the advancement of tunnel boring machines (TBM) through the application of artificial intelligence. It highlights the significance of AI-based management subsystems for automatic TBM operations and presents recent contributions in this field. The paper evaluates modeling, monitoring, and control subsystems and suggests research paths for integrating existing management subsystems into TBM automation.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Alireza Shamshiri, Kyeong Rok Ryu, June Young Park
Summary: This paper reviews the application of text mining and natural language processing in the construction field, highlighting the need for automation and minimizing manual tasks. The study identifies potential research opportunities in strengthening overlooked construction aspects, coupling diverse data formats, and leveraging pre-trained language models and reinforcement learning.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zhengyi Chen, Hao Wang, Keyu Chen, Changhao Song, Xiao Zhang, Boyu Wang, Jack C. P. Cheng
Summary: This study proposes an improved coverage path planning system that leverages building information modeling and robotic configurations to optimize coverage performance in indoor environments. Experimental validation shows the effectiveness and applicability of the system. Future research will focus on further enhancing coverage ratio and optimizing computation time.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Yonglin Fu, Junjie Chen, Weisheng Lu
Summary: This study presents a review of human-robot collaboration (HRC) in modular construction manufacturing (MCM), focusing on tasks, human roles, and interaction levels. The review found that HRC solutions are applicable to various MCM tasks, with a primary focus on timber component production. It also revealed the diverse collaborative roles humans can play and the varying levels of interaction with robots.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Qiong Liu, Shengbo Cheng, Chang Sun, Kailun Chen, Wengui Li, Vivian W. Y. Tam
Summary: This paper presents an approach to enhance the path-following capability of concrete printing by integrating steel cables into the printed mortar strips, and validates the feasibility and effectiveness of this approach through experiments.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Honghu Chu, Lu Deng, Huaqing Yuan, Lizhi Long, Jingjing Guo
Summary: The study proposes a method called Cascade CATransUNet for high-resolution crack image segmentation. This method combines the coordinate attention mechanism and self-cascaded design to accurately segment cracks. Through a customized feature extraction architecture and an optimized boundary loss function, the proposed method achieves impressive segmentation performance on HR images and demonstrates its practicality in UAV crack detection tasks.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Daniel Lamas, Andres Justo, Mario Soilan, Belen Riveiro
Summary: This paper introduces a new method for creating synthetic point clouds of truss bridges and demonstrates the effectiveness of a deep learning approach for semantic and instance segmentation of these point clouds. The proposed methodology has significant implications for the development of automated inspection and monitoring systems for truss bridges.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Kahyun Jeon, Ghang Lee, Seongmin Yang, Yonghan Kim, Seungah Suh
Summary: This study proposes two enhanced unsupervised text classification methods for domain-specific non-English text. The results of the tests show that these methods achieve excellent performance on Korean building defect complaints, outperforming state-of-the-art zero-shot and few-shot text classification methods, with minimal data preparation effort and computing resources.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Yoonhwa Jung, Julia Hockenmaier, Mani Golparvar-Fard
Summary: This study introduces a transformer-based natural language processing model, UNIfORMATBRIDGE, that automatically labels activities in a project schedule with Uniformat classification. Experimental results show that the model performs well in matching unstructured schedule data to Uniformat classifications. Additionally, the study highlights the importance of this method in developing new techniques.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
De-Graft Joe Opoku, Srinath Perera, Robert Osei-Kyei, Maria Rashidi, Keivan Bamdad, Tosin Famakinwa
Summary: This paper introduces a digital twin technology combining Building Information Modelling and the Internet of Things for the construction industry, aiming to optimize building conditions. The technology is implemented in a university library, successfully achieving real-time data capture and visual representation of internal conditions.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zaolin Pan, Yantao Yu
Summary: The construction industry faces safety and workforce shortages globally, and worker-robot collaboration is seen as a solution. However, robots face challenges in recognizing worker intentions in construction. This study tackles these challenges by proposing a fusion method and investigating the best granularity for recognizing worker intentions. The results show that the proposed method can recognize multi-granular worker intentions effectively, contributing to seamless worker-robot collaboration in construction.
AUTOMATION IN CONSTRUCTION
(2024)
