Article
Engineering, Civil
Ji-Gang Xu, De-Cheng Feng, Sujith Mangalathu, Jong-Su Jeon
Summary: This paper proposes an approach for regional seismic performance assessment of reinforced concrete bridges using machine-learning techniques. The results show that the extreme gradient boosting (XGBoost) model has the best performance, accurately predicting the damage states of the bridges.
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
(2022)
Article
Engineering, Civil
Yong Huang, Jing He, Zhihui Zhu
Summary: This study uses machine learning and empirical vulnerability curves to predict earthquake damage and assess risk for railway bridges, creating a rapid risk assessment procedure. By collecting and tallying seismic damage data from 335 damaged railway bridges in the Tangshan and Menyuan earthquakes, six variables were identified that had a significant impact on seismic risk outcomes, and the damage levels were categorized into five categories. Four algorithms were tested, with Random Forest (RF) being the most effective method. The study describes in detail the rapid assessment procedure for 269 randomly selected bridges, including predicting the seismic damage rating using RF and drawing the empirical vulnerability curve using a two-parameter normal distribution function. The findings of this study can guide the selection of machine learning approaches and inputs to build a rapid assessment model for railway bridges.
INTERNATIONAL JOURNAL OF STRUCTURAL STABILITY AND DYNAMICS
(2023)
Article
Engineering, Civil
Mojtaba Salkhordeh, Masoud Mirtaheri, Najib Rabiee, Ehsan Govahi, Siavash Soroushian
Summary: Recent earthquakes have highlighted the importance of assessing damage to highway bridges quickly to minimize social and economic losses. This study presents a rapid Machine Learning-based framework for detecting damage to primary and secondary components of reinforced concrete bridges under earthquake motions. The proposed algorithm uses a dataset of scaled acceleration records and applies damage indicators extracted from these records as input attributes. The results show that Support Vector Machines (SVMs) are the most accurate learners for determining the level of damage in the bridge's components.
JOURNAL OF EARTHQUAKE ENGINEERING
(2023)
Article
Engineering, Civil
Hoang D. Nguyen, James M. LaFave, Young-Joo Lee, Myoungsu Shin
Summary: This study aims to develop machine learning models for the rapid seismic damage-state assessment of steel moment frames. After training and testing with a large dataset, the RF model is suggested as the most accurate for prediction, while AdaBoost and naive Bayes models performed relatively poorly. The importance of input variables on the prediction was inspected using the SHAP method.
ENGINEERING STRUCTURES
(2022)
Article
Computer Science, Artificial Intelligence
M. Abedi, M. Z. Naser
Summary: The study introduces a rapid, automated, and intelligent approach that leverages machine learning to identify vulnerable bridges to fire hazard, backed by a comprehensive database comprising actual observations. This method can assist engineers and government officials in swiftly assessing fire-vulnerable bridges with a high accuracy of 89.6%.
APPLIED SOFT COMPUTING
(2021)
Article
Construction & Building Technology
Haoyou Zhang, Xiaowei Cheng, Yi Li, Dianjin He, Xiuli Du
Summary: Three machine learning algorithms were used to develop models for rapidly assessing the seismic damage states of reinforced concrete (RC) frames. The results indicated that one of the algorithms achieved an accuracy of 84% in the testing dataset.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Construction & Building Technology
Andelko Vlasic, Mladen Srbic, Dominik Skokandic, Ana Mandic Ivankovic
Summary: This paper presents the results of the rapid post-earthquake assessment for eight bridges in and around the city of Glina in northwestern Croatia. Although most of the bridges were found to be deteriorated due to age and lack of maintenance, only one bridge required immediate strengthening measures and use restrictions.
Article
Engineering, Civil
Xuguang Wang, Cristoforo Demartino, Yasutaka Narazaki, Giorgio Monti, Billie F. Spencer Jr
Summary: This paper proposes a framework for rapid seismic risk assessment of bridges using aerial photogrammetric surveys conducted by Unmanned Aerial Vehicles (UAVs). The data acquisition process for the photogrammetric 3D reconstruction of an asset and the subsequent procedure for computer-vision-based automatic extraction of visible geometric features are presented. The framework combines extracted features in the structural models to perform a seismic risk assessment in terms of capacity-to-demand ratios.
ENGINEERING STRUCTURES
(2023)
Review
Engineering, Civil
Eloi Figueiredo, Luis Oliveira Santos, Ionut Moldovan, Dimitrios Kraniotis, Jose Melo, Luis Dias, Guilherme B. A. Coelho
Summary: Bridges are essential in modern societies and climate change poses a significant threat to their health. The adaptation of bridges to climate change requires an integrated assessment approach rooted in multiple disciplines. This paper aims to review existing research and provide a roadmap for such an approach, prioritizing measures based on location, climate scenario, impact, vulnerability, risk, and cost. Structural health monitoring technology is proposed for assessing the condition of bridges and triggering adaptation measures as needed.
JOURNAL OF BRIDGE ENGINEERING
(2023)
Article
Engineering, Civil
Mustesin Ali Khan, Aatif Ali Khan, Ghazanfar Ali Anwar, Asif Usmani
Summary: Bridge fires are a major concern due to their social and economic consequences when bridges are closed to traffic. This paper presents a framework for evaluating fire risk to bridges by considering criteria such as social and economic impact, vulnerability of bridge structures to fire, and likelihood of a bridge fire. The proposed framework utilizes the Analytical Hierarchy Process (AHP) to estimate weightings for different factors and provides an important methodology for estimating fire risk and calculating fire protection requirements for bridge structures.
Article
Biochemistry & Molecular Biology
Salvatore Greco, Alessandro Salatiello, Nicolo Fabbri, Fabrizio Riguzzi, Emanuele Locorotondo, Riccardo Spaggiari, Alfredo De Giorgi, Angelina Passaro
Summary: We introduce two new classification methods that can accurately predict the mortality risk of COVID-19 patients using routine clinical variables. These methods leverage machine learning and clinical expertise and were validated using two independent cohorts of patients from different waves of the pandemic.
Article
Engineering, Civil
Sanjeev Bhatta, Ji Dang
Summary: This study examines the damage assessment of buildings after an earthquake using machine learning techniques, exploring the applicability of different methods by considering both structural properties and ground motion characteristics. The results show that classifying the damage into three categories performs better than classifying it into five categories. This research contributes to planning and decision-making for emergency response and recovery following an earthquake.
JOURNAL OF EARTHQUAKE ENGINEERING
(2023)
Article
Engineering, Civil
Zoran Stojadinovic, Milos Kovacevic, Dejan Marinkovic, Bozidar Stojadinovic
Summary: This article proposes a new framework for rapid earthquake loss assessment using machine learning and representative sampling algorithm. The framework predicts damage probability distribution and calculates repair costs to assess direct losses in the earthquake-affected area. By selecting representative buildings using a sampling algorithm, capturing the seismic risk independently of future earthquakes, and utilizing trained damage assessors, the framework improves the accuracy of loss assessment.
EARTHQUAKE SPECTRA
(2022)
Article
Chemistry, Analytical
Eloi Figueiredo, Ionut Moldovan, Pedro Alves, Hugo Rebelo, Laura Souza
Summary: This paper presents a smartphone application called App4SHM, which uses the phone's internal accelerometer to measure accelerations and employs a machine learning algorithm to detect structural damage. It shows reliable precision and accurate damage detection, making it a low-cost solution for long-term SHM and post-disaster assessment.
Article
Environmental Sciences
Jin Chen, Hong Tang, Jiayi Ge, Yaozhong Pan
Summary: This study proposes a novel method to rapidly assess building damage by utilizing earth observation-derived data and field investigation. The effectiveness of the proposed method is validated using building damage data interpreted from satellite images. The results show that the method accurately assesses building damage at different spatial levels and provides information on affected positions and regional damage rates.
Article
Engineering, Civil
Chang Seok Lee, Jong-Su Jeon
Summary: This study introduces a simple hysteretic model to replicate the stress-strain relationship of superelastic NiTi shape memory alloys, which includes the functional degradation effect. The proposed model shows computational efficiency and accurately captures the characteristics of functional degradation observed in experimental results.
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
(2022)
Article
Engineering, Civil
Sujith Mangalathu, Karthika Karthikeyan, De-Cheng Feng, Jong-Su Jeon
Summary: This study utilizes interpretable machine-learning approaches to analyze the complex relationship between expected damage and input parameters in earthquake engineering. Evaluation of machine-learning models helps identify their effectiveness in different levels of applications and key influential variables.
ENGINEERING STRUCTURES
(2022)
Article
Engineering, Civil
Chang Seok Lee, Eunsoo Choi, Jong-Su Jeon
Summary: This study derives an analytical expression for the plastic hinge length of rectangular concrete columns reinforced with nickel-titanium shape memory alloy (SMA) bars and explores the effect of various parameters. The proposed plastic hinge expression reduces SMA usage by half while maintaining similar nonlinear response.
ENGINEERING STRUCTURES
(2022)
Article
Engineering, Civil
Chang Seok Lee, Jong-Su Jeon
Summary: This paper presents a probabilistic model for estimating the nonlinear response and demolition probability of reinforced concrete structures. The proposed model better represents the central tendency of observed residual deformations compared to deterministic models.
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
(2022)
Article
Engineering, Civil
Seong-Hoon Hwang, Sujith Mangalathu, Jinwon Shin, Jong-Su Jeon
Summary: This study analyzes the impact of modeling-related uncertainties on the expected annual losses of modern code-compliant steel moment-frame buildings. Probabilistic structural models are used to account for uncertainties and develop machine-learning-based prediction models that show excellent performance in estimating economic seismic losses. The effect of uncertain modeling parameters is observed to be more pronounced on loss contributors controlled by low probability ground motions.
ENGINEERING STRUCTURES
(2022)
Article
Construction & Building Technology
Bilal Ahmed, Sujith Mangalathu, Jong-Su Jeon
Summary: The study introduces a novel stacked long short-term memory (LSTM) network for early and accurate damage evaluation after earthquakes, reducing training time and enhancing prediction accuracy by overlapping data and generating new features.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Engineering, Civil
Ji-Gang Xu, De-Cheng Feng, Sujith Mangalathu, Jong-Su Jeon
Summary: This paper proposes an approach for regional seismic performance assessment of reinforced concrete bridges using machine-learning techniques. The results show that the extreme gradient boosting (XGBoost) model has the best performance, accurately predicting the damage states of the bridges.
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
(2022)
Article
Engineering, Civil
Bilal Ahmed, Sujith Mangalathu, Jong-Su Jeon
Summary: In order to organize accurate and effective emergency responses after an earthquake, an early and precise assessment of damage to structures is vital. The use of fragility/vulnerability curves is an advanced approach for structural damage assessments. However, the analysis based on these curves can vary significantly depending on soil conditions, ground motion, and structural characteristics. To address this issue, a stacked long short-term memory network is proposed in this research.
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
(2023)
Article
Engineering, Civil
Nadia Saleem, Sujith Mangalathu, Bilal Ahmed, Jong-Su Jeon
Summary: This study presents a novel approach that integrates a geographic information system with a spatial data analysis-based machine learning PGA prediction model, achieving accurate results in predicting peak ground motion parameters and assessing seismic vulnerability of bridges.
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
(2023)
Article
Engineering, Civil
Mengdie Chen, Sujith Mangalathu, Jong-Su Jeon
Summary: This paper proposes a methodology based on origin-destination pair betweenness centrality to rank bridges in a complex network according to their importance. The methodology considers user equilibrium and topology, and significantly reduces computational time. The study also suggests two strategies, retrofitting bridges and constructing new ones, to mitigate the seismic risk of bridge networks.
ENGINEERING STRUCTURES
(2023)
Article
Engineering, Civil
Chang Seok Lee, Jong-Su Jeon
Summary: This paper proposes a risk-based seismic design method using shape memory alloy wires to enhance the performance of older concrete bridge classes. It adopts an existing SMA-SCB system to examine further applications to nonductile bridges. A sophisticated finite element model, probabilistic bridge models, and the total probability theorem are employed to develop the risk-based seismic design of the SMA-SCB.
ENGINEERING STRUCTURES
(2023)
Article
Materials Science, Multidisciplinary
Bilal Ahmed, Taehyo Park, Jong-Su Jeon
Summary: This study utilizes machine learning techniques to predict the maximum vertical displacement of reinforced concrete slabs subjected to air-blast loading. Different convolutional neural networks were trained using images transformed from tabular data, and most models demonstrated promising results.
INTERNATIONAL JOURNAL OF DAMAGE MECHANICS
(2023)
Article
Instruments & Instrumentation
Eunsoo Choi, Jong-Su Jeon, Jong-Han Lee
Summary: This study investigates the self-centering capacity of RC columns with martensitic SMA bars in the plastic hinge region through experiments. The results show that the RC column with SMA bars exhibits a plastic hinge around the couplers, demonstrating excellent self-centering capacity, but lower energy-dissipation capacity compared to conventional RC columns.
SMART MATERIALS AND STRUCTURES
(2023)
Article
Engineering, Civil
Chang Seok Lee, Jong-Su Jeon
Summary: This study introduces the seismic risk-based design of SMA devices for steel moment-resisting frame buildings. The traditional design method was found to have inconsistencies in response compared to actual test results. To address this issue, a seismic risk-based design approach was employed, using nonlinear time history analysis and optimization algorithm to determine the quantity of SMA devices, resulting in cost reduction and a significant decrease in the probability of collapse and demolition.
ENGINEERING STRUCTURES
(2023)
Article
Construction & Building Technology
Sergei Shturmin, Chang Seok Lee, Jong-Su Jeon
Summary: A simplified modeling approach based on nonlinear spring model is proposed to simulate the seismic behavior of concrete-filled steel tube columns. The approach was calibrated and validated using experimental data, and it showed better accuracy and reduced computational time compared to the existing fiber-based beam-column model.
JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH
(2023)
Article
Engineering, Civil
Renbing An, Jiacong Yuan, Yi Pan, Duhang Yi
Summary: Traditional timber structures built on sloped land are more susceptible to seismic damage compared to structures built on flat land. The upper portion of the structure is found to be the weak point on sloped land, with potential issues such as tenon failure and column foot sliding.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Elyas Bayat, Federica Tubino
Summary: The current design guidelines for assessing floor vibration performance do not consider the influence of variability in the walking path on the dynamic response of floors. This study investigates the dynamic response of floors under a single pedestrian walking load, taking into account the randomness of the walking path and load. The effectiveness of the current guidelines in predicting floor response is critically assessed.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Gao Ma, Chunxu Hou, Hyeon-Jong Hwang, Linghui Chen, Zhenhao Zhang
Summary: Minimizing earthquake damage and improving repair efficiency are the main principles of resilient structures. This study proposed a repairable column with UHPC segments and replaceable energy dissipaters. The test results showed that the columns with UHPC segments and replaceable dissipaters exhibited high strength, deformation capacity, and energy dissipation.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Kartheek S. M. Sonti, Pavan Kumar Penumakala, Suresh Kumar Reddy Narala, S. Vincent
Summary: In this study, the compressive behavior of alumina hollow particles reinforced aluminum matrix syntactic foams (AMSF) was investigated using analytical, numerical, and experimental methods. The results showed that the FE solver ABAQUS could accurately predict the elastic and elastio-plastic behavior of AMSFs. The study also suggested that FE models have great potential in developing new materials and composites under compression loading.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Zheqi Peng, Xin Wang, Zhishen Wu
Summary: In this study, the statistical modeling of fiber-reinforced polymer (FRP) cables using the classic fiber bundle model is explored. The study considers important features of large-scale multi-tendon FRP cables, such as initial random slack and uneven tensile deformation among tendons. A parametric study and reliability analysis are conducted to predict the load-displacement relation and design thousand-meter-scale FRP cables. The study emphasizes the relation between the reliability index beta of the cable and the safety factor gamma of the FRP material.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Yanchao Shi, Shaozeng Liu, Ye Hu, Zhong-Xian Li, Yang Ding
Summary: This paper introduces a damage assessment method for reinforced concrete (RC) columns under blast loading, using modal parameter measurement as the evaluation index. The validity of the proposed method is validated through numerical and experimental analysis. The results show that this modal-based damage assessment method is applicable for non-destructive evaluation of blast-induced damage of RC columns.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Xiaolin Zou, Maosheng Gong, Zhanxuan Zuo, Qifang Liu
Summary: This paper proposes an efficient framework for assessing the collapse capacity of structures in earthquake engineering. The framework is based on an accurate equivalent single-degree-of-freedom (ESDOF) system, calibrated by a meta-heuristic optimization method. The proposed framework has been validated through case studies, confirming its accuracy and efficiency.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Jie Hu, Weiping Wen, Chenyu Zhang, Changhai Zhai, Shunshun Pei, Zhenghui Wang
Summary: A deep learning-based rapid peak seismic response prediction model is proposed for the most common two-story and three-span subway stations. The model predicts the peak seismic responses of subway stations using a data-driven approach and limited information, achieving good predictive performance and generalization ability, and demonstrating significantly higher computational efficiency compared to numerical simulation methods.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Jin Ho Lee, Jeong-Rae Cho
Summary: A simplified model is proposed to estimate the earthquake responses of a rectangular liquid storage tank considering the fluid-structure interactions. The complex three-dimensional structural behavior of the tank is represented by a combination of fundamental modes of a rectangular-ring-shaped frame structure and a cantilever beam. The system's governing equation is derived, and earthquake responses such as deflection, hydrodynamic pressure, base shear, and overturning moment are obtained from the solution.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
W. J. Lewis, J. M. Russell, T. Q. Li
Summary: The work discusses the key features and advantages of optimal 2-pin arches shaped by statistically prevalent load and constant axial stress. It extends the design space of symmetric arches to cover asymmetric forms and provides minimum values of constant stress for form-finding of such arches made of different materials. The analysis shows that constant stress arches exhibit minimal stress response and have potential implications for sustainability and durability of future infrastructure.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Wen-ming Zhang, Han-xu Zou, Jia-qi Chang, Tian-cheng Liu
Summary: Saddle position is crucial in the construction and control of suspension bridges. This study proposes an analytical approach to estimate the saddle positions in the completed bridge state and discusses the calculation under different definitions. The relationship between the saddle position and the tower's centerline is analyzed, along with the eccentric compression of the tower. The feasibility of the proposed method is verified through a real-life suspension bridge.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Shaise K. John, Alessio Cascardi, Yashida Nadir
Summary: This study experimentally investigated the use of TRM material for reinforcing concrete columns. The results showed that increasing the number of textile layers effectively increased the axial strength. Additionally, the choice of fiber type and hybrid textile configuration also had a significant impact on strength improvement. A new design model that considers the effects of both the confining matrix and textile was proposed.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Chandrashekhar Lakavath, S. Suriya Prakash
Summary: This study experimentally investigated the shear behavior of post-tensioned UHPFRC girders, considering factors such as prestress level, fiber volume fraction, and types of steel fibers. The results showed that increasing prestress and fiber dosage could enhance the ultimate load-carrying capacity of the girders, reduce crack angle, and increase shear cracking load.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Vahid Goodarzimehr, Siamak Talatahari, Saeed Shojaee, Amir H. Gandomi
Summary: In this paper, an Improved Marine Predators Algorithm (IMPA) is proposed for size and shape optimization of truss structures subject to natural frequency constraints. The results indicate that IMPA performs better in solving these nonlinear structural optimization problems compared to other state-of-the-art algorithms.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Chun-Xu Qu, Jin-Zhao Jiang, Ting-Hua Yi, Hong-Nan Li
Summary: In this paper, a computer vision-based method is proposed to monitor the deformation and displacement of building structures by obtaining 3D coordinates of surface feature points. The method can acquire a large number of 3D coordinates in a noncontact form, improve the flexibility and density of measurement point layout, and is simple and cost-effective to operate.
ENGINEERING STRUCTURES
(2024)