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Article
Engineering, Industrial
Guoqi Li et al.
Summary: This study develops a multidimensional quantitative risk assessment framework for evaluating the risk of hazardous materials (HazMat) vehicles in dense urban areas. Through a case study and the use of simulation and GIS technology, the spatial distribution of different risk levels is visualized.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Marine
Wenjun Zhang et al.
Summary: This study developed a dynamic Bayesian network (DBN) model for deepwater drilling and demonstrated its feasibility through a case study on managed pressure drilling (MPD). The model identified various risk influencing factors, constructed a network structure, and determined the probabilities of equipment failures, abnormal processes, and operator errors. By evaluating the probabilistic risk of drilling operations, the model provided early warnings for risk elimination or mitigation measures in real time.
Article
Energy & Fuels
Bingyuan Hong et al.
Summary: Failure and leakage of natural gas pipelines can lead to serious ecological losses and casualties. This paper proposes a dynamic risk probability analysis method based on Dynamic Bayesian network (DBN), which is validated by a third-party damage case under uncertainty.
Review
Construction & Building Technology
Honghong Song et al.
Summary: BIM plays a crucial role in bridge engineering for the design and construction stages, while Digital Twin technology has the potential to enhance the entire lifecycle of digital construction in the operation and maintenance phases. However, the current adoption of Digital Twin in bridge engineering lacks conceptual and technical clarity, hindering its full potential. This paper fills the gap by proposing a DT-enhanced BIM framework for bridge engineering, based on the analysis of 125,116 documents on BIM and DT. A performance hierarchy for bridge digital twin is established, contributing to the future development of BIM and DT and their integrated advanced technologies.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Construction & Building Technology
Yuan Xie et al.
Summary: Building Information Modeling (BIM) is recognized and promoted in the construction industry. This paper proposes a solution to automatically reconstruct the as-built BIM of piping systems in buildings from LiDAR scanned point cloud data. The solution includes a deep learning network called PipeNet for pipe detection and prediction, and line fitting, refinement, and graph-based connectivity analysis for pipe model reconstruction. The results demonstrate the robustness, fast speed, and high recognition rate and precision of the solution.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Construction & Building Technology
Zhen-Song Chen et al.
Summary: Building information modeling (BIM) maturity models are essential for guiding stakeholders and enterprises in identifying BIM capabilities and improving processes. However, there are limited quantitative BIM maturity models available for measuring and enhancing BIM utilization performance. This study presents a refined assessment system for measuring the maturity of BIM-based projects during design and construction stages. By combining probability distribution function aggregation and group decision-making, the proposed BIM maturity model offers an expert-based assessment system for evaluating project-based BIM performance. The case study of a glass substrate production workshop in Wuhan demonstrates the feasibility and effectiveness of this model.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Computer Science, Information Systems
Xinyue Shao et al.
Summary: With the increasing convergence of AI and daily life scenarios, the application scenarios for intelligent decision methods are becoming more complex. Challenges include selecting the most suitable algorithm among many options and addressing the lack of interpretability in current machine learning algorithms. The proposed EFFECT framework aims to provide an interpretable meta-learning solution for autonomous algorithm selection.
INFORMATION SCIENCES
(2023)
Article
Engineering, Chemical
Qingqing Xu et al.
Summary: This paper focuses on the dynamic risk assessment method for the underground gas storage process, which combines fault tree and Bayesian network to identify risk factors and introduces fuzzy numbers to determine the prior probability. Causal and diagnostic reasoning is performed to determine the failure level of the underground gas storage facilities, and sensitivity and impact analysis are used to identify significant risk factors and possible failure paths. The time factor is also considered in the dynamic assessment and analysis of underground gas storage facilities using a dynamic Bayesian network.
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
(2023)
Article
Engineering, Industrial
Yuntao Li et al.
Summary: During the road transportation of hazardous chemicals, both random and centralized parking strategies have severe consequences. This study proposes a novel zone parking strategy that separates vehicles based on their cargo, significantly reducing the risk associated with hazardous chemicals.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
P. Antao et al.
Summary: The paper evaluates the contribution of specific Risk Influencing Factors to ship collision accidents using a combination of Cox proportional hazard regression model, Bayesian rule, and least-squares method. Historical data of collision accidents worldwide and information of the world's merchant fleet are used for the assessment. Based on a global sample of 936 collision events from 2005 to 2017, six Risk Influencing Factors are assessed, including Ship length, Ship type, age of the ship, Classification Society, flag, and geographical area. The results indicate that ship type and geographical area have the greatest impact on ship collisions.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Construction & Building Technology
Chunyi Cui et al.
Summary: The development of subways is booming, but there is a lack of comprehensive automated seismic risk evaluation research for underground structures. This paper aims to develop a framework using Monte Carlo simulation and ontology theory to evaluate the seismic risk of subway stations based on economic losses, casualties, disaster relief costs, and post-earthquake recovery time. The study demonstrates the feasibility of the proposed framework and validates the semantic web rule language and the semantic query-enhanced web rule language.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2023)
Review
Construction & Building Technology
Lang Zheng et al.
Summary: Numerous studies have found that the climate of cities and human settlements have an impact on building performance and human comfort. Traditionally, ambient data was collected through on-site measurements or physical models, but now data-based techniques like Building Information Modeling (BIM) and Computational Fluid Dynamics (CFD) are more popular. This paper reviews publications in this field up until 2022, categorizing them into different sections based on the BIM-CFD integration process, building design optimization, and integration process optimization. The results show that BIM and CFD play an essential role in building design practice, although there is room for improvement in their dynamic data transfer and synchronization capabilities.
BUILDING AND ENVIRONMENT
(2023)
Article
Engineering, Mechanical
Bilal Ervural et al.
Summary: The Failure Mode and Effect Analysis (FMEA) is a widely used method for identifying and prioritizing potential risks in a system or process. This study introduces a data-driven approach to address the limitations of traditional FMEA methods, which often rely on subjective assessments and inadequate risk prioritization. The proposed approach utilizes data-driven risk factors to determine objective rankings of failure modes.
ENGINEERING FAILURE ANALYSIS
(2023)
Article
Computer Science, Artificial Intelligence
Fang-Le Peng et al.
Summary: The operational hazard management of utility tunnel infrastructure is crucial for sustainable and resilient urban development. Current practices relying on engineers’ experience are insufficient for ensuring management quality, thus increasing the risk of accidents. Therefore, a knowledge graph-based decision support approach is proposed to improve the hazard management capabilities of utility tunnels.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Industrial
Chenyushu Wang et al.
Summary: This study proposes a novel risk assessment method for deepwater equipment that incorporates preventive maintenance strategies and dynamic operating conditions. By establishing a dynamic Bayesian network structure, the failure model and dynamic fault probabilities of deepwater equipment are evaluated. The matter element theory is used to assess the failure consequences and characteristic values of different failure modes. The study on subsea blowout preventers demonstrates the efficacy of the proposed method in accurately and effectively performing dynamic risk assessment for deepwater equipment.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Gang Xue et al.
Summary: This paper proposes a probabilistic deep learning framework for risk path forecasting in urban rail transit. It constructs a large-scale risk path ground truth dataset and uses multi-source data and feature extraction methods to optimize parameters and improve forecasting performance. The experimental analysis results demonstrate that the proposed model outperforms baseline models in terms of F1 value, and integrating multi-source data can further improve forecasting performance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Construction & Building Technology
Qirui Wang et al.
Summary: A quantitative risk assessment model of HGV-involved tunnel fires is established using the FRAM and BN methods, helping to identify critical risk factors and assist in tunnel management and firefighting.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2023)
Article
Engineering, Chemical
Jingyu Zhu et al.
Summary: This study presents an integrated methodology that considers the interaction among drilling risk factors and assesses the blowout risk throughout the deepwater drilling operation's lifecycle, demonstrating its effectiveness in evaluating blowout risk.
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
(2022)
Article
Construction & Building Technology
Han Zhao et al.
Summary: A comprehensive risk assessment model was proposed and tested for urban underground spaces, highlighting the importance of management policies as the main factor influencing UUS risks in different economic circles. The study demonstrated variations in UUS risks among different regions in China, with the Greater Bay Area showing the highest risk level.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2022)
Article
Engineering, Civil
Yifan Guo et al.
Summary: This paper proposes a risk decision support approach for metro tunnel construction based on Continuous Time Bayesian Network (CTBN) technique, which can solve the uncertainty problem caused by insufficient utilization of information and provide multi-form decision support using multi-source information.
JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT
(2022)
Article
Engineering, Industrial
Lipeng Fu et al.
Summary: This study aims to develop a general modeling and analysis procedure for risk interactions and investigate the interactions among deep foundation pit project (DFPP) safety risks in the subway construction in China using association rule mining and the weighted network theory.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Multidisciplinary
Jing Li et al.
Summary: This study analyzes the historical monthly hidden danger quantity pattern in coal mines and constructs three prediction models. The results show that the Adam-BP model improves prediction accuracy, and the Month-Adam-BP model further enhances it.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2022)
Article
Engineering, Industrial
Federico Antonello et al.
Summary: This study proposes a novel framework that combines System-Theoretic Accident Model and Processes (STAMP), Modeling and Simulation (M&S), and Goal-Tree Success-Tree Master Logic Diagram (GTST-MLD) to qualitatively and quantitatively assess the risk of accidents in interconnected socio-technical systems. The effectiveness of this framework is demonstrated through its application in the safety assessment of Nuclear Batteries (NBs).
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Construction & Building Technology
Mingzhu Wang et al.
Summary: This study conducts a comprehensive review of research on digital technologies for underground infrastructure construction and O&M. It identifies the challenges, limitations, and potentials of digital technologies in this field, and proposes future research directions to facilitate digital transformation.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Construction & Building Technology
Xuewei Li et al.
Summary: This study proposed a semantic approach to automate safety checking through SPARQL-based reasoning, integrating safety risk factors from different data sources. The framework can improve knowledge sharing and promote real-time and automated safety checking.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Engineering, Industrial
Rui He et al.
Summary: This paper proposes a risk updating method based on dynamic Bayesian network, which incorporates real-time data monitoring into probabilistic risk assessment (PRA). The method updates the probabilistic risk for basic events by considering their prior probability and the probability of their online monitoring signals exceeding the alarm threshold.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Construction & Building Technology
Mingzhu Wang
Summary: This paper proposes an ontology-based framework for modeling lifecycle utility information to facilitate activities and support decision making during utility operation and maintenance.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Engineering, Chemical
Favour Ikwan et al.
Summary: This paper presents a quantitative analysis of relevant risks in storage tank leak through fault tree analysis and risk analysis methods, utilizing risk matrix to rank and make decisions on risks based on past data. An intelligent system and dynamic risk modeling are used to predict risk likelihood in near real-time, enhancing risk assessment and evaluation.
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
(2021)
Review
Construction & Building Technology
Song-Shun Lin et al.
Summary: This paper provides a brief review and bibliometric analysis of major accidents and risk assessment methods for excavation system in recent years. The study highlights the importance of summarizing potential risks during excavation for establishing an early warning system. It also presents the applications of fuzzy set theory and machine learning methods in risk assessment, along with a case study demonstrating the use of machine learning for risk evaluation in excavation. Moreover, the integration of 3S techniques and sensors into building information modelling platform shows promising perspectives for dynamic safety risk monitoring, control, and management.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Engineering, Marine
Liangbin Zhao et al.
Summary: The article proposes the 'margin of projected collision (MPC)' index, which combines dimension data from AIS and velocity obstacle approach to more accurately and objectively assess the risk of collision between ships. Real encounter cases demonstrate the high practical value of the proposed index, particularly in high-precision applications such as waters with heavy maritime traffic and maritime autonomous surface ships.
Article
Engineering, Industrial
Shuyi Xie et al.
Summary: This study focuses on the prevention and control of Fire and Explosion Accidents in Oil Depots (FEAOD) by building a Bow-tie (BT) model and proposing a novel risk quantitative assessment algorithm based on Cloud Model (CM) theory. Through a case study, it was found that the proposed method can more accurately identify the weak links in the safety system, providing a theoretical basis for risk prevention and control.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Construction & Building Technology
Hongyu Chen et al.
Summary: This research aims to develop a hybrid approach integrating system dynamics (SD) and Monte Carlo (MC) simulation to evaluate the long-term vulnerability of urban metro systems. By merging multiple resource information, an SD model with 4 sub-systems and 16 feedback loops is constructed to reveal complex relationships among factors and simulate overall vulnerability. The study utilizes MC simulation to analyze sensitive factors and improvement strategies of metro system vulnerability under uncertainty, with promising results for enhancing safety and security in metro operations.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Construction & Building Technology
Xianfei Yin et al.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2020)
Article
Construction & Building Technology
Min Hu et al.
AUTOMATION IN CONSTRUCTION
(2019)
