Xianguo Wu

Bayesian-network-based safety risk analysis in construction projects

This paper presents a systemic decision support approach for safety risk analysis under uncertainty in tunnel construction. Fuzzy Bayesian Networks (FBN) is used to investigate causal relationships between tunnel-induced damage and its influential variables based upon the risk/hazard mechanism analysis. Aiming to overcome limitations on the current probability estimation, an expert confidence indicator is proposed to ensure the reliability of the surveyed data for fuzzy probability assessment of basic risk factors. A detailed fuzzy-based inference procedure is developed, which has a capacity of implementing deductive reasoning, sensitivity analysis and abductive reasoning. The “3Iƒ criterion†is adopted to calculate the characteristic values of a triangular fuzzy number in the probability fuzzification process, and the I±-weighted valuation method is adopted for defuzzification. The construction safety analysis progress is extended to the entire life cycle of risk-prone events, including the pre-accident, during-construction continuous and post-accident control. A typical hazard concerning the tunnel leakage in the construction of Wuhan Yangtze Metro Tunnel in China is presented as a case study, in order to verify the applicability of the proposed approach. The results demonstrate the feasibility of the proposed approach and its application potential. A comparison of advantages and disadvantages between FBN and fuzzy fault tree analysis (FFTA) as risk analysis tools is also conducted. The proposed approach can be used to provide guidelines for safety analysis and management in construction projects, and thus increase the likelihood of a successful project in a complex environment.

Decision support analysis for safety control in complex project environments based on Bayesian Networks

This paper presents a novel and systemic decision support model based on Bayesian Networks (BN) for safety control in dynamic complex project environments, which should go through the following three sections. At first, priori expert knowledge is integrated with training data in model design, aiming to improve the adaptability and practicability of model outcome. Then two indicators, Model Bias and Model Accuracy, are proposed to assess the effectiveness of BN in model validation, ensuring the model predictions are not significantly different from the actual observations. Finally we extend the safety control process to the entire life cycle of risk-prone events in model application, rather than restricted to pre-accident control, but during-construction continuous and post-accident control are included. Adapting its reasoning features, including forward reasoning, importance analysis and background reasoning, decision makers are provided with systematic and effective support for safety control in the overall work process. A frequent safety problem, ground settlement during Wuhan Changjiang Metro Shield Tunnel Construction (WCMSTC), is taken as a case study. Results demonstrate the feasibility of BN model, as well as its application potential. The proposed model can be used by practitioners in the industry as a decision support tool to increase the likelihood of a successful project in complex environments.

Prospective safety performance evaluation on construction sites

This paper presents a systematic Structural Equation Modeling (SEM) based approach for Prospective Safety Performance Evaluation (PSPE) on construction sites, with causal relationships and interactions between enablers and the goals of PSPE taken into account. According to a sample of 450 valid questionnaire surveys from 30 Chinese construction enterprises, a SEM model with 26 items included for PSPE in the context of Chinese construction industry is established and then verified through the goodness-of-fit test. Three typical types of construction enterprises, namely the state-owned enterprise, private enterprise and Sino-foreign joint venture, are selected as samples to measure the level of safety performance given the enterprise scale, ownership and business strategy are different. Results provide a full understanding of safety performance practice in the construction industry, and indicate that the level of overall safety performance situation on working sites is rated at least a level of III (Fair) or above. This phenomenon can be explained that the construction industry has gradually matured with the norms, and construction enterprises should improve the level of safety performance as not to be eliminated from the government-led construction industry. The differences existing in the safety performance practice regarding different construction enterprise categories are compared and analyzed according to evaluation results. This research provides insights into cause-effect relationships among safety performance factors and goals, which, in turn, can facilitate the improvement of high safety performance in the construction industry.

A dynamic Bayesian network based approach to safety decision support in tunnel construction

This paper presents a systemic decision approach with step-by-step procedures based on dynamic Bayesian network (DBN), aiming to provide guidelines for dynamic safety analysis of the tunnel-induced road surface damage over time. The proposed DBN-based approach can accurately illustrate the dynamic and updated feature of geological, design and mechanical variables as the construction progress evolves, in order to overcome deficiencies of traditional fault analysis methods. Adopting the predictive, sensitivity and diagnostic analysis techniques in the DBN inference, this approach is able to perform feed-forward, concurrent and back-forward control respectively on a quantitative basis, and provide real-time support before and after an accident. A case study in relating to dynamic safety analysis in the construction of Wuhan Yangtze Metro Tunnel in China is used to verify the feasibility of the proposed approach, as well as its application potential. The relationships between the DBN-based and BN-based approaches are further discussed according to analysis results. The proposed approach can be used as a decision tool to provide support for safety analysis in tunnel construction, and thus increase the likelihood of a successful project in a dynamic project environment.

Developing a cloud model based risk assessment methodology for tunnel-induced damage to existing pipelines

This paper presents a cloud model (CM) based approach with step-by-step procedures for risk assessment of existing pipelines in tunneling environments (RAEPTE), where CM provides a basis for uncertainty transforming between qualitative concepts and their quantitative expressions. An evaluation index system of multiple layers and attributes is established for RAEPTE based upon the tunnel-induced pipeline failure mechanism analysis. The evaluation result is assessed by the correlation with CMs of each risk level. A confidence indicator is proposed to illustrate the reliability of evaluating results. Risk analysis for ten underground buried pipelines adjacent to the construction of Wuhan Metro Line Two in China is shown in a case study. Comparisons between different evaluation methods are further discussed according to results. The proposed approach is verified to be a more competitive solution, where the uncertainties of fuzziness and randomness are incorporated in the risk assessment system. This approach can serve as a decision tool for the safety risk assessment in other similar projects, and to increase the likelihood of a successful project in an uncertain environment.

Feedforward Analysis for Shield-Ground System

AbstractGround surface settlement is an important measurement in identifying potential damages for shield tunneling. Identifying the relationship between shield parameters and the resulting settlement is of vital importance to the reasonable adjustment of the shield parameters so as to control settlement development. However, many other factors, besides the shield parameters, affect settlement, which makes shield-ground interaction complicated. Therefore, a better method is necessary for extracting the shield-ground relationship for the purpose of steering shield tunneling. This paper proposes a method that incorporates smooth relevance vector machine (sRVM) and particle swarm optimization (PSO) for shield steering with concern for settlement control. First, smooth relevance vector machine with adaptive Gaussian kernel function is used to establish the relationship between the identified factors and the settlement. Particle swarm optimization is then applied to identify the appropriate kernel parameters. ...

Bim-Based Risk Identification System in tunnel construction

AbstractThis paper presents an innovative approach of integrating Building Information Modeling (BIM) and expert systems to address deficiencies in traditional safety risk identification process in tunnel construction. A BIM-based Risk Identification Expert System (B-RIES) composed of three main built-in subsystems: BIM extraction, knowledge base management, and risk identification subsystems, is proposed. The engineering parameter information related to risk factors is first extracted from BIM of a specific project where the Industry Foundation Classes (IFC) standard plays a bridge role between the BIM data and tunnel construction safety risks. An integrated knowledge base, consisting of fact base, rule base and case base, is then established to systematize the fragmented explicit and tacit knowledge. Finally, a hybrid inference approach, with case-based reasoning and rule-based reasoning combined, is developed to improve the flexibility and comprehensiveness of the system reasoning capacity. B-RIES is u...

Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel-Induced Pipeline Damage

Tunneling excavation is bound to produce significant disturbances to surrounding environments, and the tunnel-induced damage to adjacent underground buried pipelines is of considerable importance for geotechnical practice. A fuzzy Bayesian networks (FBNs) based approach for safety risk analysis is developed in this article with detailed step-by-step procedures, consisting of risk mechanism analysis, the FBN model establishment, fuzzification, FBN-based inference, defuzzification, and decision making. In accordance with the failure mechanism analysis, a tunnel-induced pipeline damage model is proposed to reveal the cause-effect relationships between the pipeline damage and its influential variables. In terms of the fuzzification process, an expert confidence indicator is proposed to reveal the reliability of the data when determining the fuzzy probability of occurrence of basic events, with both the judgment ability level and the subjectivity reliability level taken into account. By means of the fuzzy Bayesian inference, the approach proposed in this article is capable of calculating the probability distribution of potential safety risks and identifying the most likely potential causes of accidents under both prior knowledge and given evidence circumstances. A case concerning the safety analysis of underground buried pipelines adjacent to the construction of the Wuhan Yangtze River Tunnel is presented. The results demonstrate the feasibility of the proposed FBN approach and its application potential. The proposed approach can be used as a decision tool to provide support for safety assurance and management in tunnel construction, and thus increase the likelihood of a successful project in a complex project environment.

Perceiving Interactions on Construction Safety Behaviors: Workers’ Perspective

AbstractThis paper presents a systematic approach that incorporates structural equation modeling (SEM) and exploratory factor analysis (EFA) to perceive and verify causal-relationships and interactions between enablers and goals of construction workers’ safety behaviors (CWSB). A sample of 450 questionnaire surveys regarding CWSB was collected from construction workers in several Chinese construction companies. EFA was used to extract eight common factors in order to identify the model structure among 28 questionnaire items. Then, SEM was employed to investigate the interrelationships among variables in the hypothesized safety behavior model. The built causal model was verified in terms of the hypothesis test and goodness-of-fit test. The impact of the path coefficient on CWSB was investigated and analyzed in detail. Results indicate that management-oriented supervision and system (F3) and leadership (F8) exert obvious positive impacts on CWSB in accordance with the path coefficients analysis, whereas psy...

An improved Dempster–Shafer approach to construction safety risk perception

Abstract This paper proposes a novel hybrid approach that merges fuzzy matter element (FME), Monte Carlo (MC) simulation technique, and Dempster–Shafer (D–S) evidence theory to perceive the risk magnitude of tunnel-induced building damage at an early construction stage. The membership measurement in FME is used to construct basic probability assignments (BPAs) of influential factors within different risk states. An improved evidence fusion rule that integrates the Dempster’ rule and the weighted average rule is developed to synthesize multi-source conflicting evidence. A new defuzzification method, Centre of Distribution (COD), is proposed to achieve a crisp value that represents the final safety risk perception result. A confidence indicator, δ , is put forward to measure the reliability of the safety risk perception result. A comprehensive information fusion framework that incorporates 14 influential factors is proposed to perceive the risk magnitude of tunnel-induced building damage. Six existing buildings adjacent to the excavation of Wuhan Yangtze Metro Tunnel (WYMT), China, are utilized as a case study to verify the effectiveness and applicability of the proposed approach. Results indicate that the proposed approach is capable of (i) achieving a more accurate result for safety risk perception, and (ii) identifying global sensitivities of input factors throughout a series of MC simulation enabled iterations. A discussion on how to define a reasonable membership function for configuration of BPAs is further presented. The authors recommend that the constant coefficient λ that affects the shape of the defined correlation function in BPA (Basic Probability Assignment) constructs should have a value of three, and the risk perception result can thus reach up to the highest reliability level. This approach can enable a comprehensive preliminary safety risk perception during tunnel design phases, which can further substantially reduce the risk of building damage induced by tunneling excavation.