Nonlinear Fuzzy Evaluation of Construction Risks in Integral Hoisting of Steel Tube Concrete Tied Arch Bridges

Literature Overview

The paper by An Lang and Zhang Xinran, published in the Journal of Highway and Transportation Research in 2015, proposes a nonlinear fuzzy evaluation method for assessing construction risks associated with the integral hoisting of steel tube concrete tied arch bridges. The method addresses the limitations of traditional fuzzy evaluation approaches by incorporating nonlinear characteristics and structural entropy weighting. The research was supported by the Central Universities Basic Scientific Research Fund (Grant No. CHD2009JC166). The study focuses on the specific risk characteristics of integral hoisting operations, which involve the lifting and installation of large, pre-assembled bridge segments containing steel tube concrete members.

Risk Source Identification and Hierarchical Evaluation System

The paper begins with a systematic identification of risk sources based on the construction sequence of integral hoisting operations. The risk sources are organized into a hierarchical evaluation system that considers both structural safety and personnel safety. This dual consideration is important because construction risks in large-scale bridge hoisting operations can manifest as structural failures, equipment malfunctions, personnel injuries, or environmental hazards.

Risk Category	Risk Source	Potential Consequence	Severity Level
Structural safety	Hoisting load imbalance	Segment damage or collapse	Critical
Structural safety	Steel tube concrete member defect	Loss of structural capacity	Critical
Structural safety	Connection failure at joints	Progressive structural failure	Critical
Personnel safety	Crane operator error	Equipment collision or drop	High
Personnel safety	Wind load during hoisting	Uncontrolled swing of segment	High
Personnel safety	Ground crew positioning	Crush injury or fall from height	Medium
Equipment safety	Hoisting wire rope fatigue	Wire rope breakage	Critical
Environmental	Adverse weather conditions	Reduced visibility or wind gusts	Medium

The hierarchical evaluation system consists of two levels: the first level categorizes risks into broad groups such as structural safety, personnel safety, and equipment safety, while the second level identifies specific risk sources within each category. This structure allows for a systematic and comprehensive risk assessment that can be applied to different integral hoisting projects with appropriate adjustments.

Nonlinear Fuzzy Evaluation Methodology

The core innovation of the paper is the introduction of a nonlinear fuzzy evaluation algorithm that better reflects the disproportionate impact of high-risk indicators on the overall evaluation result. Traditional fuzzy evaluation methods use linear aggregation, which may underrepresent the significance of critical risk factors. The nonlinear approach applies a nonlinear transformation to the membership degrees of each risk indicator, amplifying the influence of high-risk indicators and attenuating the influence of low-risk indicators.

The structural entropy weighting method is employed to determine the weights of the risk indicators. This method combines subjective weighting (based on expert judgment) with objective weighting (based on the information entropy of the indicator data). The structural entropy approach calculates the entropy of each indicator's membership distribution and assigns weights inversely proportional to the entropy, thereby giving higher weights to indicators with more concentrated (i.e., more decisive) information.

Method Component	Traditional Approach	Proposed Approach	Advantage
Weight determination	Subjective (AHP) or objective (entropy) alone	Structural entropy (combined)	Balances expert knowledge with data-driven objectivity
Fuzzy aggregation	Linear (weighted sum)	Nonlinear transformation	Better reflects critical risk dominance
Risk level classification	Fixed thresholds	Adaptive thresholds based on nonlinear aggregation	More sensitive to extreme risk conditions
Indicator treatment	Equal treatment of all indicators	Differential treatment based on risk severity	More realistic risk representation

Engineering Case Study and Method Validation

The paper validates the proposed method through an engineering case study involving the integral hoisting of a steel tube concrete tied arch bridge. The case study demonstrates the feasibility and effectiveness of the nonlinear fuzzy evaluation method by comparing the evaluation results with the actual construction risk events that occurred during the project. The results show that the method successfully identified the critical risk factors and provided actionable recommendations for risk mitigation.

Study Insights and Implications

The nonlinear fuzzy evaluation method proposed in this paper offers a more realistic and sensitive approach to construction risk assessment for integral hoisting operations. The incorporation of nonlinear aggregation addresses a well-known limitation of traditional fuzzy evaluation methods, where the influence of critical risk factors may be diluted by the averaging effect of linear aggregation. For engineers involved in large-scale bridge construction, this method provides a structured framework for identifying, quantifying, and prioritizing construction risks. The structural entropy weighting approach is particularly valuable because it leverages both expert knowledge and empirical data, reducing the subjectivity inherent in purely qualitative risk assessment methods.