Safety assessment of excavation system via TOPSIS-based MCDM modelling in fuzzy environment
journal contribution
posted on 2024-11-03, 09:21authored bySong-Shun Lin, Annan ZhouAnnan Zhou, Shui-Long Shen
Excavation construction is a high-risk activity, where involves various aspects. Accurate recognition of high-risk factors and implementation of countermeasures can greatly reduce probability occurrence of accidents. Thus, identification for high-risk factors of excavation system is performed through MCDM modelling, which is implemented via technique for order preference by similarity to an ideal solution (TOPSIS). Expert coefficient was developed and applied in relative significant evaluation of experts. In according with engineering practice, risk factors were summarized from geotechnical conditions, surrounding environment, construction measurement, construction and management, which subsequently were applied to build the decision hierarchy. Latest Spherical fuzzy set were utilized to display the judgments of experts on evaluated objects. Apart from that, fuzziness and uncertainties in measured data for risk factors were tackled with triangular fuzzy set. In this regard, expert's judgments and measured data were both considered in comprehensive weight's determination on risk factors. The high-risk factors were determined via TOPSIS method. An engineering project about excavation construction was provided to illustrate the potentials of TOPSIS-based MCDM modelling. Risk analysis results indicated that static load, settlement of pipelines, and dynamic load were top three high-risk factors, which were consistent with engineering practice via field inspections. Finally, applicability and robustness of the TOPSIS-based MCDM modelling in high-risk factors’ target was performed through sensitivity and comparative analysis. The identification of high-risk factors via MCDM modelling not only considers the objective measured data and subjective experts’ judgments, but also provides the references for decision making in engineering practice with online survey platform.