A Cloud Model-Based Risk Assessment Methodology for Tunneling-Induced Damage to Existing Tunnel
| Autor: | Zhanping Song, Yuncai Song, Desai Guo, Tian Xu |
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| Rok vydání: | 2020 |
| Předmět: |
Risk level
Article Subject Mathematical model Index system business.industry Computer science Project risk management 0211 other engineering and technologies Cloud computing 02 engineering and technology Engineering (General). Civil engineering (General) Reliability engineering Transformation (function) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing TA1-2040 business Risk assessment Randomness 021101 geological & geomatics engineering Civil and Structural Engineering |
| Zdroj: | Advances in Civil Engineering, Vol 2020 (2020) |
| ISSN: | 1687-8094 1687-8086 |
| Popis: | This study presents a cloud model-based approach for risk assessment of existing tunnels in tunneling construction environments where the cloud model provides a basis for uncertainty transformation between its qualitative concepts and quantitative expressions. An evaluation index system is established for risk assessment of existing tunnels based on the tunnel-induced failure mechanism analysis. The assessment result is obtained through the correlation with the cloud model of each risk level. Risk assessment for existing Guangzhou-Shenzhen-Hong Kong Railway Tunnel in the tunneling environment of Shenzhen Metro Line 6 is shown in a case study. Comparisons between Fuzzy Analytic Hierarchy Process (FAHP) methods are further discussed according to results. The proposed evaluation method is verified to be more competitive as the fuzziness and randomness of uncertainties in the risk assessment system can be considered comprehensively. This method can serve as a decision-making tool for other similar project risk assessment methods to increase the likelihood of a successful project in an uncertain environment. |
| Databáze: | OpenAIRE |
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