Risk Assessment for Stability and Containment Property of an Underground Oil Storage Facility in Construction Phase Using Fuzzy Comprehensive Evaluation Method

Wang, Zhechao; Qiao, Liping; Li, Shucai; Bi, Liping

doi:10.1061/ajrua6.0000885

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…They used geological properties as the risk assessment criteria in order to study the risk. Finally, a proper match was obtained between the risk analysis using the fuzzy logic and the visual results obtained from this underground depot, indicating the suitability of soft methods in the risk assessment of underground projects [21].…”

Section: Introductionmentioning

confidence: 70%

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Assessment of risks of tunneling project in Iran using artificial bee colony algorithm

et al. 2019

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The soft computing techniques have been widely applied to model and analyze the complex and uncertain problems. This paper aims to develop a novel model for the risk assessment of tunneling projects using artificial bee colony algorithm. To this end, the risk of the second part of the Emamzade Hashem tunnel was assessed and analyzed in seven sections after testing geotechnical characteristics. Five geotechnical and hydrological properties of study zone are considered for the clustering of geological units in front of tunneling project including length of tunnel, uniaxial compressive strength, rock mass rating, tunneling index Q, density and underground water condition. These sections were classified in two lowrisk and high-risk groups based on their geotechnical characteristics and using clustering technique. It was resulted that three sections with lithologies Durood Formation, Mobarak Formation, and Ruteh Formation are placed in the high risk group and the other sections with lithologies Baroot Formation, Elika Formation, Dacite tuff of Eocene, and Shear Tuff, and Lava Eocene are placed in the low risk group. In addition, the underground water condition and density with 0.722 and 1 Euclidean distances have the highest and lowest impacts in the high risk group, respectively. Therefore, comparing the obtained results of modelling and actual excavation data demonstrated that this technique can be applied as a powerful tool for modeling risks of tunnel and underground constructions.

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Section: Introductionmentioning

confidence: 70%

“…Various methods are used for the risk assessment of tunneling projects. In a research, the risk of underground projects in the construction phase (oil depot) was assessed by Wang et al [21] using the fuzzy comprehensive evaluation method. They used geological properties as the risk assessment criteria in order to study the risk.…”

Section: Introductionmentioning

confidence: 99%

Assessment of risks of tunneling project in Iran using artificial bee colony algorithm

et al. 2019

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“…The transformation of qualitative and quantitative concepts needs to be addressed, and the qualitative level should be quantified with different indices. A great deal of methods and methodologies have been proposed to determine water quality in the past few decades, including multivariate statistical models, fuzzy set-based models [12], and hybrid models [13,14]. Multivariate statistical models for randomness have included cluster analysis (CA), factor analysis (FA), and principal component analysis (PCA) [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

A Normal Cloud Model-Based Method for Water Quality Assessment of Springs and Its Application in Jinan

Wang

Yang

et al. 2019

Sustainability

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Springs are a source of drinking water and a famous tourist attraction in Jinan, China. In this paper, a multi-index evaluation method was proposed based on a normal cloud model. This model is new graphic model, which could synthetically picture the randomness and fuzziness of concepts. Ten parameters were selected, and water quality was classified into five levels. Three numerical characteristics were calculated, and the weights were assigned by an integrated weighting algorithm. The uncertainty of each spring was calculated by a cloud generator and the integrated certainty grades of water quality were determined. To ensure the accuracy of the normal cloud model, the proposed method was used to assess the water quality of springs in Jinan, China. The results obtained by the proposed method were compared with that of the other four methods. The results obtained by different methods are highly consistent. The proposed cloud model-based method can reflect the water quality level and provides a practical guide for water quality evaluation, as demonstrated in Jinan springs.

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Current research trends and application areas of fuzzy and hybrid methods to the risk assessment of construction projects

Islam

Skitmore

Attarzadeh

2017

Advanced Engineering Informatics

135

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Risk Assessment for Stability and Containment Property of an Underground Oil Storage Facility in Construction Phase Using Fuzzy Comprehensive Evaluation Method

Cited by 5 publications

References 21 publications

Assessment of risks of tunneling project in Iran using artificial bee colony algorithm

Assessment of risks of tunneling project in Iran using artificial bee colony algorithm

A Normal Cloud Model-Based Method for Water Quality Assessment of Springs and Its Application in Jinan

Current research trends and application areas of fuzzy and hybrid methods to the risk assessment of construction projects

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