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Babatunde, S O, Ekundayo, D, Babalola, O and Jimoh, J A (2018) Analysis of the drivers and benefits of BIM incorporation into quantity surveying profession. Journal of Engineering, Design and Technology, 16(05), 750–66.

Dosumu, O and Aigbavboa, C O (2018) Adoption of light steel (LS) for building projects in South Africa. Journal of Engineering, Design and Technology, 16(05), 711–33.

Ogunsina, O, Ekwus Obiegbu, M and Adeniyi, O (2018) Factors confronting quantity surveying practice: the case of Nigeria. Journal of Engineering, Design and Technology, 16(05), 767–82.

Poghosyan, A, Manu, P, Mahdjoubi, L, Gibb, A G F, Behm, M and Mahamadu, A (2018) Design for safety implementation factors: a literature review. Journal of Engineering, Design and Technology, 16(05), 783–97.

Shurrab, J and Hussain, M (2018) An empirical study of the impact of lean on the performance of the construction industry in UAE. Journal of Engineering, Design and Technology, 16(05), 694–710.

Tangwe, S L and Simon, M (2018) Impact of standby losses and isotherm blanket contributions on the hot water cylinders of various heating technologies. Journal of Engineering, Design and Technology, 16(05), 798–810.

Zhang, X, Wang, M, Zhou, B and Wang, X (2018) Influence of factors on collapse risk of loess tunnel: a multi-index assessment model. Journal of Engineering, Design and Technology, 16(05), 734–49.

  • Type: Journal Article
  • Keywords: Data mining; Extension theory; Risk factors; Collapse risk; Loess tunnel; Rough set theory;
  • ISBN/ISSN: 1726-0531
  • URL: https://doi.org/10.1108/JEDT-02-2018-0018
  • Abstract:
    Because of the properties of loess, the occurrence of collapse following deformation of a large settlement is a common problem during the excavation of tunnels on loess ground. Hence, risk management for safer loess tunnel construction is of great significance. The purpose of this paper is to explore the influence of factors on collapse risk of loess tunnels and establish a risk assessment model using rough set theory and extension theory. Design/methodology/approach The surrounding rock level, groundwater conditions, burial depth, excavation method and support close time were selected as the factors and settlement deformation was the verification index for risk assessment. First, using rough set theory, the influence of risk factors on the collapse risk of loess tunnels was calculated by researching engineering data of excavated sections. Then, a collapse risk assessment model was developed based on extension theory. As the final step, the model was applied to practical engineering in the Loess Plateau of China. Findings The weights of surrounding rock level, groundwater conditions, burial depth, excavation method and support close time obtained using rough set theory were respectively 10.811 per cent, 18.919 per cent, 24.324 per cent, 40.541 per cent and 5.406 per cent. The assessment results obtained using the model were in good agreement with field observations. Originality/value This study highlights key points in collapse risk management of loess tunnels, which could be very useful for future construction methods. The model, using easily obtained parameters, helps in predicting the collapse risk level of loess tunnels excavated under different geological conditions and by different construction organizations and provides a reference for future studies.