A Study on Landslide Risk Management by Applying Fault Tree Logics

Kazmi, D. and Qasim, S. and Harahap, I.S.H. and Baharom, S. and Masood, A. and Imran, M. (2017) A Study on Landslide Risk Management by Applying Fault Tree Logics. In: UNSPECIFIED.

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Abstract

Slope stability is one of the focal areas of curiosity to geotechnical designers and also appears logical for the application of probabilistic approaches since the analysis lead to a "probability of failure". Assessment of the existing slopes in relation with risks seems to be more meaningful when concerning with landslides. Probabilistic slope stability analysis (PSSA) is the best option in covering the landslides events. The intent here is to bid a probabilistic framework for quantified risk analysis with human uncertainties. In this regard, Fault Tree Analysis is utilized and for prediction of risk levels, consequences of the failures of the reference landslides have been taken. It is concluded that logics of fault trees is best fit, to clinch additional categories of uncertainty; like human, organizational, and knowledge related. In actual, the approach has been used in bringing together engineering and management performances and personnel, to produce reliability in slope engineering practices. © The Authors, published by EDP Sciences, 2017.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 3; Conference of 3rd International Conference on Mechatronics and Mechanical Engineering, ICMME 2016 ; Conference Date: 21 October 2016 Through 23 October 2016; Conference Code:126345
Uncontrolled Keywords: Fault tree analysis; Human resource management; Landslides; Risk analysis; Risk assessment; Risk management; Slope protection; Uncertainty analysis, Fault-trees; Geotechnical; Landslide risk managements; Probabilistic approaches; Probabilistic framework; Probability of failure; Slope engineering; Slope stability analysis, Slope stability
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:20
Last Modified: 09 Nov 2023 16:20
URI: https://khub.utp.edu.my/scholars/id/eprint/8839

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