A Methodological Proposal for Risk Analysis in the Construction of Tunnels

Ospina, Luis Guillermo Garzón; Rueda, Astrid Johanna Bernal; Bessolo, Andrés Felipe Moggio; Tienda, Jose Luis Ponz

doi:10.1007/978-3-030-00220-6_98

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…Difficulty selecting an input distribution that comprehensively represents risk impact [67] has limited the use of probabilistic simulation-based risk assessment in practice-particularly in the planning and construction phase of wind farm projects that are characterized by a lack of historical data. While various methods and recommendations to overcome this challenge have been suggested in literature [67], existing methods are not capable of incorporating a large amount of subjective knowledge in a time-sensitive, practical manner. Indeed, a flexible method that allows the expert to represent their subjective knowledge as a probability distribution has not been described in literature.…”

Section: Discussionmentioning

confidence: 99%

Fuzzy-Based Multivariate Analysis for Input Modeling of Risk Assessment in Wind Farm Projects

2020

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Currently, input modeling for Monte Carlo simulation (MSC) is performed either by fitting a probability distribution to historical data or using expert elicitation methods when historical data are limited. These approaches, however, are not suitable for wind farm construction, where—although lacking in historical data—large amounts of subjective knowledge describing the impacts of risk factors are available. Existing approaches are also limited by their inability to consider a risk factor’s impact on cost and schedule as dependent. This paper is proposing a methodology to enhance input modeling in Monte Carlo risk assessment of wind farm projects based on fuzzy set theory and multivariate modeling. In the proposed method, subjective expert knowledge is quantified using fuzzy logic and is used to determine the parameters of a marginal generalized Beta distribution. Then, the correlation between the cost and schedule impact is determined and fit jointly into a bivariate distribution using copulas. To evaluate the feasibility of the proposed methodology and to demonstrate its main features, the method was applied to an illustrative case study, and sensitivity analysis and face validation were used to evaluate the method. The results demonstrated that the proposed approach provides a reliable method for enhancing input modeling in Monte Carlo simulation (MCS).

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Section: Discussionmentioning

confidence: 99%

Fuzzy-Based Multivariate Analysis for Input Modeling of Risk Assessment in Wind Farm Projects

2020

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“…Kuo and Lu [103] used Fuzzy MADM approach to assess risk of a metropolitan construction project. Risk analysis can be done using many methods such as Monte Carlo Simulation [104], [105], [106], [107], and [108], Event Trees [109] and [110], Fault Trees [111], [112] and [25], Dynamic Event trees [113], Markov models [114], Failure mode and Effective Analysis [115], [93], and [116], and Petri net [117], [118], [119] and [120]. Due to the importance of these products and the critical related risk, some researches are performed in order to evaluate risks and identify best trajectory to travel as in [121], [122], and [123].…”

Section: Literature Surveymentioning

confidence: 99%

Dynamic Decision Making Process for Dangerous Good Transportation Using a Combination of TOPSIS and AHP Methods With Fuzzy Sets

Kanj,

Kotb,

Alakkoumi

et al. 2024

IEEE Access

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Dangerous Goods Transportation in smart cities is one of the most intriguing topics that researchers are interested in to reduce the risks caused by hazardous events. This article proposes a novel technique to avoid hazardous events during the transportation of dangerous goods using realtime information provided by the cloud. This article applies Fuzzy AHP-TOPSIS hybrid method for risk analysis applied to Dangerous goods transportation in a smart city. The article assumes that we have three criteria that dictate the choice of routs the vehicle follows: cost, duration, and risk. The main objective is to choose the best route through calculated weights assigned to the three criteria based on predefined pairwise comparisons. The study is done on both static and dynamic environments. In static environments, the decision is made and is followed prior to actions and no change of actions is made even if criteria values change. In dynamic environments on the other hand, the decision could change during the transportation process due to the change of the valuation the criteria contribute to. The study shows that risk is reduced and therefore safety is increased for the transportation of dangerous goods.

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“…Tokdemir et al [22] evaluated risk of delay in repetitious construction projects with MCS. Ospina et al [23] proposed a risk analysis methodology in tunneling construction projects with MCS. Zolfaghari and Mousavi [24] introduced a novel approach of FMEA by the aim of prioritizing construction project risks under uncertain conditions of projects.…”

Section: Literature Reviewmentioning

confidence: 99%

An Approach for Risk Prioritization in Construction Projects Using Analytic Network Process and Decision Making Trial and Evaluation Laboratory

Karamoozian

Chen

et al. 2019

IEEE Access

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Construction projects always deal with different types of risks such as financial problems, legal factors, availability of resources and other issues during the project lifecycle. According to the type, size and complexity of the project, the number and intensity of risks could be different and many projects cannot reach the project goals due to exposure to multiple risks. This study aims to propose a hybrid DEMATEL-ANP model for risk prioritization in construction projects and the originality of the work comes from its ability to consider interdependencies between risk factors. The first stage of model applied Delphi method to use experts' judgments for risk identification. The second stage used Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to define the interdependencies' relative intensity among the risks. Afterwards, Analytic Network Process (ANP) method is used in the third stage to assess the relative importance of the risk factors to define risk priorities in project. A case study of oil pipeline project is reported to indicate efficiency and performance of the proposed model. The results indicated that the proposed methodology could successfully reveal the important risk factors and define the interdependencies between them in the case study. On the whole, the proposed methodology can be considered as an efficient approach for risk assessment in construction projects.

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A Methodological Proposal for Risk Analysis in the Construction of Tunnels

Cited by 3 publications

References 5 publications

Fuzzy-Based Multivariate Analysis for Input Modeling of Risk Assessment in Wind Farm Projects

Fuzzy-Based Multivariate Analysis for Input Modeling of Risk Assessment in Wind Farm Projects

Dynamic Decision Making Process for Dangerous Good Transportation Using a Combination of TOPSIS and AHP Methods With Fuzzy Sets

An Approach for Risk Prioritization in Construction Projects Using Analytic Network Process and Decision Making Trial and Evaluation Laboratory

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