Application of the Decision Aids for Tunneling (DAT) to update excavation cost/time information

Min, Sang-Yoon; Einstein, Herbert H.; Lee, J. S.; Lee, H. S.

doi:10.1007/bf02829047

Cited by 16 publications

(2 citation statements)

References 3 publications

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“…Based on them, the probability distributions of the construction cost and time of the entire project can be obtained. Min et al (2005) applied the DAT technique to predict and update the total construction cost and time of a road tunnel project [11].…”

Section: Decision Aids For Tunnelingmentioning

confidence: 99%

A Causal Network-Based Risk Matrix Model Applicable to Shield TBM Tunneling Projects

et al. 2021

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The present study compares and analyzes three risk analysis models that are applicable to shield tunnel boring machine (TBM) tunneling, and thus proposes an improved risk matrix model based on the causal networks applicable to sustainable tunnel projects. The advantages and disadvantages of three risk analysis models are compared, and causal networks are structured by analyzing the causal relationship between risk factors and risk events. Based on the comparison and analysis results, the causal network-based risk matrix model (CN-Matrix model), which complements the disadvantages and exploits the advantages of the three existing models, is proposed in this paper. Furthermore, this study suggests a means of modifying the weighting scores in the estimation of the risk score, which permits the CN-Matrix model to determine the risk level more reasonably. Thus, the improved CN-Matrix model is more reliable and robust compared to the three existing models.

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Section: Decision Aids For Tunnelingmentioning

confidence: 99%

A Causal Network-Based Risk Matrix Model Applicable to Shield TBM Tunneling Projects

et al. 2021

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“…Uncertainty in future progress is an inherent characteristic of construction projects (5), especially underground construction (6). In this regard, taking a probabilistic approach is inevitable in providing reliable forecasts of the future.…”

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confidence: 99%

Finding Best Model to Forecast Construction Duration of Road Tunnels with New Austrian Tunneling Method Using Bayesian Inference

Hosseinian

Reinschmidt

2015

Transportation Research Record: Journal of the Transportation R

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Forecasting project final duration (i.e., time at completion) is crucial to project risk management and is always sought by project managers during the construction period. Because of a strong correlation between past and future performances in linear projects, past progress data are the best source of information to forecast final duration of this type of project, including tunneling projects constructed by the new Austrian tunneling method (NATM). Bayesian inference is a robust probabilistic approach that can provide accurate forecasts of final duration based on a project's past performance. However, results of research in this field have shown that selecting an appropriate model, which represents the unknown pattern of the project's actual progress well, is the most challenging and subjective part of this approach. Effective risk management necessitates looking for the best model that can forecast project final duration accurately and precisely, especially early in the project. This research was aimed at finding a best progress model for NATM tunneling projects by conducting Bayesian analysis on available data of a massive project, the Niayesh highway tunnel in Iran. The analysis showed that the dual Gompertz function (with flexible lower asymptote) was the most reliable model for this purpose. The results of this research bring advantages to the planning and risk management of NATM tunneling projects, which are discussed in this paper, and can be very useful for future NATM tunnel constructions.

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Vibration response of exposed gas pipeline placed to temporary structure

Park

2005

KSCE Journal of Civil Engineering

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Application of the Decision Aids for Tunneling (DAT) to update excavation cost/time information

Cited by 16 publications

References 3 publications

A Causal Network-Based Risk Matrix Model Applicable to Shield TBM Tunneling Projects

A Causal Network-Based Risk Matrix Model Applicable to Shield TBM Tunneling Projects

Finding Best Model to Forecast Construction Duration of Road Tunnels with New Austrian Tunneling Method Using Bayesian Inference

Vibration response of exposed gas pipeline placed to temporary structure

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