Probabilistic time estimation of tunnels constructed with multiple headings

Transport infrastructure projects frequently encounter challenges such as schedule delays and cost overruns, leading to substantial misallocation of public or private resources. These issues are often exacerbated by uncertainties in time and cost estimation outcomes. To address this, various models have been developed in recent years to enable probabilistic estimation for tunneling projects, considering uncertainties. However, the impact of uncertainties on the critical path and its implications on time and cost estimations have not been discussed explicitly and in detail for network underground structures encompassing multiple construction paths. In this study, we update the KTH time and cost estimation model using the Markov Chain Monte Carlo (MCMC) method. This updated model enables simultaneous round-by-round construction simulation across all paths in network underground structures. Consequently, it accommodates uncertainty in the critical path and its influence on time estimation outcomes. Additionally, the updated model introduces an innovative technique to model geological uncertainties along tunnel routes, thereby contributing to the field’s diversity. Practical application of the updated model is showcased using the Uri Hearace tunnel as an illustrative example. The paper also delves into the practical implications of the findings from a decision-maker’s standpoint, as well as discussing the model’s limitations.

Authors

Institutions

Publication Details

Journal
Tunnelling and Underground Space Technology
Published
2024-08-12
DOI
https://doi.org/10.1016/j.tust.2024.106013
Citations
4
Primary Topic
Tunneling and Rock Mechanics
Type
article
Field-Weighted Citation Impact
1.04

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Probabilistic time estimation of tunnels constructed with multiple headings

Johan Spross, Mohammad Mohammadi
4 citations
Tunnelling and Underground Space Technology
Tunneling and Rock Mechanics
1.04
article

Probabilistic time estimation of tunnels constructed with multiple headings

Johan Spross, Mohammad Mohammadi
article en
4 citations

Abstract

Transport infrastructure projects frequently encounter challenges such as schedule delays and cost overruns, leading to substantial misallocation of public or private resources. These issues are often exacerbated by uncertainties in time and cost estimation outcomes. To address this, various models have been developed in recent years to enable probabilistic estimation for tunneling projects, considering uncertainties. However, the impact of uncertainties on the critical path and its implications on time and cost estimations have not been discussed explicitly and in detail for network underground structures encompassing multiple construction paths. In this study, we update the KTH time and cost estimation model using the Markov Chain Monte Carlo (MCMC) method. This updated model enables simultaneous round-by-round construction simulation across all paths in network underground structures. Consequently, it accommodates uncertainty in the critical path and its influence on time estimation outcomes. Additionally, the updated model introduces an innovative technique to model geological uncertainties along tunnel routes, thereby contributing to the field’s diversity. Practical application of the updated model is showcased using the Uri Hearace tunnel as an illustrative example. The paper also delves into the practical implications of the findings from a decision-maker’s standpoint, as well as discussing the model’s limitations.

Tunnelling and Underground Space TechnologyVol. 153
KTH Royal Institute of Technology (SE)
Skogs- och Jordbrukets Forskningsråd, Svenska Forskningsrådet Formas, Stiftelsen Bergteknisk Forskning
Sustainable cities and communities
Openalex Percentile: Top 26%
Tunneling and Rock Mechanics
1.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.