Tunnelling and Underground Space Technology 125 (2022) 104502 0886-7798/© 2022 Elsevier Ltd. All rights reserved. Introducing uniform discrete event simulation (CSM2020) for modeling the TBM tunneling process A. Khetwal a, * , J. Rostami b , P.P. Nelson b a Research Associate, Colorado School of Mines, USA b Professor, Dept. of Mining Eng., Colorado School of Mines, USA A R T I C L E INFO Keywords: TBM Discrete event simulation Excavation Tunnel Utilization ABSTRACT Several models have been developed to predict utilization of Tunnel Boring Machines (TBMs) based on statistical analysis of available project databases. Apart from the existing models, use of discrete event simulation (DES) for estimation has also been examined for utilization prediction. The results of these models demonstrate strong sensitivity to the influence of geological conditions and site logistics and offer the ability to take the site specific conditions into account for estimation of machine utilization. The present study proposes the stochastic simu- lation model CSM2020 using Arena© software that encompasses all major tunneling activities that impact ma- chine utilization. CSM2020 model offers more accurate estimation of machine utilization and higher flexibility to customize the estimates based on equipment, logistics, and ground conditions. Given the observed limitations in various commercial software packages including Arena©, and lack of access/experience with such software in the typical tunneling projects, a DES model was also developed by using MATLAB. The accuracy of both the CSM2020 and MATLAB DES models depends on the availability of data to incorporate the complex in- terdependencies of various subsystems and different tunneling activities. The utilizations estimated for selected projects using the two simulation models were within 1% of each other and the results were verified by comparing the estimated values with those from field observation. The MATLAB code did not require a license, and it offers a better opportunity to keep track of the activities in a database that can be subsequently used for data visualization and analyzed to evaluate utilization and availability of individual subsystems and resources. 1. Introduction and background Tunnel boring machines (TBMs) have proven their capabilities in tunnel construction since the 1950s and the variety of successful ap- plications has increased with time. The main factor for assessment of machine performance is the daily advance rate, which is product of penetration rate and utilization. Penetration rate is the amount of penetration the machine does in an hour while utilization is the per- centage of time the machine is boring per the total time. The generalized formula for utilization estimation is. Utilization(U%)= T b T b + T g + T m + T u + T t + T s + T ub + T me + T o + ⋯. × 100 Where T b is the boring / excavation time, T g is the ground related delays, T m is the maintenance related delays, T u is the time taken to extend utilities, T t is the transportation related delays, T s is the surveying time, T ub is the time to repair the unforeseen breakdown, T me is the combined meeting, lunch, shift change time and T o is the time spent in other activities. While various models have been developed that can predict the penetration rate with reasonable accuracy, utilization estimation models are limited with shortcoming of being empirical and based on databases that include only certain machine types. The available models for uti- lization estimation include the Colorado School of Mines (CSM) model (Sharp and Ozdemir, 1991), Norwegian Technological University (NTNU) model (Macias, 2016), the Q TBM model (Barton, 2000), the Rock Mass Excavability Index (RME) (Bieniawski et al., 2007), the empirical models by Laughton (1998) and Farrokh (2012), and the simulation based model by Abd-Al Jalil (1998). All these models are based on data available at that time, and most of them have not been updated since their introduction. The advantages and disadvantages of these models * Corresponding author. E-mail address: akhetwal@mines.edu (A. Khetwal). Contents lists available at ScienceDirect Tunnelling and Underground Space Technology incorporating Trenchless Technology Research journal homepage: www.elsevier.com/locate/tust https://doi.org/10.1016/j.tust.2022.104502 Received 13 July 2021; Received in revised form 10 March 2022; Accepted 3 April 2022