The “penalty factors” method for the prediction of TBM performances in changing grounds

Dudt, Jean-Paul; Delisio, Andrea

doi:10.1016/j.tust.2016.01.006

Cited by 13 publications

(3 citation statements)

References 9 publications

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“…For the structural design and vibration reduction optimization of the cutterhead system. Liu, 14 Hasanpour et al, 15,16 and Afrasiabi et al 17–23 were devoted to studying various performance parameters that affect the work of TBM, such as rock parameters and machine parameters to establish prediction theoretical models of TBM performance. Methods such as “penalty factor” and “pso-ann hybrid model” were proposed to estimate the performance of TBM, which enriched the theoretical model of intelligent prediction.…”

Section: Introductionmentioning

confidence: 99%

Research on rock breaking mechanism and load characteristics of TBM cutter based on discrete element method

Ling

Cheng

Tong

et al. 2021

Advances in Mechanical Engineering

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Tunnel boring machine (TBM) is a large-scale tunnel engineering equipment, which has unparalleled advantages in safety and work efficiency. The cutter is subjected to complex and variable random impact loads, resulting in damage to bearings, cutter rings, and cutter shafts. Therefore, based on the discrete element simulation platform and experiment, this paper established the cutter rock simulation model based on the experimental data, and analyzed the rock breaking process, cutter load magnitude, and variation law. The research results show that when the cutter pole diameter decreases from 200 mm, 100 mm, and 0 mm in sequence, the rolling force increases accordingly, and the maximum increase of the rolling force is 56%. Meanwhile the lateral force decreases and the maximum average decrease value is 26%. Moreover, the rolling force showed a downward trend with the increase of the cutter spacing. When the cutter spacing is increased from 80 mm to 120 mm, the average rolling force decreases by 51%, and the maximum value rises slightly, increasing by 2%. And, the lateral force tends to increase, with an increase of 17% and the maximum lateral force value increase was 29%. The results can provide load input reference for TBM cutter layout, cutterhead structure design, and performance evaluation.

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Section: Introductionmentioning

confidence: 99%

Research on rock breaking mechanism and load characteristics of TBM cutter based on discrete element method

Ling

Cheng

Tong

et al. 2021

Advances in Mechanical Engineering

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“…Lin et al [14] proposed a novel fuzzy model for identifying high-risk factors during deep excavations in karst geological ground. Dudt and Delisio [15] used the penalty factor method to predict the performance of a TBM in highly variable strata. Furthermore, owing to the uncertainties of the various impact factors of TBM tunnelling, fuzzy mathematical methods have been widely used to predict the boreability of the machine [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Adaptability of an EPB TBM to Tunnelling through Highly Variable Composite Strata

Zhan

Li³

et al. 2021

Mathematical Problems in Engineering

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The adaptability of an earth pressure balance (EPB) tunnel boring machine (TBM) to complex geological strata needs to be evaluated when a tunnel project is set up. It is helpful for better design and more suitable technical parameters of the machine. Because the factors that influence adaptability are numerous and interrelated, their effects also differ; hence, a quantitative assessment of adaptability is generally difficult. In the present study, a method for quantitatively evaluating the excavation adaptability of an EPB TBM was developed using an analytic hierarchy process (AHP) and fuzzy comprehensive evaluation. The method first involves an initial selection of factors that may influence tunnelling. Based on the expert questionnaire and their influence weights determined by AHP, the 10 evaluation indexes from 25 primary indexes were selected to establish the evaluation index system (EIS) including a target, criteria, and index level. Fuzzy membership functions are then derived one after another based on the effect of each evaluation index on the EBP TBM tunnelling process. A fuzzy mathematical method was finally presented to determine the adaptability of an EPB TBM excavation performance. The proposed method was applied to two special sections of diameter 6.98 m excavated by two EPB TBMs in the Shenzhen Metro Line 11 project. The geological exploration shows that these two tunnel sections pass through typical composite strata in Shenzhen. The determined adaptability grades of the EPB TBMs used for composite strata were confirmed by the actual tunnel excavation. It indicates that the developed method is reasonable and useful to evaluate tunnelling adaptability of EPB TBM.

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“…TBM penetration rate estimates can be used to reduce the risks associated with the costs of current investment in excavating operations [10], [11]. Estimating the penetration rate has a great impact on controlling the project time and choosing the excavating method [12], [13]. However, TBMs are susceptible to geological conditions such as fractures, cracks and swelling and rock explosions [14], [15].…”

Section: Introductionmentioning

confidence: 99%

Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel

Afradi¹,

Ebrahimabadi²,

Hallajian³

2020

Min. miner. depos.

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The purpose of this study is to use a novel approach to estimate the tunnel boring machine (TBM) penetration rate in diverse ground conditions. Methods. The methods used in this study include ant colony optimization (ACO), bee colony optimization (BCO) and the particle swarm optimization (PSO). Moreover, a comprehensive database was created based on machine performance using penetration rate (m/h) as an output parameteras well as intact rock and rock mass parameters including uniaxial compressive strength (UCS) (MPa), Brazilian tensile strength (BTS) (MPa), rock quality designation (RQD) (%), cohesion (MPa), elasticity modulus (GPa), Poisson's ratio, density(g/cm 3 ), joint angle (deg.) and joint spacing (m) as input parameters. Findings. Results showed that the analyses yielded several realistic and reliable models for predicting penetration rate of TBMs. ACO model has R 2 = 0.8830 and RMSE = 0.6955, BCO model has R 2 = 0.9367 and RMSE = 0.5113 and PSO model has R 2 = 0.9717 and RMSE = 0.3418. Originality. Prediction of TBM penetration rate using these methods has been carried out in the Sabzkooh water conveyance tunnel for the first time. Practical implications. According to the results, all three approaches are very effective but PSO yields more precise and realistic findings than other methods.

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The “penalty factors” method for the prediction of TBM performances in changing grounds

Cited by 13 publications

References 9 publications

Research on rock breaking mechanism and load characteristics of TBM cutter based on discrete element method

Research on rock breaking mechanism and load characteristics of TBM cutter based on discrete element method

Evaluation of the Adaptability of an EPB TBM to Tunnelling through Highly Variable Composite Strata

Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel

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