Performance Evaluation of TBM Using an Improved Load Prediction Model
Excavation load prediction is of great importance for the prior design and latter performance evaluation of tunnel boring machines (TBMs). In this paper, an improved load prediction model is developed based on classical Colorado school of mines model for TBMs equipped with constant cross-sectional d...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/11/2/141 |
| _version_ | 1797619766674849792 |
|---|---|
| author | Xinghai Zhou Guofang Gong Yakun Zhang Weiqiang Wu Yuxi Chen |
| author_facet | Xinghai Zhou Guofang Gong Yakun Zhang Weiqiang Wu Yuxi Chen |
| author_sort | Xinghai Zhou |
| collection | DOAJ |
| description | Excavation load prediction is of great importance for the prior design and latter performance evaluation of tunnel boring machines (TBMs). In this paper, an improved load prediction model is developed based on classical Colorado school of mines model for TBMs equipped with constant cross-sectional disc cutters. The typical structure and principle are introduced to predict the single cutter force, and the total cutter group load is calculated by defining the equivalent diameter and cutter spacing. Subsequently, the improved model of a more brief and acceptable type is established via summation. Some novel performance indexes, including the reformed field penetration index, torque/thrust penetration index, and specific energy are, respectively, derived in formulaic form. By field data verification in the borehole zones of two cases, the proposed model is proven to be more accurate in the total load prediction. The single-factor regression results show that the reformed field penetration index reveals the nonlinear relationship between TBM load and penetration rate, and the torque/thrust penetration index is a new TBM inherent index to evaluate the working conditions. Specific energy, used to evaluate the excavation efficiency, is positive with rock strength and proved negative with penetration rate via a normalization analysis. Finally, suggestions on the cutter group configuration against abominable stratum are discussed. |
| first_indexed | 2024-03-11T08:31:30Z |
| format | Article |
| id | doaj.art-63e484e9084f4441926413ee96168ae3 |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-11T08:31:30Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-63e484e9084f4441926413ee96168ae32023-11-16T21:44:27ZengMDPI AGMachines2075-17022023-01-0111214110.3390/machines11020141Performance Evaluation of TBM Using an Improved Load Prediction ModelXinghai Zhou0Guofang Gong1Yakun Zhang2Weiqiang Wu3Yuxi Chen4State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, ChinaState Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, ChinaState Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, ChinaState Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, ChinaState Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, ChinaExcavation load prediction is of great importance for the prior design and latter performance evaluation of tunnel boring machines (TBMs). In this paper, an improved load prediction model is developed based on classical Colorado school of mines model for TBMs equipped with constant cross-sectional disc cutters. The typical structure and principle are introduced to predict the single cutter force, and the total cutter group load is calculated by defining the equivalent diameter and cutter spacing. Subsequently, the improved model of a more brief and acceptable type is established via summation. Some novel performance indexes, including the reformed field penetration index, torque/thrust penetration index, and specific energy are, respectively, derived in formulaic form. By field data verification in the borehole zones of two cases, the proposed model is proven to be more accurate in the total load prediction. The single-factor regression results show that the reformed field penetration index reveals the nonlinear relationship between TBM load and penetration rate, and the torque/thrust penetration index is a new TBM inherent index to evaluate the working conditions. Specific energy, used to evaluate the excavation efficiency, is positive with rock strength and proved negative with penetration rate via a normalization analysis. Finally, suggestions on the cutter group configuration against abominable stratum are discussed.https://www.mdpi.com/2075-1702/11/2/141tunnel boring machineimproved load prediction modelperformance evaluation indexTBM working conditionscutter group configuration |
| spellingShingle | Xinghai Zhou Guofang Gong Yakun Zhang Weiqiang Wu Yuxi Chen Performance Evaluation of TBM Using an Improved Load Prediction Model Machines tunnel boring machine improved load prediction model performance evaluation index TBM working conditions cutter group configuration |
| title | Performance Evaluation of TBM Using an Improved Load Prediction Model |
| title_full | Performance Evaluation of TBM Using an Improved Load Prediction Model |
| title_fullStr | Performance Evaluation of TBM Using an Improved Load Prediction Model |
| title_full_unstemmed | Performance Evaluation of TBM Using an Improved Load Prediction Model |
| title_short | Performance Evaluation of TBM Using an Improved Load Prediction Model |
| title_sort | performance evaluation of tbm using an improved load prediction model |
| topic | tunnel boring machine improved load prediction model performance evaluation index TBM working conditions cutter group configuration |
| url | https://www.mdpi.com/2075-1702/11/2/141 |
| work_keys_str_mv | AT xinghaizhou performanceevaluationoftbmusinganimprovedloadpredictionmodel AT guofanggong performanceevaluationoftbmusinganimprovedloadpredictionmodel AT yakunzhang performanceevaluationoftbmusinganimprovedloadpredictionmodel AT weiqiangwu performanceevaluationoftbmusinganimprovedloadpredictionmodel AT yuxichen performanceevaluationoftbmusinganimprovedloadpredictionmodel |