Your browser doesn't support javascript.
loading
Prediction of TBM penetration rate for different surrounding rocks and cutter head diameters.
Yalei, Yang; Lijie, Du; Rong, Tang; Fei, Wei; Huilan, Zhang.
Afiliación
  • Yalei Y; School of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang, 050043, China.
  • Lijie D; Collaborative Innovation Center for Performance and Safety of Large-scale Infrastructure, Shijiazhuang Tiedao University, Shijiazhuang, 050043, China.
  • Rong T; School of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang, 050043, China.
  • Fei W; Xinjiang Irtysh River Investment and Development (Group) Co., Ltd., Urumqi, 830002, China.
  • Huilan Z; Xinjiang Irtysh River Investment and Development (Group) Co., Ltd., Urumqi, 830002, China.
Heliyon ; 10(12): e33174, 2024 Jun 30.
Article en En | MEDLINE | ID: mdl-39005917
ABSTRACT
The penetration rate (PR) of tunnel boring machines (TBMs) is often used to evaluate tunneling performance and predict construction period costs. However, most penetration rate (PR) prediction models are based on a single specific project, which leads to poor universality of the models.Furthermore, the value of the cutter head speed set for the prediction of the construction period in the survey and planning stages depends on manual experience and lacks theoretical guidance. Therefore, based on a set of engineering data from TBM of different surrounding rocks and diameters, this study statistically analyzed the distribution law of the cutter head speed (N) and the relationship between the field penetration index (FPI), geological parameters (uniaxial compressive strength (UCS) and the integrity coefficient of the rock mass (Kv)), and penetration (P). The results show that the FPI is strongly correlated with the geological parameters and the P. The geological and tunnelling parameters are the main factors affecting the penetration rate (PR). On the basis of this, prediction models of the FPI and P and a calculation model of the cutter head speed were developed, and a prediction model of the PR was obtained. The accuracy and reliability of this model were verified and analyzed for the EHe (EH) project. The average prediction error was 15.15 %.
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2024 Tipo del documento: Article País de afiliación: China