English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Timely and reasonable matching of the control parameters and geologicalconditions of the rock mass in tunnel excavation is crucial for hard rocktunnel boring machines (TBMs). Therefore, this paper proposes an intelligentdecision method for the main control parameters of the TBM based on themulti-objective optimization of excavation efficiency and cost. The mainobjectives of this method are to obtain the most important parameters of therock mass and machine, determine the optimization objective, and establish theobjective function. In this study, muck information was included as animportant parameter in the traditional rock mass and machine parameterdatabase. The rock-machine interaction model was established through animproved neural network algorithm. Using 250 sets of data collected in thefield, the validity of the rock-machine interaction relationship model wasverified. Then, taking the cost as the optimization objective, the costcalculation model related to tunneling and the cutter was obtained.Subsequently, combined with rock-machine interaction model, the objectivefunction of control parameter optimization based on cost was established.Finally, a tunneling test was carried out at the engineering site, and the mainTBM control parameters (thrust and torque) after the optimization decision wereused to excavate the test section. Compared with the values in the sectionwhere the TBM operators relied on experience, the average penetration rate ofthe TBM increased by 11.10%, and the average cutter life increased by 15.62%.The results indicate that this method can play an effective role in TBMtunneling in the test section.

Intelligent Decision Method for Main Control Parameters of Tunnel Boring  Machine based on Multi-Objective Optimization of Excavation Efficiency and  Cost