Multi-Objective Optimization Study of Annular Fluid Flow Structure in Cordless Core Drilling Tools

Abstract

Traditional drilling methods often face difficulty meeting the demand for efficient and accurate coring under complex geological conditions. Cordless coring is an advanced technology that uses hydraulic lifting to carry out coring, which can achieve automation and automated and intelligent drilling operations. In this research, a new type of hydraulic lifting cordless coring drilling tool is designed. Moreover, a numerical simulation model of the fluid flow in the annulus between the spearhead and spool of the cordless coring drilling tool was established. Orthogonal simulation tests are carried out, and according to the orthogonal test data, a numerical prediction model of the spool annulus fluid field based on the Backpropagation Neural Network (BP neural network) is established. The prediction of the flow rate of the drilling fluid and the spool back-pressure ratio was obtained when the structural parameters of the spearhead and the spool annulus were different. A multi-objective optimization of the annulus flow structure of the cordless core drilling tool has been carried out. The optimization objectives include deciding the back pressure ratio of the spool overcoming the spring and the flow rate of the drilling fluid. According to the established nonlinear optimization model and based on the improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) multi-objective optimization algorithm, it is verified that the convergence speed and diversity of the improved algorithm are better than those before the improvement. The simulation and experimental validation are carried out. It is verified that the flow rate of drilling fluid increased by 33.56% after optimization, and the force ratio was lowered by 5.825%. Finally, based on the simulation and optimization results, the φ96 cordless core drilling tool was manufactured on a trial basis, and on-site concrete drilling, coring, and hydraulic lifting operations were conducted for smooth coring and lifting. This study could provide an important scientific basis and technical support for the application and development of hydraulic lifting cordless coring technology.

Keywords

• hydraulic lifting
• cordless coring drilling tool
• numerical simulation model
• BP neural network
• multi-objective optimization