GPU-Accelerated Anisotropic Random Field and Its Application in the Modeling of a Diversion Tunnel

Abstract

In this paper, a GPU-accelerated Cholesky decomposition technique and a coupled anisotropic random field are suggested for use in the modeling of diversion tunnels. Combining the advantages of GPU and CPU processing with MATLAB programming control yields the most efficient method for creating large numerical model random fields. Based on the geological structural characteristics of red-bedded soft rocks in central Yunnan, anisotropic rock random fields and tunnel excavation with various rotation degrees are simulated. In the comparison of anisotropic random fields specifically, the relationship between the anisotropic rotation angle and the plastic zone, as well as the multiple measurements for the overall safety factor, are analyzed. The distribution of the plastic zone after excavation has a significant relationship with the random parameters of the anisotropic random field. When the stronger or weaker random parameters are located in the surrounding rock of the cavern, they will cause a change in the radius of the plastic zone. The overall safety factor of the anisotropic random field is relatively stable, with an average value of about 2, which mainly depends on the strength of the random parameter of the rock mass. Based on the random fluctuation of the suggested value in the engineering report, the simulation result is safe. This study can provide theoretical and technical support for the design and construction of relevant rock engineering in the red-bedded soft rock region of central Yunnan.