This paper presents a new hybrid scheme which combines the fifth-order Targeted Essentially Non-Oscillatory (TENO) reconstruction and the tangent of hyperbola for interface capturing (THINC) reconstruction by using a modified boundary variation diminishing (MBVD) algorithm to select one of the two candidate reconstructions. The THINC scheme has a jump-like distribution can approximate a discontinuity well within a mesh cell with high fidelity. The original BVD algorithm is based on minimisation of jumps of reconstructed variables at cell interfaces in order to reduce the dissipation in numerical flux. The present MBVD algorithm minimises the dissipation terms of the HLL flux which includes jumps of both variables and fluxes at cell interfaces. A number of benchmark examples demonstrate that the MBVD algorithm is more robust than the original BVD algorithm. Applications in stiff detonation problems show that the present hybrid scheme can capture detonation fronts better than the single TENO scheme.

本文提出了一种新的混合方案，它结合了五阶目标基本非振荡 (TENO) 重建和界面捕获双曲线切线 (THINC) 重建，通过使用改进的边界变化递减 (MBVD) 算法来选择其中一个两个候选重建。THINC 方案具有类似跳跃的分布，可以以高保真度很好地近似网格单元内的不连续性。原始 BVD 算法基于最小化单元界面处重构变量的跳跃，以减少数值通量的耗散。本 MBVD 算法最小化 HLL 通量的耗散项，包括变量和单元界面处的通量的跳跃。许多基准示例表明 MBVD 算法比原始 BVD 算法更健壮。在刚性爆轰问题中的应用表明，目前的混合方案可以比单一的 TENO 方案更好地捕获爆轰前沿。