This study presents a dual Eulerian–Lagrangian particle approach for time-accurate computational fluid dynamics (CFD) modeling of volcanic ash in gas turbine engines and initial results. The objective is to enable high-fidelity simulations of calcia–magnesia–alumina-silica (CMAS) particles in gas turbine engines to better predict deposition and particle paths to rapidly test mitigation solutions. The approach uses a primarily first principles framework to account for the various physical phenomena in the system. Particles are modeled using Lagrangian methods which track individual particles and Equilibrium Eulerian methods which track particles in terms of concentration densities. Lagrangian methods become prohibitively expensive for fine particles. Eulerian methods are physically appropriate for fine particles but become inaccurate for large particle sizes. A dual approach using both Eulerian and Lagrangian methods allows for optimal computational cost with maximum accuracy. Simulation results using the proposed approach are compared against experimental data for a representative gas turbine engine blade.

这项研究提出了一种双重欧拉-拉格朗日粒子方法，用于对燃气轮机中的火山灰进行时间精确的计算流体动力学（CFD）建模，并获得了初步结果。目的是对燃气轮机中的氧化钙-氧化镁-氧化铝-二氧化硅（CMAS）颗粒进行高保真模拟，以更好地预测沉积和颗粒路径，从而快速测试缓解方案。该方法主要使用第一个原理框架来解释系统中的各种物理现象。使用跟踪单个粒子的拉格朗日方法和跟踪浓度密度的均衡欧拉方法对粒子进行建模。对于细颗粒，拉格朗日方法变得过分昂贵。欧拉方法在物理上适合于细颗粒，但对于大颗粒则变得不准确。同时使用欧拉和拉格朗日方法的双重方法可实现最佳的计算成本和最高的准确性。将使用提出的方法的模拟结果与代表燃气涡轮发动机叶片的实验数据进行比较。