We establish stochastic functional integral representations for solutions of Oberbeck-Boussinesq equations in the form of McKean-Vlasov-type mean field equations, which can be used to design numerical schemes for calculating solutions and for implementing Monte-Carlo simulations of Oberbeck-Boussinesq flows. Our approach is based on the duality of conditional laws for a class of diffusion processes associated with solenoidal vector fields, which allows us to obtain a novel integral representation theorem for solutions of some linear parabolic equations in terms of the Green function and the pinned measure of the associated diffusion. We demonstrate via numerical experiments the efficiency of the numerical schemes, which are capable of revealing numerically the details of Oberbeck-Boussinesq flows within their thin boundary layer, including B{\'e}nard's convection feature.
翻译:我们建立了 Oberbeck-Boussinesq 方程的随机泛函积分表示形式,采用 McKean-Vlasov 类型的均场方程,可以用于设计计算解的数字方案和实现 Oberbeck-Boussinesq 流动的蒙特卡罗模拟。我们的方法基于伴随给定一类与无旋向量场关联的扩散过程的条件律的对偶性,这使得我们能够获得一种关于绿函数和相关随机过程的固定测度的线性抛物型方程解的新型积分表示定理。我们通过数值实验证明了数字方案的有效性,这种方案能够在 Oberbeck-Boussinesq 流动的薄边界层内数值地揭示 Bernoulli 对流特征等细节。