the purpose of this paper is to investigate the egm method and the behavior of a solid particle suspended in a twodimensional rectangular cavity due to conjugate natural convection. a thermal lattice boltzmann bgk model is implemented to simulate the two dimensional natural convection and the particle phase was modeled using the lagrangian–lagrangian approach where the solid particles are treat...

The augmented Lagrangian method is a popular method for solving linearly constrained convex minimization problem and has been used many applications. In recently, the accelerated version of augmented Lagrangian method was developed. The augmented Lagrangian method has the subproblem and dose not have the closed form solution in general. In this talk, we propose the inexact version of accelerate...

We present a multi-scale lattice Boltzmann scheme, which adaptively refines particles' velocity space. Different sets of lower and higher order are consistently efficiently coupled, allowing us to use the higher-order model only when where needed. This includes regions high Mach or Knudsen numbers. The coupling procedure discrete consists either projection populations onto lower-order lifting B...

We present and test a new hybrid numerical method for simulating layerwise-twodimensional geophysical flows. The method radically extends the original ContourAdvective Semi-Lagrangian (CASL) algorithm (Dritschel & Ambaum, 1997) by combining three computational elements for the advection of general tracers (e.g. potential vorticity, water vapor, etc.): (1) a pseudo-spectral method for large scal...

This report considers the solution of estimation problems based on the maximum likelihood principle when a xed number of equality constraints are imposed on the problem. Consistency and the asymptotic distribution of the parameter estimates as n ! 1, where n is the number of observations, are discussed, and it is shown that a suitably scaled limiting multiplier vector is known. It is suggested ...

Dual decomposition has been recently proposed as a way of combining complementary models, with a boost in predictive power. However, in cases where lightweight decompositions are not readily available (e.g., due to the presence of rich features or logical constraints), the original subgradient algorithm is inefficient. We sidestep that difficulty by adopting an augmented Lagrangian method that ...