This paper presents a new computer code to solve the general relativistic magnetohydrodynamics (GRMHD) equations using distributed parallel adaptive mesh refinement (AMR). The fluid equations are solved using a finite difference Convex ENO method (CENO) in 3 + 1 dimensions, and the AMR is Berger-Oliger. Hyperbolic divergence cleaning is used to control the ∇ · B = 0 constraint. We present resul...

A high-order accurate finite-volume scheme for the compressible ideal magnetohydrodynamics (MHD) equations is proposed. The high-order MHD scheme is based on a central essentially non-oscillatory (CENO) method combined with the generalized Lagrange multiplier divergence cleaning method for MHD. The CENO method uses k-exact multidimensional reconstruction together with a monotonicity procedure t...

Forecasts of departure demand are one of the driving inputs to tactical decision-support tools (DSTs) for airport surface traffic. While there are well-known results on averageor worst-case forecast uncertainty, it is the forecast errors which occur under best-case minimum-uncertainty conditions which constrain robust DST design and the achievable traffic benefits. These best-case errors have n...

A novel parallel, high-order, anisotropic, block-based, adaptive mesh re nement (AMR), nite-volume scheme is proposed and developed herein for the numerical solution of physically complex ow problems having disparate spatial and temporal scales, and with strong anisotropic features. A block-based AMR approach is used which permits highly e cient and scalable implementations on parallel computin...