  We present a general methodology for constructing lattice Boltzmann models of
hydrodynamics with certain desired features of statistical physics and kinetic
theory. We show how a methodology of linear programming theory, known as
Fourier-Motzkin elimination, provides an important tool for visualizing the
state space of lattice Boltzmann algorithms that conserve a given set of
moments of the distribution function. We show how such models can be endowed
with a Lyapunov functional, analogous to Boltzmann's H, resulting in
unconditional numerical stability. Using the Chapman-Enskog analysis and
numerical simulation, we demonstrate that such entropically stabilized lattice
Boltzmann algorithms, while fully explicit and perfectly conservative, may
achieve remarkably low values for transport coefficients, such as viscosity.
Indeed, the lowest such attainable values are limited only by considerations of
accuracy, rather than stability. The method thus holds promise for
high-Reynolds number simulations of the Navier-Stokes equations.
