DK
D. Krasauskas
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This paper presents a comparative benchmark study of different lattice Boltzmann schemes for simulating ideal-gas supersonic flows. In particular, two approaches are investigated: a D3Q33 scheme that solves the momentum and total energy equations using two distinct particle distribution functions, and a D2Q49 scheme based on an entropy Lattice Boltzmann formulation, also employing two populations. These methods are implemented in two different computational frameworks, namely a CPU-based industrial solver and a GPU-based research solver. Their numerical properties are first analyzed in terms of dissipation and dispersion errors through the propagation of a Gaussian plane wave. Subsequently, the classical two-dimensional Schardin’s shock tube problem is used to evaluate both accuracy and computational performance. In addition to validation and algorithmic comparison, the study introduces an original GPU-oriented optimization strategy, which is essential for enabling future three-dimensional extensions of the entropic LBM scheme and represents a key contribution of this work.
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This paper presents a comparative benchmark study of different lattice Boltzmann schemes for simulating ideal-gas supersonic flows. In particular, two approaches are investigated: a D3Q33 scheme that solves the momentum and total energy equations using two distinct particle distribution functions, and a D2Q49 scheme based on an entropy Lattice Boltzmann formulation, also employing two populations. These methods are implemented in two different computational frameworks, namely a CPU-based industrial solver and a GPU-based research solver. Their numerical properties are first analyzed in terms of dissipation and dispersion errors through the propagation of a Gaussian plane wave. Subsequently, the classical two-dimensional Schardin’s shock tube problem is used to evaluate both accuracy and computational performance. In addition to validation and algorithmic comparison, the study introduces an original GPU-oriented optimization strategy, which is essential for enabling future three-dimensional extensions of the entropic LBM scheme and represents a key contribution of this work.