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Compressible N-phase fluid mixture models

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arxiv 2503.24225 v1 pith:55DGM7AN submitted 2025-03-31 physics.flu-dyn math-phmath.APmath.MP

classification physics.flu-dynmath-phmath.APmath.MP
keywords compressiblemodelsmixturestheorydynamicsfluidmixturephase-field
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Fluid mixture models are essential for describing a wide range of physical phenomena, including wave dynamics and spinodal decomposition. However, there is a lack of consensus in the modeling of compressible mixtures, with limited connections between different classes of models. On the one hand, existing compressible two-phase flow models accurately describe wave dynamics, but do not incorporate phase separation mechanisms. On the other hand, phase-field technology in fluid dynamics consists of models incorporating spinodal decomposition, however, a general phase-field theory for compressible mixtures remains largely undeveloped. In this paper, we take an initial step toward bridging the gap between compressible two-phase flow models and phase-field models by developing a theory for compressible, isothermal N-phase mixtures. Our theory establishes a system of reduced complexity by formulating N mass balance laws alongside a single momentum balance law, thereby naturally extending the Navier-Stokes Korteweg model to N-phases and providing the Navier-Stokes Cahn-Hilliard/Allen-Cahn model for compressible mixtures. Key aspects of the framework include its grounding in continuum mixture theory and its preservation of thermodynamic consistency despite its reduced complexity.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Global weak solutions to a compressible Navier--Stokes/Cahn--Hilliard system with singular entropy of mixing

    math.AP 2025-06 conditional novelty 7.0 of 10

    Global weak solutions exist for the compressible Navier-Stokes/Cahn-Hilliard system with singular Flory-Huggins entropy in 3D for gamma > 3/2 and large initial data.

  2. An entropy-stable and kinetic energy-preserving macro-element HDG method for compressible flows

    cs.CE 2025-07 conditional novelty 6.0 of 10

    A macro-element HDG method with entropy-stable, kinetic energy-preserving fluxes satisfies a discrete entropy inequality and achieves about 2.7x speedup over standard HDG on vortex benchmarks.

  3. Equivariant U-Shaped Neural Operators for the Cahn-Hilliard Phase-Field Model

    cs.LG 2025-09 conditional novelty 4.0 of 10

    E-UNO, a U-shaped Fourier neural operator with a D4 equivariance loss, predicts Cahn-Hilliard microstructure evolution more accurately than FNO and UNO baselines in reported experiments.

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