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In the present work, the Tensor-Train decomposition algorithm is applied to reduce the memory footprint of a stochastic discrete velocity solver for rarefied gas dynamics simulation. An energy-conserving modification to the algorithm is…

Fluid Dynamics · Physics 2023-03-28 Georgii Oblapenko

The simulation of rarefied gas flow based on the Boltzmann equation is challenging, especially when the gas mixtures have disparate molecular masses. In this paper, a computationally tractable kinetic model is proposed for monatomic gas…

Fluid Dynamics · Physics 2024-03-12 Qi Li , Jianan Zeng , Lei Wu

In this contribution we propose reduced order methods to fast and reliably solve parametrized optimal control problems governed by time dependent nonlinear partial differential equations. Our goal is to provide a tool to deal with the time…

Numerical Analysis · Mathematics 2023-08-08 Francesco Ballarin , Gianluigi Rozza , Maria Strazzullo

An implicit high-order discontinuous Galerkin (DG) method is developed to find steady-state solution of rarefied gas flow described by the Boltzmann equation with full collision operator. In the physical space, velocity distribution…

Computational Physics · Physics 2019-01-08 Wei Su , Peng Wang , Yonghao Zhang , Lei Wu

This work explores the capability of simulating complex fluid flows by directly solving the Boltzmann equation. Due to the high-dimensionality of the governing equation, the substantial computational cost of solving the Boltzmann equation…

Fluid Dynamics · Physics 2023-12-05 Tarik Dzanic , Luigi Martinelli

Adjoint based shape optimization is a powerful technique in fluid-dynamics optimization, capable of identifying an optimal shape within only dozens of design iterations. However, when extended to rarefied gas flows, the computational cost…

Computational Physics · Physics 2025-11-25 Yanbing Zhang , Ruifeng Yuan , Lei Wu

Reduced order modeling has gained considerable attention in recent decades owing to the advantages offered in reduced computational times and multiple solutions for parametric problems. The focus of this manuscript is the application of…

Numerical Analysis · Mathematics 2018-11-21 Gianluigi Rozza , Haris Malik , Nicola Demo , Marco Tezzele , Michele Girfoglio , Giovanni Stabile , Andrea Mola

The parallel solver of the general synthetic iterative scheme (GSIS), as recently developed by Zhang \textit{et. al.} in Comput. Fluids 281 (2024) 106374, is an efficient method to find the solution of the Boltzmann equation…

Computational Physics · Physics 2025-01-07 Yanbing Zhang , Jianan Zeng , Lei Wu

Two kinetic models are proposed for high-temperature rarefied (or non-equilibrium) gas flows with radiation. One of the models uses the Boltzmann collision operator to model the translational motion of gas molecules, which has the ability…

Fluid Dynamics · Physics 2023-06-28 Qi Li , Jianan Zeng , Lei Wu

One of the central problems in the study of rarefied gas dynamics is to find the steady-state solution of the Boltzmann equation quickly. When the Knudsen number is large, i.e. the system is highly rarefied, the conventional iteration…

Computational Physics · Physics 2020-02-19 Wei Su , Lianhua Zhu , Peng Wang , Yonghao Zhang , Lei Wu

With growing interest in space exploration, optimized airfoil design has become increasingly important. However, airfoil design in rarefied gas flows remains underexplored because solving the Boltzmann equation formulated in a six…

Fluid Dynamics · Physics 2025-12-09 Xiaoda Li , Ruifeng Yuan , Yanbing Zhang , Lei Wu

Rooted from the gas kinetics, the lattice Boltzmann method is a powerful tool in modeling hydrodynamics. In the past decade, it has been extended to simulate the rarefied gas flow beyond the Navier-Stokes level, either by using the…

Fluid Dynamics · Physics 2017-08-30 Scott Lindsay , Wei Su , Haihu Liu , Lei Wu

Mode-based model-reduction is used to reduce the degrees of freedom of high dimensional systems, often by describing the system state by a linear combination of spatial modes. Transport dominated phenomena, ubiquitous in technical and…

Numerical Analysis · Mathematics 2020-02-28 Julius Reiss

An efficient third-order discrete unified gas kinetic scheme (DUGKS) with efficiency is presented in this work for simulating continuum and rarefied flows. By employing two-stage time-stepping scheme and the high-order DUGKS flux…

Fluid Dynamics · Physics 2018-02-28 Chen Wu , Chang Shu , Baochang Shi , Zhen Chen

We introduce reduced order methods as an efficient strategy to solve parametrized non-linear and time dependent optimal flow control problems governed by partial differential equations. Indeed, the optimal control problems require a huge…

Numerical Analysis · Mathematics 2023-08-08 Maria Strazzullo , Zakia Zainib , Francesco Ballarin , Gianluigi Rozza

For accurate simulations of rarefied gas flows around moving obstacles, we propose a cut cell method on Cartesian grids: it allows exact conservation and accurate treatment of boundary conditions. Our approach is designed to treat Cartesian…

Numerical Analysis · Mathematics 2016-04-20 Guillaume Dechristé , Luc Mieussens

This work proposes an adaptive structure-preserving model order reduction method for finite-dimensional parametrized Hamiltonian systems modeling non-dissipative phenomena. To overcome the slowly decaying Kolmogorov width typical of…

Numerical Analysis · Mathematics 2022-02-02 Jan S. Hesthaven , Cecilia Pagliantini , Nicolò Ripamonti

This paper proposes a novel computational framework for the solution of geometrically parametrised flow problems governed by the Stokes equation. The proposed method uses a high-order hybridisable discontinuous Galerkin formulation and the…

Numerical Analysis · Mathematics 2020-09-10 Ruben Sevilla , Luca Borchini , Matteo Giacomini , Antonio Huerta

A kinetic model is proposed for rarefied flows of molecular gas with rotational and temperature-dependent vibrational degrees of freedom. The model reduces to the Boltzmann equation for monatomic gas when the energy exchange between the…

Fluid Dynamics · Physics 2022-01-19 Qi Li , Lei Wu

We propose a probabilistic way for reducing the cost of classical projection-based model order reduction methods for parameter-dependent linear equations. A reduced order model is here approximated from its random sketch, which is a set of…

Numerical Analysis · Mathematics 2020-05-19 Oleg Balabanov , Anthony Nouy
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