SMARTA: A code based on the view-factor method for collisionless flows
We present our open-source code SMARTA. It can be used to compute internal and external collisionless gas flows when surface reflections are fully diffuse and gas sources are described by drifting Maxwell-Boltzmann distribution functions. The code is based on the view-factor method, analogous to the...
Gespeichert in:
Hauptverfasser: | , , |
---|---|
Format: | Tagungsbericht |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | We present our open-source code SMARTA. It can be used to compute internal and external collisionless gas flows when surface reflections are fully diffuse and gas sources are described by drifting Maxwell-Boltzmann distribution functions. The code is based on the view-factor method, analogous to the radiosity method commonly used in the fields of radiative heat transfer and computer graphics. In SMARTA, surfaces, including flow inlets and outlets, are represented using triangle meshes. In this work, we first show the derivation of the method. Then, we provide some details of the implementation and the algorithms used in the code to increase its efficiency and accuracy. Finally, we present some simple test cases that are used to verify the code and show its capabilities. These include a numerical experiment to analyze the convergence of the solution with the mesh size, as well as more practical applications to external and internal flows. Specifically, the computation of the aerodynamic pressure on a satellite in free molecular conditions, and the evaluation of the transmissivity of an intake for Air-Breathing Electric Propulsion. Strengths and weaknesses of the code, in relation to particle methods and panel methods, will be highlighted. We show that, in the cases where the underlying assumptions of the method are valid, SMARTA represents a simple to set-up alternative that can complement or even substitute the use of a Monte Carlo method. The main advantages are represented by the absence of stochastic noise in the results, and the possibility to reuse the view-factors for different computations. |
---|---|
ISSN: | 0094-243X 1551-7616 |
DOI: | 10.1063/5.0187438 |