{"title":"ANEMONE: A framework for three-dimensional simulations of solid-state electroaerodynamic propulsion systems","authors":"Hisaichi Shibata , Soya Shimizu , Takahiro Nozaki","doi":"10.1016/j.cpc.2025.109749","DOIUrl":null,"url":null,"abstract":"<div><div>Solid-state electro-aerodynamic propulsion systems are devices that utilize atmospheric pressure corona discharge and have been actively researched in recent years as a means of achieving silent drones. However, these systems contain multiple, widely disparate time and spatial scales. Therefore, the governing equations of the systems, a three-component plasma fluid model that considers the presence of electrons, positive ions, and negative ions, constitute a stiff non-linear system of partial differential equations, challenging to solve. Here, we have developed an ANEMONE simulator capable of numerically estimating the corona inception voltage and energy conversion efficiency in three-dimensional solid-state electro-aerodynamic propulsion systems. Specifically, on the basis of the governing equations, we adopted the method of characteristics and the perturbation method to obtain the sub-problems. Furthermore, we have successfully obtained the integral equations, making the sub-problems easier to solve. Finally, we validated the prediction results based on the theoretical results in a previous study. Remarkably, ANEMONE is the first simulator in the world which predicted the two representative performance (i.e., the corona inception voltage and energy conversion efficiency) of fully three-dimensional propulsion systems.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> ANEMONE</div><div><em>CPC Library link to program files:</em> <span><span><span>https://doi.org/10.17632/2sxsg2pmyp.1</span></span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> MIT</div><div><em>Programming language:</em> C++</div><div><em>Nature of problem:</em> Solid-state electro-aerodynamic propulsion system [1] ionizes the ambient air and can propel silent drones. For the rapid-prototyping of the system, it is important to utilize numerical simulation, but the spatial and temporal scales of the system are diverse; hence, the corresponding governing equations (e.g. the three-component plasma fluid model which can simultaneously consider electrons, positive and negative ions) are too stiff to solve. For example, the overall spatial scale of the system is the order of meters, while the scale of the electrodes is the order of micrometers. Moreover, the ions move between electrodes in the order of milliseconds, while the Maxwell dielectric relaxation time scale is in the order of nanoseconds.</div><div><em>Solution method:</em> For the issue of the spatial scales, we adopt a three-dimensional hierarchical Cartesian grid method together with the adaptive mesh refinement method. Moreover, this leads fully automatic mesh generation and ensures the grid convergence. For the issue of the temporal scales, we adopt the perturbation method [2] combined with the method of characteristics. This can decompose the original problem into many subproblems easy to solve.</div></div><div><h3>References</h3><div><ul><li><span>[1]</span><span><div>Haofeng Xu, et al., Flight of an aeroplane with solid-state propulsion, Nature 563 (7732) (2018) 532–535.</div></span></li><li><span>[2]</span><span><div>Hisaichi Shibata, et al., Performance prediction of electrohydrodynamic thrusters by the perturbation method, Phys. Plasmas 23 (5) (2016).</div></span></li></ul></div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"315 ","pages":"Article 109749"},"PeriodicalIF":3.4000,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Physics Communications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010465525002516","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Solid-state electro-aerodynamic propulsion systems are devices that utilize atmospheric pressure corona discharge and have been actively researched in recent years as a means of achieving silent drones. However, these systems contain multiple, widely disparate time and spatial scales. Therefore, the governing equations of the systems, a three-component plasma fluid model that considers the presence of electrons, positive ions, and negative ions, constitute a stiff non-linear system of partial differential equations, challenging to solve. Here, we have developed an ANEMONE simulator capable of numerically estimating the corona inception voltage and energy conversion efficiency in three-dimensional solid-state electro-aerodynamic propulsion systems. Specifically, on the basis of the governing equations, we adopted the method of characteristics and the perturbation method to obtain the sub-problems. Furthermore, we have successfully obtained the integral equations, making the sub-problems easier to solve. Finally, we validated the prediction results based on the theoretical results in a previous study. Remarkably, ANEMONE is the first simulator in the world which predicted the two representative performance (i.e., the corona inception voltage and energy conversion efficiency) of fully three-dimensional propulsion systems.
Program summary
Program Title: ANEMONE
CPC Library link to program files:https://doi.org/10.17632/2sxsg2pmyp.1
Licensing provisions: MIT
Programming language: C++
Nature of problem: Solid-state electro-aerodynamic propulsion system [1] ionizes the ambient air and can propel silent drones. For the rapid-prototyping of the system, it is important to utilize numerical simulation, but the spatial and temporal scales of the system are diverse; hence, the corresponding governing equations (e.g. the three-component plasma fluid model which can simultaneously consider electrons, positive and negative ions) are too stiff to solve. For example, the overall spatial scale of the system is the order of meters, while the scale of the electrodes is the order of micrometers. Moreover, the ions move between electrodes in the order of milliseconds, while the Maxwell dielectric relaxation time scale is in the order of nanoseconds.
Solution method: For the issue of the spatial scales, we adopt a three-dimensional hierarchical Cartesian grid method together with the adaptive mesh refinement method. Moreover, this leads fully automatic mesh generation and ensures the grid convergence. For the issue of the temporal scales, we adopt the perturbation method [2] combined with the method of characteristics. This can decompose the original problem into many subproblems easy to solve.
References
[1]
Haofeng Xu, et al., Flight of an aeroplane with solid-state propulsion, Nature 563 (7732) (2018) 532–535.
[2]
Hisaichi Shibata, et al., Performance prediction of electrohydrodynamic thrusters by the perturbation method, Phys. Plasmas 23 (5) (2016).
期刊介绍:
The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper.
Computer Programs in Physics (CPiP)
These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged.
Computational Physics Papers (CP)
These are research papers in, but are not limited to, the following themes across computational physics and related disciplines.
mathematical and numerical methods and algorithms;
computational models including those associated with the design, control and analysis of experiments; and
algebraic computation.
Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.