Non-thermal plasma represent a unique state of matter composed of neutral atoms and molecules, radicals, excited states, ions and electrons, with electrons typically having much higher energies than heavy species. There are many industrial, medical and aerospace applications of non-thermal plasma, such as pollution control, food processing, biomedical treatments and electric propulsion. Non-thermal plasma can be generated under diverse conditions, depending on e.g., the power source, electrode geometry and gas used. Numerical modeling is essential for investigating fundamental processes and for providing quantitative predictions for specific applications. However, applications often include multiscale and/or multiphysics dynamics. The resulting modeling challenges drive the ongoing development of novel algorithms and computational methods.
Conventional approaches for modeling non-thermal plasma include kinetic models, fluid models and global reaction-kinetic models. These models differ in their range of applicability, computational efficiency, and accuracy. It is important to choose the model and the numerical solution procedure according to the characteristics of the specific plasma problem, balancing the accuracy and efficiency of simulations.
Algorithmic developments include for example the construction of hybrid models (e.g., fluid-kinetic) and the application of various model reduction methods. There is also increasing interest in data-driven modeling and the application of machine learning techniques. Computationally, high-performance computing methods such as parallelization, adaptive-mesh-refinement (AMR), and graphical-processing-units (GPUs) are frequently used. A combination of efficient algorithms and HPC implementations will be required for simulating current and future applications of non-thermal plasma.
This Research Topic aims to collect research articles on novel methods for modeling non-thermal plasma. This includes applications of new algorithms, computational methods or model reduction techniques for specific non-thermal plasma problems, as well as improvements to existing algorithms and methods, for example, to account for modern computational hardware architectures. High-quality Original Research articles and Review articles are welcomed. Specific topics of interest include, but are not limited to:
1. Novel or improved modeling approaches for non-thermal plasma, including kinetic, fluid, global, hybrid and data-driven or data-augmented models. The benchmarking and/or verification of such novel models is encouraged.
2. Algorithmic developments, for example for the efficient numerical solution of partial differential equations (PDEs) in non-thermal plasma modeling.
3. Computational developments, for example, related to parallelization, GPU computing, adaptive computational methods, or the efficient use of modern computational hardware.
4. Papers describing current non-thermal plasma simulation codes, elucidating their algorithmic and computational design, applicability and usage.
Non-thermal plasma represent a unique state of matter composed of neutral atoms and molecules, radicals, excited states, ions and electrons, with electrons typically having much higher energies than heavy species. There are many industrial, medical and aerospace applications of non-thermal plasma, such as pollution control, food processing, biomedical treatments and electric propulsion. Non-thermal plasma can be generated under diverse conditions, depending on e.g., the power source, electrode geometry and gas used. Numerical modeling is essential for investigating fundamental processes and for providing quantitative predictions for specific applications. However, applications often include multiscale and/or multiphysics dynamics. The resulting modeling challenges drive the ongoing development of novel algorithms and computational methods.
Conventional approaches for modeling non-thermal plasma include kinetic models, fluid models and global reaction-kinetic models. These models differ in their range of applicability, computational efficiency, and accuracy. It is important to choose the model and the numerical solution procedure according to the characteristics of the specific plasma problem, balancing the accuracy and efficiency of simulations.
Algorithmic developments include for example the construction of hybrid models (e.g., fluid-kinetic) and the application of various model reduction methods. There is also increasing interest in data-driven modeling and the application of machine learning techniques. Computationally, high-performance computing methods such as parallelization, adaptive-mesh-refinement (AMR), and graphical-processing-units (GPUs) are frequently used. A combination of efficient algorithms and HPC implementations will be required for simulating current and future applications of non-thermal plasma.
This Research Topic aims to collect research articles on novel methods for modeling non-thermal plasma. This includes applications of new algorithms, computational methods or model reduction techniques for specific non-thermal plasma problems, as well as improvements to existing algorithms and methods, for example, to account for modern computational hardware architectures. High-quality Original Research articles and Review articles are welcomed. Specific topics of interest include, but are not limited to:
1. Novel or improved modeling approaches for non-thermal plasma, including kinetic, fluid, global, hybrid and data-driven or data-augmented models. The benchmarking and/or verification of such novel models is encouraged.
2. Algorithmic developments, for example for the efficient numerical solution of partial differential equations (PDEs) in non-thermal plasma modeling.
3. Computational developments, for example, related to parallelization, GPU computing, adaptive computational methods, or the efficient use of modern computational hardware.
4. Papers describing current non-thermal plasma simulation codes, elucidating their algorithmic and computational design, applicability and usage.