Modelling and Simulation

Computational techniques for describing and predicting plasma properties. Accurate and well benchmarked simulations and models can predict new power coupling and distribution mechanisms, excitation schemes and configurations. 

About the Research Area

Plasma modelling and simulations are essential tools in the field of plasmas, helping us understand and predict the behaviour of plasmas in various applications, from fusion energy to plasma processing. By utilising mathematical models and computer simulations, we can gain insight into the complex and dynamic behaviour of plasmas and develop new techniques and technologies to manipulate and control them. Plasma modelling and simulation techniques include particle-in-cell (PIC) simulations, fluid simulations and hybrid models, each with its own advantages and limitations for different types of plasma applications. Plasma simulations coupled with diagnostics are particularly powerful in gaining a more complete understanding of plasma behaviour, and thus optimise plasma sources and develop new plasma-based technologies.

Modelling and Simulation Publications


Improved buffered block forward backward method applied to 3D scattering problems. Mullen, M; Brennan, C; Downes, T. IET Conference Publications 2008

Design of a capillary viscometer with numerical and computational methods. Shah, A; Brabazon, D; Looney, L. International Journal of Manufacturing Technology and Management 2008

Plasma ionization in low-pressure radio-frequency discharges – Part II: Particle-in-cell simulation. Meige, A; O’Connell, D; Gans, T; Boswell, R.W. IEEE Transactions on Plasma Science 2008

A hybridized forward backward method applied to electromagnetic wave scattering problems. Mullen, M; Brennan, C; Downes, T. IEEE Transactions on Antennas and Propagation 2009

Numerical model for light propagation and light intensity distribution inside coated fused silica capillaries. Piasecki, T; MacKa, M; Paull, B; Brabazon, D. Optics and Lasers in Engineering 2011

Finite element method for predicting the cohesive strength of DLC film on 316L stainless steel by four point bend test and validation with experimental results. Morshed, M.M; Daniels, S.M; Hashmi, M.S.J. Advanced Materials Research 2011

Tailoring electron energy distribution functions through energy confinement in dual radio-frequency driven atmospheric pressure plasmas. Oneill, C; Waskoenig, J; Gans, T. Applied Physics Letters 2012

Topic 14+16: High-performance and scientific applications and extreme-scale computing (Introduction). Downes, T.P; Roller, S; Seitsonen, A.P; Valcke, S; Keyes, D; Sawley, M.-C; Schulthess, T; Shalf, J. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2013

Numerical effects on energy distribution functions in particle-in-cell simulations with Monte Carlo collisions: Choosing numerical parameters. Turner, M.M. Plasma Science and Technology 2013

Improved fluid simulations of radio-frequency plasmas using energy dependent ion mobilities. Greb, A; Niemi, K; O’Connell, D; Ennis, G.J; Macgearailt, N; Gans, T. Physics of Plasmas 2013

Theory for the self-bias formation in capacitively coupled plasmas excited by arbitrary waveforms. Lafleur, T; Chabert, P; Turner, M.M; Booth, J.P. Plasma Sources Science and Technology 2013

Comparison of a global model to semi-kinetic fluid simulations for atmospheric pressure radio-frequency plasmas. Niemi, K; Gans, T; O’Connell, D. Plasma Sources Science and Technology 2013