Impact of state-specific flowfield modeling on atomic nitrogen radiation

Johnston, Christopher O.; Panesi, Marco

doi:10.1103/physrevfluids.3.013402

Cited by 19 publications

(10 citation statements)

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“…These are determined by the equilibrium equations presented in Chapter 1.2, Equation (1) and (2). Thus, for electron impact excitation between lower state i and excited state j, [17] = exp � −( − ) �…”

Section: Backward Ratesmentioning

confidence: 99%

“…Johnston and Panesi [17] then analysed the effects of state-specific flowfield modelling, sufficiently demonstrating where outdated approximations are not sufficient (such as the quasi-steady-state approach). By combining the wide consideration of gas interactions by Johnston in [4] with the well performing grouping methods by Panesi and Lani in [11], an efficient and accurate time dependant model was developed.…”

Section: Review Of State Specific Flow Solversmentioning

confidence: 99%

“…These formulations are then applied together, for both excitation and ionisation to define a final equation for the rate of change of a particular electronic species of the gas. This equation is the final stage of the physical modelling and is defined as [17] 1 :…”

Section: Master Equation For Electronic Speciesmentioning

confidence: 99%

“…A similar method of data fitting was taken for the equilibrium constant to determine the backwards rate, but fitting a function of a different form. This was given in [17] as,…”

Section: Reaction Rate Fittingmentioning

confidence: 99%

“…In his paper on the modelling of atomic nitrogen [17], Johnston suggested reducing the degree of grouping used by Panesi and Lani [11] from 8 to 7. There is strong support for this method, as the 7 th and 8 th distinct groups formed by the final position of the gas packet are only marginally separated.…”

Section: Distancementioning

confidence: 99%

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I can't thank Dr. Rowan Gollan enough for his assistance in this project. Already providing projects to, and ready to supervise 10 other students, he not only took on another, but has provided great insight into the physicality of the interactions in the model. Your experience in the complexities of modelling abstract physical phenomena made it so much more enjoyable trying to get my head around this thesis in the beginning months. You provided great insight into the implementation of similar cutting edge applications, and the way that those are modelled, which really gave me insight and drive to the how and why of this project. Thanks. Also, to my partner Jess Bilyj, who while finishing her own chemistry Ph D. thesis, has always been there for me to complain about simulations to. She's also sat there through my long explanations of the modelling, while I try to work things out. I love that I have someone so close who is also so scientifically minded, who while we don't really understand each other's work, it's nice to have someone to talk to about it.Finally, a quick thanks to Dr. Peter Jacobs, for your timely edits of my code when my inexperience in large scale coding projects showed through. It was also reassuring to have someone else interested in what was going on, and ready to answer any questions in implementing coding problems.

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Section: Backward Ratesmentioning

confidence: 99%

Section: Review Of State Specific Flow Solversmentioning

confidence: 99%

Section: Master Equation For Electronic Speciesmentioning

confidence: 99%

“…A similar method of data fitting was taken for the equilibrium constant to determine the backwards rate, but fitting a function of a different form. This was given in [17] as,…”

Section: Reaction Rate Fittingmentioning

confidence: 99%

Section: Distancementioning

confidence: 99%

See 3 more Smart Citations