P-DRGEP: a novel methodology for the reduction of kinetics mechanisms for plasma-assisted combustion applications

Bellemans, André; Kincaid, Nicholas; Deak, Nicholas E.; Pepiot, Perrine; Bisetti, Fabrizio

doi:10.1016/j.proci.2020.06.363

Cited by 17 publications

(10 citation statements)

References 25 publications

(31 reference statements)

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“…The reduction procedure adopted here keeps the effective electron temperature almost unchanged as shown in Fig. 10a contrary to what was observed in [17]. This is a consequence of the use of an EEDF solver within the plasma reactors in our simulations.…”

Section: Resultsmentioning

confidence: 76%

“…The DRGEP method was recently applied in [17], where contrary to Eq. ( 5) the time evolution of electron temperature T e is governed by:…”

Section: Methodsmentioning

confidence: 99%

“…A trade-off between detailed and phenomenological models is to use chemical reduction: by choosing suitable targets and cases, accuracy is preserved while keeping the computational cost reasonable. This method has already proven its worth in a combustion framework [15,16] and is considered as an interesting basis for the reduction of plasma-combustion kinetic mechanism [17].…”

Section: Introductionmentioning

confidence: 99%

“…As the mechanism is rather computationally expensive for dimensional simulations, a reduction step is mandatory. In [17], an extension of the DRGEP [15] reduction method was employed to reduce the mechanism of [30]. In this work, the original DRGEP method developed in ARCANE [16] is successfully employed to reduce the detailed mechanism in Section 6 without the need of any plasma specific procedure by choosing suitable reduction cases.…”

Section: Introductionmentioning

confidence: 99%

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Plasma assisted combustion of methane-air mixtures: Validation and reduction

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Combustion and Flame

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Section: Resultsmentioning

confidence: 76%

“…The DRGEP method was recently applied in [17], where contrary to Eq. ( 5) the time evolution of electron temperature T e is governed by:…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Plasma assisted combustion of methane-air mixtures: Validation and reduction

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Cuenot

et al. 2022

Combustion and Flame

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“…The objective is to represent the reaction kinetics using a reduced number of variables that reflect the behavior of the full system. Recent work has investigated various data-driven reduction techniques to obtain surrogate representations of the detailed plasma-assisted combustion physics ranging from graph-based techniques [3] to correlation-based techniques using principal component analysis [2]. A first class of techniques is given by the graph-based methods, such as the Directed Relation Graph method with Error Propagation (DRGEP) [9].…”

Section: Introductionmentioning

confidence: 99%

A Machine-Learning Framework for Plasma-Assisted Combustion Using Principal Component Analysis and Gaussian Process Regression

Bellemans

Malik

Bisetti

et al. 2021

Advances in Uncertainty Quantification and Optimization Under Uncertainty With Aerospace Applications

Self Cite

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The intricate nature of detailed kinetic mechanisms for plasmaassisted combustion motivates the development of high-fidelity surrogates to simplify their use in extensive numerical simulations. This paper presents a machine-learning approach based on the coupling of Principal Component Analysis (PCA) with Gaussian Process Regression (GPR) to produce a reliable reduced-order representation of the detailed plasmacombustion physics. The entire state-space is expressed in function of a selected number of principal components using a non-linear Gaussian regression model. This machine-learning framework allows for a superior dimensionality compression compared to conventional data-driven reduction strategies based solely on principal component analysis. The performance of the present technique is assessed for the simulation of ethylene-air ignition by nanosecond repetitive pulsed discharges at conditions relevant to supersonic combustion and flame holding in scramjet cavities: temperatures from 600 K to 1000 K, and a pressure of 0.5 atm.

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