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Cluster Analysis of Turbulent Premixed Combustion Using On-the-fly Flame Particle Tracking

Hatwar, M and Nayak, AS and Dave, HL and Aggarwal, U and Chaudhuri, S (2021) Cluster Analysis of Turbulent Premixed Combustion Using On-the-fly Flame Particle Tracking. In: Green Energy and Technology . pp. 389-413.

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Official URL: https://dx.doi.org/10.1007/978-981-15-5667-8_15


The recently developed flame particle tracking (FPT) technique18 has provided critical insights into turbulence�flame interactions from the viewpoint of an observer co-moving with the flame. So far, FPT was implemented and used as a post-processing tool which required saving the Eulerian fields of fluid velocity and other scalars, obtained from the direct numerical simulations (DNS), onto external storage media. The field data were stored at equal time intervals which were usually smaller than the Kolmogorov time scale to accurately track the trajectories of the flame particles. The FPT, therefore, became extremely demanding on the storage space requirements, especially with increase in the domain size and/or the turbulence Reynolds number. Thus, there is a considerable advantage in terms of data storage, without compromising the accuracy of particle tracking, by implementing the algorithm to track flame particles within the DNS solver. We refer to this implementation as �on-the-fly� FPT as the particle tracking is performed concomitantly with the DNS. In this paper, we report the details of the first implementation of on-the-fly FPT in an open-source reacting flow DNS solver�the Pencil Code. The results from on-the-fly FPT are validated by analyzing the time series of the scalar property which by definition is required to be conserved along the trajectories of the flame particles. Subsequently, we use on-the-fly FPT to investigate the dynamics of flame annihilation. As the flame surfaces interact with turbulence, the flame particles defined on them preferentially drift and cluster in the trailing, concave regions of the surface before annihilation. Analyzing such clustering phenomenon elucidates mechanisms like kinematic restoration and flame island formation that leads to the local flame annihilation events. © 2021, Springer Nature Singapore Pte Ltd.

Item Type: Journal Article
Publication: Green Energy and Technology
Publisher: Springer Science and Business Media Deutschland GmbH
Additional Information: The copyright of this article belongs to Springer Science and Business Media Deutschland GmbH
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited: 01 Oct 2020 06:44
Last Modified: 01 Oct 2020 06:44
URI: http://eprints.iisc.ac.in/id/eprint/66662

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