Reduced Order Modeling of Rotational Detonation Engines

Humble, Jenna; Sardeshmukh, Swanand V.; Heister, Stephen D.

doi:10.2514/6.2019-0201

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…Consequentially, several research groups have developed reduced-order modeling approaches that adequately predict trends at a fraction of the computational cost. Such models exist for recreating the RDE canonical flowfield [46,47], predicting thermodynamic trends [48], predicting application-based propulsive performance [49], or reproducing the dynamics of the waves [25,50,51] with varying degrees of success. However, because of the multi-scale nature of the RDE and the intricate interactions of its fundamental physical processes, these modeling efforts are often constrained to geometry, propellant, or mode-specific operating regimes, with a priori knowledge of wave topology or detonation structure.…”

Section: B Theoretical and Computational Considerationsmentioning

confidence: 99%

Modeling Thermodynamic Trends of Rotating Detonation Engines

Koch,

Kutz

2020

Preprint

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The formation of a number of co-and counter-rotating coherent combustion wave fronts is the hallmark feature of the Rotating Detonation Engine (RDE). The engineering implications of wave topology are not well understood nor quantified, especially with respect to parametric changes in combustor geometry, propellant chemistry, and injection and mixing schemes. In this article, a modeling framework that relates the time and spacial scales of the RDE to engineering performance metrics is developed and presented. The model is built under assumptions of backpressure-insensitivity and nominally choked gaseous propellant injection. The Euler equations of inviscid, compressible fluid flow in one dimension are adapted to model the combustion wave dynamics along the circumference of an annular-type rotating detonation engine. These adaptations provide the necessary mass and energy input and output channels to shape the traveling wave fronts and decaying tails. The associated unit processes of injection, mixing, combustion, and exhaust are all assigned representative time scales necessary for successful wave propagation. We find that the separation, or lack of, these time scales are responsible for the behavior of the system, including wave co-and counterpropagation and bifurcations between these regimes and wave counts. Furthermore, as there is no imposition of wave topology, the model output is used to estimate the net available mechanical work output and thermodynamic efficiency from the closed trajectories through pressure-volume and temperature-entropy spaces. These metrics are investigated with respect to variation in the characteristic scales for the RDE unit physical processes.

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Section: B Theoretical and Computational Considerationsmentioning

confidence: 99%

Modeling Thermodynamic Trends of Rotating Detonation Engines

Koch,

Kutz

2020

Preprint

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“…The computational cost of simulations can quickly become prohibitive and it typically requires high-performance computing architectures for even moderate lengths of simulation time. Consequentially, ROMs have been developed, with varying degrees of success, for recreating the RDE canonical flowfield [25,26], predicting thermodynamic trends [27], predicting application-based propulsive performance [28], or reproducing the dynamics of the waves [29,30,7,8]. However, because of the multi-scale nature of the RDE and the intricate interactions of its fundamental physical processes, these modeling efforts are often constrained to geometry, propellant, or mode-specific operating regimes, with the imposition of wave topology or detonation structure.…”

Section: Introductionmentioning

confidence: 99%

Data-driven Modeling of Rotating Detonation Waves

Mendible,

Koch,

Lange

et al. 2020

Preprint

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The direct monitoring of a rotating detonation engine (RDE) combustion chamber has enabled the observation of combustion front dynamics that are composed of a number of coand/or counter-rotating coherent traveling shock waves whose nonlinear mode-locking behavior exhibit bifurcations and instabilities which are not well understood. Computational fluid dynamics simulations are ubiquitous in characterizing the dynamics of RDE's reactive, compressible flow. Such simulations are prohibitively expensive when considering multiple engine geometries, different operating conditions, and the long-time dynamics of the mode-locking interactions. Reduced-order models (ROMs) provide a critically enabling simulation framework because they exploit low-rank structure in the data to minimize computational cost and allow for rapid parameterized studies and long-time simulations. However, ROMs are inherently limited by translational invariances manifest by the combustion waves present in RDEs. In this work, we leverage machine learning algorithms to discover moving coordinate frames into which the data is shifted, thus overcoming limitations imposed by the underlying translational invariance of the RDE and allowing for the application of traditional dimensionality reduction techniques. We explore a diverse suite of data-driven ROM strategies for characterizing the complex shock wave dynamics and interactions in the RDE. Specifically, we employ the dynamic mode decomposition and a deep Koopman embedding to give new modeling insights and understanding of combustion wave interactions in RDEs.

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Reduced Order Modeling of Rotational Detonation Engines

Cited by 2 publications

References 2 publications

Modeling Thermodynamic Trends of Rotating Detonation Engines

Modeling Thermodynamic Trends of Rotating Detonation Engines

Data-driven Modeling of Rotating Detonation Waves

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