Simulation of real gas effects in supersonic methane jets using a tabulated equation of state with a discontinuous Galerkin spectral element method

Hempert, Fabian; Boblest, Sebastian; Ertl, Thomas; Sadlo, Filip; Offenhäuser, Philipp; Glass, Colin W.; Hoffmann, M.; Beck, Andrea; Munz, Claus‐Dieter; Iben, Uwe

doi:10.1016/j.compfluid.2016.12.024

Cited by 17 publications

(6 citation statements)

References 43 publications

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“…20 Nonetheless, several recent RANS studies for hydrogen 21 or both hydrogen and methane 22 have shifted the focus to high-pressure conditions, highlighting the necessity for real-gas thermodynamic modeling in the process. This was also recognized in one of the LES studies 19 and in the spectral elements based study of Hempert et al, 23 which compared underexpanded methane jet structure at the same pressure ratio but different pressure levels, both with ideal- and real-gas modeling. In Banholzer et al 21 the effect of injection and chamber temperatures on Mach disk location and jet tip penetration were investigated, whereas Banholzer et al 22 focused on the effect of pressure ratio on jet tip penetration, but only through variation in chamber pressure at fixed injection pressure.…”

Section: Introductionmentioning

confidence: 74%

The effect of high-pressure injection variations on the mixing state of underexpanded methane jets

Sakellarakis

Vera-Tudela

Doll

et al. 2020

International Journal of Engine Research

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This work presents a joint experimental and numerical study of global characteristics and mixing behavior of underexpanded methane jets at high-pressure conditions in a Constant Volume Chamber. Injection pressures of 200, 250, and 300 bar and pressure ratios of 4, 5, 6, 8, and 10 at each of those pressures have been investigated. Tracer LIF with acetone as tracer has been applied to experimentally quantify the mixing of methane and quiescent air. In order to exploit the symmetry of the configuration, accompanying simulations have been carried out in Reynolds-Averaged Navier-Stokes framework with the k – w SST turbulence model and real-gas modelling based on the Soave-Redlich-Kwong Equation of State has been employed to account for high-pressure corrections in thermodynamic and caloric properties. The experiments confirm the hyperbolic decay of axial fuel concentration and the Gaussian shape of traverse concentration profiles in the self-similar region of the jets, while simulation results match well with experimentally determined fuel concentration fields. It is found that scaling laws proposed in literature for steady-state jet propagation can qualitatively interpret the effect of injection variations on jet tip penetration and volume. Increasing pressure ratio at fixed injection pressure leads to the formation of slightly richer jets, with slightly smaller mass percentage in the range of air-to-fuel ratios most favorable to autoignition. By contrast, increasing pressure ratio at fixed chamber pressure leads to virtually identical Probability Distribution Functions of local air-to-fuel ratios and the same is observed when employing a fixed pressure ratio at higher pressure levels.

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Section: Introductionmentioning

confidence: 74%

The effect of high-pressure injection variations on the mixing state of underexpanded methane jets

Sakellarakis

Vera-Tudela

Doll

et al. 2020

International Journal of Engine Research

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“…• Multiphase and multicomponent capabilities, in which phase boundaries are tracked with a sharp interface approach [87] • Complex equations of state based on realistic models or tabulated data [88] • A Lagrangian particle tracking method for high order geometry, used in LES and DNS of particle laden flows [89] • Asymptotic consistent low Mach number schemes based on IMEX splittings [90] • Semi-implicit and fully implicit time integration schemes…”

Section: Discussionmentioning

confidence: 99%

FLEXI: A high order discontinuous Galerkin framework for hyperbolic-parabolic conservation laws

Krais¹,

Beck²,

Bolemann³

et al. 2019

Preprint

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High order (HO) schemes are attractive candidates for the numerical solution of multiscale problems occurring in fluid dynamics and related disciplines. Among the HO discretization variants, discontinuous Galerkin schemes offer a collection of advantageous features which have lead to a strong increase in interest in them and related formulations in the last decade. The methods have matured sufficiently to be of practical use for a range of problems, for example in direct numerical and large eddy simulation of turbulence. However, in order to take full advantage of the potential benefits of these methods, all steps in the simulation chain must be designed and executed with HO in mind. Especially in this area, many commercially available closed-source solutions fall short. In this work, we therefor present the FLEXI framework, a HO consistent, open-source simulation tool chain for solving the compressible Navier-Stokes equations in a high performance computing setting. We describe the numerical algorithms and implementation details and give an overview of the features and capabilities of all parts of the framework. Beyond these technical details, we also discuss the important, but often overlooked issues of code stability, reproducibility and user-friendliness. The benefits gained by developing an open-source framework are discussed, with a particular focus on usability for the open-source community. We close with sample applications that demonstrate the wide range of use cases and the expandability of FLEXI and an overview of current and future developments.

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“…At the same time, the artificial neural network can store and organize data and has good generalization ability. Therefore, in a production environment where large amounts of data have been collected, artificial neural networks can be used as an important technical means of constructing a digital twin prediction system [37,38]. The neural network goes through two steps, feed-forward and reverse propagation [39].…”

Section: Operation-based State Prediction Mechanism Based On Neural Networkmentioning

confidence: 99%

Construction Theory for a Building Intelligent Operation and Maintenance System Based on Digital Twins and Machine Learning

et al. 2022

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The operation and maintenance (O&M) of buildings plays an important role in ensuring that the buildings work normally, as well as reducing the damage caused by functional errors. There are obvious problems in the traditional O&M modality, and an effective way to solve them is to make the model smarter. In this paper, a digital twin framework for building operation is proposed, which consists of two key components: a digital twin O&M model and a machine learning algorithm. The process of establishing the digital twin model is introduced in detail, and the method is explained according to the structure, equipment, and energy consumption characteristics of the model. A mechanism of fusing the digital twin and machine learning algorithm is proposed and the prediction process based on an artificial neural network (ANN) is shown. Finally, based on a systematic summary of the modeling process and fusion mechanism, the development path and overall structure of the intelligent O&M system utilizing digital twins is proposed.

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Simulation of real gas effects in supersonic methane jets using a tabulated equation of state with a discontinuous Galerkin spectral element method

Cited by 17 publications

References 43 publications

The effect of high-pressure injection variations on the mixing state of underexpanded methane jets

The effect of high-pressure injection variations on the mixing state of underexpanded methane jets

FLEXI: A high order discontinuous Galerkin framework for hyperbolic-parabolic conservation laws

Construction Theory for a Building Intelligent Operation and Maintenance System Based on Digital Twins and Machine Learning

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