Engine Flow Calculations Using a Reynolds Stress Model in the Kiva-II Code

Lebrere, Laurent; Dillies, Bruno

doi:10.4271/960636

Cited by 14 publications

(9 citation statements)

References 23 publications

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“…POD is the decomposition of a time dependent velocity field u(x,t) (or scalar distribution) into a linear combination of M spatial basis functions; POD modes denoted by ψ (k) (x) and time-dependent coefficients a (k) (t), as defined in equation (3) (3) Where k = 1,2,…,M.…”

Section: The Proper Orthogonal Decomposition Methodologymentioning

confidence: 99%

“…Traditionally a Reynolds Averaged Navier-Stokes (RANS) approach to turbulence modelling has been used in ICE 3D-CFD modelling [2,3] due to fairy high Reynolds numbers, immaturity of Sub-Grid Scale (SGS) closure models and insufficient computing power, but this approach has inherent limitations. The time or Favre weighted averaging techniques cause information related to the fluctuating component of the flow field to be lost, making investigations into unsteady phenomenon like CCV difficult at best.…”

Section: Introductionmentioning

confidence: 99%

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Numerical Simulations of a GDI Engine Flow Using LES and POD

Beavis

Ibrahim

Malalasekera

2016

SAE Technical Paper Series

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This paper presents the findings from a numerical study of a gasoline direct injection engine flow using the Large Eddy Simulation (LES) modelling technique. The study is carried out over 30 successive engine cycles.The study illustrates how the more simple but robust Smagorinsky LES sub-grid scale turbulence model can be applied to a complex engine geometry with realistic engineering mesh size and computational expense whilst still meeting the filter width requirements to resolve the majority of large scale turbulent structures.Detailed description is provided here for the computational setup, including the initialisation strategy. The mesh is evaluated using a turbulence resolution parameter and shows the solution to generally resolve upwards of 80% of the turbulence kinetic energy. The calculated mean and fluctuating velocity components have been validated across multiple cutting planes at key crank angles within the intake stroke with good agreement obtained against experimental data and compared with RANS model predictions.A Proper Orthogonal Decomposition (POD) technique is then used to evaluate the in-cylinder flow field with the results focusing around the eigenvalue/energy content and time coefficients associated with each mode. The findings have shown how this technique can be used to assess the amount of small scale turbulence generated at the point of spark timing, the level of flow field cyclic variability and the degree of statistical convergence to be expected from an ensemble average result based on the number of cycles and the level of cyclic variability present in the flow field.

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Section: The Proper Orthogonal Decomposition Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Numerical Simulations of a GDI Engine Flow Using LES and POD

Beavis

Ibrahim

Malalasekera

2016

SAE Technical Paper Series

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“…Other turbulence representations have been explored, including complex Reynolds stress transport models [20,21], but lack of widespread use suggests that the benefits, if any, are marginal. Given that a similar picture exists in other areas of CFD application, this is scarcely surprising.…”

Section: Turbulence Modelingmentioning

confidence: 99%

State of the Art of Multi-Dimensional Modeling of Engine Reacting Flows

Gosman

1999

Oil & Gas Science and Technology - Rev. IFP

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RŽsumŽ Ñ ƒtat de lÕart de la modŽlisation multidimensionnelle pour les Žcoulements rŽactifs dans les moteurs Ñ Cet article dresse un aper•u de lÕŽtat de lÕart et des perspectives de lÕutilisation de la modŽlisation 3D pour lÕanalyse et le dŽveloppement des moteurs. Les aspects abordŽs comprennent lÕacquisition des gŽomŽtries, la gŽnŽration des maillages, les mŽthodologies numŽriques, la modŽlisation mathŽmatique des phŽnom•nes physiques importants, lÕexploitation des calculateurs parall•les et lÕapplication industrielle. Les conclusions principales de cette analyse font appara"tre les points suivants : Ð les mŽthodologies numŽriques et la gŽnŽration des maillages, associŽes au calcul parall•le, permettent maintenant de raccourcir notablement le cycle total de simulation ; Ð la modŽlisation physique a atteint sa maturitŽ dans la plupart des aspects relatifs ˆ la simulation de la combustion en allumage commandŽ ; en revanche, elle reste encore ˆ acquŽrir en ce qui concerne la combustion Diesel et certains aspects des processus reliŽs aux sprays ; Ð globalement, lÕutilisation de la simulation 3D pour la conception des moteurs est en forte augmentation ; Ð les dŽveloppements futurs, dont lÕutilisation de la LES, promettent une amŽlioration croissante des rŽsultats.Mots-clŽs : moteur, combustion, simulation 3D, aper•u. Abstract Ñ State of the Art of Multi-Dimensional Modeling of Engine Reacting Flows

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“…The practical utility of these models, which require very high computational power, may be questionable in those cases where many repeated computations are involved, as in design applications. Moreover, their quantitative precision, which require an appropriate "balanced precision" in all their sub-models, could even be inadequate for some applications 26 . By a literature analysis on the models devoted to engine control applications, an articulate picture emerges concerning structure, goals and complexity 1,4,5,9 , ranging from input-output black-box models, mostly oriented to control design, to gray-box mean-value models, with a simplified description of the most relevant physical processes 1,2,3 , up to complex 3-D fluid-dynamic models 4,5 .…”

Section: Introductionmentioning

confidence: 99%

“…By a literature analysis on the models devoted to engine control applications, an articulate picture emerges concerning structure, goals and complexity 1,4,5,9 , ranging from input-output black-box models, mostly oriented to control design, to gray-box mean-value models, with a simplified description of the most relevant physical processes 1,2,3 , up to complex 3-D fluid-dynamic models 4,5 . These classes of model substantially differ in terms of computational time and experimental data required: for the validation of the simplest black-box models, hundreds or thousands of engine data could be needed to compensate for the lack of physical information, resulting in high experimental effort and lower model flexibility; on the other hands, the computational cost of the detailed 3-D models is not yet compatible with most control applications, and their predictivity still questionable 26 . From these considerations, it emerges that in many cases a suitable solution could be represented by the adoption of a mixed approach, in order to combine the advantages of various kind of models.…”

Section: Introductionmentioning

confidence: 99%

Development and Identification of a Hierarchical System of Models for Rapid Prototyping of Si Engines

Arsie

Pianese

Rizzo

1999

Theory and Practice of Control and Systems

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The structure of a hierarchical system of models for model based optimization and rapid prototyping of control strategies in automotive spark ignition engines is presented. The advantages of a distributed and hybrid modeling approach are discussed, in order to meet the conflicting goals of high flexibility and precision with limited experimental cost and computational time. The critical role played by the identification phase is discussed, and a comparative analysis of the estimation procedures adopted during model validation is presented, analyzing their connections with the model development process.

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Engine Flow Calculations Using a Reynolds Stress Model in the Kiva-II Code

Cited by 14 publications

References 23 publications

Numerical Simulations of a GDI Engine Flow Using LES and POD

Numerical Simulations of a GDI Engine Flow Using LES and POD

State of the Art of Multi-Dimensional Modeling of Engine Reacting Flows

Development and Identification of a Hierarchical System of Models for Rapid Prototyping of Si Engines

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