The use of dynamic adaptive chemistry in combustion simulation of gasoline surrogate fuels

Liang, Long; Stevens, John G.; Raman, Sumathy; Farrell, John T.

doi:10.1016/j.combustflame.2009.02.008

Cited by 93 publications

(67 citation statements)

References 32 publications

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“…In this work, DAC has been extended to full CFD meshes with wall heat transfer. The reduction algorithm is executed before every call to the stiff solver according to the directed relation graph (DRG) method, which identifies the relevant species and reactions according to the thermodynamic conditions in each cell [13].…”

Section: Tabulation Of Dynamic Adaptive Chemistry (Tdac)mentioning

confidence: 99%

“…Hence, the sizes of mechanisms employed in practical simulations are generally limited to 50 species and 100 reactions [20,14] with a consequent lack in terms of accuracy mainly when advanced combustion modes, high EGR conditions and soot formation processes need to be computed. To make the use of more detailed mechanisms possible (up to 150 species for Diesel combustion) in a reasonable amount of time, the TDAC algorithm [3] was employed in this work that combines the ISAT and DAC techniques [25,13].…”

Section: Tabulation Of Dynamic Adaptive Chemistry (Tdac)mentioning

confidence: 99%

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Computational fluid dynamics modeling of combustion in heavy-duty diesel engines

D’Errico

Onorati

Hardy³

2014

International Journal of Engine Research

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The design and optimization stages of combustion systems for modern Heavy Duty Diesel engines must be supported by reliable CFD tools for the definition of the chamber geometry and injection strategy. To be fully predictive in terms of in-cylinder thermodynamics and flame structure, the employed combustion models must account for complex chemistry and turbulence-kinetics interactions. Within this context, the authors have implemented into an opensource code a model based on the multiple Representative Interactive Flamelets approach (mRIF ) and applied it to Diesel combustion simulations. New numerical techniques were integrated in the proposed mRIF model in order to speed up the CPU time in integrating chemistry and the β-pdf of the chemical species to compute composition in the CFD domain. A parallel validation was performed both with constant-volume and Heavy-Duty Diesel Engine experiments, selecting similar operating conditions. In such way, both flame structure and heat release rate predictions are analyzed and the model capabilities with respect to its set-up and mesh structure are assessed. IntroductionDevelopment of heavy duty Diesel engines is strongly affected by more and more demanding requirements for a contemporary reduction of both fuel consumption and pollutant emissions. To fulfill such objectives, a combination and integration of different technologies is necessary: efficient combustion systems, engine downsizing, new after-treatment devices and heat recovery [7,11,8,19]. In particular, fuel-air mixing and combustion processes must be investigated and optimized in detail since they both affect the quality of exhaust gases and energy conversion efficiency. Within this context, promising solutions appear to be the use of very high injection pressures (up to 3000 bar), further increase of full-load bmep, extension of engine operating range with advanced combustion 1

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Section: Tabulation Of Dynamic Adaptive Chemistry (Tdac)mentioning

confidence: 99%

Section: Tabulation Of Dynamic Adaptive Chemistry (Tdac)mentioning

confidence: 99%

Computational fluid dynamics modeling of combustion in heavy-duty diesel engines

D’Errico

Onorati

Hardy³

2014

International Journal of Engine Research

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“…the integration of large and stiff ODE systems, by storing those results and all the necessary data to retrieve them. The DAC method dynamically reduces the chemical mechanism is each cell and time-step before every call to the stiff solver according to the directed relation graph (DRG) method, which identifies the relevant species and reactions according to the thermodynamic conditions in each cell [44]. Combined operation of CCM, ISAT and DAC is schematically illustrated in Fig.…”

Section: Cpu Time Reductionmentioning

confidence: 99%

“…When using direct-integration, CPU time can be drastically reduced by the use of on-line techniques for mechanism reduction and tabulation [43,44,30,45] preserving the accuracy of the results and the flexibility of the method with respect to the adopted kinetic mechanism. In this work, a novel parallel methodology was developed which combines three different chemistry acceleration techniques: a multi-zone method, known as Chemistry Coordinate Mapping (CCM), Dynamic Adaptive Chemistry (DAC) and InSitu Adaptive Tabulation (ISAT).…”

Section: Cpu Time Reductionmentioning

confidence: 99%

“…Accuracy of the CCM method was extensively verified by the authors in [31,45] where it was applied to RANS and DNS non-premixed combustion simulations. To further reduce the CPU time for chemistry integration, the CCM method operates together with the TDAC algorithm [30,32] which combines the ISAT and DAC techniques [41,44,48]. The ISAT algorithm intends to reuse computationally demanding results, e.g.…”

Section: Cpu Time Reductionmentioning

confidence: 99%

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Towards the Use of Eulerian Field PDF Methods for Combustion Modeling in IC Engines

Lucchini¹,

D’Errico²,

Contino

et al. 2014

SAE Int. J. Engines

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Dear session organizers, authors thanks the reviewers for the very useful suggestion and comments to include the quality of the paper. The text was modified accordingly and changed parts were highlighted with the red color. A detailed response to reviewer comments follows. Response to Reviewer 1 Stochastic Eulerian field PDF methods are combined with a combination of acceleration strategies to reduce the computational cost associated with the use of large chemical mechanisms in CFD.The resulting model is used to simulate autoignition in a high-pressure turbulent spray combustion vessel under diesel-engine-like conditions. While the individual methods are not new, the combination of methods and their application to autoignition for enginerelevant conditions is novel, and would be of interest to the SAE audience. This is an approach that has significant potential for accurately capturing effects of turbulence-chemistry interaction over a wide range of engine operating conditions.Authors thanks the reviewer for the comments. The proposed combustion model based on Eulerian Stochastic fields will be continuosly developed and applied soon to more realistic engine studies. The title of the paper "Towards the Use of Eulerian Field PDF Methods for Combustion Modeling in IC Engines" should clearly indicate that this is a first attempt to apply what is considered by the combustion community to be one of the most complex and realistic models currently available to predict flame propagation. Presentation of preliminary results and discussion about them within the SAE world congress toghether with the major experts of the engine combustion community represents, to the authors' opinion, one of the best ways to understand the main advantages and drawbacks of such model and to find proper ways to improve it. For this reason, authors do not think this work is incomplete but it represents an important step towards the adoption of advanced models to predict combustion in IC engines. This reviewer's comment is not completely clear to the authors. The first sentence is just a general consideration, while the last one clearly states that this is just a preliminary work and for this reason further validation is required. For what concerns the model description, in this work it was not possible to include all the complete details about 1 how stochastic combustion models and related processes work. We recommend the reviewer to look at references [21][22][23][24][25][26][27][28] for further information. Eq. 1 illustrate the generic formulation of a transport equation for the joint pdf function inside the computational domain. Such equation is too complex to be solved directly (it is a transport equation for a function and not a scalar or vector field) and for this reason it is solved either with the help of Lagrangian particles (Lagrangian PDF methods) or by using Stochastic fields. The statement "summation is implied ..." is referred to divergence terms appearing in Eq. 1 and other transport equations included in this work as well. The W...

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A hybrid CPU‐GPU paradigm to accelerate reactive CFD simulations

Ghioldi,

Piscaglia

2024

Numerical Methods in Fluids

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The solution of reactive computational fluid dynamics (CFD) simulations is accelerated by the implementation of a hybrid central processing unit/graphics processing units (CPU/GPU) Finite Volume solver based on the operator‐splitting strategy, where the chemistry integration is treated independently of the flow solution. The integration of ordinary differential equations (ODEs) describing the finite‐rate chemical kinetics is solved by an adaptive multi‐block explicit solver on GPUs, while the load of the fluid solution is distributed on a multicore CPU algorithm. The resulting speed‐up for reactive CFD simulations is up to 10; the performance gain increases with the size of the mechanism. The proposed implementation is general and can be applied to any CFD problem where the governing equations for the fluid transport are coupled with an ODE system. Code validation is performed against reference solutions on a selection of test cases involving reacting flows.

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The use of dynamic adaptive chemistry in combustion simulation of gasoline surrogate fuels

Cited by 93 publications

References 32 publications

Computational fluid dynamics modeling of combustion in heavy-duty diesel engines

Computational fluid dynamics modeling of combustion in heavy-duty diesel engines

Towards the Use of Eulerian Field PDF Methods for Combustion Modeling in IC Engines

A hybrid CPU‐GPU paradigm to accelerate reactive CFD simulations

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