Acceleration of the chemistry solver for modeling DI engine combustion using dynamic adaptive chemistry (DAC) schemes

Shi, Yu; Liang, Long; Ge, Haiwen; Reitz, Rolf D.

doi:10.1080/13647830903548834

Cited by 71 publications

(61 citation statements)

References 32 publications

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“…It has also been successfully coupled with the DAC scheme and parallelized using a load balancing scheme [18]. It was found in these studies that significant amounts of computational time were saved with the adaptive multigrid chemistry model.…”

Section: Multigrid Modelmentioning

confidence: 99%

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A Two-Zone Multigrid Model for SI Engine Combustion Simulation Using Detailed Chemistry

Juneja²,

Shi

et al. 2010

Journal of Combustion

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An efficient multigrid (MG) model was implemented for spark-ignited (SI) engine combustion modeling using detailed chemistry. The model is designed to be coupled with a level-set-G-equation model for flame propagation (GAMUT combustion model) for highly efficient engine simulation. The model was explored for a gasoline direct-injection SI engine with knocking combustion. The numerical results using the MG model were compared with the results of the original GAMUT combustion model. A simpler one-zone MG model was found to be unable to reproduce the results of the original GAMUT model. However, a two-zone MG model, which treats the burned and unburned regions separately, was found to provide much better accuracy and efficiency than the one-zone MG model. Without loss in accuracy, an order of magnitude speedup was achieved in terms of CPU and wall times. To reproduce the results of the original GAMUT combustion model, either a low searching level or a procedure to exclude hightemperature computational cells from the grouping should be applied to the unburned region, which was found to be more sensitive to the combustion model details.

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Section: Multigrid Modelmentioning

confidence: 99%

“…This algorithm has been validated on diesel engine simulations and has proven to be very efficient [18,34].…”

Section: Adaptive Load-balancing Algorithm For Parallelizationmentioning

confidence: 99%

A Two-Zone Multigrid Model for SI Engine Combustion Simulation Using Detailed Chemistry

Juneja²,

Shi

et al. 2010

Journal of Combustion

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“…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%

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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“…The efficiency of the graph search algorithm is also an important factor due to the recent use of DRGEP in dynamic skeletal reduction approaches [10][11][12]. In the worst case, DRGEP is applied at every spatial grid location and each time step to generate locally relevant skeletal mechanisms, although as Shi et al [12] demonstrated this can be eased by combining dynamic DRGEP-based reduction with an adaptive multi-grid chemistry model.…”

Section: Introductionmentioning

confidence: 99%

“…Development of this approach has since focused on variants of the method [5][6][7][8], but DRG with error propagation (DRGEP) in particular has received much attention [6,[8][9][10][11][12][13]. The DRGEP differs mainly from DRG in that it takes error propagation down graph pathways into account.…”

Section: Introductionmentioning

confidence: 99%

On the importance of graph search algorithms for DRGEP-based mechanism reduction methods

Niemeyer

Sung

2011

Combustion and Flame

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The importance of graph search algorithm choice to the directed relation graph with error propagation (DRGEP) method is studied by comparing basic and modified depth-first search, basic and R-value-based breadth-first search (RBFS), and Dijkstra's algorithm. By using each algorithm with DRGEP to produce skeletal mechanisms from a detailed mechanism for nheptane with randomly-shuffled species order, it is demonstrated that only Dijkstra's algorithm and RBFS produce results independent of species order. In addition, each algorithm is used with DRGEP to generate skeletal mechanisms for n-heptane covering a comprehensive range of autoignition conditions for pressure, temperature, and equivalence ratio. Dijkstra's algorithm combined with a coefficient scaling approach is demonstrated to produce the most compact skeletal mechanism with a similar performance compared to larger skeletal mechanisms resulting from the other algorithms. The computational efficiency of each algorithm is also compared by applying the DRGEP method with each search algorithm on the large detailed mechanism for n-alkanes covering n-octane to n-hexadecane with 2115 species and 8157 reactions. Dijkstra's algorithm implemented with a binary heap priority queue is demonstrated as the most efficient method, with a CPU cost two orders of magnitude less than the other search algorithms.

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Acceleration of the chemistry solver for modeling DI engine combustion using dynamic adaptive chemistry (DAC) schemes

Cited by 71 publications

References 32 publications

A Two-Zone Multigrid Model for SI Engine Combustion Simulation Using Detailed Chemistry

A Two-Zone Multigrid Model for SI Engine Combustion Simulation Using Detailed Chemistry

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

On the importance of graph search algorithms for DRGEP-based mechanism reduction methods

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