An Analysis on Time Scale Separation for Engine Simulations with Detailed Chemistry

Perini, Federico; Cantore, Giuseppe; Reitz, Rolf D.

doi:10.4271/2011-24-0028

Cited by 7 publications

(5 citation statements)

References 31 publications

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“…In order to provide a common simulation landscape for each of the mechanisms, 18 initial value problems are simulated for each of them, corresponding to a matrix of cases involving two initial reactor pressure values ( p 0 ∈ {2.0; 20.0}bar), three temperature values ( T 0 ∈ {750; 1000; 1500} K ), and three initial lambda values of the air-fuel mixture (λ ∈ {0.5; 1.0; 2.0}). , Each ignition case is finally integrated for a time interval corresponding to about 1.5 times the mixture autoignition time. Full details of the initialization matrix, including the species mass fractions, are given in the Simulation Details found in the Appendix.…”

Section: Resultsmentioning

confidence: 99%

An Analytical Jacobian Approach to Sparse Reaction Kinetics for Computationally Efficient Combustion Modeling with Large Reaction Mechanisms

Galligani²,

2012

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This study presents an analytical Jacobian formulation for detailed gas-phase reaction kinetics, suitable for accurate and computationally efficient combustion simulations using either skeletal or detailed reaction mechanisms. A general chemical kinetics initial value problem in constant volume environments is considered, where the gas-phase mixture thermodynamic properties are polynomial functions of temperature according to the JANAF standard. Three different reaction behaviors are accounted for, including modified Arrhenius kinetic law reactions, third-body collisions, and pressure-dependent reactions in Lindemann’s or Troe’s kinetic law forms. The integration of the chemistry ordinary differential equations (ODE) system is carried out using a software package specifically developed in Fortran language, and the solution is compared to a reference chemical kinetics library. Two analytical Jacobian formulations, an exact one and a sparser approximate one, are proposed and compared to numerical Jacobians computed by finite differences internally generated by a variety of commonly used stiff ODE solvers. The results show significant reductions in total computational times for the chemistry ranging from factors of 2 to more than 2 orders of magnitude for 29 species, 56 reactions to 2878 species, 8555 reactions, respectively. Finally, the code has been coupled to an engine combustion simulation software, where at each time step the chemistry ODE system is integrated in each cell of the computational grid, allowing 77% faster computations with a 160 species combustion mechanism.

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Section: Resultsmentioning

confidence: 99%

An Analytical Jacobian Approach to Sparse Reaction Kinetics for Computationally Efficient Combustion Modeling with Large Reaction Mechanisms

Galligani²,

2012

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“…The most important equations driving the sparse analytical Jacobian approach for combustion chemistry are described here. The implementation has been made within a framework, in Fortran, previously developed [14,16] for thermodynamic properties and reaction kinetics of gas-phase species. A full derivation of the Jacobian elements, also including the derivatives of the thermodynamic functions and potentials involved is described in detail in [12].…”

Section: The Sparse Analytical Jacobian Approachmentioning

confidence: 99%

“…In order to test each of the reference mechanisms at a variety of reactive conditions, a simulation landscape similar to that adopted in [16,23] was used. In particular, a matrix of 18 IVP integration cases was considered, corresponding to the possible combinations of two initial pressure values, ∈ 2.0; 20.0 , three initial air-fuel mixture equivalence ratios, ∈ 0.5; 1.0; 2.0 , and three initial reactor temperatures: ∈ 750; 1000; 1500 .…”

Section: Constant Volume Reactorsmentioning

confidence: 99%

Validation of a Sparse Analytical Jacobian Chemistry Solver for Heavy-Duty Diesel Engine Simulations with Comprehensive Reaction Mechanisms

Perini¹,

Galligani²,

Cantore³

et al. 2012

SAE Technical Paper Series

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The paper presents the development of a novel approach to the solution of detailed chemistry in internal combustion engine simulations, which relies on the analytical computation of the ordinary differential equations (ODE) system Jacobian matrix in sparse form. Arbitrary reaction behaviors in either Arrhenius, third-body or fall-off formulations can be considered, and thermodynamic gasphase mixture properties are evaluated according to the well-established 7-coefficient JANAF polynomial form. The current work presents a full validation of the new chemistry solver when coupled to the KIVA-4 code, through modeling of a single cylinder Caterpillar 3401 heavy-duty engine, running in two-stage combustion mode. The code has been tested on a wide range of simulations, at different injection timings, intake pressures, and EGR mass fractions, and considering two reaction mechanisms: a skeletal one with 29 species and 52 reactions, and a comprehensive, semi-detailed one with 160 species and 1540 reactions. The results show that the developed approach allows computational time savings of more than one order of magnitude in comparison to a reference chemistry solver, even with no reduction of the combustion mechanism size.

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“…The number of timescales involved in combustion processes can span more than 10 orders of magnitude [11]; as a consequence, the system's eigenvalues are very far from each other. This requires the ODE system integrator to pursue very small advancement steps in order to keep the solution error under control.…”

Section: Introductionmentioning

confidence: 98%

Computationally Efficient Simulation of Multicomponent Fuel Combustion Using a Sparse Analytical Jacobian Chemistry Solver and High-Dimensional Clustering

Perini

Krishnasamy

et al. 2014

Journal of Engineering for Gas Turbines and Power

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The need for more efficient and environmentally sustainable internal combustion engines is driving research towards the need to consider more realistic models for both fuel physics and chemistry. As far as compression ignition engines are concerned, phenome nological or lumped fuel models are unreliable to capture spray and combustion strategies outside o f their validation domains-typically, high-pressure injection and hightemperature combustion. Furthermore, the development of variable-reactivity combustion strategies also creates the need to model comprehensively different hydrocarbon families even in single fuel surrogates. From the computational point of view, challenges to achieving practical simulation times arise from the dimensions of the reaction mecha nism, which can be o f hundreds species even if hydrocarbon families are lumped into rep resentative compounds and, thus, modeled with nonelementary, skeletal reaction pathways. In this case, it is also impossible to pursue further mechanism reductions to lower dimensions, central processing unit (CPU) times for integrating chemical kinetics in internal combustion engine simulations ultimately scale with the number of cells in the grid and with the cube number of species in the reaction mechanism. In the present work, two approaches to reduce the demands of engine simulations with detailed chemistry are presented. The first one addresses the demands due to the solution of the chemistry ordi nary differential equation (ODE) system, and features the adoption of SpeedCHEM, a newly developed chemistry package that solves chemical kinetics using sparse analytical Jacobians. The second one aims to reduce the number of chemistry calculations by bin ning the computational fluid dynamics (CFD) cells of the engine grid into a subset of clusters, where chemistry is solved and then mapped back to the original domain. In par ticular, a high-dimensional representation of the chemical state space is adopted for keeping track of the different fuel components, and a newly developed bounding-boxconstrained k-means algorithm is used to subdivide the cells into reactively homogeneous clusters. The approaches have been tested on a number of simulations featuring multicomponent diesel fuel surrogates and different engine grids. The results show that signifi cant CPU time reductions, of about 1 order of magnitude, can be achieved without loss of accuracy in both engine performance and emissions predictions, prompting for their applicability to more refined or full-sized engine grids.

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An Analysis on Time Scale Separation for Engine Simulations with Detailed Chemistry

Cited by 7 publications

References 31 publications

An Analytical Jacobian Approach to Sparse Reaction Kinetics for Computationally Efficient Combustion Modeling with Large Reaction Mechanisms

An Analytical Jacobian Approach to Sparse Reaction Kinetics for Computationally Efficient Combustion Modeling with Large Reaction Mechanisms

Validation of a Sparse Analytical Jacobian Chemistry Solver for Heavy-Duty Diesel Engine Simulations with Comprehensive Reaction Mechanisms

Computationally Efficient Simulation of Multicomponent Fuel Combustion Using a Sparse Analytical Jacobian Chemistry Solver and High-Dimensional Clustering

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