Integration of on‐the‐fly kinetic reduction with multidimensional CFD

He, Kebin; Ierapetritou, Marianthi G.; Androulakis, Ioannis P.

doi:10.1002/aic.12072

Cited by 16 publications

(7 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A two-dimensional axial symmetric mesh (Figure 1) with 1052 computational cells at bottom dead center (BDC) is employed in KIVA-3V to simulate HCCI engine combustion. The on-thefly reduction is integrated with KIVA-3V and CHEMKIN code to generate locally accurate reduced mechanism for each computational cell during each time step, 39 and DVODE is applied to numerically solve the resulting ODE system based on each reduced mechanism.…”

Section: ■ Proposed Simulation Frameworkmentioning

confidence: 99%

Comparison of Biodiesel Performance Based on HCCI Engine Simulation Using Detailed Mechanism with On-the-fly Reduction

et al. 2012

Self Cite

View full text Add to dashboard Cite

Biodiesel is a complex mixture of long-chain methyl esters. Accurate numerical study of biodiesel combustion requires detailed chemistry of large biodiesel surrogates representing realistic biodiesel fuels. However, the detailed kinetic mechanisms for large biodiesel surrogates involve large number of species and reactions, leading to extremely expensive or even infeasible computation when incorporated in engine CFD (computational fluid dynamics) calculations. In this study, the scheme of on-the-fly mechanism reduction incorporated with engine CFD code KIVA-3V is first extended to two large biodiesel surrogate mechanisms, namely methyl decanoate and methyl-9-decenoate. Detailed combustion and engine performance characterization for biodiesel fuels are enabled, and the computational intensity is significantly reduced with satisfactory accuracy. In the simulations, lower CO and NO emissions and lower engine power are observed for biodiesel surrogates. Combustion features such as early oxidation of ester groups are also well captured. This work provides the insight to study combustion and engine operation of complex fuels on the basis of detailed chemistry with efficient mechanism reduction technique.

show abstract

Section: ■ Proposed Simulation Frameworkmentioning

confidence: 99%

Comparison of Biodiesel Performance Based on HCCI Engine Simulation Using Detailed Mechanism with On-the-fly Reduction

et al. 2012

Self Cite

View full text Add to dashboard Cite

show abstract

“…For example, the oxidation of n-heptane contains 560 species and 2539 reactions [21]. Previous studies have demonstrated that even with mechanisms with species less than 50, over 90% of the CPU time was consumed in solving the ODE systems in the reactive flow calculation [22]. A solution to this problem is to reduce the reaction mechanism.…”

Section: Introductionmentioning

confidence: 98%

Combustion-response mapping procedure for internal-combustion engine emissions

Korakianitis

Imran

Chung³

et al. 2015

Applied Energy

View full text Add to dashboard Cite

“…Moreover, it is usually impossible to measure the concentrations of all the kinetically significant chemical species . Numerically solving these large systems of differential equations in a reasonable time also remains a challenge, in particular when these models need to be implemented in computational fluid dynamics (CFD) codes .…”

Section: Introductionmentioning

confidence: 99%

Automatic Mechanism and Kinetic Model Generation for Gas‐ and Solution‐Phase Processes: A Perspective on Best Practices, Recent Advances, and Future Challenges

Vijver

Vandewiele

Bhoorasingh

et al. 2015

Int J of Chemical Kinetics

113

View full text Add to dashboard Cite

Completely automated mechanism generation of detailed kinetic models is within reach in the coming decade. The recent developments in this field of chemical reaction engineering are anticipated to lead to some groundbreaking discoveries in the future, extending our fundamental understanding and resolving many of today's society problems such as energy production and conversion, emission reduction, greener chemical production processes, etc. In the present review, the focus is on the core of these automated mechanism generation for gas‐phase and solution‐phase processes that is on how the reaction kinetics and thermodynamic and transport properties of species are estimated and calculated starting from the fundamental elements of the software. With tasks such as the definition of reaction rules and reaction families, the unambiguous representation of species, and the choice of different termination criteria, generating a good reaction mechanism is still not as simple as pressing a “run” button. One of the main challenges that still needs to be overcome is how to deal with data scarcity and the combination with affordable computational chemistry calculations seems the logical step forward. The best practices are illustrated in a butane pyrolysis case study, which also exposes the challenges in the field of automatic kinetic model generation.

show abstract

Integration of on‐the‐fly kinetic reduction with multidimensional CFD

Cited by 16 publications

References 43 publications

Comparison of Biodiesel Performance Based on HCCI Engine Simulation Using Detailed Mechanism with On-the-fly Reduction

Comparison of Biodiesel Performance Based on HCCI Engine Simulation Using Detailed Mechanism with On-the-fly Reduction

Combustion-response mapping procedure for internal-combustion engine emissions

Automatic Mechanism and Kinetic Model Generation for Gas‐ and Solution‐Phase Processes: A Perspective on Best Practices, Recent Advances, and Future Challenges

Contact Info

Product

Resources

About