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PREDICTION OF PREMIXED INTERNAL COMBUSTION ENGINE MASS FRACTON BURNED PROFILES USING A PHYSICAL FORM OF THE WIEBE FUNCTION AND THE THEORY OF TURBULENT FLAME BRUSH THICKNESS DYNAMICS

Abstract Details

2020, Doctor of Philosophy, Ohio State University, Mechanical Engineering.
The goal of this work is to investigate a new approach for modeling the combustion process of a premixed internal combustion engine. The outcome is the development and validation of a simple, computationally-inexpensive model of the premixed engine combustion process which is capable of predicting the mean mass fraction burned (MFB) profiles of combustion without the extensive use of model calibration that is typically required of this class of modeling. One of the main contributions of this research is the development of a new flame brush thickness dynamics (FBTD) theory which allows the prediction of the transient turbulent flame speed when the statistical description of turbulence is known. The predicted transient turbulent flame speed is then passed in a re-derived form of the Wiebe function, referred to as the BRN model, to determine the instantaneous MFB of the mixture within the engine’s combustion chamber. This new low fidelity combustion model (BRN + FBTD) has been validated against three sets of data in this work. The first set is a theoretical comparison between the FBTD theory and instantaneous G-equation solutions across a range of turbulence parameters for a synthetic, frozen, turbulent flow field. The second being a comparison of a 0D engine simulator utilizing the BRN + FBTD combustion model against real engine cylinder pressure derived measurements of the mass fraction burned profile for a 3.5L GDI V6 engine. Lastly, the dynamics of the flame radius and flame brush thickness as predicted by BRN + FBTD are compared against high speed optical engine measurements on a laser sheet illuminated plane of an optically accessible 3.5L GDI V6 engine from the same family as the two previous datasets. In each case, the good agreement seen between simulation and experiment presented here suggests that the BRN + FBTD combustion model is capable of predicting the MFB profile without the hardware or condition specific calibrations typically required of this class of modeling.
Seung Hyun Kim, PhD (Advisor)
Shawn Midlam-Mohler, PhD (Advisor)
Marcello Canova, PhD (Committee Member)
Giorgio Rizzoni, PhD (Committee Member)
341 p.

Recommended Citations

Citations

  • Aquino, P. A. (2020). PREDICTION OF PREMIXED INTERNAL COMBUSTION ENGINE MASS FRACTON BURNED PROFILES USING A PHYSICAL FORM OF THE WIEBE FUNCTION AND THE THEORY OF TURBULENT FLAME BRUSH THICKNESS DYNAMICS [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1606987013001077

    APA Style (7th edition)

  • Aquino, Phillip. PREDICTION OF PREMIXED INTERNAL COMBUSTION ENGINE MASS FRACTON BURNED PROFILES USING A PHYSICAL FORM OF THE WIEBE FUNCTION AND THE THEORY OF TURBULENT FLAME BRUSH THICKNESS DYNAMICS. 2020. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1606987013001077.

    MLA Style (8th edition)

  • Aquino, Phillip. "PREDICTION OF PREMIXED INTERNAL COMBUSTION ENGINE MASS FRACTON BURNED PROFILES USING A PHYSICAL FORM OF THE WIEBE FUNCTION AND THE THEORY OF TURBULENT FLAME BRUSH THICKNESS DYNAMICS." Doctoral dissertation, Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1606987013001077

    Chicago Manual of Style (17th edition)