An engine size–scaling method for kinetically controlled combustion strategies

Abstract

A substantial amount of research has recently focused on kinetically controlled combustion strategies such as reactivity-controlled compression ignition combustion. These strategies are promising methods to achieve high efficiency with near-zero NOx and soot emissions; however, despite promising results, very few attempts have been made to develop size-scaling relationships that would allow these results to be generalized to any engine design. Engine design is a long and arduous process that requires a substantial amount of experimental work. Consequently, it is of interest to develop scaling laws that allow results from one engine to be extrapolated to new designs. Several scaling laws have been proposed for diffusion combustion (i.e. mixing limited) that scale parameters such as liquid length and lift-off length. Such parameters have been deemed unimportant for highly premixed low-temperature combustion strategies; thus, a new methodology is needed. The present effort uses a combination of detailed computational fluid dynamics simulations and engine experiments in two engines with different bore sizes to develop a new engine size–scaling methodology for low-temperature kinetically controlled combustion strategies. The effects of pressure, temperature, and turbulence timescales are explored in order to replicate the large-bore engine performance in a small-bore engine. A size-scaling relationship based on the ignition timescale is proposed and used to generalize the results to an arbitrary bore size and fuel combination.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 15, 2018
Source ID
10.1177/1468087418786130

Entities

People

  • Dan Delvescovo
  • Flavio Dal Forno Chuahy
  • Jamen Olk
  • Sage L. Kokjohn

Organizations

  • Oakland University
  • Office of Naval Research Global
  • University of Wisconsin–Madison

Tags

Fields of Study

  • Physics

Readers

  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development
  • Internal Combustion Engine (ICE) Technology.