Publications by topic
Automatic Mechanism Generation:
From an extensive database of molecular and reaction chemistry, an automatic means of generating oxidation mechanisms, valid for both high and low regimes, for a wide range of species is presented. This work is a key component in developing large hydrocarbon, linear and branched, and aromatic mechanisms for surrogate fuel simulations of gasoline, diesel, jet-a and bio-fuels. The following papers show applications and development of the database of crucial oxidative reaction kinetics spanning a wide range of temperatures and conditions.
1. Hexadecane mechanisms: Comparison of hand-generated and automatically generated with pathways, Mersin, I. E., Blurock, E., Soyhan, H. S., & Konnov, A., Fuel, 115, 132-144 (2014). DOI:10.1016/j.fuel.2013.06.055
2. Development of detailed chemical kinetic models for cleaner combustion, Editors: F. Battin-Leclerc, J. M. Simmie, E. Blurock, ISBN: 978-1-4471-5306-1 (Print) 978-1-4471-5307-8 (Online), Springer, 2013
a. Chapter 1: Introduction, Battin-Leclerc, Frédérique; Blurock, Edward S.; Simmie, John M.; Alzueta, Maria U.; Tomlin, Alison S.; Olzmann, Matthias
b. Chapter 2: Modeling Combustion with Detailed Kinetic Mechanisms, Blurock, Edward; Battin-Leclerc, Frédérique
c. Chapter 3: Automatic Generation of Detailed Mechanisms, Blurock, Edward; Battin-Leclerc, Frédérique; Faravelli, Tiziano; Green, William H.
3. Towards cleaner internal combustion engines through groundbreaking detailed chemical kinetic models, Frédérique Battin-Leclerc, Edward Blurock, René Fournet a Pierre-Alexandre Glaude, Olivier Herbinet and Baptiste Sirjean, Chemical Society Reviews, 40 4762-4782 (2011).
4. Automatic Generation of a Detailed Mechanism for the Oxidation of n-Decane, Moreac, G., Blurock, Edward S., and Mauss, F.; Combustion Science Technology 178: 2025-2038 (2006).
5. Detailed Mechanism Generation 1: Generalized Reactive Properties as Reaction Class Substructures, Blurock, Edward S.; J. of Chemical Information and Computer Sciences, 44:1336-1347 (2004).
6. Detailed Mechanism Generation 2.: Aldehydes, ketones and olefins, Blurock, Edward S., J. Chemical Information and Computer Sciences, 44:1348-1357 (2004).
7. Reaction: System for Modeling Chemical Reactions, Blurock, Edward S.; J. Chem. Inf. Comput. Sci., 35:607-616 (1995).
Mechanism Characterization and Reduction
This work involves a multi-strategy machine learning approach to automatically produce a viable adaptive chemistry method applied to an engine simulation. A fuzzy logic based machine learning clustering and a decision tree technique is applied. Another characterization of the ignition process is through the finding of generic curves. All are used as the basis of mechanism characterization and reduction:
1. Phase Optimized Skeletal Mechanisms for Engine Simulation, Turner, Blurock, Edward S., Martin, Mauss, Fabian; Combustion Theory and Modeling, 14:295-313(2010).
2. Automatic Characterization of Ignition Processes with Machine Learning Clustering Techniques, Blurock, Edward S.; International Journal of Chemical Kinetics, 38:621-633 (2006).
3. Characterizing Complex Reaction Mechanisms using Machine Learning Clustering Techniques, Blurock, Edward S., International Journal of Chemical Kinetics, 36:107-118 (2003).
4. Towards Ignition Curve Parameterization: Non-linearity of Ignition Progress and Generic Ignition Curves, Blurock, Edward S., Combustion Theory and Modeling, under 2nd revision, (2010).
The foundation of my work in combustion kinetics stems from an background in organic and physical chemistry and using AI techniques for extracting information from chemical databases. These are two representative papers of this work:
1. Computer Aided Synthesis Design at RISC-Linz: Automatic Extraction and Use of Reaction Classes, Blurock, Edward S.; J. Chem. Inf. Comp. Sci., 30, 505 (1990).
2. Use of Atomic and Bond Parameters in a Spectral Representation of a Molecule for Physical Property Determination, Blurock, Edward S.; J. Chem. Inf. Comput. Sci., (1998).