Large Combustion Kinetic Mechanisms

The work on large kinetic combustion mechanisms actually started with early work in the 1990’s in Computer Aided Organic Synthesis and the retrograde analysis of organic synthesis. The key was the representation of molecules as 2D-graphical structures (basically containing the Lewis structure of the molecule) and generating ‘reaction rules’ , essentially a representation of the reactive center of a reaction, i.e. that part of the set of molecules, the functional groups, that change during the reaction. This work expanded to using similar ‘reaction rules’ to simulate how a molecular species ‘combusts’ in the presence of oxygen.

Automatic generation of large combustion mechanisms. The generation of large combustion mechanisms using reaction pathways and reaction patterns (the rules)
ChemConnect2019: A searchable repository of large kinetic mechanisms based on onological relationships.

Automatic Combustion Mechanism Genreation

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). DOI:10.1039/C0CS00207K

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). DOI: https://doi.org/10.1080/0010220060079326210.1080/00102200600793262

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). DOI 10.1021/ci0341518

6. Detailed Mechanism Generation 2.: Aldehydes, ketones and olefins, Blurock, Edward S., J. Chemical Information and Computer Sciences, 44:1348-1357 (2004). DOI 10.1021/ci034153s

7. Reaction: System for Modeling Chemical Reactions, Blurock, Edward S.; J. Chem. Inf. Comput. Sci., 35:607-616 (1995). DOI 10.1021/ci00025a032

Chemconnect2019

ChemConnect2019 is a smart cloud-based repository of experimental, theoretical and computational data. ChemConnect2019 goes beyond traditional data repositories in that the data is parsed and analysed with respect to an extensive chemical and combustion knowledge base. The parsed data is then linked allowing for efficient searching and comparison of combustion data. The goal is to have all data associated with experiments, from a device description, to the intermediate data (both computed and measured) and to their associated interpretations and the procedures and methodologies to the final published results and references to be available. Having published data linked to its dependent measurements and constants, devices, subsystems, sensors and even people and laboratories provides an effective accountability and more confidence in the data. Data entry and availability can range from private user, to user defined consortia to general public.

The linking and interconnection of data is the implementation of the concept that no data point is isolated. For a single set of published data there is a large interconnected network of interdependencies that went into producing this final result. The first raw measurement is connected to the sensor making the measurement, the calibrations associated with that sensor, the device where the sensor is found and even the person or group which made the measurement. That raw measurement is rarely the final published result, so the data is connected to other measurements and this set of measurements is connected to methodologies to interpret the results. The main utility of this interconnection is the analysis and comparison of data points for analysing uncertainties, errors and differences between the ‘same’ measurements made with the ‘same’ device by different laboratories. The technology behind the linked data is the resource description framework (RDF) that is used to analyse and search links in the world wide web.

The extent of ‘knowledge’ in a traditional repository is limited to keywords and their human interpretation. A simple example of concept relationships is units of measurements. A temperature measurement is related to the different units of temperature, Kelvin, Celsius, Fahrenheit, etc. and conversions between them. Furthermore, the concept of temperature can be related to the general concept of thermodynamics, or even how it is used, for example, as a parameter in experimental conditions. There is also a knowledge base of devices and their subsystems and sensors. Having more complete knowledge of the experimental device through descriptions and relationships between the parts of the device can help investigate sources of uncertainties within a measurement and differences in measurements between different laboratories. The technology behind the knowledge base is the ontology, a formalized description of knowledge into types, properties, and interrelationships.