Сloud data-processing system for the automated generation of combustion models

Abstract

Demands of energy for the twenty-first century and beyond will require the development of alternative, renewable fuel sources. Validating an alternative fuel source or fuel additive inherently comes from a posteriori knowledge: run a series of experiments whose results will assist in determining whether additional experiments should be conducted. Unfortunately, this knowledge is acquired at the expense of the fuel.The development of data-processing system of this type will not only timely and promptly provide engineers predictive chemical models of combustion processes of real fuels, but also will create a basis for organizing and coordination of fundamental data on the thermodynamic and kinetic properties of the hydrocarbon molecules, mechanisms of combustion of the individual components of real fuels and mixtures thereof. As an example, it suffices to mention that due to the inconsistency of data used by different research groups at the same time there are multiple versions of this simple combustion of fuel such as hydrogen, not to mention the much more complex hydrocarbon fuels.PrIMe (Process Informatics Model)- is a new approach for developing predictive models of chemical reaction systems that is based on the scientific collaborator paradigm and takes full advantage of existing and developing cyber infrastructure.