Methods of Model Reduction of Mechanisms of Chemical Kinetics in Combustion Science and System Biology

Dear Colleagues,

Computational methods have become fundamental in advancing the basic understanding of combustion processes, in development, in design, and optimization of combustion facilities. Very detailed models to address the chemical reaction taking place in a combustion wavefront have been developed in recent decades and offer very reliable and accurate results about steady and unsteady combustion phenomena. The results look very promising for academic scale problems, explain experimental observations, and provide accurate predictions of the relevant physics to devise robust control and optimization frameworks. However, because of the complexity of chemical reaction models in terms of a number of variables involved and the non-linearity of the chemical reaction source term problems of an industrial scale are still beyond computational power of even today’s computational frames.

In order to cope with the problem, different model reduction approaches have been developed and implemented in combustion science. These approaches have shown great potential to speed-up computations and perform parameter studies based on system numerical integrations in acceptable CPU times. The progress made in the field of model reduction, both in its theoretical and application aspects, is now available and can be extended to other fields of science and engineering such as system biology, where mechanisms of biochemical reactions have also grown enormously in recent years.

This Special Issue on “Methods of Model Reduction of Mechanisms of Chemical Kinetics in Combustion Science and System Biology” aims to provide an overview of recent development and progress made in the reduced modeling and its application to address challenges in open problems of combustion theory, in industrial-scale combustion problems and in system biology.

Topics include, but are not limited to the following:

• Development of new model reduction concepts to speed-up computations;
• Representation of application examples of the reduced modeling in combustion and biochemistry;
• Usage of model reduction strategies to assist the experimental investigation and make the detailed model predictions more reliable, validation of detailed models;
• Integration of model reduction approaches developed for combustion systems to those typical for system biology;
• The development of methods for automatic information extraction of multi-dimensional data to guide the understanding of dynamics of complex reaction networks.

Dr. Viatcheslav Bykov
Dr. Vladimit Gubernov
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.