@article{echekki_mirgolbabaei_2015, title={Principal component transport in turbulent combustion: A posteriori analysis}, volume={162}, ISSN={["1556-2921"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84937770499&partnerID=MN8TOARS}, DOI={10.1016/j.combustflame.2014.12.011}, abstractNote={This paper presents a posteriori validation of the solution of a turbulent combustion problem based on the transport of principal components (PCs). The PCs are derived from a priori principal component analysis (PCA) of the same composition space. This analysis is used to construct and tabulate the PCs’ chemical source terms and diffusion coefficients in terms of the PCs using artificial neural networks (ANN). The a posteriori validation is implemented on a stand-alone one-dimensional turbulence (ODT) simulation of Sandia Flame F resulting in a very good reconstruction of the original thermo-chemical scalars profiles with 3 PCs at different downstream distances.}, number={5}, journal={COMBUSTION AND FLAME}, author={Echekki, Tarek and Mirgolbabaei, Hessam}, year={2015}, month={May}, pages={1919–1933} }
 @article{mirgolbabaei_echekki_2015, title={The reconstruction of thermo-chemical scalars in combustion from a reduced set of their principal components}, volume={162}, ISSN={["1556-2921"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84940000388&partnerID=MN8TOARS}, DOI={10.1016/j.combustflame.2014.11.027}, abstractNote={We compare two reconstruction approaches for thermo-chemical scalars (TCSs) in turbulent combustion using principal component analysis. The first approach is based on the inversion of the linear relation between the TCSs and their principal components (PCs). The second is based on a regression of TCSs with a reduced set of the PCs using artificial neural networks. The study is based on one-dimensional turbulence simulation data of Sandia Flame F. We find that regression potentially offers superior reconstruction to the inversion expression when a truncated set of the original PCs is used.}, number={5}, journal={COMBUSTION AND FLAME}, author={Mirgolbabaei, Hessam and Echekki, Tarek}, year={2015}, month={May}, pages={1650–1652} }
 @article{mirgolbabaei_echekki_smaoui_2014, title={A nonlinear principal component analysis approach for turbulent combustion composition space}, volume={39}, ISSN={["1879-3487"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84895441869&partnerID=MN8TOARS}, DOI={10.1016/j.ijhydene.2013.12.195}, abstractNote={An approach for the determination of principal components using nonlinear principal component analysis (NLPCA) is proposed in the context of turbulent combustion. NLPCA addresses complex data sets where the contours of the inherent principal directions are curved in the original manifold. Thermo-chemical scalars' statistics are reconstructed from the optimally derived moments. The tabulation of the scalars is then implemented, using artificial neural networks (ANN). The approach is implemented on numerical data generated for the stand-alone one-dimensional turbulence (ODT) simulation of hydrogen autoignition in a turbulent jet with preheated air. It is found that 2 nonlinear principal components are sufficient to capture thermo-chemical scalars' profiles. For some of the scalars, a single principal component reasonably captures the scalars' profiles as well.}, number={9}, journal={INTERNATIONAL JOURNAL OF HYDROGEN ENERGY}, author={Mirgolbabaei, Hessam and Echekki, Tarek and Smaoui, Nejib}, year={2014}, month={Mar}, pages={4622–4633} }
 @article{mirgolbabaei_echekki_2014, title={Nonlinear reduction of combustion composition space with kernel principal component analysis}, volume={161}, ISSN={["1556-2921"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84887826057&partnerID=MN8TOARS}, DOI={10.1016/j.combustflame.2013.08.016}, abstractNote={Kernel principal component analysis (KPCA) as a nonlinear alternative to classical principal component analysis (PCA) of combustion composition space is investigated. With the proposed approach, thermo-chemical scalar’s statistics are reconstructed from the KPCA derived moments. The tabulation of the scalars is then implemented using artificial neural networks (ANN). Excellent agreement with the original data is obtained with only 2 principal components (PCs) from numerical simulations of the Sandia Flame F flame for major species and temperature. A formulation for the source and diffusion coefficient matrix for the PCs is proposed. This formulation enables the tabulation of these key transport terms in terms of the PCs and their potential implementation for the numerical solution of the PCs’ transport equations.}, number={1}, journal={COMBUSTION AND FLAME}, author={Mirgolbabaei, Hessam and Echekki, Tarek}, year={2014}, month={Jan}, pages={118–126} }
 @article{mirgolbabaei_echekki_2013, title={A novel principal component analysis-based acceleration scheme for LES-ODT: An a priori study}, volume={160}, ISSN={["1556-2921"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84875091614&partnerID=MN8TOARS}, DOI={10.1016/j.combustflame.2013.01.007}, abstractNote={A parameterization of the composition space based on principal component analysis (PCA) is proposed to represent the transport equations with the one-dimensional turbulence (ODT) solutions of a hybrid large-eddy simulation (LES) and ODT scheme. The 1D ODT solutions are embedded in the 3D LES domain and solve for thermo-chemical scalars; while, the LES governing equations solve for the flow. An a priori validation of the proposed approach is implemented based on stand-alone ODT solutions of the Sandia Flame F, which is characterized by different regimes of combustion starting with pilot stabilization, to extinction and reignition and self-stabilized combustion. The PCA analysis is carried out with a full set of the thermo-chemical scalars’ vector as well as a subset of this vector. The subset is made up primarily of major species and temperature. The results show that the different regimes are reproduced using only three principal components for the thermo-chemical scalars based on the full and a subset of the thermo-chemical scalars’ vector. Reproduction of the source term of the principal components represents a challenge, because of the inherent non-linearity of reaction rates’ expressions. It is found that using the subset of the thermo-chemical scalars’ vector both minor species and the first three principal components source terms are reasonably well predicted.}, number={5}, journal={COMBUSTION AND FLAME}, author={Mirgolbabaei, Hessam and Echekki, Tarek}, year={2013}, month={May}, pages={898–908} }
 @article{amini_taghipour_mirgolbabaei_2011, title={Numerical assessment of hydrodynamic characteristics in chlorine contact tank}, volume={67}, number={7}, journal={International Journal for Numerical Methods in Fluids}, author={Amini, R. and Taghipour, R. and Mirgolbabaei, H.}, year={2011}, pages={885–898} }