TY - JOUR

T1 - Proper orthogonal decomposition of direct numerical simulation data

T2 - 30th International Symposium on Combustion

AU - Frouzakis, C. E.

AU - Kevrekidis, Y. G.

AU - Lee, J.

AU - Boulouchos, K.

AU - Alonso, A. A.

N1 - Funding Information:
This work was performed with the financial support of the Swiss National Energy Research Foundation (SNSF), the Swiss Office of Energy (BFE), the Air Force Office of Scientific Research (AFOSR), and the United Technologies Research Center (UTRC).

PY - 2000

Y1 - 2000

N2 - In this paper, direct numerical simulation (DNS) data of an opposed-jet hydrogen/air diffusion flame are, in a postprocessing step, analyzed using the proper orthogonal decomposition (POD) technique. The aim of this work is twofold. The first goal is to compute a small number of space-dependent empirical eigenfunctions, so that a low-dimensional representation of the data generated by the large model of the discretized partial differential equations can be obtained using a weighted sum of these few eigenfunctions (POD modes). It is found that only six modes are needed for an accurate representation of the data in an extended range of inflow velocities. This large data reduction takes into account not only chemical kinetics but also transport phenomena in a full two-dimensional context and constitutes the first step toward the construction of low-dimensional dynamic models for the opposed-jet system. It is also found that the PODs have very good interpolatory properties. The second goal is to use part of the available data (i.e., partial measurements), together with the computed modes, to estimate, or, in the terminology of process control, to observe, the "unmeasured" quantities. It is found that only a small number of measurements are needed to obtain accurate estimates of the rest of the data.

AB - In this paper, direct numerical simulation (DNS) data of an opposed-jet hydrogen/air diffusion flame are, in a postprocessing step, analyzed using the proper orthogonal decomposition (POD) technique. The aim of this work is twofold. The first goal is to compute a small number of space-dependent empirical eigenfunctions, so that a low-dimensional representation of the data generated by the large model of the discretized partial differential equations can be obtained using a weighted sum of these few eigenfunctions (POD modes). It is found that only six modes are needed for an accurate representation of the data in an extended range of inflow velocities. This large data reduction takes into account not only chemical kinetics but also transport phenomena in a full two-dimensional context and constitutes the first step toward the construction of low-dimensional dynamic models for the opposed-jet system. It is also found that the PODs have very good interpolatory properties. The second goal is to use part of the available data (i.e., partial measurements), together with the computed modes, to estimate, or, in the terminology of process control, to observe, the "unmeasured" quantities. It is found that only a small number of measurements are needed to obtain accurate estimates of the rest of the data.

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U2 - 10.1016/S0082-0784(00)80197-6

DO - 10.1016/S0082-0784(00)80197-6

M3 - Conference article

AN - SCOPUS:84939782309

VL - 28

SP - 75

EP - 81

JO - Proceedings of the Combustion Institute

JF - Proceedings of the Combustion Institute

SN - 1540-7489

IS - 1

Y2 - 25 July 2004 through 30 July 2004

ER -