Adaptive Chemical Model Reduction using Computational Singular Perturbation (CSP) Analysis

1. Adaptive Chemical Model Reduction using Computational Singular Perturbation (CSP) Analysis H.N. Najm, J.C. Lee* M. Valorani, F. Creta D. Goussis M. Frenklach Sandia National Laboratories Universita di Roma “La Sapienza” Agiou Georgiou 49 University of California Livermore, CA, USA Rome, Italy Patra, Greece Berkeley, CA, USA *Present address: United Technologies Research Center, East Hartford CT Identification of low dimensional manifolds in chemical systems • Coupling CSP with Piecewise Reusable Implementation of Solution Mapping (PRISM) enables adaptive chemistry construction • CSP solver provides for efficient explicit time integration of stiff chemical systems: • Filter out exhausted fast time scales • Integrate slow modes explicitly • Projection correction for exhausted fast modes • Effective use of adaptively reduced chemical models • PRISM provides: • Discretization of chemical composition space into hypercubes • Tabulation of local response surface fits for components of CSP tensors in each hypercube • Fast identification of local CSP manifolds Identification of comprehensive simplified chemical models Flame topology is reflected in the spatial distribution of manifold dimension Premixed flame speed over a range of premixed CH4-air flame stoichiometry, with a number of simplified mechanisms Identification of slow and fast chemical and transport time scales Computational speed-up is quadratic in the number of species, linear in the number of reactions Transport time scales are slower than the set of fast chemical time scales CSP solver for a transport-chemistry system Automatic reduction of chemical models Adaptive chemistry integration using CSP-PRISM exhibits good accuracy Convergence of predicted premixed flame speed with increasing number of reactions in the model Alternative simplifications governed by CSP tolerance Acknowledgement: US Dept. of Energy, Basic Energy Sciences; SciDAC Computational Chemistry SciDAC PI Meeting, San Francisco, CA June 26-20, 2005