Hee-Chul Chang

Estimation of the Properties for a Charring Material Using the RPSO Algorithm

Fire characteristics can be analyzed more realistically by using more accurate properties related to the fire dynamics and one way to acquire these fire properties is to use one of the inverse property estimation techniques. In this study two optimization algorithms which are frequently applied for the inverse heat transfer problems are selected to demonstrate the procedure of obtaining pyrolysis properties of charring material with relatively simple thermal decomposition. Thermal decomposition is occurred at the surface of the charring material heated by receiving the radiative energy from external heat sources and in this process the heat transfer through the charring material is simplified by an unsteady 1-dimensional problem. The basic genetic algorithm(GA) and repulsive particle swarm optimization(RPSO) algorithm are used to find the eight properties of a charring material; thermal conductivity(virgin, char), specific heat(virgin, char), char density, heat of pyrolysis, pre-exponential factor and activation energy by using the surface temperature and mass loss rate history data which are obtained from the calculated experiments. Results show that the RPSO algorithm has better performance in estimating the eight pyrolysis properties than the basic GA for problems considered in this study.

Effects of additive and preheat on the partially premixed CH4-air counter flow flames considering non-gray gas radiation

Detailed structures of the counterflow flames formed for different inlet fluid temperatures and different amount of additives are studied numerically. The detailed chemical reactions are modeled by using the CHEMKIN-II code. The discrete ordinates method and the narrow band based WSGGM with a gray gas regrouping technique (WSGGM-RG) are applied for modeling the radiative transfer through non-homogeneous and non-isothermal combustion gas mixtures generated by the counterflow flames. The results compared with those obtained by using the SNB model show that the WSGGM-RG is very successful in modeling the counterflow flames with non-gray gas mixture. The numerical results also show that the addition of CO2 or H2O to the oxidant lowers the peak temperature and the NO concentration in flame. But preheat of fuel or oxidant raises the flame temperature and the NO production rates. O2 enrichment also causes to raise the temperature distribution and the NO production in flame. And it is found that the O2 enrichment and the fuel preheat were the major parameters in affecting the flame width.