Inverse analysis and optimization of thermal systems for parameter retrieval


Parameter retrieval in engineering systems using inverse optimization has a wide range of applications, particularly relating to the design and performance of the system. Our group is specifically focused in applying the concept of inverse optimization for parameter retrieval to many thermal thermal systems such as finned heat transfer, flat-plate solar collectors, cooling towers, combined thermodynamic cycles and solid oxide fuel cells. Presently our group is working on both simulation and experimental studies to develop novel parameter retrieval techniques for highly nonlinear and practical thermal problems. Furthermore, closed form forward algorithms for diverse nonlinear heat transfer problems are also reported by our group and this is an additional aspect of our research. We use various techniques such as genetic algorithm, simulated annealing, differential evolution, artificial bee colony algorithm, experimental correlations, golden section method, simplex search methods along with many other computational techniques for parameter retrieval. 

Contact details:

Dr. Ranjan Das

Department of Mechanical Engineering