M.Tech (R22)
After completion of the course, students will be able to:
Thermal Systems – Characteristics- formulation of design problem - Steps in the design process - Modeling of thermal systems – importance - Types of models - Mathematical Modeling
Linear programming models – Formulation - Simplex method – Artificial variable technique – Big M method - Concept of Sensitive analysis.
Unconstrained Optimization: Single variable optimization – Fibonacci & Golden section method - Multi variable optimization – Gradient methods – Gradient of the function - Steepest descent – Flecher-Reeves method -Variable metric method - Constrained Non-linear Optimization Methods - Lagrangian multiplier – Application to thermal and electrical systems.
Geometric programming – Polynomial – Arithmetic and Geometric inequalities – Unconstrained GP - Constrained GP with constraints of type less than or equal- Application to thermal and electrical systems- Dynamic Programming- Bellman’s principle of optimality- shortest route problems
Simulation - Definition- Types of Simulation models - Steps involved in simulation models - Application of simulation - Advantages and disadvantages – Introduction to Genetic algorithm – Applications in Genetic Algorithm - Similarities and dissimilarities with traditional methods - Genetic operators.
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