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Professor GAETANO CONTINILLO
Period Primo Semestre
Teaching style Tradizionale
39811 - MODELLING AND OPTIMIZATION OF ENERGY CONVERSION PROCESSES
Academic Year 2015/2016 Free text for the University
Course Curriculum CFU Length(h)
Prerequisites
Good command of Calculus and Linear Algebra:
programming skills in MATLAB.
Program
Models of unit operations: distributed vs lumped, continuous vs discrete, steady-state vs dynamical. Model parameters. Models derived from experiments. Least squares approximation. Experiment design.
General formulation of an optimization problem:
objective function, equality and inequality constraints.
Restrictions for the solutions. Challenges in optimization:
discontinuity of the objective function, model uncertainties.
Basic concepts: continuity of functions, functions with single or multiple extrema, concave and convex functions, convex regions. Necessary and sufficient conditions for the existence of unconstrained extrema.
Unrestricted optimization of functions of a single variable. Application of repeated unidimensional search to multidimensional optimization.
Unrestricted optimization of multivariable functions.
Direct methods: direct search, simplex method, conjugate directions. Indirect methods of the first order: gradient and conjugate gradient methods. Indirect methods of the second order.
Linear objective function and inequality restrictions
2012 © by KION a CINECA Company
(Linear Programming, LP): standard formulation of an LP problem. Multivariable optimization under equality constraints. Lagrangian multipliers. Sensitivity analysis.
Application of MATLAB tools to standard multivariable optimization problems, with and without constraints.
Multiobjective optimization. Paretian optimum.
Applications with MODEFRONTIER.
Books
Bibliography:
T. F. Edgar and D. M. Himmelblau, “Optimization of Chemical Processes”, McGraw-Hill, 1988 (coursebook) C. Vercellis, “Ottimizzazione”, McGraw-Hill Italia, 2008 (in Italian)
S.S. Rao, Engineering Optimization, 4th Ed., McGraw Hill, 2009
MATLAB Optimization toolbox - Manuals MODEFRONTIER - Manual
Purposes
Course goals:The student at the end of the course will have learnt how to formulate a mathematical model of a process and how to compute the optimal solution of a design or operation problem for that process.
Didactic Methods
Teaching method:Classroom lectures and computational lab training.
Teaching aids:
Notes from the teacher and coded examples in MATLAB Examination method:
Oral with discussion of a project report, developed individually or in team.
Course registration: Yes - Examination registration: Yes
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