First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Engineering
MECHANICAL ENGINEERING
Course unit
ADVANCED METHODS FOR OPTIMIZATION OF MACHINE THERMOFLUIDODYNAMICS
INN1027679, A.A. 2017/18

Information concerning the students who enrolled in A.Y. 2016/17

Information on the course unit
Degree course Second cycle degree in
MECHANICAL ENGINEERING
IN0518, Degree course structure A.Y. 2011/12, A.Y. 2017/18
N0
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Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination ADVANCED METHODS FOR OPTIMIZATION OF MACHINE THERMOFLUIDODYNAMICS
Department of reference Department of Industrial Engineering
Mandatory attendance No
Language of instruction English
Branch PADOVA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge ERNESTO BENINI ING-IND/08

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses ING-IND/08 Fluid Machines 9.0

Mode of delivery (when and how)
Period First semester
Year 2nd Year
Teaching method frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours of
Individual study
Shifts
Lecture 9.0 72 153.0 No turn

Calendar
Start of activities 25/09/2017
End of activities 19/01/2018

Syllabus
Prerequisites: For a better understanding of the topics covered it is recommended that the student has attended basic courses on fluid machines.
Target skills and knowledge: Acquisition of fundamental knowledge related to modern methods for single and multiobjective optimization, with particular reference to fluid machines. Use of specific computer codes for dealing with optimization problems in fluid machinery .
Examination methods: Conventional viva
Assessment criteria: Assessment on the course program and discussion of the project developed during the course.
Course unit contents: Mathematical calculus, maxima and minima in bounded vector functions of several variables. Single- and multi-objective optimality. Classical and advanced optimization methods: deterministic, stochastic and pseudo-stochastic algorithms. Gradient algorithms, genetic-evolutionary algorithms, simulated annealing, fuzzy logic. Hybrid methods. Constraints in optimization problems. Functional optimization of fluid machines and their components. Calculation models for rotodynamic machines. Numerical models and experimental models. Interface between optimization algorithms and performance codes in turbomachines. Applications: optimization of compressible and incompressible flow turbo machinery; optimization of 2D cascades, optimization of rotor - stator interaction; 3D optimization of both rotating and stationary blades; optimization of internal combustion engines.
Planned learning activities and teaching methods: After a general discussion concerning the methods for single and multi-objective numerical optimization (both traditional and advanced), students are provided with the necessary knowledge for proper formulation, implementation and troubleshooting in optimized design of fluid machines (with particular reference to turbomachinery).
The student is guided step-by-step in the development of an optimization procedure according to two- and three-dimensional approaches; This procedure includes: (i) the geometric parameterization of a machine or one of its component, (ii) the analysis thereof by CFD (computational fluid dynamics) and (iii) interfacing with appropriate recursive algorithms of operational research. The procedure has the peculiarity of being fully automated and to enable, starting from a baseline design, to obtain optimized shapes after a finite number of iterations.
Additional notes about suggested reading: Lecture notes
Textbooks (and optional supplementary readings)
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