NUMERICAL OPTIMIZATION OF MECHANICAL STRUCTURES AND PROCESSES

Course Information
TitleΑΡΙΘΜΗΤΙΚΗ ΒΕΛΤΙΣΤΟΠΟΙΗΣΗ ΣΕ ΜΗΧΑΝΟΛΟΓΙΚΕΣ ΚΑΤΑΣΚΕΥΕΣ ΚΑΙ ΔΙΕΡΓΑΣΙΕΣ / NUMERICAL OPTIMIZATION OF MECHANICAL STRUCTURES AND PROCESSES
Code323
FacultyEngineering
SchoolMechanical Engineering
Cycle / Level1st / Undergraduate
Teaching PeriodWinter
CoordinatorPanagiotis Seferlis
CommonYes
StatusActive
Course ID20000380

Programme of Study: UPS of School of Mechanical Engineering

Registered students: 19
OrientationAttendance TypeSemesterYearECTS
EnergyElective Course belonging to the selected specialization (Elective Specialization Course)955
Design and StructuresCompulsory Course belonging to the selected specialization (Compulsory Specialization Course)955
Industrial ManagementElective Course belonging to the selected specialization (Elective Specialization Course)955

Class Information
Academic Year2020 – 2021
Class PeriodWinter
Faculty Instructors
Weekly Hours4
Class ID
600170981
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Knowledge Deepening / Consolidation
Mode of Delivery
  • Face to face
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
Prerequisites
Required Courses
  • 128 ENERGY TRANSFORMING SYSTEMS
  • 125 OPERATIONS RESEARCH I
  • 113 THERMODYNAMICS I
  • 118 FLUID MECHANICS I
  • 122 HEAT TRANSFER
  • 206 PHYSICAL PROCESSES TECHNOLOGY
  • 108 STATICS
  • 116 DYNAMICS
  • 101 CALCULUS I (MATHEMATICS I)
  • 106 CALCULUS II (MATHEMATICS II)
  • 111 DIFFERENTIAL EQUATIONS (MATHEMATICS III)
  • 120 NUMERICAL ANALYSIS
  • 131 LINEAR ALGEBRA
Learning Outcomes
The implementation of numerical optimization in mechanical, manufacturing and process systems. Major emphasis is given in the optimization problem formulation using a single or multiple criteria using gradient based methods and non-gradient probabilistic methods.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Work in teams
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Appreciate diversity and multiculturality
  • Demonstrate social, professional and ethical commitment and sensitivity to gender issues
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Optimization problem formulation Decision hierarchy, selection of criteria, decision variables (continuous, discrete), mathematical model formulation, constraints, parameters Applications (1st Assignment): Manufacturing: Mechanical system model development Energy: Thermal process model development. Industrial management: Supply chain modellig. Numerical Optimization (gradient-based) Unconstrained and Constrained problems Linear and non-linear programming Linear and non-linear integer programming Solution of optimality conditions, Optimal solution sensitivity Applications (2nd Assignment) – Continuous decision variables (3rd Assignment) – Continuous and discrete decision variables Manufacturing: Mechanical system optimization. Energy: Heat exchanger network optimization. Industrial management: Supply chain optimization. Optimization using probabilistic methods (non-gradient methods) Simulated annealing, genetic algorithms. Applications (4th Assignment) – Implementation of probabilistic optimization methods Manufacturing: Mechanical system optimization. Energy: Heat exchanger network optimization. Industrial management: Supply chain optimization. Multi-objective optimization Pareto front. Numerical optimization of multi-objective optimization problems. Applications (5th Assignment) – Implementation of multi-objective optimization methods Manufacturing: Mechanical system optimization. Energy: Heat exchanger network optimization. Industrial management: Supply chain optimization. Optimization under uncertainty Uncertainty characterization – Problem formulation and solution Applications (6th Assignment) – Implementation of optimization methods under uncertainty. Manufacturing: Mechanical system optimization. Energy: Heat exchanger network optimization. Industrial management: Supply chain optimization. Optimization of dynamic problems Time discretization. Decision vector parameterization. Numerical solution (direct methods, sequential method, multiple shooting) Applications (4th Assignment) – Implementation of dynamic optimization methods. Manufacturing: Mechanical system optimization. Energy: Heat exchanger network optimization. Industrial management: Supply chain optimization.
Keywords
optimization, nonlinear programming, mixed integer programming, multi-objective optimization
Educational Material Types
  • Notes
  • Slide presentations
  • Video lectures
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Description
Electronic form of presentations.
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures451.5
Seminars150.5
Reading Assigment250.8
Interactive Teaching in Information Center150.5
Project501.7
Exams0
Total1505
Student Assessment
Description
Assignments - Projects (100%)
Student Assessment methods
  • Written Assignment (Formative, Summative)
  • Performance / Staging (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
  • Report (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
Βελτιστοποίηση και Δυναμική Προσομοίωση Διεργασιών, Ιωάννης Κούκος, Εκδόσεις Τζιόλα. Βελτιστοποίηση και Λογισμικό Κατασκευών: Πεπερασμένα Στοιχεία, Ισογεωμετρικά Στοιχεία, Συνοριακά Στοιχεία, Χριστόφορος Προβατίδης, Εκδόσεις Τζιόλα. Σχεδιασμός Θερμικών Διεργασιών, Μ. Κροκίδα, Δ. Μαρίνος - Κουρής, Ζ. Μαρούλης Σχεδιασμός και Οικονομική Μελέτη Εγκαταστάσεων για Μηχανικούς, Peters Max, Timmerhaus Klaus D., West Ronald E, Εκδόσεις ΤΖΙΟΛΑ Εισαγωγή στο Σχεδιασμό Χημικών Εργοστασίων , Κούκος Ι. , Εκδόσεις ΤΖΙΟΛΑ
Additional bibliography for study
Ενεργειακός Τομέας Ajah Α.Ν., J. Grievink, P.L.J. Swinkels, “Delft Design Matrix: Framework for conceptual process design of future plants”, 2003. Biegler L.T., I.E. Grossmann, A.W. Westerberg, “Systematic methods of chemical process design”, Prentice-Hall, 1997. Douglas J.M., “Conceptual design of processes”, McGraw-Hill, 1988. Jaluria Y., “Design and optimization of thermal systems”, CRC Press, 2008. Seider W.D., J.D. Seader, D.R. Lewin, “Product and process design principles”, Wiley, 2nd Ed., 2004. Smith R., “Chemical Process – Design and Integration”, Wiley, 2005. Suryanarayana N.V., Oner Arici, and N. Suryanarayana, “Design and Simulation of Thermal Systems”, McGraw Hill,
Last Update
01-10-2020