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Instructor: Dr.- Ing . Mostafa Ranjbar

Multidisciplinary Engineering Design Optimization (MCE 540 Graduate Course – Mechanical Engineering Department). Instructor: Dr.- Ing . Mostafa Ranjbar Ph.D. ( Dr-Ing .), Multidisciplinary Engineering Design Optimization of Structures,Technische Universität Dresden, Germany, 2011

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Instructor: Dr.- Ing . Mostafa Ranjbar

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  1. Multidisciplinary Engineering Design Optimization (MCE 540 Graduate Course – Mechanical Engineering Department) • Instructor: • Dr.-Ing. Mostafa Ranjbar • Ph.D. (Dr-Ing.), Multidisciplinary Engineering Design Optimization of Structures,TechnischeUniversität Dresden, Germany, 2011 • M.Sc., Vibration Monitoring and Fault Diagnosis of Structures, TarbiatModares University, Tehran, Iran, 2000 • B.Sc., Mechanical Engineering, Shiraz university, Iran, 1998

  2. LECTURE OUTLINE (see the course outline as well!) • Course Introduction • Introduction to (Multidisciplinary) (System) Design Optimization • Systems • Evolution of Design Process • Optimization

  3. HOW DO WE INTEND TO DELIVER LECTURES, LABs, QUIZ and EXAM • LECTURES • Lecture notes will be on Power Point Slides in pdf format • We will have them available in class and you are welcome to take them after the class • Students can bring anything they are comfortable with for taking the class notes • Please equip your Laptops with ANSYS along with MATLAB, or we may use them in Computer Room

  4. EXAM METHODS • EXAMS • There will be Assignments and Quizzes in most of the lectures with appropriate weightage. • Absentees in Quizzes will be marked ZERO. • All students will submit their assignments either as a hard or soft copy (Instructor would specify in all the assignments). We expect professional reports. • Late assignments without prior approval of the instructor will not be accepted. • Mid Term and End Term Exams as per Department’s policy.

  5. EVALUATIONS (Tentative)

  6. CLASS PARTICIPATION • Class Participation is highly recommended as this would be an interactive class. • – Add on whenever you like. • – Ask question as soon as it comes to mind, keeping in mind the flow of lecture. • – We will write down questions that come and we would review them at the end of the semester as to what we think today and how does this change over the course of the semester.

  7. KEEP IN MIND • This is not a classic optimization class……. • The aim is not to teach you the details of optimization algorithms, but rather • To expose you to different methods • To increase the understanding of optimization methods • We will utilize optimization techniques – the goal is to understand enough to be able to utilize them wisely

  8. MSDOIntroductionTEXT BOOKS

  9. TEXT BOOKS • Lecture notes will be handed out in class ?? But various books for reference are: • TEXT BOOK: • Engineering Optimization: Theory and Practice, 4th ed., Singiresu S. Rao, John Wiley, 2009. • REFERENCE BOOK(S): • Modern Heuristic Optimization Techniques, Kwang Y Lee, Mohamed A El-Sharkawi, John Wiley, 2008. • Numerical Optimization Techniques for Engineering Design, Vanderplaats, Garret N, 3rd ed., Colorado Springs: Vanderplaats Research & Development Inc., 2001. • Optimization Techniques, George Leitmann, Academic Press, NY

  10. BOOKS • Belegundu, A. and Tirupathi, R., Optimization Concepts and Applications in Engineering, Prentice Hall, 1999. • Onwubiko, C., Introduction to Engineering Design Optimization, Prentice Hall, 2000. • Venkataraman, P., Applied Optimization with MATLAB programming. Interscience, 2001. • Goldberg, David E. Genetic Algorithms – in Search, Optimization & Machine Learning. MA: Addison-Wesley, 1989. ISBN: 0201157675 • Murray B. Anderson, Genetic Algorithms In Aerospace Design: Substantial Progress, Tremendous Potential, Sverdrup Technology Inc./TEAS Group Eglin Air Force Base, FL 32542, USA. • Kennedy J, Eberhart R. and Shi, Y.H., Swarm Intelligence, [M] Morgan Kaufmann Publishers, 2001. • Kwang Y Lee, Mohamed A El-Sharkawi, Modern Heuristic Optimization Techniques, [M] John Wiley and Sons, 2008. • Vanderplaats, Garret N. Numerical Optimization Techniques for Engineering Design. 3rd ed. Colorado Springs: Vanderplaats Research & Development Inc., 2001. ISBN: 0944956017 • Gill, P. E., W. Murray and M. H. Wright. Practical Optimization. Academic Press, 1986 • Blair J.C., Ryan R.S., Schutzenhofer L.A. Launch Vehicle Design Process: Characterization, Technical Integration, and Lessons Learned, Marshall Space Flight Center, Alabama NASA/TP2001–210992, 2001 • Phadke, M. S., Quality Engineering Using Robust Design. Prentice Hall. 1989. • Taguchi, G., Elsayed, E., Hsiang, T., Quality Engineering in Production Systems. McGraw-Hill, NY. 1989.

  11. BOOKS

  12. BOOKS

  13. BOOKS

  14. BOOKS

  15. SUMMARY OF LEARNING OBJECTIVES • Learning Objectives: • decompose and integrate multidisciplinary design models • formulate meaningful problems mathematically • explore design space and understand optimization • critically analyze results, incl. sensitivity analysis • Understand current state of the Art in MDO • see depth and breadth of applications in industry & science • get a feel for interaction of quantitative-qualitative design • understand limitations of techniques • good overview of literature in the field • Research … and have fun !

  16. MULTIDISCIPLINARY SYSTEM DESIGN Optimization ______________________________________AN INTRODUCTION LECTURE #1

  17. MULTIDISCIPLINARY SYSTEM DESIGNOptimization LECTURE #1

  18. MULTIDISCIPLINARY SYSTEM DESIGN Optimization ______________________________________INTRODUCTION TO SYSTEM LECTURE #1

  19. SYSTEMS • System: A system is a physical or virtual object that is composed of more than one element and that exhibits some behavior or performs some function as a consequence of interactions between these constituent elements. • A system is a collection of interacting components.

  20. The World Around Us “All modern products are designed as a SYSTEM”

  21. The World Around Us

  22. The World Around Us

  23. The World Within Us SYSTEMS?

  24. More Examples of Systems

  25. More Examples of Systems SYSTEMS? Level Specific Name • System Launch vehicle • Subsystem Propulsion • Element SRM • Component Ignition Device • Part Igniter

  26. Relationships System System Subsystem Components • A Component can itself be a SYSTEM. .

  27. Analysis codes should reside with experts ? System analysis should execute analysis codes on experts’ computers or … ? Aerodynamics Expert System Analysis Controls Expert Structures Expert SYSTEM COMPLEXITY

  28. More Examples of Systems COMPARTMENTALIZATION • Helicopter as an example of a Multidisciplinary Complex System “Helicopters don’t fly. They beat the air into submission.” Dr. Ed Smith

  29. f(t) input + x(t) output - - c k MODELING RS Model Meta Model The Modeling Space Model Physical system World

  30. MULTIDISCIPLINARY SYSTEM DESIGN Optimization ______________________________________DESIGN LECTURE #1

  31. EVOLUTION OF DESIGN PROCESS • HOW DO WE DEFINE DESIGN?????????? • Design of a product is an iterative focused activity that requires application of various techniques and scientific principles in fulfilling human needs with technically perfect, economically favorable and esthetically satisfactory solution. • The process of conceiving and planning an object or process with a specific goal in mind.

  32. DEFINITIONS AND OVERVIEW DESIGN Engineering design is a process that requires application of various techniques and scientific problems • Taylor (1959): Engineering design is the process of applying various techniques and scientific principles for the purpose of defining a device, a process, or a system in sufficient detail to permit its physical realization. • Asimow (1962): Engineering design is a purposeful activity directed towards the goal of fulfilling human needs, particularly those which can be met by the technology factors of our culture. Goal of Engineering design is fulfilling of Human Needs

  33. DEFINITIONS AND OVERVIEW DESIGN Performing pre-specified functions with the maximum economy and efficiency • Feilden (1963): Mechanical engineering design is the use of scientific principles, technical information and imagination in the definition of a mechanical structure, machine or system to perform pre‐specified functions with the maximum economy and efficiency. • Kesselring (1964): Designing means to find a technically perfect, economically favorable and esthetically satisfactory solution for a given task. Finding a technically perfect, economically favorable and esthetically satisfactory solution for a given task

  34. DEFINITIONS AND OVERVIEW DESIGN Iterative process • Booker (1964): Simulating what we want to make (or do) before we make (or do) it as many times as may be necessary to feel confident in the final result. • Archer (1964): A goal‐directed problem‐solving activity. • Reswick (1965): A creative activity ‐‐ it involves bringing into being something new and useful that has not existed previously. • Hansen (1966): Developing a technical construct is determined through prior visual thinking out. Very focused activity Creative activity Designing is visualizing an object

  35. DEFINITIONS AND OVERVIEW • The design of any system involves several diverse disciplines with strong interaction between each other. • The overall activity is therefore a typical Multidisciplinary Design and Optimization (MDO) process. • MDO problems typically involve a large number of design constraints and variables. The analysis required to compute the objective and constraint functions are usually highly complex, coupled and imprecise. • In such problems, traditional optimization techniques based on principles of mathematical programming have shown to be inadequate.

  36. DEFINITIONS AND OVERVIEW DESIGN • This course focuses on engineering design problems (e.g. vehicles, transportation systems, communication networks) and not primarily management problems (resource allocation, supply chain optimization, revenue management, etc.). • As such, students should have a background and interest in engineering and system or product design and have had previous exposure to optimization. The course will present many quantitative methods and tools.

  37. DEFINITIONS AND OVERVIEW DESIGN----FINAL WORDS • Design of a product is an iterative focused activity that requires application of various techniques and scientific principles in fulfilling human needs with technically perfect, economically favorable and esthetically satisfactory solution. • The process of conceiving and planning an object or process with a specific goal in mind. • In the context of this class this refers to the conceiving of a system that will subsequently be implemented and operated for some beneficial purpose. “WHAT DO YOU THINK???????????”

  38. MULTIDISCIPLINARY SYSTEM DESIGN Optimization ______________________________________EVOLUTION OF THE DESIGN PROCESS LECTURE #1

  39. `` EVOLUTION OF DESIGN PROCESS Trial & Error Empirical Mathematical Probabilistic Stochastic (Risk Quantified) Deterministic (Factors of Safety) Random Experimentation Experience-based Graphical Approaches Systematic Experimentation Computer models based on system physics Point estimates Computer Simulations based on system physics Robust Solutions

  40. CONCEPTUAL DESIGN PRELIMINARY DESIGN DETAIL DESIGN PRODUCT ATTRIBUTES 100:1 10:1 1:1 EVOLUTION OF DESIGN PROCESS Conceptual design is crucial to the success of the overall design process and resulting system. It has been estimated that “at least 80% of a Mission’s life-cycle cost is locked in by the concept that is chosen” and “conceptual design decision have a 100:1 leverage on end product quality and cost”

  41. EVOLUTION OF DESIGN PROCESS CONVENTIONAL OPTIMAL 1. Specification 2. Baseline design 3. Analysis (or experiment) 4. Check performance or failure criteria 5. Is design satisfactory? (If yes, then stop) 6. Change design parameters based on intuition and experience, return to 3. 1. Specification 2. Baseline design 3. Analysis 4. Check constraints 5. Does design satisfy the optimality conditions? (If yes, then stop) 6. Change design parameters using an optimization strategy, return to 3.

  42. MULTIDISCIPLINARY SYSTEM DESIGN Optimization ______________________________________OPTIMIZATION LECTURE #1

  43. WHAT IS OPTIMIZATION? • “Making things better” • “Generating more profit” • “Determining the best” • “Do more with less”

  44. WHAT IS OPTIMIZATION? • “The determination of values for design variableswhich minimize (maximize) the objective, while satisfying all constraints” • Principles of Optimal Design: Modeling and Computation • 2d Ed. by Panos Y. Papalambros and Douglass J. Wilde, Cambridge University Press, New York, 1988, 2000.

  45. OPTIMIZATION Design Space: The space of working (Hill in this case) Objective: Find the Highest Point. Design Variables: Longitude and latitude. Constraints: Stay inside the fences.

  46. OPTIMIZATION

  47. OPTIMIZATION Objective Function Constraints Bounds Design Variables

  48. Responses Derivatives ofresponses (design sensitivities) SOLVING OPTIMIZATION PROBLEMS • Optimization problems are typically solved using an iterative algorithm: Design variables Model Optimizer

  49. LOCAL AND GLOBAL OPTIMA LOCAL OPTIMA maxima Local maxima Local minima minima GLOBAL MINIMA

  50. Optimization Problems

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