Surrogates and Approximations in Engineering Design

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About Course

Surrogates and Approximations in Engineering Design.

In the context of engineering design, often the functional objective and the design constraints are approximated by connecting the design variables and the responses of interest at few points in the design space. Since these are approximations of the original functions, they are called surrogates and are widely used in design studies. This course will focus on introducing such surrogates – how to build, evaluate and use them in design. Surrogates discussed will include polynomial regression, kriging, and radial basis function while Design of Experiments discussions will include Latin hypercube sampling and Hammersley sequence.

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What Will You Learn?

  • -Introduction, physical versus computational experiments, introduction to engineering optimization, need for surrogates in optimization
  • -Sampling plans, Latin squares, Latin hypercubes sampling, stratification, Orthogonal arrays, Hammersley sequences
  • -Surrogates: Polynomial Regression, Radial basis function, Kriging
  • -Using surrogates in design space exploration and exploitation, infill criteria, adaptive sampling

Course Content

Surrogates and Approximations in Engineering Design

  • Lecture 1 – Overview and Motivation of Course
    00:00
  • Lecture 2 – Basic Optimization Problem Formulation
    00:00
  • Lecture 3 – Problem Formulation Example
    00:00
  • Lecture 4 – Calculus related to Optimization
    00:00
  • Lecture 5 – The big picture – Overview
    00:00
  • Lecture 6 – Introduction to DOE – 1
    00:00
  • Lecture 7 – Introduction to DOE – 2
    00:00
  • Lecture 8 – Types of DOE – 1
    00:00
  • Lecture 9 – Types of DOE – 2 and some examples
    00:00
  • Lecture 10 – Introduction to surrogate modeling
    00:00
  • Lecture 11 – Types of surrogate – Polynomial models
    00:00
  • Lecture 12 – Radial basis function – 1
    00:00
  • Lecture 13 – Radial basis function – 2
    00:00
  • Lecture 14 – Kriging – 1
    00:00
  • Lecture 15 – Kriging – 2
    00:00
  • Lecture 16 – Metamodels for Safe and Efficient Automotive Structures
    00:00
  • Lecture 17 – Exploration and Exploitation in Surrogates
    00:00
  • Lecture 18 – Errors Based Exploration
    00:00
  • Lecture 19 – Ensemble of Surrogates
    00:00

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