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