Graduate Course Descriptions

The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.

5512. Introduction to Structural Optimization

3.00 credits

Prerequisites: Recommended preparation: Previous knowledge in principles of optimum design and in finite element analysis.

Grading Basis: Graded

Application of mathematical optimization techniques to the design of structures modeled via the finite element method, including size, shape and topology optimization. Mathematical derivation and computational implementation aspects of material and shape sensitivities used for shape and topology optimization, including direct and adjoint sensitivity analysis, and finite difference sensitivities. Size optimization of discrete systems and of distributed parameter systems. Optimization techniques for structural optimization, including fully-stressed design, optimality criterion methods and gradient-based nonlinear programming methods. Topology optimization of discrete systems and of continua, including density-based and level-set-based methods. Shape optimization techniques.


Last Refreshed: 14-APR-21 05.20.22.124364 AM
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Term Class Number Campus Instruction Mode Instructor Section Session Schedule Enrollment Location Credits Grading Basis Notes
Fall 2020 16052 Storrs Distance Learning Norato Escobar, Julian 001 Reg TuTh 2:00pm‑3:15pm
21/30 No Room Required - Online 3.00 Graded Application of mathematical optimization techniques to the design of structures modeled via the finite element method, including size, shape and topology optimization. Mathematical derivation and computational implementation aspects of material and shape sensitivities used for shape and topology optimization, including direct and adjoint sensitivity analysis, and finite difference sensitivities. Size optimization of discrete systems and of distributed parameter systems. Optimization techniques for structural optimization, including fully-stressed design, optimality criterion methods and gradient-based nonlinear programming methods. Topology optimization of discrete systems and of continua, including density-based and level-set-based methods. Shape optimization techniques.