SE 598 DDM - Special Topics - Data-driven Design Methods
Subject offerings of new and developing areas of knowledge in general engineering intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: 1 to 4 graduate hours. No professional credit. May be repeated in the same or separate terms if topics vary to a maximum of 12 hours.
Engineering systems design relies on quantitative and qualitative data to describe design-related engineering phenomena and prescribe improvements for design practice. Data-driven design refers to making engineering design decisions based on data. While using data-driven design framework, data is of primary importance. Moreover, advanced computational methods that create mathematical models and develop computer tools based upon data for engineering design decision making are critical for engineering design. In this course, we will explore advanced computational methods for data-driven design, including engineering design and optimization, system modeling and simulation, probabilistic design, uncertainty quantification, advanced sampling and analysis of physical experiments, physics-informed machine learning, as well as multifidelity approaches for design. Engineering design applications in structures, energy storage systems, power systems, engineering materials, and design for additive
Option 1Number of Required Visit(s): 0
Course Level: Graduate