Theory and application of linear programming. Includes formulation of linear programming models, simplex, revised simplex and dual simplex algorithms, duality, parametric procedures, interpretation of results, and the decomposition principle. Prerequisite: consent of instructor.

Principles of mechanical behavior and failure of metals, polymers, and ceramics. Analysis of problems in design of structural materials that must meet certain strength and performance criteria. Emphasis on the engineering significance and use of various experimentally measured properties such as fatigue life, critical stress intensity factor, relaxation modulus, creep rupture life, and crack growth rate.

The course provides advanced background to fluid mechanics including statics, kinematics, governing equations of fluid flow, viscous flow, inviscid ideal flow and gravity waves.

Numerical methods of solving problems in engineering analysis. Topics include interpolation polynomials, numerical integration and differential equations, multiple regression and correlation, roots of equations and solution of simultaneous equations and numerical solution of partial differential equations. Prerequisites: undergraduate calculus and differential equations.

Review of classical thermodynamics and conventional energy conversion systems. Introduction to kinetic theory of gases, and statistical thermodynamics. Selected topics in chemical thermodynamics. Mr. McGowan

This course will provide students with a basic understanding of the state of the art in Augmented (AR) and Virtual Reality (VR) technologies, how these technologies work, and how to leverage these technologies to design extended reality experiences and tools in commercial, industrial, and entertainment settings. This course will focus on understanding and addressing limitations of AR and VR that allow for their effective use, and on principles of Human Computer Interaction and processes for designing AR and VR applications.

The course will cover nanomaterial science and sensor science and technology with an emphasis on nano-enabled sensors and biosensors.

Innovation in materials, IT, manufacturing and intelligent techniques is propelling the revolution of manufacturing industry. The integration of the innovative materials and artificial intelligent (AI) and sensing techniques in manufacturing processes, called Industry 4.0, is bringing lower cost and higher quality products to our life and changing our life.

Introduction to automated vehicle systems with emphasis on transportation safety. Topics include historical background, advanced technologies in sensors and control, human factors design and application, research methodologies and state of the science, and policy and regulation.

This course will cover statistical methods now widely used in data analysis, learning and prediction such as regression and classification techniques, feature selection, decision trees, and unsupervised learning methods such as clustering and principal components analysis. The emphasis will be on applying the statistical methods to data sets and understanding the optimization theory that drives these methods.