The University of Texas at Dallas

MECH 6318: Engineering Optimization, Fall 2017

  • Basics of optimization theory, numerical algorithms, and applications. The course is divided into three main parts: linear programming (simplex method, duality theory), unconstrained methods (optimality conditions, descent algorithms and convergence theorems), and constrained minimization (Lagrange multipliers, Karush-Kuhn-Tucker conditions, active set, penalty and interior point methods). Applications in engineering, operations, finance, statistics, etc. will be emphasized. Students will also use MATLAB optimization toolbox to obtain practical experience with the material.

MECH 6V49: Renewable Energy Systems Design and Optimization, Spring 2017

  • As the amount of wind and solar power capacity has rapidly increased in the past few years, variable renewable energy has started to play an increasing role in power system operations and planning. This course will discuss renewable energy and energy efficiency systems modeling, design, and optimization. This course will begin with an introduction to the power grid including planning and operations for the transmission and distribution level power grid. After examining the technological specifications of the most important renewable energy sources (wind energy, photovoltaics, and solar thermal power) and energy efficiency technologies (energy storage, home and building energy, electric vehicles), grid integration of renewable energy and energy efficiency technologies will be examined in detail. From the bulk power system level, the unit commitment and economic dispatch process will be thoroughly covered, with exercises that emphasize how it can change based on new variable generation. This includes topics such as dynamic reserve levels, stochastic unit commitment, and flexibility reserves, variable generation forecasting, and demand response. Distribution planning with high penetrations will be examined. All of these concepts will be explored in great detail and reinforced through the completion of a semester long project, where the students will be solving problems of broad interest in a group setting. Students will use Matlab and R for project design. The course builds on prerequisite knowledge in engineering system design, engineering mathematics, probability and statistics, and optimization methods.

MECH 6318/SYSM 6305: Optimization Theory and Practice, Fall 2016

  • Basics of optimization theory, numerical algorithms, and applications. The course is divided into three main parts: linear programming (simplex method, duality theory), unconstrained methods (optimality conditions, descent algorithms and convergence theorems), and constrained minimization (Lagrange multipliers, Karush-Kuhn-Tucker conditions, active set, penalty and interior point methods). Applications in engineering, operations, finance, statistics, etc. will be emphasized. Students will also use MATLAB optimization toolbox to obtain practical experience with the material.

MECH 1208: Introduction to Mechanical Engineering II, Spring 2016

  • The purpose of this course is to give students a general understanding of the broad range of technical areas and applications specific to the mechanical engineering profession. Course activities include team oriented competitions and lectures by mechanical engineering experts. Introduction of mechanical engineering topics (mechanical design, forces in structures and machines, materials and stresses, motion and power transmission, fluids engineering, thermal and energy systems).

ENGY 3300: Introduction to Energy Technology, Fall 2015, Spring 2016 (Guest Lecturer)