Graduate Courses Descriptions: Energy Systems Engineering
Energy Systems Engineering Curriculum
A University of Maryland Field Committee has developed the interdisciplinary ESE curriculum. It will provide a coherent approach to energy engineering by equipping its students with the tools needed to conceptualize, analyze, design and integrate advanced energy systems. This approach is informed by a broad perspective on energy production, transmission and utilization technology options and trade-offs, and an appreciation for public policy and regulatory issues.
The curriculum will focus on the science and engineering that underpins energy conversion systems and will address engineering, science, and societal issues in the areas of fossil, nuclear, and renewable power generation, including hydrogen production and generation, energy usage, conservation and optimization, and sustainable development.
Research and education in the science and engineering of fossil, nuclear, and renewable energy production are current areas of strength at UMD and are perceived to be of critical importance to the future well being of this nation. ESE students will be uniquely qualified to participate in the formulation and implementation of future energy strategies and will provide a leadership cadre for the energy engineering community.
Participating students will be expected to complete the MS or PhD degree requirements of their respective departments' programs, while taking as many courses as possible from the ESE Curriculum. The final decision on course selection is reached in coordination with the student, his/her adviser and the respective department's graduate director.
Students participating in the ESE Curriculum must be accepted as advisee by one of the faculty participating in the ESE Curriculum and should have completed a BS in an engineering discipline.
Faculty of Participating Colleges and Departments
A. J. Clark School of Engineering- Department of Civil Engineering: Steve Gabriel, Deborah Goodings
- Department of Electrical and Computer Engineering: Thomas M. Antonsen, Patrick O'Shea
- Department of Materials Science and Engineering: Aris Christou
- Department of Mechanical Engineering: Ashwani Gupta, Greg Jackson, Jungho Kim, Mohammad Modarres, Reinhard Radermacher
- Department of Chemistry and Biochemistry: Bryan Eichhorn
- School of Public-Policy: Mathias Ruth
More information & Faculty Links
The Energy Systems Engineering curriculum identifies the following core courses that all students are expected to take:
ENME 808D Sustainable Energy Production and Usage
The objective of the course is to a) provide understanding of conventional and sustainable energy production and utilization which will serve as a foundation for the Energy Systems Engineering Program and b) to identify areas where research and development is needed to move the world toward a sustainable energy future.
This course reviews the major sources and end-uses of energy in our current society as well as treating the sources and end-uses that are expected to become important in the near term. Renewable energy sources will be highlighted with a focus on projections for a sustainable energy future. The course will provide an overview of the major energy flows and the issues associated with production and end-use. Major current sources of energy include fossil fuel, hydroelectric, nuclear power, and wind energy. Major end-use categories include industrial uses, transportation and buildings. The course will introduce a range of innovative technologies and put them in the context of the current energy infrastructure. These will include fuel cells, hybrid cars, advanced nuclear reactor designs, combined cycle power plants, photovoltaics and other current topics. Attention will also be devoted to societal and regulatory aspects of energy production and use. (Kim, Radermacher)
ENME 635 Energy Systems Analysis
The course discusses Rankin cycles from traditional power plants to move, two-, multi-and variable-stage absorption cycles and vapor compression cycles with pure and mixed working fluids and gas turbine cycles. Student projects are designed to foster the understanding of opportunities and challenges in energy system integration focusing predominantly on conventional and well-established energy conversion technologies. (Radermacher)
The following lists the elective courses of the curriculum:
ENME 632 Advanced Convection Heat Transfer
Statement of conservation of mass, momentum and energy. Laminar and turbulent heat transfer in ducts, separated flows, and natural convection. Heat and mass transfer in laminar boundary layers. Nucleate boiling, film boiling, Leidenfrost transition, and critical heat flux. Interfacial phase change processes; evaporation, condensation, industrial applications such as cooling towers, condensers. Heat exchanger design. ( Jackson )
ENME 633 Advanced Thermodynamics
This course will focus on developing physical and mathematical insight into the properties of matter and the interactions between molecules, which govern macro-scale processes relevant to energy engineering as well as other fields. The course emphasizes how thermodynamics at the smallest scales is used to derive models for larger scale processes ranging from phase changes, surface wetting, combustion, adsorption, and electrochemistry. The link between classical thermodynamics and statistical analysis is established for calculating properties and process behavior. The statistical approaches are combined with molecular level simulations at the end of the course to investigate processes relevant to engineering design using such fundamental computational approaches. ( Jackson )
ENME 706 Impact of Energy Conversion on the Environment
This course begins with a review of the energy flow diagram of the US and discusses the current status of energy production, transportation and consumption. This is followed by an introduction to environmental issues that are caused through energy conversion: Ozone depletion, global warming and air quality issues. Based on this background information, the students then develop, through classroom discussions, student presentations and lectures, alternative energy conversion concepts, assess their performance in design projects, and evaluate the potential environmental, infrastructure and cost impacts. The course focuses extensively and in considerable detail on the understanding and application of the latest energy conversion technologies. (Jackson, Radermacher)
ENME 707 Combustion and Reacting Flow
This course covers thermochemistry and chemical kinetics of reacting flows in depth. In particular, we focus on the combustion of hydrocarbon fuels in both a phenomenological and mechanistic approach. The course covers the specifics of premixed and nonpremixed flame systems, as well as ignition and extinction. Combustion modeling with equilibrium and chemical kinetics methods will be addressed. Environmental impact and emissions minimization will be covered in detail. Finally, the course will cover available combustion diagnostic methods and their application in laboratory and real-world systems. (Zachariah)
ENME 712 Measurement and Instrumentation
This course is designed to offer systematic coverage of the methodologies for measurement and data analysis of thermal and fluid processes at the graduate level. The course materials will cover three broad categories: (1) Fundamentals of thermal and fluid processes in single phase and multi phase flows as related to this course; (2) Measurement/Instrumentation techniques for measurement of basic quantities such as pressure, temperature, flow rate, heat flux, etc.; and (3) Experimental design and planning, sources of errors in measurements, and uncertainty analysis. (Ohadi, Kiger)
ENRE 602 Reliability Analysis
Principal methods of reliability analysis, including fault tree and reliability block diagrams; Failure Mode and Effects Analysis (FMEA); event tree construction and evaluation; reliability data collection and analysis; methods of modeling systems for reliability analysis. Focus on problems related to process industries, fossil-fueled power plant availability, and other systems of concern to engineers. (Modarres, Mosleh)
ENRE 620 Mathematical Techniques for Engineers
Basic probability and statistics. Application of selected mathematical techniques to the analysis and solution of reliability engineering problems. Applications of matrices, vectors, tensors, differential equations, integral transforms, and probability methods to a wide range of engineering problems. (Bernard, Modarres, Smidts)
ENRE 670 Risk Assessment for Engineers
Why study risk, sources of risk, probabilistic risk assessment procedure, factors affecting risk acceptance, statistical risk acceptance analysis, psychometric risk of lately a new loan the more you do you of him and him who me in the you really want new in the end of on of of the the design to the mom to acceptance, perception of risk, comparison or risks, consequence analysis, risk benefit assessment. Risk analysis performed for light water reactors, chemical industry, and dams. Class projects on risk management concepts. (Mosleh, Modarres)
ENCE 722 Market, Spatial, and Traffic Equilibrium Models
Provide motivation and introduction to equilibrium models involving economics and engineering. We will concentrate on models involving markets (Nash-Cournot, etc.), those wherein the activities are spatially diverse, and those involving energy activities or traffic flow. Areas that will be covered include:
- Review of relevant optimization theory
- Presentation of the nonlinear complementarity problem (NCP) and variational inequality problem (VIP) formats to solve equilibrium problems as well as introduction to existence and uniqueness results
- Review of relevant game theory notions
- Presentation of specific models for market, spatial, energy, and traffic equilibrium problems
- Presentations for algorithms to solve these equilibrium problems (Gabriel)
ENCE 723 Multiobjective Optimization
In many engineering and applied mathematics settings, one needs to compute a solution to a problem with more than one objective. The traditional optimization model in these settings is not sufficient to accurately depict the problem at hand. Examples include: maximizing an organization's profit while also maximizing reliability and minimizing environmental pollution, or minimizing both time and cost on a project at the same time. This course is an introduction to the theory and algorithms behind optimization under such competing objectives, also called "multiobjective optimization". In this course, we explore the concepts of dominated solutions, Pareto optimal or "efficient" solutions, as well as several approaches to finding such points. We develop the theory for general nonlinear multiobjective optimization problems but concentrate the majority of effort on the linear case for the algorithms. In addition, we consider other multi-objective type models such as goal programming to solve problems with competing objectives. (Gabriel)
ENCE 724 Nonlinear Programming
Many problems in engineering and economics involve optimizing an objective subject to certain constraints. This course provides mathematically rigorous motivation and introduction to nonlinear programming theory, relevant to numerous problems in economics, engineering, and other disciplines. We will concentrate on models the necessary and sufficient conditions for optimality of nonlinear programs. Areas that will be covered include:
- Classification of optimization problems, definitions of local vs. global optimality, examples, directional differentiability, Existence and uniqueness results for nonlinear programs
- Derivation of necessary and sufficient conditions for unconstrained nonlinear program, derivation of necessary and sufficient conditions for constrained nonlinear programs (not specific to Karush-Kuhn-Tucker conditions), motivation and derivation of Karush-Kuhn-Tucker optimality conditions from both a geometric and algebraic perspective
- Duality theory for nonlinear programs
- Second order optimality conditions for constrained problems
- Equilibrium problems as extensions to the KKT conditions: nonlinear complementarity and variational inequality formulation
- Algorithms to solve optimization and equilibrium problems (Gabriel)
ENCE 725 Probabilistic Optimization
Many problems in engineering and economics involve both uncertainty due to measurement error, lack of information, or inherent unpredictability. In the presence of such uncertainty, it is often necessary to come up with optimal decisions relative to investments or operational aspects of the problem at hand. This course provides an introduction to optimization under uncertainty covering:
- chance-constrained programming
- reliability programming
- value of information
- two stage problems with recourse
- decomposition methods
- nonlinear and linear programming theory
- probability theory (Gabriel)
ENME 610 Engineering Optimization
To present an overview of computational methods for single- and multi-objective design optimization problems with continuous design variables. The course will include a project and the use of Matlab optimization toolbox in some homework and also in the project.
- Concepts, definitions and examples
- Optimality and convexity
- Linear programming
- Single objective optimization: unconstrained methods
- Single objective optimization: constrained methods
- Multi-objective optimization methods
- Post-optimality analysis
- Optimization with Matlab and Excel (Azarm)
ENME 625 Multidisciplinary Optimization
(in transition to become: DISCRETE ENGINEERING OPTIMIZATION)
- Optimality and duality
- Mixed (continuous) integer/discrete optimization: single objective
- Mixed continuous-discrete optimization: multiple objectives
- Robust optimization
- Multi-Disciplinary optimization
- Multi-Level Post optimality sensitivity analysis (Azarm)
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