Teaching

General Teaching Philosophy:

A complete undergraduate education in nuclear and radiation engineering requires a broad exposure to the many facets of theoretical, computational, and experimental nuclear engineering.  Because the undergraduates at Texas are some of the brightest in the world and crave being challenged with innovative research, I will have a high-level of expectations for the classroom education, but also draw undergraduate students into research opportunities to collaborate on teams that include graduate students to develop their educations beyond the books and develop a deep understanding and apprecation for research.

The fundamental courses required for computational nuclear energy research include these courses taught by Dr. Clarno:

1. Introduction to Nuclear Power Systems (ME337C), which provides the foundational understanding of nuclear physics, reactor components, and reactor safety.
2. Nuclear Reactor Theory I (ME338D), which provides an overview of nuclear reactor design, operation, and analysis;
3. Computational Methods in Radiation Transport (ME388F/CSE397), because radiation is unique to nuclear;
4. Design of Nuclear Systems (ME388N), to understand the unique aspects of thermal-fluids in reactor safety; and
5. Nuclear Fuel Performance, to understand the nuclear complexities of the material science and thermo-mechanics of fuel.

These courses require a strong complimentary education in numerical analysis, heat and mass transfer, computational science, and computer programming, which are taught in the Oden Institute for Computational Engineering and Sciences.  To supplment the complimentary coursework from the Oden Institute, students will also be exposed to numerical analysis, scripting languages (Python), and object-oriented programming (Matlab, C++, and/or FORTRAN) in Dr. Clarno’s courses to prepare students for a broad array of opportunities in methods development or reactor analysis.  However, these courses will also complimented with other nuclear classes to provide a broad understanding of experimental nuclear engineering, radiochemistry, radiation shielding and protection, and national security.

To succeed in computational nuclear energy, it is imperative that students gain experience with practical applications to develop the experience and intuition of a reactor engineer and the skillset to acquire competitive job opportunities.  I will incorporate both the theory from the text book with analysis using production software for reactor physics and nuclear fuel performance.  This will provide each student with practical experience with tools used in the nuclear industry and enable them to gain research opportunities in the nuclear industry.

For students with a desire to focus on computational nuclear energy, it is imperative that they develop the foundational knowledge and experience to effectively develop and use advanced software and parallel computing hardware to analyze reactors.  Through both research and course work, I also will instill these vocational educational skills to prepare students for careers in academia and research:

1. Experience with production nuclear analysis software;
2. Utilization of scripting software to enable efficient analyses;
3. Collaborative development of production quality software; and
4. Critical evaluation of technical concepts through review of journals and oral presentations.

Once I have developed a strong cadre of graduate students with a solid foundation in computational methods and software development for each of the individual physics in reactor analysis, I will develop an advanced course in Multiscale, Multiphysics Modeling of Nuclear Systems.  This course will prepare students to deeply understand the complexities associated with my key research interests:

1. Multiphysics coupling methods for advanced simulation of nuclear reactors to integrate analyses and improve accuracy;
2. Multiscale neutronics, fuel performance, and thermal-hydraulics to enable high resolution analyses in coupled physics applications;
3. Design, optimization, and analysis of advanced commercial and test reactor concepts;
4. Integration of software to optimize advanced manufacturing of nuclear technologies; and
5. Propagation of uncertainties through multiphysics applications to optimize experiments.

Course Descriptions

• ME337C – Introduction to Nuclear Power Systems
  • Joint undergraduate and graduate course introducing nuclear energy, reactors components, reactor modeling, and reactor safety
  • Uses “Introduction to Nuclear Engineering,” by Lamarsh and Baratta
• ME388D – Nuclear Reactor Theory 1
  • Graduate course required for the PhD Qualifying Exam with in-depth coverage of nuclear reactor theory and analysis, including lattice physics, isotopic depletion, core analysis, operation and accident analysis, for multiple physics, with a focus on neutronics, for light-water and advanced reactors.
  • Uses “Nuclear Reactor Analysis” by Duderstadt and Hamilton
• ME388F/CSE397 – Computational Methods in Radiation Transport
  • Graduate course covering numerical methods for modeling radiation transport using analytic, deterministic, stochastic, and hybrid methods for neutral particles using both discrete ordinate (Sn) and spherical harmonic (Pn) discretizations in direction of travel as well as multi-group and advanced methods for discretization of neutron/photon energies.  Students will be introduced to time-dependent transport, adjoint methods, perturbation theory, and multiphysics coupling.  This course will include a series of software development projects and literature reviews that will develop insight about the inner workings of production radiation transport software.
• ME388N – Design of Nuclear Systems
  • Graduate course Integration of fluid mechanics, heat transfer, thermomechanics, and thermodynamics with reactor theory for core design.
  • Uses “Nuclear Systems Volume 1: Thermal Hydraulics Fundamentals,” by Todreas and Kazimi