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Course Criteria
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3.00 Credits
Credits: 3 Cross-Listed with PHYS 385 Introduction to basic concepts and methods of materials science. Review of metallic alloys and compounds, ceramic materials, ionic solids, semiconductors, polymers, and nano-structured materials. Mechanical, thermal, electric, magnetic and optical properties of materials. Theoretical background and experimental methods of materials characterization. Various materials applications with emphasis on renewable energy. Prerequisites PHYS 262 or 266 or 245 and a C or better in MATH 113 Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Data mining techniques from statistics, machine learning, and visualization to scientific knowledge discovery. Students will be given a set of case studies and projects to test their understanding of this field and provide a foundation for future applications in their careers. Prerequisites CDS 302. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with MATH 447 Numerical differentiation and integration, initial-value and boundary-value problems for ordinary differential equations, methods of solution of partial differential equations, iterative methods of solution of nonlinear systems, and approximation theory. Prerequisites MATH 214 or 216, and 446. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 This course covers the application of modeling and simulation methods to various scientific applications, including fluid dynamics, solid mechanics, materials science, molecular mechanics, and astrophysics. It will also provide an introduction to modeling and simulation software, as well as high-performance computing. Prerequisites CDS 410 or Math 447. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 The course will cover the governing equations of fluid dynamics; numerical discretization of the governing equations and popular techniques for solving flow problems; applications of CFD to some classic fluid dynamics problems; and setting up the CFD simulation using a CFD software package. At the end of the course, students will understand the process of developing a geometrical model of the flow, applying appropriate boundary conditions, specifying solution parameters, and visualizing the results. The students are expected to complete several computer projects, including writing their own CFD computer program to analyze simple fluid flow problems, as well as setting up the CFD simulation using a CFD software package. Prerequisites MATH 446, proficiency in at least one computer programming language and computer operating system, or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Covers particle methods to solve variety of physical systems. Emphasizes study and development of numerical results, and visualization of these results in complex physical systems. Applications and projects include stellar and galaxy dynamics, smoothed particle hydrodynamics, plasma simulations, and semiconductor device theory algorithms on parallel and vectorized systems. Prerequisites PHYS 510 and MATH 446. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Covers selected topics in computational and data sciences not covered in fixed content courses. Prerequisites Permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Covers computational aspects of materials science, such as first-principles methods of electronic structure calculations of solids, clusters, and molecules, as well as the use of empirical potentials. Examples will be drawn from metals, insulators, and semiconductors. The students will be directed to construct simple codes and guided in the use of the more sophisticated available computational packages. Prerequisites PHYS 308. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Students work under the guidance of a faculty member on an independent study or directed research project in the computational and data sciences. May be repeated up to a total of 6 credits. Prerequisites Permission of the instructor and the department chair. For computational and data science majors and minors in their junior or senior year only. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 On-the-job experience for CDS majors and minors working in industry and government laboratories, including summer programs. Supervision and approval of this course must be arranged with department before registering. May be repeated up to a total of 6 credits. Prerequisites Permission of the instructor and the department chair. For computational and data science majors and minors in their junior or senior year only. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0
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