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1 - 4 of 4 results for: CME104

AA 113: Aerospace Computational Science

Computational methods are pervasive in analysis, design and optimization of aerospace systems. This course introduces the fundamental concepts underlying aerospace computational science. Starting from the concepts of meshes, elements and point clouds, interpolation, quadrature and time integration, the techniques of finite difference, finite volume and finite element discretization of general PDE problems, and analysis of the accuracy, consistency and stability of discretized problems including treatment of boundary conditions are developed. In depth applications to computations of ideal subsonic, transonic and supersonic flows, and viscous internal and external flow with a turbulence model are introduced. Through the use of commercial and research software (ANSYS Fluent, SU2 and AERO Suite) the student is exposed to the use of computational tools for solving practical aerospace engineering problems. The course culminates with the treatment of multidisciplinary aerospace problems invol more »
Computational methods are pervasive in analysis, design and optimization of aerospace systems. This course introduces the fundamental concepts underlying aerospace computational science. Starting from the concepts of meshes, elements and point clouds, interpolation, quadrature and time integration, the techniques of finite difference, finite volume and finite element discretization of general PDE problems, and analysis of the accuracy, consistency and stability of discretized problems including treatment of boundary conditions are developed. In depth applications to computations of ideal subsonic, transonic and supersonic flows, and viscous internal and external flow with a turbulence model are introduced. Through the use of commercial and research software (ANSYS Fluent, SU2 and AERO Suite) the student is exposed to the use of computational tools for solving practical aerospace engineering problems. The course culminates with the treatment of multidisciplinary aerospace problems involving coupling across more than one discipline, such as aero-thermal analysis (for hypersonic vehicle performance analysis or gas turbine blade cooling), fluid-structure interaction problems (such as flutter or flapping wing aeroelastic performance), and aeroacoustics (such as jet noise for next generation commercial supersonic transport or noise radiation from multi-rotor urban air mobility platform). Students are expected to pursue significant computational projects in two-person teams. nPrerequisites: CME102, CME104 (multivariable calculus, linear algebra, ODEs and some PDEs), ENGR 14, ME 30, ME70, and Recommended courses: AA102, AA103.
Terms: Win | Units: 3

BIOE 244: Advanced Frameworks and Approaches for Engineering Integrated Genetic Systems

Concepts and techniques for the design and implementation of engineered genetic systems. Topics covered include the quantitative exploration of tools that support (a) molecular component engineering, (b) abstraction and composition of functional genetic devices, (c) use of control and dynamical systems theory in device and systems design, (d) treatment of molecular "noise", (e) integration of DNA-encoded programs within cellular chassis, (f) designing for evolution, and (g) the use of standards in measurement, genetic layout architecture, and data exchange. Prerequisites: CME104, CME106, CHEM 33, BIO41, BIO42, BIOE41, BIOE42, and BIOE44 (or equivalents), or permission of the instructors.
Last offered: Spring 2019

CME 104: Linear Algebra and Partial Differential Equations for Engineers (ENGR 155B)

Linear algebra: systems of algebraic equations, Gaussian elimination, undetermined and overdetermined systems, coupled systems of ordinary differential equations, LU factorization, eigensystem analysis, normal modes. Linear independence, vector spaces, subspaces and basis. Numerical analysis applied to structural equilibrium problems, electrical networks, and dynamic systems. Fourier series with applications, partial differential equations arising in science and engineering, analytical solutions of partial differential equations. Applications in heat and mass transport, mechanical vibration and acoustic waves, transmission lines, and fluid mechanics. Numerical methods for solution of partial differential equations: iterative techniques, stability and convergence, time advancement, implicit methods, von Neumann stability analysis. Examples and applications drawn from a variety of engineering fields. Prerequisite: CME102/ ENGR155A.
Terms: Spr | Units: 5 | UG Reqs: GER:DB-Math, WAY-FR
Instructors: Khayms, V. (PI)

CME 104A: Linear Algebra and Partial Differential Equations for Engineers, ACE

Students attend CME104/ENGR155B lectures with additional recitation sessions; two to four hours per week, emphasizing engineering mathematical applications and collaboration methods. Prerequisite: students must be enrolled in the regular section ( CME104) prior to submitting application at: https://engineering.stanford.edu/students/programs/engineering-diversity-programs/additional-calculus-engineers
Terms: Spr | Units: 6 | UG Reqs: GER:DB-Math, WAY-FR
Instructors: Khayms, V. (PI)
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