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22.00J Introduction to Modeling and Simulation (MIT) 22.00J Introduction to Modeling and Simulation (MIT)

Description

This course surveys the basic concepts of computer modeling in science and engineering using discrete particle systems and continuum fields. It covers techniques and software for statistical sampling, simulation, data analysis and visualization, and uses statistical, quantum chemical, molecular dynamics, Monte Carlo, mesoscale and continuum methods to study fundamental physical phenomena encountered in the fields of computational physics, chemistry, mechanics, materials science, biology, and applied mathematics. Applications are drawn from a range of disciplines to build a broad-based understanding of complex structures and interactions in problems where simulation is on equal footing with theory and experiment. A term project allows development of individual interests. Students are mentor This course surveys the basic concepts of computer modeling in science and engineering using discrete particle systems and continuum fields. It covers techniques and software for statistical sampling, simulation, data analysis and visualization, and uses statistical, quantum chemical, molecular dynamics, Monte Carlo, mesoscale and continuum methods to study fundamental physical phenomena encountered in the fields of computational physics, chemistry, mechanics, materials science, biology, and applied mathematics. Applications are drawn from a range of disciplines to build a broad-based understanding of complex structures and interactions in problems where simulation is on equal footing with theory and experiment. A term project allows development of individual interests. Students are mentor

Subjects

computer modeling | computer modeling | discrete particle system | discrete particle system | continuum | continuum | continuum field | continuum field | statistical sampling | statistical sampling | data analysis | data analysis | visualization | visualization | quantum | quantum | quantum method | quantum method | chemical | chemical | molecular dynamics | molecular dynamics | Monte Carlo | Monte Carlo | mesoscale | mesoscale | continuum method | continuum method | computational physics | computational physics | chemistry | chemistry | mechanics | mechanics | materials science | materials science | biology; applied mathematics | biology; applied mathematics | fluid dynamics | fluid dynamics | heat | heat | fractal | fractal | evolution | evolution | melting | melting | gas | gas | structural mechanics | structural mechanics | FEM | FEM | finite element | finite element | biology | biology | applied mathematics | applied mathematics | 1.021 | 1.021 | 2.030 | 2.030 | 3.021 | 3.021 | 10.333 | 10.333 | 18.361 | 18.361 | HST.588 | HST.588 | 22.00 | 22.00

License

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3.021J Introduction to Modeling and Simulation (MIT) 3.021J Introduction to Modeling and Simulation (MIT)

Description

This course explores the basic concepts of computer modeling and simulation in science and engineering. We'll use techniques and software for simulation, data analysis and visualization. Continuum, mesoscale, atomistic and quantum methods are used to study fundamental and applied problems in physics, chemistry, materials science, mechanics, engineering, and biology. Examples drawn from the disciplines above are used to understand or characterize complex structures and materials, and complement experimental observations. This course explores the basic concepts of computer modeling and simulation in science and engineering. We'll use techniques and software for simulation, data analysis and visualization. Continuum, mesoscale, atomistic and quantum methods are used to study fundamental and applied problems in physics, chemistry, materials science, mechanics, engineering, and biology. Examples drawn from the disciplines above are used to understand or characterize complex structures and materials, and complement experimental observations.

Subjects

computer modeling | computer modeling | discrete particle system | discrete particle system | continuum | continuum | continuum field | continuum field | statistical sampling | statistical sampling | data analysis | data analysis | visualization | visualization | quantum | quantum | quantum method | quantum method | chemical | chemical | molecular dynamics | molecular dynamics | Monte Carlo | Monte Carlo | mesoscale | mesoscale | continuum method | continuum method | computational physics | computational physics | chemistry | chemistry | mechanics | mechanics | materials science | materials science | biology | biology | applied mathematics | applied mathematics | fluid dynamics | fluid dynamics | heat | heat | fractal | fractal | evolution | evolution | melting | melting | gas | gas | structural mechanics | structural mechanics | FEM | FEM | finite element | finite element

License

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18.310 Principles of Applied Mathematics (MIT) 18.310 Principles of Applied Mathematics (MIT)

Description

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world. Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world.

Subjects

sorting algorithms | sorting algorithms | information theory | information theory | coding theory | coding theory | secret codes | secret codes | generating functions | generating functions | linear programming | linear programming | game theory | game theory | discrete applied mathematics | discrete applied mathematics | mathematical analysis | mathematical analysis | sorting data | sorting data | efficient data storage | efficient data storage | efficient data transmission | efficient data transmission | error correction | error correction | secrecy | secrecy | Fast Fourier Transform | Fast Fourier Transform | network-flow problems | network-flow problems | mathematical economics | mathematical economics | statistics | statistics | probability theory | probability theory | combinatorics | combinatorics | linear algebra | linear algebra

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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3.016 Mathematics for Materials Scientists and Engineers (MIT) 3.016 Mathematics for Materials Scientists and Engineers (MIT)

Description

The class will cover mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from 3.012 to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, fourier analysis and random walks.Technical RequirementsMathematica® software is required to run the .nb files found on this course site. The class will cover mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from 3.012 to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, fourier analysis and random walks.Technical RequirementsMathematica® software is required to run the .nb files found on this course site.

Subjects

energetics | energetics | materials structure and symmetry: applied fields | materials structure and symmetry: applied fields | mechanics and physics of solids and soft materials | mechanics and physics of solids and soft materials | linear algebra | linear algebra | orthonormal basis | orthonormal basis | eigenvalues | eigenvalues | eigenvectors | eigenvectors | quadratic forms | quadratic forms | tensor operations | tensor operations | symmetry operations | symmetry operations | calculus | calculus | complex analysis | complex analysis | differential equations | differential equations | theory of distributions | theory of distributions | fourier analysis | fourier analysis | random walks | random walks | mathematical technicques | mathematical technicques | materials science | materials science | materials engineering | materials engineering | materials structure | materials structure | symmetry | symmetry | applied fields | applied fields | materials response | materials response | solids mechanics | solids mechanics | solids physics | solids physics | soft materials | soft materials | multi-variable calculus | multi-variable calculus | ordinary differential equations | ordinary differential equations | partial differential equations | partial differential equations | applied mathematics | applied mathematics | mathematical techniques | mathematical techniques

License

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18.307 Integral Equations (MIT) 18.307 Integral Equations (MIT)

Description

This course emphasizes concepts and techniques for solving integral equations from an applied mathematics perspective. Material is selected from the following topics: Volterra and Fredholm equations, Fredholm theory, the Hilbert-Schmidt theorem; Wiener-Hopf Method; Wiener-Hopf Method and partial differential equations; the Hilbert Problem and singular integral equations of Cauchy type; inverse scattering transform; and group theory. Examples are taken from fluid and solid mechanics, acoustics, quantum mechanics, and other applications. This course emphasizes concepts and techniques for solving integral equations from an applied mathematics perspective. Material is selected from the following topics: Volterra and Fredholm equations, Fredholm theory, the Hilbert-Schmidt theorem; Wiener-Hopf Method; Wiener-Hopf Method and partial differential equations; the Hilbert Problem and singular integral equations of Cauchy type; inverse scattering transform; and group theory. Examples are taken from fluid and solid mechanics, acoustics, quantum mechanics, and other applications.

Subjects

integral equations | integral equations | applied mathematics | applied mathematics | Volterra equation | Volterra equation | Fredholm equation | Fredholm equation | Fredholm theory | Fredholm theory | Hilbert-Schmidt theorem | Hilbert-Schmidt theorem | Wiener-Hopf Method | Wiener-Hopf Method | partial differential equations | partial differential equations | Hilbert Problem | Hilbert Problem | ingular integral equations | ingular integral equations | Cauchy type | Cauchy type | inverse scattering transform | inverse scattering transform | group theory | group theory | fluid mechanics | fluid mechanics | solid mechanics | solid mechanics | acoustics | acoustics | quantum mechanics | quantum mechanics

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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18.311 Principles of Applied Mathematics (MIT) 18.311 Principles of Applied Mathematics (MIT)

Description

18.311 Principles of Continuum Applied Mathematics covers fundamental concepts in continuous applied mathematics, including applications from traffic flow, fluids, elasticity, granular flows, etc. The class also covers continuum limit; conservation laws, quasi-equilibrium; kinematic waves; characteristics, simple waves, shocks; diffusion (linear and nonlinear); numerical solution of wave equations; finite differences, consistency, stability; discrete and fast Fourier transforms; spectral methods; transforms and series (Fourier, Laplace). Additional topics may include sonic booms, Mach cone, caustics, lattices, dispersion, and group velocity. 18.311 Principles of Continuum Applied Mathematics covers fundamental concepts in continuous applied mathematics, including applications from traffic flow, fluids, elasticity, granular flows, etc. The class also covers continuum limit; conservation laws, quasi-equilibrium; kinematic waves; characteristics, simple waves, shocks; diffusion (linear and nonlinear); numerical solution of wave equations; finite differences, consistency, stability; discrete and fast Fourier transforms; spectral methods; transforms and series (Fourier, Laplace). Additional topics may include sonic booms, Mach cone, caustics, lattices, dispersion, and group velocity.

Subjects

partial differential equation | partial differential equation | hyperbolic equations | hyperbolic equations | dimensional analysis | dimensional analysis | perturbation methods | perturbation methods | hyperbolic systems | hyperbolic systems | diffusion and reaction processes | diffusion and reaction processes | continuum models | continuum models | equilibrium models | equilibrium models | continuous applied mathematics | continuous applied mathematics | traffic flow | traffic flow | fluids | fluids | elasticity | elasticity | granular flows | granular flows | continuum limit | continuum limit | conservation laws | conservation laws | quasi-equilibrium | quasi-equilibrium | kinematic waves | kinematic waves | characteristics | characteristics | simple waves | simple waves | shocks | shocks | diffusion (linear and nonlinear) | diffusion (linear and nonlinear) | numerical solution of wave equations | numerical solution of wave equations | finite differences | finite differences | consistency | consistency | stability | stability | discrete and fast Fourier transforms | discrete and fast Fourier transforms | spectral methods | spectral methods | transforms and series (Fourier | Laplace) | transforms and series (Fourier | Laplace) | sonic booms | sonic booms | Mach cone | Mach cone | caustics | caustics | lattices | lattices | dispersion | dispersion | group velocity | group velocity

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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22.00J Introduction to Modeling and Simulation (MIT)

Description

This course surveys the basic concepts of computer modeling in science and engineering using discrete particle systems and continuum fields. It covers techniques and software for statistical sampling, simulation, data analysis and visualization, and uses statistical, quantum chemical, molecular dynamics, Monte Carlo, mesoscale and continuum methods to study fundamental physical phenomena encountered in the fields of computational physics, chemistry, mechanics, materials science, biology, and applied mathematics. Applications are drawn from a range of disciplines to build a broad-based understanding of complex structures and interactions in problems where simulation is on equal footing with theory and experiment. A term project allows development of individual interests. Students are mentor

Subjects

computer modeling | discrete particle system | continuum | continuum field | statistical sampling | data analysis | visualization | quantum | quantum method | chemical | molecular dynamics | Monte Carlo | mesoscale | continuum method | computational physics | chemistry | mechanics | materials science | biology; applied mathematics | fluid dynamics | heat | fractal | evolution | melting | gas | structural mechanics | FEM | finite element | biology | applied mathematics | 1.021 | 2.030 | 3.021 | 10.333 | 18.361 | HST.588 | 22.00

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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3.021J Introduction to Modeling and Simulation (MIT)

Description

This course explores the basic concepts of computer modeling and simulation in science and engineering. We'll use techniques and software for simulation, data analysis and visualization. Continuum, mesoscale, atomistic and quantum methods are used to study fundamental and applied problems in physics, chemistry, materials science, mechanics, engineering, and biology. Examples drawn from the disciplines above are used to understand or characterize complex structures and materials, and complement experimental observations.

Subjects

computer modeling | discrete particle system | continuum | continuum field | statistical sampling | data analysis | visualization | quantum | quantum method | chemical | molecular dynamics | Monte Carlo | mesoscale | continuum method | computational physics | chemistry | mechanics | materials science | biology | applied mathematics | fluid dynamics | heat | fractal | evolution | melting | gas | structural mechanics | FEM | finite element

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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18.310 Principles of Applied Mathematics (MIT)

Description

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world.

Subjects

sorting algorithms | information theory | coding theory | secret codes | generating functions | linear programming | game theory | discrete applied mathematics | mathematical analysis | sorting data | efficient data storage | efficient data transmission | error correction | secrecy | Fast Fourier Transform | network-flow problems | mathematical economics | statistics | probability theory | combinatorics | linear algebra

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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3.016 Mathematics for Materials Scientists and Engineers (MIT)

Description

The class will cover mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from 3.012 to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, fourier analysis and random walks.Technical RequirementsMathematica® software is required to run the .nb files found on this course site.

Subjects

energetics | materials structure and symmetry: applied fields | mechanics and physics of solids and soft materials | linear algebra | orthonormal basis | eigenvalues | eigenvectors | quadratic forms | tensor operations | symmetry operations | calculus | complex analysis | differential equations | theory of distributions | fourier analysis | random walks | mathematical technicques | materials science | materials engineering | materials structure | symmetry | applied fields | materials response | solids mechanics | solids physics | soft materials | multi-variable calculus | ordinary differential equations | partial differential equations | applied mathematics | mathematical techniques

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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18.311 Principles of Applied Mathematics (MIT)

Description

18.311 Principles of Continuum Applied Mathematics covers fundamental concepts in continuous applied mathematics, including applications from traffic flow, fluids, elasticity, granular flows, etc. The class also covers continuum limit; conservation laws, quasi-equilibrium; kinematic waves; characteristics, simple waves, shocks; diffusion (linear and nonlinear); numerical solution of wave equations; finite differences, consistency, stability; discrete and fast Fourier transforms; spectral methods; transforms and series (Fourier, Laplace). Additional topics may include sonic booms, Mach cone, caustics, lattices, dispersion, and group velocity.

Subjects

partial differential equation | hyperbolic equations | dimensional analysis | perturbation methods | hyperbolic systems | diffusion and reaction processes | continuum models | equilibrium models | continuous applied mathematics | traffic flow | fluids | elasticity | granular flows | continuum limit | conservation laws | quasi-equilibrium | kinematic waves | characteristics | simple waves | shocks | diffusion (linear and nonlinear) | numerical solution of wave equations | finite differences | consistency | stability | discrete and fast Fourier transforms | spectral methods | transforms and series (Fourier | Laplace) | sonic booms | Mach cone | caustics | lattices | dispersion | group velocity

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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18.307 Integral Equations (MIT)

Description

This course emphasizes concepts and techniques for solving integral equations from an applied mathematics perspective. Material is selected from the following topics: Volterra and Fredholm equations, Fredholm theory, the Hilbert-Schmidt theorem; Wiener-Hopf Method; Wiener-Hopf Method and partial differential equations; the Hilbert Problem and singular integral equations of Cauchy type; inverse scattering transform; and group theory. Examples are taken from fluid and solid mechanics, acoustics, quantum mechanics, and other applications.

Subjects

integral equations | applied mathematics | Volterra equation | Fredholm equation | Fredholm theory | Hilbert-Schmidt theorem | Wiener-Hopf Method | partial differential equations | Hilbert Problem | ingular integral equations | Cauchy type | inverse scattering transform | group theory | fluid mechanics | solid mechanics | acoustics | quantum mechanics

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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