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15.070J Advanced Stochastic Processes (MIT) 15.070J Advanced Stochastic Processes (MIT)

Description

This class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models. This class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.Subjects

analysis | analysis | modeling | modeling | stochastic processes | stochastic processes | theoretic probability | theoretic probability | martingales | martingales | filtration | filtration | stopping theorems | stopping theorems | large deviations theory | large deviations theory | Brownian motion | Brownian motion | reflected Brownian motion | reflected Brownian motion | stochastic integration | stochastic integration | Ito calculus | Ito calculus | functional limit theorems | functional limit theorems | applications | applications | finance theory | finance theory | insurance | insurance | queueing | queueing | inventory models | inventory modelsLicense

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.htmSite sourced from

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See all metadata15.070 Advanced Stochastic Processes (MIT) 15.070 Advanced Stochastic Processes (MIT)

Description

The class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models. The class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.Subjects

analysis | analysis | modeling | modeling | stochastic processes | stochastic processes | theoretic probability | theoretic probability | martingales | martingales | filtration | filtration | stopping theorems | stopping theorems | large deviations theory | large deviations theory | Brownian motion | Brownian motion | reflected Brownian motion | reflected Brownian motion | stochastic integration | stochastic integration | Ito calculus | Ito calculus | functional limit theorems | functional limit theorems | applications | applications | finance theory | finance theory | insurance | insurance | queueing | queueing | inventory models | inventory modelsLicense

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.htmSite sourced from

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See all metadata2.57 Nano-to-Macro Transport Processes (MIT) 2.57 Nano-to-Macro Transport Processes (MIT)

Description

This course provides parallel treatments of photons, electrons, phonons, and molecules as energy carriers, aiming at fundamental understanding and descriptive tools for energy and heat transport processes from nanoscale continuously to macroscale. Topics include the energy levels, the statistical behavior and internal energy, energy transport in the forms of waves and particles, scattering and heat generation processes, Boltzmann equation and derivation of classical laws, deviation from classical laws at nanoscale and their appropriate descriptions, with applications in nano- and microtechnology. This course provides parallel treatments of photons, electrons, phonons, and molecules as energy carriers, aiming at fundamental understanding and descriptive tools for energy and heat transport processes from nanoscale continuously to macroscale. Topics include the energy levels, the statistical behavior and internal energy, energy transport in the forms of waves and particles, scattering and heat generation processes, Boltzmann equation and derivation of classical laws, deviation from classical laws at nanoscale and their appropriate descriptions, with applications in nano- and microtechnology.Subjects

nanotechnology | nanotechnology | nanoscale | nanoscale | transport phenomena | transport phenomena | photons | photons | electrons | electrons | phonons | phonons | energy carriers | energy carriers | energy transport | energy transport | heat transport | heat transport | energy levels | energy levels | statistical behavior | statistical behavior | internal energy | internal energy | waves and particles | waves and particles | scattering | scattering | heat generation | heat generation | Boltzmann equation | Boltzmann equation | classical laws | classical laws | microtechnology | microtechnology | crystal | crystal | lattice | lattice | quantum oscillator | quantum oscillator | laudaurer | laudaurer | nanotube | nanotube | Louiville equation | Louiville equation | X-ray | X-ray | blackbody | blackbody | quantum well | quantum well | Fourier | Fourier | Newton | Newton | Ohm | Ohm | thermoelectric effect | thermoelectric effect | Brownian motion | Brownian motion | surface tension | surface tension | van der Waals potential. | van der Waals potential. | van der Waals potential | van der Waals potentialLicense

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.htmSite sourced from

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See all metadata18.175 Theory of Probability (MIT) 18.175 Theory of Probability (MIT)

Description

This course covers the laws of large numbers and central limit theorems for sums of independent random variables. It also analyzes topics such as the conditioning and martingales, the Brownian motion and the elements of diffusion theory. This course covers the laws of large numbers and central limit theorems for sums of independent random variables. It also analyzes topics such as the conditioning and martingales, the Brownian motion and the elements of diffusion theory.Subjects

Earth | Earth | Solar System | Solar System | Geophysics | Geophysics | Gravitational Field | Gravitational Field | Magnetic Field | Magnetic Field | Seismology | Seismology | Geodynamics | Geodynamics | Laws of large numbers | Laws of large numbers | central limit theorems for sums of independent random variables | central limit theorems for sums of independent random variables | conditioning and martingales | conditioning and martingales | Brownian motion and elements of diffusion theory | Brownian motion and elements of diffusion theory | functional limit theorems | functional limit theoremsLicense

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.htmSite sourced from

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See all metadata18.175 Theory of Probability (MIT) 18.175 Theory of Probability (MIT)

Description

This course covers the laws of large numbers and central limit theorems for sums of independent random variables. It also analyzes topics such as the conditioning and martingales, the Brownian motion and the elements of diffusion theory. This course covers the laws of large numbers and central limit theorems for sums of independent random variables. It also analyzes topics such as the conditioning and martingales, the Brownian motion and the elements of diffusion theory.Subjects

Earth | Earth | Solar System | Solar System | Geophysics | Geophysics | Gravitational Field | Gravitational Field | Magnetic Field | Magnetic Field | Seismology | Seismology | Geodynamics | Geodynamics | Laws of large numbers | Laws of large numbers | central limit theorems for sums of independent random variables | central limit theorems for sums of independent random variables | conditioning and martingales | conditioning and martingales | Brownian motion and elements of diffusion theory | Brownian motion and elements of diffusion theory | functional limit theorems | functional limit theoremsLicense

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.htmSite sourced from

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See all metadata15.070 Advanced Stochastic Processes (MIT)

Description

The class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.Subjects

analysis | modeling | stochastic processes | theoretic probability | martingales | filtration | stopping theorems | large deviations theory | Brownian motion | reflected Brownian motion | stochastic integration | Ito calculus | functional limit theorems | applications | finance theory | insurance | queueing | inventory modelsLicense

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.htmSite sourced from

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See all metadata22.616 Plasma Transport Theory (MIT) 22.616 Plasma Transport Theory (MIT)

Description

This course describes the processes by which mass, momentum, and energy are transported in plasmas, with special reference to magnetic confinement fusion applications. The Fokker-Planck collision operator and its limiting forms, as well as collisional relaxation and equilibrium, are considered in detail. Special applications include a Lorentz gas, Brownian motion, alpha particles, and runaway electrons. The Braginskii formulation of classical collisional transport in general geometry based on the Fokker-Planck equation is presented. Neoclassical transport in tokamaks, which is sensitive to the details of the magnetic geometry, is considered in the high (Pfirsch-Schluter), low (banana) and intermediate (plateau) regimes of collisionality. This course describes the processes by which mass, momentum, and energy are transported in plasmas, with special reference to magnetic confinement fusion applications. The Fokker-Planck collision operator and its limiting forms, as well as collisional relaxation and equilibrium, are considered in detail. Special applications include a Lorentz gas, Brownian motion, alpha particles, and runaway electrons. The Braginskii formulation of classical collisional transport in general geometry based on the Fokker-Planck equation is presented. Neoclassical transport in tokamaks, which is sensitive to the details of the magnetic geometry, is considered in the high (Pfirsch-Schluter), low (banana) and intermediate (plateau) regimes of collisionality.Subjects

Plasmas | Plasmas | magnetic confinement fusion | magnetic confinement fusion | Fokker-Planck collision operator | Fokker-Planck collision operator | collisional relaxation and equilibrium | collisional relaxation and equilibrium | Lorentz gas | Lorentz gas | Brownian motion | Brownian motion | alpha particles | alpha particles | runaway electrons | runaway electrons | Braginskii formulation | Braginskii formulation | tokamak | tokamak | Pfirsch-Schluter | Pfirsch-Schluter | regimes of collisionality | regimes of collisionalityLicense

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.htmSite sourced from

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See all metadata18.175 Theory of Probability (MIT) 18.175 Theory of Probability (MIT)

Description

This course covers topics such as sums of independent random variables, central limit phenomena, infinitely divisible laws, Levy processes, Brownian motion, conditioning, and martingales. This course covers topics such as sums of independent random variables, central limit phenomena, infinitely divisible laws, Levy processes, Brownian motion, conditioning, and martingales.Subjects

Laws of large numbers | Laws of large numbers | central limit theorems | central limit theorems | independent random variables | independent random variables | conditioning | conditioning | martingales | martingales | Brownian motion | Brownian motion | elements of diffusion theory | elements of diffusion theory | functional limit theorems | functional limit theoremsLicense

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.htmSite sourced from

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See all metadata18.175 Theory of Probability (MIT) 18.175 Theory of Probability (MIT)

Description

This course covers the laws of large numbers and central limit theorems for sums of independent random variables. It also analyzes topics such as the conditioning and martingales, the Brownian motion and the elements of diffusion theory. This course covers the laws of large numbers and central limit theorems for sums of independent random variables. It also analyzes topics such as the conditioning and martingales, the Brownian motion and the elements of diffusion theory.Subjects

Earth | Earth | Solar System | Solar System | Geophysics | Geophysics | Gravitational Field | Gravitational Field | Magnetic Field | Magnetic Field | Seismology | Seismology | Geodynamics | Geodynamics | Laws of large numbers | Laws of large numbers | central limit theorems for sums of independent random variables | central limit theorems for sums of independent random variables | conditioning and martingales | conditioning and martingales | Brownian motion and elements of diffusion theory | Brownian motion and elements of diffusion theory | functional limit theorems | functional limit theoremsLicense

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.htmSite sourced from

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See all metadataDescription

This course develops and applies scaling laws and the methods of continuum and statistical mechanics to biomechanical phenomena over a range of length scales, from molecular to cellular to tissue or organ level. This course develops and applies scaling laws and the methods of continuum and statistical mechanics to biomechanical phenomena over a range of length scales, from molecular to cellular to tissue or organ level.Subjects

biomechanics | biomechanics | molecular mechanics | molecular mechanics | cell mechanics | cell mechanics | Brownian motion | Brownian motion | Reynolds numbers | Reynolds numbers | mechanochemistry | mechanochemistry | Kramers' model | Kramers' model | Bell model | Bell model | viscoelasticity | viscoelasticity | poroelasticity | poroelasticity | optical tweezers | optical tweezers | extracellular matrix | extracellular matrix | collagen | collagen | proteoglycan | proteoglycan | cell membrane | cell membrane | cell motility | cell motility | mechanotransduction | mechanotransduction | cancer | cancer | biological systems | biological systems | molecular biology | molecular biology | cell biology | cell biology | cytoskeleton | cytoskeleton | cell | cell | biophysics | biophysics | cell migration | cell migration | biomembrane | biomembrane | tissue mechanics | tissue mechanics | rheology | rheology | polymer | polymer | length scale | length scale | muscle mechanics | muscle mechanics | experimental methods | experimental methodsLicense

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.htmSite sourced from

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See all metadata15.070 Advanced Stochastic Processes (MIT)

Description

The class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.Subjects

analysis | modeling | stochastic processes | theoretic probability | martingales | filtration | stopping theorems | large deviations theory | Brownian motion | reflected Brownian motion | stochastic integration | Ito calculus | functional limit theorems | applications | finance theory | insurance | queueing | inventory modelsLicense

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.htmSite sourced from

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See all metadata15.070J Advanced Stochastic Processes (MIT)

Description

This class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.Subjects

analysis | modeling | stochastic processes | theoretic probability | martingales | filtration | stopping theorems | large deviations theory | Brownian motion | reflected Brownian motion | stochastic integration | Ito calculus | functional limit theorems | applications | finance theory | insurance | queueing | inventory modelsLicense

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.htmSite sourced from

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See all metadata18.175 Theory of Probability (MIT)

Description

This course covers the laws of large numbers and central limit theorems for sums of independent random variables. It also analyzes topics such as the conditioning and martingales, the Brownian motion and the elements of diffusion theory.Subjects

Earth | Solar System | Geophysics | Gravitational Field | Magnetic Field | Seismology | Geodynamics | Laws of large numbers | central limit theorems for sums of independent random variables | conditioning and martingales | Brownian motion and elements of diffusion theory | functional limit theoremsLicense

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.htmSite sourced from

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See all metadata22.616 Plasma Transport Theory (MIT)

Description

This course describes the processes by which mass, momentum, and energy are transported in plasmas, with special reference to magnetic confinement fusion applications. The Fokker-Planck collision operator and its limiting forms, as well as collisional relaxation and equilibrium, are considered in detail. Special applications include a Lorentz gas, Brownian motion, alpha particles, and runaway electrons. The Braginskii formulation of classical collisional transport in general geometry based on the Fokker-Planck equation is presented. Neoclassical transport in tokamaks, which is sensitive to the details of the magnetic geometry, is considered in the high (Pfirsch-Schluter), low (banana) and intermediate (plateau) regimes of collisionality.Subjects

Plasmas | magnetic confinement fusion | Fokker-Planck collision operator | collisional relaxation and equilibrium | Lorentz gas | Brownian motion | alpha particles | runaway electrons | Braginskii formulation | tokamak | Pfirsch-Schluter | regimes of collisionalityLicense

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.htmSite sourced from

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See all metadata18.175 Theory of Probability (MIT)

Description

This course covers the laws of large numbers and central limit theorems for sums of independent random variables. It also analyzes topics such as the conditioning and martingales, the Brownian motion and the elements of diffusion theory.Subjects

Earth | Solar System | Geophysics | Gravitational Field | Magnetic Field | Seismology | Geodynamics | Laws of large numbers | central limit theorems for sums of independent random variables | conditioning and martingales | Brownian motion and elements of diffusion theory | functional limit theoremsLicense

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.htmSite sourced from

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See all metadata2.57 Nano-to-Macro Transport Processes (MIT)

Description

This course provides parallel treatments of photons, electrons, phonons, and molecules as energy carriers, aiming at fundamental understanding and descriptive tools for energy and heat transport processes from nanoscale continuously to macroscale. Topics include the energy levels, the statistical behavior and internal energy, energy transport in the forms of waves and particles, scattering and heat generation processes, Boltzmann equation and derivation of classical laws, deviation from classical laws at nanoscale and their appropriate descriptions, with applications in nano- and microtechnology.Subjects

nanotechnology | nanoscale | transport phenomena | photons | electrons | phonons | energy carriers | energy transport | heat transport | energy levels | statistical behavior | internal energy | waves and particles | scattering | heat generation | Boltzmann equation | classical laws | microtechnology | crystal | lattice | quantum oscillator | laudaurer | nanotube | Louiville equation | X-ray | blackbody | quantum well | Fourier | Newton | Ohm | thermoelectric effect | Brownian motion | surface tension | van der Waals potential. | van der Waals potentialLicense

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.htmSite sourced from

https://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

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See all metadata18.175 Theory of Probability (MIT)

Description

This course covers the laws of large numbers and central limit theorems for sums of independent random variables. It also analyzes topics such as the conditioning and martingales, the Brownian motion and the elements of diffusion theory.Subjects

Earth | Solar System | Geophysics | Gravitational Field | Magnetic Field | Seismology | Geodynamics | Laws of large numbers | central limit theorems for sums of independent random variables | conditioning and martingales | Brownian motion and elements of diffusion theory | functional limit theoremsLicense

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.htmSite sourced from

https://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

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See all metadata18.175 Theory of Probability (MIT)

Description

This course covers the laws of large numbers and central limit theorems for sums of independent random variables. It also analyzes topics such as the conditioning and martingales, the Brownian motion and the elements of diffusion theory.Subjects

Earth | Solar System | Geophysics | Gravitational Field | Magnetic Field | Seismology | Geodynamics | Laws of large numbers | central limit theorems for sums of independent random variables | conditioning and martingales | Brownian motion and elements of diffusion theory | functional limit theoremsLicense

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.htmSite sourced from

https://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

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See all metadata18.175 Theory of Probability (MIT)

Description

This course covers topics such as sums of independent random variables, central limit phenomena, infinitely divisible laws, Levy processes, Brownian motion, conditioning, and martingales.Subjects

Laws of large numbers | central limit theorems | independent random variables | conditioning | martingales | Brownian motion | elements of diffusion theory | functional limit theoremsLicense

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.htmSite sourced from

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See all metadata20.310J Molecular, Cellular, and Tissue Biomechanics (MIT)

Description

This course develops and applies scaling laws and the methods of continuum and statistical mechanics to biomechanical phenomena over a range of length scales, from molecular to cellular to tissue or organ level.Subjects

biomechanics | molecular mechanics | cell mechanics | Brownian motion | Reynolds numbers | mechanochemistry | Kramers' model | Bell model | viscoelasticity | poroelasticity | optical tweezers | extracellular matrix | collagen | proteoglycan | cell membrane | cell motility | mechanotransduction | cancer | biological systems | molecular biology | cell biology | cytoskeleton | cell | biophysics | cell migration | biomembrane | tissue mechanics | rheology | polymer | length scale | muscle mechanics | experimental methodsLicense

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.htmSite sourced from

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See all metadata22.616 Plasma Transport Theory (MIT)

Description

This course describes the processes by which mass, momentum, and energy are transported in plasmas, with special reference to magnetic confinement fusion applications. The Fokker-Planck collision operator and its limiting forms, as well as collisional relaxation and equilibrium, are considered in detail. Special applications include a Lorentz gas, Brownian motion, alpha particles, and runaway electrons. The Braginskii formulation of classical collisional transport in general geometry based on the Fokker-Planck equation is presented. Neoclassical transport in tokamaks, which is sensitive to the details of the magnetic geometry, is considered in the high (Pfirsch-Schluter), low (banana) and intermediate (plateau) regimes of collisionality.Subjects

Plasmas | magnetic confinement fusion | Fokker-Planck collision operator | collisional relaxation and equilibrium | Lorentz gas | Brownian motion | alpha particles | runaway electrons | Braginskii formulation | tokamak | Pfirsch-Schluter | regimes of collisionalityLicense

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.htmSite sourced from

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