Searching for simulation : 308 results found | RSS Feed for this search

1 2 3 4 5 6 7 8 9 10 11 12

3.320 Atomistic Computer Modeling of Materials (SMA 5107) (MIT) 3.320 Atomistic Computer Modeling of Materials (SMA 5107) (MIT)

Description

This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations; free energy and phase transitions; fluctuations and transport properties; and coarse-graining approaches and mesoscale models. The course employs case studies from industrial applications of advanced materials to nanotechnology. Several laboratories will give students direct experience with simulations of classical force fields, electronic-structure app This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations; free energy and phase transitions; fluctuations and transport properties; and coarse-graining approaches and mesoscale models. The course employs case studies from industrial applications of advanced materials to nanotechnology. Several laboratories will give students direct experience with simulations of classical force fields, electronic-structure app

Subjects

simulation | simulation | computer simulation | computer simulation | atomistic computer simulations | atomistic computer simulations | Density-functional theory | Density-functional theory | DFT | DFT | Hartree-Fock | Hartree-Fock | total-energy pseudopotential | total-energy pseudopotential | thermodynamics | thermodynamics | thermodynamic ensembles | thermodynamic ensembles | quantum mechanics | quantum mechanics | first-principles | first-principles | Monte Carlo sampling | Monte Carlo sampling | molecular dynamics | molecular dynamics | finite temperature | finite temperature | Free energies | Free energies | phase transitions | phase transitions | Coarse-graining | Coarse-graining | mesoscale model | mesoscale model | nanotube | nanotube | alloy | alloy

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-3.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

15.066J System Optimization and Analysis for Manufacturing (MIT) 15.066J System Optimization and Analysis for Manufacturing (MIT)

Description

One objective of 15.066J is to introduce modeling, optimization and simulation, as it applies to the study and analysis of manufacturing systems for decision support. The introduction of optimization models and algorithms provide a framework to think about a wide range of issues that arise in manufacturing systems. The second objective is to expose students to a wide range of applications for these methods and models, and to integrate this material with their introduction to operations management. One objective of 15.066J is to introduce modeling, optimization and simulation, as it applies to the study and analysis of manufacturing systems for decision support. The introduction of optimization models and algorithms provide a framework to think about a wide range of issues that arise in manufacturing systems. The second objective is to expose students to a wide range of applications for these methods and models, and to integrate this material with their introduction to operations management.

Subjects

modeling | modeling | optimization | optimization | simulation | simulation | manufacturing systems | manufacturing systems | decision making | decision making | decision support | decision support | probabilistic simulation | probabilistic simulation | designing manufacturing systems | designing manufacturing systems | operations management | operations management | linear programming | linear programming | sensitivity analysis | sensitivity analysis | network flow problems | network flow problems | non-linear programming | non-linear programming | Lagrange multipliers | Lagrange multipliers | integer programming | integer programming | discrete-event simulation | discrete-event simulation | heuristics | heuristics | algorithms | algorithms | 15.066 | 15.066 | 2.851 | 2.851 | 3.83 | 3.83

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-transportation.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

3.320 Atomistic Computer Modeling of Materials (MIT) 3.320 Atomistic Computer Modeling of Materials (MIT)

Description

Theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Energy models, from classical potentials to first-principles approaches. Density-functional theory and the total-energy pseudopotential method. Errors and accuracy of quantitative predictions. Thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations. Free energies and phase transitions. Fluctuations and transport properties. Coarse-graining approaches and mesoscale models. Theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Energy models, from classical potentials to first-principles approaches. Density-functional theory and the total-energy pseudopotential method. Errors and accuracy of quantitative predictions. Thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations. Free energies and phase transitions. Fluctuations and transport properties. Coarse-graining approaches and mesoscale models.

Subjects

atomistic computer simulations | atomistic computer simulations | Density-functional theory | Density-functional theory | total-energy pseudopotential method | total-energy pseudopotential method | Thermodynamic ensembles | Thermodynamic ensembles | Monte Carlo sampling | Monte Carlo sampling | molecular dynamics simulations | molecular dynamics simulations | Free energies | Free energies | phase transitions | phase transitions | Coarse-graining approaches | Coarse-graining approaches | mesoscale models | mesoscale models

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

11.127 Computer Games and Simulations for Investigation and Education (MIT) 11.127 Computer Games and Simulations for Investigation and Education (MIT)

Description

This course will explore educational games and simulations and several computer modeling platforms. We will focus on design and research issues pertinent to learning through simulations and games. Throughout the course we will explore concepts in modeling, simulation, and gaming common to many domains, and investigate specific applications from a variety of fields ranging from weather to ecology to traffic management. This course will explore educational games and simulations and several computer modeling platforms. We will focus on design and research issues pertinent to learning through simulations and games. Throughout the course we will explore concepts in modeling, simulation, and gaming common to many domains, and investigate specific applications from a variety of fields ranging from weather to ecology to traffic management.

Subjects

simulation modeling | simulation modeling | computational technology | computational technology | SimCity | SimCity | edutainment | edutainment | "edutainment" software | "edutainment" software | Civilization | Civilization | pre-built models | pre-built models | gaming | gaming | game creation | game creation | game theory | game theory | design | design | simulation creation | simulation creation | software | software | programming | programming

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

1.124J Foundations of Software Engineering (MIT) 1.124J Foundations of Software Engineering (MIT)

Description

This is a foundation subject in modern software development techniques for engineering and information technology. The design and development of component-based software (using C# and .NET) is covered; data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web services; and the management and maintenance of software. Includes a treatment of topics such as sorting and searching algorithms; and numerical simulation techniques. Foundation for in-depth exploration of image processing, computational geometry, finite element methods, network methods and e-business applications. This course is a core requirement for the Information Technology M. Eng. program. This class was also offered in Course 13 (Department of Ocean Engineering) as 13.470J. This is a foundation subject in modern software development techniques for engineering and information technology. The design and development of component-based software (using C# and .NET) is covered; data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web services; and the management and maintenance of software. Includes a treatment of topics such as sorting and searching algorithms; and numerical simulation techniques. Foundation for in-depth exploration of image processing, computational geometry, finite element methods, network methods and e-business applications. This course is a core requirement for the Information Technology M. Eng. program. This class was also offered in Course 13 (Department of Ocean Engineering) as 13.470J.

Subjects

modern software development | modern software development | engineering and information technology | engineering and information technology | component-based software | component-based software | C# | C# | .NET | .NET | data structures | data structures | algorithms for modeling | algorithms for modeling | analysis | analysis | visualization | visualization | basic problem-solving techniques | basic problem-solving techniques | web services | web services | management and maintenance of software | management and maintenance of software | sorting | sorting | searching | searching | algorithms | algorithms | numerical simulation techniques | numerical simulation techniques | image processing | image processing | computational geometry | computational geometry | finite element methods | finite element methods | network methods | network methods | e-business applications | e-business applications | classes | classes | objects | objects | inheritance | inheritance | virtual functions | virtual functions | abstract classes | abstract classes | polymorphism | polymorphism | Java applications | Java applications | applets | applets | Abstract Windowing Toolkit | Abstract Windowing Toolkit | Graphics | Graphics | Threads | Threads | Java | Java | C++ | C++ | information technology | information technology | engineering | engineering | modeling algorithms | modeling algorithms | basic problem-solving | basic problem-solving | software management | software management | software maintenance | software maintenance | searching algorithms | searching algorithms | numerical simulation | numerical simulation | object oriented programming | object oriented programming | 13.470J | 13.470J | 1.124 | 1.124 | 2.159 | 2.159 | 13.470 | 13.470

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

3.320 Atomistic Computer Modeling of Materials (SMA 5107) (MIT)

Description

This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations; free energy and phase transitions; fluctuations and transport properties; and coarse-graining approaches and mesoscale models. The course employs case studies from industrial applications of advanced materials to nanotechnology. Several laboratories will give students direct experience with simulations of classical force fields, electronic-structure app

Subjects

simulation | computer simulation | atomistic computer simulations | Density-functional theory | DFT | Hartree-Fock | total-energy pseudopotential | thermodynamics | thermodynamic ensembles | quantum mechanics | first-principles | Monte Carlo sampling | molecular dynamics | finite temperature | Free energies | phase transitions | Coarse-graining | mesoscale model | nanotube | alloy

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

Site sourced from

https://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

15.066J System Optimization and Analysis for Manufacturing (MIT)

Description

One objective of 15.066J is to introduce modeling, optimization and simulation, as it applies to the study and analysis of manufacturing systems for decision support. The introduction of optimization models and algorithms provide a framework to think about a wide range of issues that arise in manufacturing systems. The second objective is to expose students to a wide range of applications for these methods and models, and to integrate this material with their introduction to operations management.

Subjects

modeling | optimization | simulation | manufacturing systems | decision making | decision support | probabilistic simulation | designing manufacturing systems | operations management | linear programming | sensitivity analysis | network flow problems | non-linear programming | Lagrange multipliers | integer programming | discrete-event simulation | heuristics | algorithms | 15.066 | 2.851 | 3.83

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

Site sourced from

https://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

16.888 Multidisciplinary System Design Optimization (MIT) 16.888 Multidisciplinary System Design Optimization (MIT)

Description

This course is mainly focused on the quantitative aspects of design and presents a unifying framework called "Multidisciplinary System Design Optimization" (MSDO). The objective of the course is to present tools and methodologies for performing system optimization in a multidisciplinary design context, focusing on three aspects of the problem: (i) The multidisciplinary character of engineering systems, (ii) design of these complex systems, and (iii) tools for optimization. There is a version of this course (16.60s) offered through the MIT Professional Institute, targeted at professional engineers. This course is mainly focused on the quantitative aspects of design and presents a unifying framework called "Multidisciplinary System Design Optimization" (MSDO). The objective of the course is to present tools and methodologies for performing system optimization in a multidisciplinary design context, focusing on three aspects of the problem: (i) The multidisciplinary character of engineering systems, (ii) design of these complex systems, and (iii) tools for optimization. There is a version of this course (16.60s) offered through the MIT Professional Institute, targeted at professional engineers.

Subjects

optimization | optimization | multidisciplinary design optimization | multidisciplinary design optimization | MDO | MDO | subsystem identification | subsystem identification | interface design | interface design | linear constrained optimization fomulation | linear constrained optimization fomulation | non-linear constrained optimization formulation | non-linear constrained optimization formulation | scalar optimization | scalar optimization | vector optimization | vector optimization | systems engineering | systems engineering | complex systems | complex systems | heuristic search methods | heuristic search methods | tabu search | tabu search | simulated annealing | simulated annealing | genertic algorithms | genertic algorithms | sensitivity | sensitivity | tradeoff analysis | tradeoff analysis | goal programming | goal programming | isoperformance | isoperformance | pareto optimality | pareto optimality | flowchart | flowchart | design vector | design vector | simulation model | simulation model | objective vector | objective vector | input | input | discipline | discipline | output | output | coupling | coupling | multiobjective optimization | multiobjective optimization | optimization algorithms | optimization algorithms | tradespace exploration | tradespace exploration | numerical techniques | numerical techniques | direct methods | direct methods | penalty methods | penalty methods | heuristic techniques | heuristic techniques | SA | SA | GA | GA | approximation methods | approximation methods | sensitivity analysis | sensitivity analysis | isoperformace | isoperformace | output evaluation | output evaluation | MSDO framework | MSDO framework

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

11.127 Computer Modeling for Investigation and Education (MIT) 11.127 Computer Modeling for Investigation and Education (MIT)

Description

During the past ten years, simulation modeling, especially as it helps people to understand complex systems, has become a mainstream use of computational technology. The widespread popularity of "edutainment" software like SimCity and Civilization gives a clear indication of the extent to which simulation games have permeated popular culture. As these and other games have found places in the classroom, researchers have tried to ascertain what and how students learn from these environments, and what implications this has for software and curriculum design.While it can be useful to experiment with pre-built models like SimCity, a deeper understanding can come through building and manipulating models whose underlying structure is accessible. Just as a young child learns more by buil During the past ten years, simulation modeling, especially as it helps people to understand complex systems, has become a mainstream use of computational technology. The widespread popularity of "edutainment" software like SimCity and Civilization gives a clear indication of the extent to which simulation games have permeated popular culture. As these and other games have found places in the classroom, researchers have tried to ascertain what and how students learn from these environments, and what implications this has for software and curriculum design.While it can be useful to experiment with pre-built models like SimCity, a deeper understanding can come through building and manipulating models whose underlying structure is accessible. Just as a young child learns more by buil

Subjects

simulation modeling | simulation modeling | computational technology | computational technology | SimCity | SimCity | edutainment | edutainment | "edutainment" software | "edutainment" software | Civilization | Civilization | pre-built models | pre-built models

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

15.391 Early Stage Capital (MIT) 15.391 Early Stage Capital (MIT)

Description

15.391 examines the elements of raising early stage capital, focusing on start-up ventures and the early stages of company development. This course also prepares entrepreneurs to make the best use of outside advisors, and to negotiate effective long-term relationships with funding sources. Working in teams, students interact with venture capitalists and other professionals throughout the semester. Disclaimer: The web sites for this course and the materials they offer are provided for educational use only. They are not a substitute for the advice of an attorney and no attorney-client relationship is created by using them. All materials are provided "as-is", without any express or implied warranties. 15.391 examines the elements of raising early stage capital, focusing on start-up ventures and the early stages of company development. This course also prepares entrepreneurs to make the best use of outside advisors, and to negotiate effective long-term relationships with funding sources. Working in teams, students interact with venture capitalists and other professionals throughout the semester. Disclaimer: The web sites for this course and the materials they offer are provided for educational use only. They are not a substitute for the advice of an attorney and no attorney-client relationship is created by using them. All materials are provided "as-is", without any express or implied warranties.

Subjects

raising venture capital | raising venture capital | starting business | starting business | structuring deals | structuring deals | valuating companies | valuating companies | entrepreneurship | entrepreneurship | venture capitalist | venture capitalist | finding early stage capital | finding early stage capital | negotiate investments | negotiate investments | new business laws | new business laws | financial simulations | financial simulations | build relationships | build relationships | start-up ventures | start-up ventures | company development | company development | using outside advisors | using outside advisors | funding sources | funding sources | term sheet | term sheet | VC | VC | entrepreneur | entrepreneur | pursuing seed money | pursuing seed money | biotechnology | biotechnology | biotech | biotech | angel financing | angel financing | first round money | first round money

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

16.225 Computational Mechanics of Materials (MIT) 16.225 Computational Mechanics of Materials (MIT)

Description

16.225 is a graduate level course on Computational Mechanics of Materials. The primary focus of this course is on the teaching of state-of-the-art numerical methods for the analysis of the nonlinear continuum response of materials. The range of material behavior considered in this course includes: linear and finite deformation elasticity, inelasticity and dynamics. Numerical formulation and algorithms include: variational formulation and variational constitutive updates, finite element discretization, error estimation, constrained problems, time integration algorithms and convergence analysis. There is a strong emphasis on the (parallel) computer implementation of algorithms in programming assignments. The application to real engineering applications and problems in engineering science is 16.225 is a graduate level course on Computational Mechanics of Materials. The primary focus of this course is on the teaching of state-of-the-art numerical methods for the analysis of the nonlinear continuum response of materials. The range of material behavior considered in this course includes: linear and finite deformation elasticity, inelasticity and dynamics. Numerical formulation and algorithms include: variational formulation and variational constitutive updates, finite element discretization, error estimation, constrained problems, time integration algorithms and convergence analysis. There is a strong emphasis on the (parallel) computer implementation of algorithms in programming assignments. The application to real engineering applications and problems in engineering science is

Subjects

Computational Mechanics | Computational Mechanics | Computation | Computation | Mechanics | Mechanics | Materials | Materials | Numerical Methods | Numerical Methods | Numerical | Numerical | Nonlinear Continuum Response | Nonlinear Continuum Response | Continuum | Continuum | Deformation | Deformation | Elasticity | Elasticity | Inelasticity | Inelasticity | Dynamics | Dynamics | Variational Formulation | Variational Formulation | Variational Constitutive Updates | Variational Constitutive Updates | Finite Element | Finite Element | Discretization | Discretization | Error Estimation | Error Estimation | Constrained Problems | Constrained Problems | Time Integration | Time Integration | Convergence Analysis | Convergence Analysis | Programming | Programming | Continuum Response | Continuum Response | Computational | Computational | state-of-the-art | state-of-the-art | methods | methods | modeling | modeling | simulation | simulation | mechanical | mechanical | response | response | engineering | engineering | aerospace | aerospace | civil | civil | material | material | science | science | biomechanics | biomechanics | behavior | behavior | finite | finite | deformation | deformation | elasticity | elasticity | inelasticity | inelasticity | contact | contact | friction | friction | coupled | coupled | numerical | numerical | formulation | formulation | algorithms | algorithms | Variational | Variational | constitutive | constitutive | updates | updates | element | element | discretization | discretization | mesh | mesh | generation | generation | error | error | estimation | estimation | constrained | constrained | problems | problems | time | time | convergence | convergence | analysis | analysis | parallel | parallel | computer | computer | implementation | implementation | programming | programming | assembly | assembly | equation-solving | equation-solving | formulating | formulating | implementing | implementing | complex | complex | approximations | approximations | equations | equations | motion | motion | dynamic | dynamic | deformations | deformations | continua | continua | plasticity | plasticity | rate-dependency | rate-dependency | integration | integration

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

15.668 People and Organizations (MIT) 15.668 People and Organizations (MIT)

Description

This course examines the historical evolution and current human and organizational contexts in which scientists, engineers and other professionals work. It outlines today's major challenges facing the management profession and uses interactive exercises, simulations and problems to develop critical skills in negotiations, teamwork and leadership. It also introduces concepts and tools to analyze work and leadership experiences in optional undergraduate fieldwork projects. This course examines the historical evolution and current human and organizational contexts in which scientists, engineers and other professionals work. It outlines today's major challenges facing the management profession and uses interactive exercises, simulations and problems to develop critical skills in negotiations, teamwork and leadership. It also introduces concepts and tools to analyze work and leadership experiences in optional undergraduate fieldwork projects.

Subjects

people | people | organizations | organizations | professionals | professionals | managers | managers | leadership | leadership | leadership exercises | leadership exercises | negotiation | negotiation | teamwork | teamwork | simulations | simulations | management | management | organizational change | organizational change | multi-party negotiations | multi-party negotiations | new recruit negotiations | new recruit negotiations | shareholders | shareholders | corporations | corporations | work and careers | work and careers | organizational analysis | organizational analysis | organizational politics | organizational politics

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

6.00 Introduction to Computer Science and Programming (MIT) 6.00 Introduction to Computer Science and Programming (MIT)

Description

Includes audio/video content: AV lectures. This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language. Includes audio/video content: AV lectures. This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language.

Subjects

computer science | computer science | computation | computation | problem solving | problem solving | Python programming | Python programming | recursion | recursion | binary search | binary search | classes | classes | inheritance | inheritance | libraries | libraries | algorithms | algorithms | optimization problems | optimization problems | modules | modules | simulation | simulation | big O notation | big O notation | control flow | control flow | exceptions | exceptions | building computational models | building computational models | software engineering | software engineering

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allavcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

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

Description

This course covers the 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 the materials science and engineering core courses (3.012 and 3.014) 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, and fourier analysis. Users may find additional or updated materials at Professor C This course covers the 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 the materials science and engineering core courses (3.012 and 3.014) 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, and fourier analysis. Users may find additional or updated materials at Professor C

Subjects

energetics | energetics | visualization | visualization | graph | graph | plot | plot | chart | chart | materials science | materials science | DMSE | DMSE | structure | structure | symmetry | symmetry | mechanics | mechanics | physicss | physicss | solids and soft materials | solids and soft materials | linear algebra | linear algebra | orthonormal basis | orthonormal basis | eigenvalue | eigenvalue | eigenvector | eigenvector | quadratic form | quadratic form | tensor operation | tensor operation | symmetry operation | symmetry operation | calculus | calculus | complex analysis | complex analysis | differential equations | differential equations | ODE | ODE | solution | solution | vector | vector | matrix | matrix | determinant | determinant | theory of distributions | theory of distributions | fourier analysis | fourier analysis | random walk | random walk | Mathematica | Mathematica | simulation | simulation

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-3.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

ESD.S51 Systems Leadership and Management Praxis (MIT) ESD.S51 Systems Leadership and Management Praxis (MIT)

Description

SLaM (Systems Leadership and Management) Praxis is a course is designed to introduce students to the dynamics of strategic decision making in corporate boardrooms through team exercises, simulations, and role playing. The case studies and team exercises will introduce students to strategy choices in the high tech sector, but these learnings are just as valid in other industries. We will also have invited guest speakers from the industry who have lived through difficult corporate situations and can provide insights into the cases discussed in class. SLaM (Systems Leadership and Management) Praxis is a course is designed to introduce students to the dynamics of strategic decision making in corporate boardrooms through team exercises, simulations, and role playing. The case studies and team exercises will introduce students to strategy choices in the high tech sector, but these learnings are just as valid in other industries. We will also have invited guest speakers from the industry who have lived through difficult corporate situations and can provide insights into the cases discussed in class.

Subjects

decision-making | decision-making | leadership development | leadership development | high-tech business | high-tech business | smartphones | smartphones | management | management | high-tech competition | high-tech competition | Back Bay Battery online simulation | Back Bay Battery online simulation | Nokia | Nokia | HTC | HTC | Apple | Apple | Sony | Sony | Research in Motion | Research in Motion

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-ESD.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

22.103 Microscopic Theory of Transport (MIT) 22.103 Microscopic Theory of Transport (MIT)

Description

Transport is among the most fundamental and widely studied phenomena in science and engineering. This subject will lay out the essential concepts and current understanding, with emphasis on the molecular view, that cut across all disciplinary boundaries. (Suitable for all students in research.) Broad perspectives of transport phenomena From theory and models to computations and simulations Micro/macro coupling Current research insights Transport is among the most fundamental and widely studied phenomena in science and engineering. This subject will lay out the essential concepts and current understanding, with emphasis on the molecular view, that cut across all disciplinary boundaries. (Suitable for all students in research.) Broad perspectives of transport phenomena From theory and models to computations and simulations Micro/macro coupling Current research insights

Subjects

molecular view | molecular view | transport phenomena | transport phenomena | theory | theory | models | models | computations | computations | simulations | simulations | micro/macro coupling | micro/macro coupling | microscopic collisions | microscopic collisions | transport coefficients | transport coefficients | particle transport | particle transport | radiation transport | radiation transport | microscopic kinetic equation | microscopic kinetic equation | boltzmann equation | boltzmann equation | practical engineering fluid models | practical engineering fluid models | kinetic model | kinetic model | nuclear cross sections | nuclear cross sections

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

4.491 Form-Finding and Structural Optimization: Gaudi Workshop (MIT) 4.491 Form-Finding and Structural Optimization: Gaudi Workshop (MIT)

Description

Inspired by the work of the architect Antoni Gaudi, this research workshop will explore three-dimensional problems in the static equilibrium of structural systems. Through an interdisciplinary collaboration between computer science and architecture, we will develop design tools for determining the form of three-dimensional structural systems under a variety of loads. The goal of the workshop is to develop real-time design and analysis tools which will be useful to architects and engineers in the form-finding of efficient three-dimensional structural systems. Inspired by the work of the architect Antoni Gaudi, this research workshop will explore three-dimensional problems in the static equilibrium of structural systems. Through an interdisciplinary collaboration between computer science and architecture, we will develop design tools for determining the form of three-dimensional structural systems under a variety of loads. The goal of the workshop is to develop real-time design and analysis tools which will be useful to architects and engineers in the form-finding of efficient three-dimensional structural systems.

Subjects

structures | structures | statics | statics | architecture | architecture | Gaudi | Gaudi | Barcelona | Barcelona | computer science | computer science | structural systems | structural systems | computer modeling | computer modeling | advanced dynamics | advanced dynamics | form-finding | form-finding | shaping structures | shaping structures | mesh generation | mesh generation | procedural methods for creating structural elements | procedural methods for creating structural elements | physical simulation procedures | physical simulation procedures | interactive design tools | interactive design tools | structural analysis | structural analysis | computer graphics | computer graphics | mathematics of nodal systems | mathematics of nodal systems

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

11.124 Introduction to Education: Looking Forward and Looking Back on Education (MIT) 11.124 Introduction to Education: Looking Forward and Looking Back on Education (MIT)

Description

An introductory course on teaching and learning science and mathematics in a variety of K-12 settings. Topics include education and media, education reform, the history of education, simulations, games, and the digital divide. An introductory course on teaching and learning science and mathematics in a variety of K-12 settings. Topics include education and media, education reform, the history of education, simulations, games, and the digital divide.

Subjects

education | education | teaching | teaching | learning | learning | science | science | mathematics | mathematics | education reform | education reform | education and media | education and media | history of education | history of education | simulations | simulations | games | games | digital divide | digital divide | classroom | classroom | technology | technology

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-11.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

6.0002 Introduction to Computational Thinking and Data Science (MIT)

Description

6.0002 is the continuation of 6.0001 Introduction to Computer Science and Programming in Python and is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language.

Subjects

Python 3.5 | Python | machine learning | knapsack problem | greedy algorithm | optimization | weights | models | computational thinking | data science | dynamic programming | recursion | exponential time | stochastic | random | probability | independent variables | dependent variables | monte carlo simulation | simulation | population sampling | law of large numbers | variance | confidence interval | empirical rule | standard deviation | central limit theorem | bias | error distribution | sampling | error bars | numpy | scipy | matplotlib | pylab | python | plotting | graphing | supervised learning | computer modelling | signal-to-noise | feature vectors | classification model | regression model | classification | classifier | nearest neighbors | feature scaling | decision trees | entropy | training data | clustering | cluster analysis | unsupervised learning | objective function | dendogram | statistical fallacy | systematic errors | correlation and causation | misleading statistics | GIGO | axis truncating | extrapolation | data enhancement | Texas Sharpshooter Fallacy

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

Site sourced from

https://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

ESD.84 Engineering Systems Doctoral Seminar (MIT) ESD.84 Engineering Systems Doctoral Seminar (MIT)

Description

Examines core theory and contextual applications of the emerging field of Engineering Systems. The focus is on doctoral-level analysis of scholarship on key concepts such as complexity, uncertainty, fragility, and robustness, as well as a critical look at the historical roots of the field and related areas such as systems engineering, systems dynamics, agent modeling, and systems simulations. Contextual applications range from aerospace to technology implementation to regulatory systems to large-scale systems change. Special attention is given to the interdependence of social and technical dimensions of engineering systems. Examines core theory and contextual applications of the emerging field of Engineering Systems. The focus is on doctoral-level analysis of scholarship on key concepts such as complexity, uncertainty, fragility, and robustness, as well as a critical look at the historical roots of the field and related areas such as systems engineering, systems dynamics, agent modeling, and systems simulations. Contextual applications range from aerospace to technology implementation to regulatory systems to large-scale systems change. Special attention is given to the interdependence of social and technical dimensions of engineering systems.

Subjects

engineering systems | engineering systems | complexity | complexity | fragility | fragility | robustness | robustness | systems engineering | systems engineering | systems dynamics | systems dynamics | agent modeling | agent modeling | systems simulations | systems simulations | large-scale systems change | large-scale systems change | uncertainty | uncertainty

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

11.127J Computer Games and Simulations for Investigation and Education (MIT) 11.127J Computer Games and Simulations for Investigation and Education (MIT)

Description

In this project-based course, students from all disciplines are encouraged to understand how we learn from interactive computer environments, and delve into the process of designing and understanding simulations and games for learning. In this project-based course, students from all disciplines are encouraged to understand how we learn from interactive computer environments, and delve into the process of designing and understanding simulations and games for learning.

Subjects

education | education | computers | computers | computer games | computer games | simulations | simulations | edu-tainment | edu-tainment | games | games | video games | video games | board games | board games

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

ESD.70J Engineering Economy Module (MIT) ESD.70J Engineering Economy Module (MIT)

Description

This intensive micro-subject provides the necessary skills in Microsoft® Excel spreadsheet modeling for ESD.71 – Engineering Systems Analysis for Design. Its purpose is to bring entering students up to speed on some of the advanced techniques that we routinely use in analysis. It is motivated by our experience that many students only have an introductory knowledge of Excel, and thus waste a lot of time thrashing about unproductively. Many people think they know Excel, but overlook many efficient tools – such as Data Table and Goal Seek. It is also useful for a variety of other subjects.NoteThis MIT OpenCourseWare site is based on the materials from Professor de Neufville's ESD.70J Web site. This intensive micro-subject provides the necessary skills in Microsoft® Excel spreadsheet modeling for ESD.71 – Engineering Systems Analysis for Design. Its purpose is to bring entering students up to speed on some of the advanced techniques that we routinely use in analysis. It is motivated by our experience that many students only have an introductory knowledge of Excel, and thus waste a lot of time thrashing about unproductively. Many people think they know Excel, but overlook many efficient tools – such as Data Table and Goal Seek. It is also useful for a variety of other subjects.NoteThis MIT OpenCourseWare site is based on the materials from Professor de Neufville's ESD.70J Web site.

Subjects

excel | excel | spreadsheet | spreadsheet | modeling | modeling | dynamic modeling | dynamic modeling | analysis | analysis | data table | data table | goal seek | goal seek | sensitivity analysis | sensitivity analysis | simulation | simulation | random number generator | random number generator | counting | counting | modeling uncertainties | modeling uncertainties | random variables | random variables | statistical package | statistical package | flexibility | flexibility | contingency rules | contingency rules | excel solver | excel solver | solver | solver

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

6.774 Physics of Microfabrication: Front End Processing (MIT) 6.774 Physics of Microfabrication: Front End Processing (MIT)

Description

Includes audio/video content: AV lectures. This course is offered to graduates and focuses on understanding the fundamental principles of the "front-end" processes used in the fabrication of devices for silicon integrated circuits. This includes advanced physical models and practical aspects of major processes, such as oxidation, diffusion, ion implantation, and epitaxy. Other topics covered include: high performance MOS and bipolar devices including ultra-thin gate oxides, implant-damage enhanced diffusion, advanced metrology, and new materials such as Silicon Germanium (SiGe). Includes audio/video content: AV lectures. This course is offered to graduates and focuses on understanding the fundamental principles of the "front-end" processes used in the fabrication of devices for silicon integrated circuits. This includes advanced physical models and practical aspects of major processes, such as oxidation, diffusion, ion implantation, and epitaxy. Other topics covered include: high performance MOS and bipolar devices including ultra-thin gate oxides, implant-damage enhanced diffusion, advanced metrology, and new materials such as Silicon Germanium (SiGe).

Subjects

fabrication processes | fabrication processes | silicon | silicon | integrated circuits | integrated circuits | monolithic integrated circuits | monolithic integrated circuits | physical models | physical models | bulk crystal growth | bulk crystal growth | thermal oxidation | thermal oxidation | solid-state diffusion | solid-state diffusion | ion implantation | ion implantation | epitaxial deposition | epitaxial deposition | chemical vapor deposition | chemical vapor deposition | physical vapor deposition | physical vapor deposition | refractory metal silicides | refractory metal silicides | plasma and reactive ion etching | plasma and reactive ion etching | rapid thermal processing | rapid thermal processing | process modeling | process modeling | process simulation | process simulation | technological limitations | technological limitations | integrated circuit design | integrated circuit design | integrated circuit fabrication | integrated circuit fabrication | device operation | device operation | sige materials | sige materials | processing | processing

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allavcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

11.959 Reforming Natural Resources Governance: Failings of Scientific Rationalism and Alternatives for Building Common Ground (MIT) 11.959 Reforming Natural Resources Governance: Failings of Scientific Rationalism and Alternatives for Building Common Ground (MIT)

Description

For the last century, precepts of scientific management and administrative rationality have concentrated power in the hands of technical specialists, which in recent decades has contributed to widespread disenfranchisement and discontent among stakeholders in natural resources cases. In this seminar we examine the limitations of scientific management as a model both for governance and for gathering and using information, and describe alternative methods for informing and organizing decision-making processes. We feature cases involving large carnivores in the West (mountain lions and grizzly bears), Northeast coastal fisheries, and adaptive management of the Colorado River. There will be nightly readings and a short written assignment. For the last century, precepts of scientific management and administrative rationality have concentrated power in the hands of technical specialists, which in recent decades has contributed to widespread disenfranchisement and discontent among stakeholders in natural resources cases. In this seminar we examine the limitations of scientific management as a model both for governance and for gathering and using information, and describe alternative methods for informing and organizing decision-making processes. We feature cases involving large carnivores in the West (mountain lions and grizzly bears), Northeast coastal fisheries, and adaptive management of the Colorado River. There will be nightly readings and a short written assignment.

Subjects

role-play simulation | role-play simulation | policymakers | policymakers | Cape Wind controversy | Cape Wind controversy | wind farms | wind farms | wind farm | wind farm | ecosystems | ecosystems | natural resources management | natural resources management | environmental policy-making | environmental policy-making | science organizations | science organizations | science | science | decision-making | decision-making | science agencies | science agencies | National Environmental Policy Act | National Environmental Policy Act | NEPA | NEPA | scientists | scientists | society | society | collaborative approaches | collaborative approaches | joint fact finding | joint fact finding | environment | environment | policy making | policy making | decision making | decision making | ethics in science | ethics in science | values | values | environmental policy | environmental policy | collaborative learning | collaborative learning | local and indigenous knowledge | local and indigenous knowledge | adaptive management | adaptive management | adaptive governance | adaptive governance | eco-system management | eco-system management | USGS | USGS | United States Geological Survey | United States Geological Survey

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-11.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

15.668 People and Organizations (MIT) 15.668 People and Organizations (MIT)

Description

15.668 People and Organizations examines the historical evolution and current human and organizational contexts in which scientists, engineers and other professionals work. It outlines today's major challenges facing the management profession. The course uses interactive exercises, simulations and problems to develop critical skills in negotiations, teamwork and leadership. Students will be introduced to concepts and tools to analyze work and leadership experiences in optional undergraduate fieldwork projects. 15.668 People and Organizations examines the historical evolution and current human and organizational contexts in which scientists, engineers and other professionals work. It outlines today's major challenges facing the management profession. The course uses interactive exercises, simulations and problems to develop critical skills in negotiations, teamwork and leadership. Students will be introduced to concepts and tools to analyze work and leadership experiences in optional undergraduate fieldwork projects.

Subjects

organizations | organizations | organizational analysis | organizational analysis | teamwork | teamwork | organizational structure | organizational structure | negotiations | negotiations | simulations | simulations | recruitment negotiations | recruitment negotiations | leadership | leadership | managers | managers | innovation | innovation | corporate responsibility | corporate responsibility

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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata