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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

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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

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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

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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

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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

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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

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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

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Integrated Circuits and Microelectronics Integrated Circuits and Microelectronics

Description

This course introduces to the students the current integrated circuits tecnologies, mainly for digital devices. During this course it will be studied in detail aspects related with manufacturing, packaging and modern solutions for performance and reliability improvements, as well as a design methodology with the necessary tools for obtaining competitive digital integrated circuits, such as hardware description languages, synthesis tools, design for testability, etc. This course introduces to the students the current integrated circuits tecnologies, mainly for digital devices. During this course it will be studied in detail aspects related with manufacturing, packaging and modern solutions for performance and reliability improvements, as well as a design methodology with the necessary tools for obtaining competitive digital integrated circuits, such as hardware description languages, synthesis tools, design for testability, etc.

Subjects

Design of basic combinational circuits | Design of basic combinational circuits | Design simulation | Design simulation | a Tcnica Industrial: Electrnica Industrial | a Tcnica Industrial: Electrnica Industrial | VHDL language | VHDL language | Analysis and design | Analysis and design | Microelectronics | Microelectronics | Design of secuential circuits | Design of secuential circuits | Tecnologia Electronica | Tecnologia Electronica | Manufacturing and packaging | Manufacturing and packaging | Integrated circuits test | Integrated circuits test | 2011 | 2011 | Integrated Circuits | Integrated Circuits | Analog integrated circuits | Analog integrated circuits

License

Copyright 2015, UC3M http://creativecommons.org/licenses/by-nc-sa/4.0/

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Machine Theory Machine Theory

Description

The aim of this course is to pre-dimension a machine depending on the requirements and requests that will be submitted. Analysis of the kinematic and dynamic of machines and spatial mechanisms. Analysis of the behavior of rotation and / or translation elements. Modeling and simulation of machines (modeling methods and computer simulation). The aim of this course is to pre-dimension a machine depending on the requirements and requests that will be submitted. Analysis of the kinematic and dynamic of machines and spatial mechanisms. Analysis of the behavior of rotation and / or translation elements. Modeling and simulation of machines (modeling methods and computer simulation).

Subjects

Hyperbolic | Hyperbolic | Ingenieria Mecanica | Ingenieria Mecanica | Bevel gears | Bevel gears | Synthesis of mechanisms | Synthesis of mechanisms | Kinematics | Kinematics | Spur gears | Spur gears | Spatial Mechanisms | Spatial Mechanisms | Pro-Engineer | Pro-Engineer | Mechanisms | Mechanisms | Gear trains | Gear trains | Rolling Bearings selection | Rolling Bearings selection | Balancing | Balancing | 2012 | 2012 | Simulation | Simulation | Cams design | Cams design | Plain bearings design | Plain bearings design | Analytical mechanics applied to machinery | Analytical mechanics applied to machinery | a Mecnica | a Mecnica | Helical | Helical | Flywheels | Flywheels | Friction | Friction | Lubrication | Lubrication | Software simulation | Software simulation

License

Copyright 2015, UC3M http://creativecommons.org/licenses/by-nc-sa/4.0/

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ESD.83 Doctoral Seminar in Engineering Systems (MIT) ESD.83 Doctoral Seminar in Engineering Systems (MIT)

Description

In establishing the Engineering Systems Division, MIT has embarked on a bold experiment – bringing together diverse areas of expertise into what is designed to be a new field of study. In many respects, the full scale and scope of Engineering Systems as a field is still emerging. This seminar is simultaneously designed to codify what we presently know and to give direction for future development. In establishing the Engineering Systems Division, MIT has embarked on a bold experiment – bringing together diverse areas of expertise into what is designed to be a new field of study. In many respects, the full scale and scope of Engineering Systems as a field is still emerging. This seminar is simultaneously designed to codify what we presently know and to give direction for future development.

Subjects

engineering systems | engineering systems | complexity | complexity | uncertainty | uncertainty | 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 | modeling paradigms | modeling paradigms | cumulative knowledge | cumulative knowledge | empirical data generation | empirical data generation | boundary setting | boundary setting | network models | network models | policy evaluation | policy evaluation

License

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2.854 Manufacturing Systems I (SMA 6304) (MIT) 2.854 Manufacturing Systems I (SMA 6304) (MIT)

Description

As the first in a sequence of four half-term courses, this course will provide the fundamental building blocks for conceptualizing, understanding and optimizing manufacturing systems and supply chains. These building blocks include process analysis, queuing theory, simulation, forecasting, inventory theory and linear programming. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 6304 (Manufacturing Systems I: Analytical Methods and Flow Models). As the first in a sequence of four half-term courses, this course will provide the fundamental building blocks for conceptualizing, understanding and optimizing manufacturing systems and supply chains. These building blocks include process analysis, queuing theory, simulation, forecasting, inventory theory and linear programming. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 6304 (Manufacturing Systems I: Analytical Methods and Flow Models).

Subjects

conceptualizing | conceptualizing | understanding and optimizing manufacturing systems and supply chains | understanding and optimizing manufacturing systems and supply chains | process analysis | process analysis | queueing theory | queueing theory | simulation | simulation | forecasting | forecasting | inventory theory | inventory theory | linear programming | linear programming | conceptualizing | understanding and optimizing manufacturing systems and supply chains | conceptualizing | understanding and optimizing manufacturing systems and supply chains | SMA 6304 | SMA 6304

License

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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

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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

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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

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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

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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

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

Description

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. 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

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12.010 Computational Methods of Scientific Programming (MIT) 12.010 Computational Methods of Scientific Programming (MIT)

Description

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica®. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. Students first learn the basic usage of each language, common types of problems encountered, and techniques for solving a variety of problems encountered in contemporary research: examination of data with visualization techniques, numerical analysis, and methods of dissemination and verification. No prior programming experience is required.Technical RequirementsAny number of development tools can be used to compile and run the .c and .f files found on this course site. C++ compiler is required to This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica®. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. Students first learn the basic usage of each language, common types of problems encountered, and techniques for solving a variety of problems encountered in contemporary research: examination of data with visualization techniques, numerical analysis, and methods of dissemination and verification. No prior programming experience is required.Technical RequirementsAny number of development tools can be used to compile and run the .c and .f files found on this course site. C++ compiler is required to

Subjects

programming languages | techniques used by physical scientists | programming languages | techniques used by physical scientists | FORTRAN | FORTRAN | C | C | C++ | C++ | Matlab | Matlab | Mathematica | Mathematica | program design | program design | algorithm development and verification | algorithm development and verification | comparative advantages and disadvantages of different languages | comparative advantages and disadvantages of different languages | examination of data with visualization techniques | examination of data with visualization techniques | numerical analysis | numerical analysis | methods of dissemination and verification | methods of dissemination and verification | algorithms | algorithms | formula | formula | formulae | formulae | computer programs | computer programs | graphics | graphics | computing languages | computing languages | structure | structure | documentation | documentation | program interface | program interface | syntax | syntax | advanced modeling | advanced modeling | simulation systems | simulation 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

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13.49 Maneuvering and Control of Surface and Underwater Vehicles (MIT) 13.49 Maneuvering and Control of Surface and Underwater Vehicles (MIT)

Description

This course is about maneuvering motions of surface and underwater vehicles. Topics covered include: derivation of equations of motion, hydrodynamic coefficients, memory effects, linear and nonlinear forms of the equations of motion, control surfaces modeling and design, engine, propulsor, and transmission systems modeling and simulation during maneuvering. The course also deals with stability of motion, principles of multivariable automatic control, optimal control, Kalman filtering, and loop transfer recovery. We will also explore applications chosen from autopilots for surface vehicles; towing in open seas; and remotely operated vehicles. This course is about maneuvering motions of surface and underwater vehicles. Topics covered include: derivation of equations of motion, hydrodynamic coefficients, memory effects, linear and nonlinear forms of the equations of motion, control surfaces modeling and design, engine, propulsor, and transmission systems modeling and simulation during maneuvering. The course also deals with stability of motion, principles of multivariable automatic control, optimal control, Kalman filtering, and loop transfer recovery. We will also explore applications chosen from autopilots for surface vehicles; towing in open seas; and remotely operated vehicles.

Subjects

Maneuvering | Maneuvering | motion | motion | surface and underwater vehicles | surface and underwater vehicles | Derivation of equations of motion | Derivation of equations of motion | hydrodynamic coefficients | hydrodynamic coefficients | Memory effects | Memory effects | Linear and nonlinear forms | Linear and nonlinear forms | Control surfaces | Control surfaces | modeling and design | modeling and design | Engine | Engine | propulsor | propulsor | transmission systems modeling | transmission systems modeling | simulation | simulation | Stability of motion | Stability of motion | multivariable automatic control | multivariable automatic control | Optimal control | Optimal control | Kalman filtering | Kalman filtering | loop transfer recovery | loop transfer recovery | autopilots for surface vehicles | autopilots for surface vehicles | towing in open seas | towing in open seas | remotely operated vehicles | remotely operated vehicles | 2.154 | 2.154

License

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

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22.106 Neutron Interactions and Applications (MIT) 22.106 Neutron Interactions and Applications (MIT)

Description

This course is  a foundational study of the effects of single and multiple interactions on neutron distributions and their applications to problems across the Nuclear Engineering department - fission, fusion, and RST. Particle simulation methods are introduced to deal with complex processes that cannot be studied only experimentally or by numerical solutions of equations. Treatment will emphasize basic concepts and understanding, as well as showing the underlying scientific connections with current research areas. This course is  a foundational study of the effects of single and multiple interactions on neutron distributions and their applications to problems across the Nuclear Engineering department - fission, fusion, and RST. Particle simulation methods are introduced to deal with complex processes that cannot be studied only experimentally or by numerical solutions of equations. Treatment will emphasize basic concepts and understanding, as well as showing the underlying scientific connections with current research areas.

Subjects

neutron distributions | neutron distributions | fission | fission | fusion | fusion | RST | RST | Particle simulation methods | Particle simulation methods | complex processes | complex processes | numerical solutions of equations | numerical solutions of equations | basic concepts | basic concepts | underlying scientific connections | underlying scientific connections | current research areas | current research areas | angular distributions | angular distributions | energy distributions | energy distributions | single collision | single collision | multiple collisions | multiple collisions | neutron interactions | neutron interactions | elastic scattering | elastic scattering | inelastic scattering | inelastic scattering | MCNP | MCNP | Monte Carlo | Monte Carlo | molecular dynamics | molecular dynamics

License

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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

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

Description

This course focuses on the basic concepts of computer modeling in science and engineering using discrete particle systems and continuum fields. Techniques and software for statistical sampling, simulation, data analysis and visualization. Use of statistical, quantum chemical, molecular dynamics, Monte Carlo, mesoscale and continuum methods to study fundamental physical phenomena encountered in the fields of computational physics, chemistry, mechanics, materials science, biology, and applied mathematics. Applications drawn from a range of disciplines to build a broad-based understanding of complex structures and interactions in problems where simulation is on equal-footing with theory and experiment. Term project allows development of individual interest. Student mentoring by a coordinated This course focuses on the basic concepts of computer modeling in science and engineering using discrete particle systems and continuum fields. Techniques and software for statistical sampling, simulation, data analysis and visualization. Use of statistical, quantum chemical, molecular dynamics, Monte Carlo, mesoscale and continuum methods to study fundamental physical phenomena encountered in the fields of computational physics, chemistry, mechanics, materials science, biology, and applied mathematics. Applications drawn from a range of disciplines to build a broad-based understanding of complex structures and interactions in problems where simulation is on equal-footing with theory and experiment. Term project allows development of individual interest. Student mentoring by a coordinated

Subjects

Quantum | Quantum | Modeling | Modeling | visualization | visualization | data analysis | data analysis | simulation | simulation | statistical sampling | statistical sampling | 22.00 | 22.00 | 1.021 | 1.021 | 3.021 | 3.021 | 10.333 | 10.333 | 18.361 | 18.361 | 2.030 | 2.030

License

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2.12 Introduction to Robotics (MIT) 2.12 Introduction to Robotics (MIT)

Description

This course provides an overview of robot mechanisms, dynamics, and intelligent controls. Topics include planar and spatial kinematics, and motion planning; mechanism design for manipulators and mobile robots, multi-rigid-body dynamics, 3D graphic simulation; control design, actuators, and sensors; wireless networking, task modeling, human-machine interface, and embedded software. Weekly laboratories provide experience with servo drives, real-time control, and embedded software. Students will design and fabricate working robotic systems in a group-based term project.Technical RequirementsRealOne™ Player software is required to run the .rm files found on this course site. This course provides an overview of robot mechanisms, dynamics, and intelligent controls. Topics include planar and spatial kinematics, and motion planning; mechanism design for manipulators and mobile robots, multi-rigid-body dynamics, 3D graphic simulation; control design, actuators, and sensors; wireless networking, task modeling, human-machine interface, and embedded software. Weekly laboratories provide experience with servo drives, real-time control, and embedded software. Students will design and fabricate working robotic systems in a group-based term project.Technical RequirementsRealOne™ Player software is required to run the .rm files found on this course site.

Subjects

robot | robot | robot design | robot design | dynamics | dynamics | statics | statics | intelligent control | intelligent control | planar and spatial kinematics | planar and spatial kinematics | motion planning | motion planning | manipulator | manipulator | mobile robots | mobile robots | multi-rigid-body dynamics | multi-rigid-body dynamics | 3D graphic simulation | 3D graphic simulation | control design | control design | actuator | actuator | sensor | sensor | task modeling | task modeling | human-machine interface | human-machine interface | embedded software | embedded software | servo | servo | servomechanism | servomechanism | real-time control | real-time control | computer vision | computer vision | navigation | navigation | tele-robotics | tele-robotics | virtual reality | virtual reality

License

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17.506 Ethnic Politics II (MIT) 17.506 Ethnic Politics II (MIT)

Description

This course is designed mainly for political science graduate students conducting or considering conducting research on identity politics. While 17.504 Ethnic Politics I is designed as a primarily theoretical course, Ethnic Politics II switches the focus to methods. It aims to familiarize the student with the current conventional approaches as well as major challenges to them. The course discusses definition and measurement issues as well as briefly addressing survey techniques and modeling. This course is designed mainly for political science graduate students conducting or considering conducting research on identity politics. While 17.504 Ethnic Politics I is designed as a primarily theoretical course, Ethnic Politics II switches the focus to methods. It aims to familiarize the student with the current conventional approaches as well as major challenges to them. The course discusses definition and measurement issues as well as briefly addressing survey techniques and modeling.

Subjects

measurement | measurement | ethnic diversity | ethnic diversity | fluidity | fluidity | identity | identity | social identity theory | social identity theory | mechanisms of group comparison | mechanisms of group comparison | memory | memory | death | death | stigma | stigma | prejudice | prejudice | contact hypothesis | contact hypothesis | cascade models | cascade models | identity simulation | identity simulation

License

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17.914 International Politics in the New Century - via Simulation, Interactive Gaming, and 'Edutainment' (MIT) 17.914 International Politics in the New Century - via Simulation, Interactive Gaming, and 'Edutainment' (MIT)

Description

This workshop is designed to introduce students to different perspectives on politics and the state of the world through new visualization techniques and approaches to interactive political gaming (and selective 'edutainment'). Specifically, we shall explore applications of interactive tools (such as video and web-based games, blogs or simulations) to examine critical challenges in international politics of the 21C century focusing specifically on general insights and specific understandings generated by operational uses of core concepts in political science. This workshop is designed to introduce students to different perspectives on politics and the state of the world through new visualization techniques and approaches to interactive political gaming (and selective 'edutainment'). Specifically, we shall explore applications of interactive tools (such as video and web-based games, blogs or simulations) to examine critical challenges in international politics of the 21C century focusing specifically on general insights and specific understandings generated by operational uses of core concepts in political science.

Subjects

Workshop | Workshop | political science | political science | politics | politics | world | world | visualization | visualization | techniques | techniques | interactive | interactive | gaming | gaming | edutainment | edutainment | interactive tools | interactive tools | video | video | web-based games | web-based games | blogs | blogs | simulations | simulations | international | international | twenty-first century | twenty-first century

License

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

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