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Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks. This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

ESD.04 | ESD.04 | 1.041 | 1.041 | ESD.01 | ESD.01 | frameworks and models in engineering systems | frameworks and models in engineering systems | quantitative models | quantitative models | qualitative frameworks | qualitative frameworks | complex engineering systems | complex engineering systems | analysis and design | analysis and design | emergent behavior | emergent behavior | stochasticity | stochasticity | non-linearities | non-linearities | architectural system configuration | architectural system configurationLicense

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

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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 evaluationLicense

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

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See all metadataESD.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 | uncertaintyLicense

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

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This course deals with modeling multi-domain engineering systems at a level of detail suitable for design and control system implementation. Topics covered include network representation, state-space models; multi-port energy storage and dissipation, Legendre transforms, nonlinear mechanics, transformation theory, Lagrangian and Hamiltonian forms and control-relevant properties. Application examples may include electro-mechanical transducers, mechanisms, electronics, fluid and thermal systems, compressible flow, chemical processes, diffusion, and wave transmission. This course deals with modeling multi-domain engineering systems at a level of detail suitable for design and control system implementation. Topics covered include network representation, state-space models; multi-port energy storage and dissipation, Legendre transforms, nonlinear mechanics, transformation theory, Lagrangian and Hamiltonian forms and control-relevant properties. Application examples may include electro-mechanical transducers, mechanisms, electronics, fluid and thermal systems, compressible flow, chemical processes, diffusion, and wave transmission.Subjects

Modeling multi-domain engineering systems | Modeling multi-domain engineering systems | design and control system implementation | design and control system implementation | Network representation | Network representation | state-space models | state-space models | dissipation | dissipation | Legendre transforms | Legendre transforms | Nonlinear mechanics | Nonlinear mechanics | transformation theory | transformation theory | Hamiltonian forms | Hamiltonian forms | Control-relevant properties | Control-relevant properties | electro-mechanical transducers | electro-mechanical transducers | mechanisms | mechanisms | electronics | electronics | thermal systems | thermal systems | compressible flow | compressible flow | chemical processes | chemical processes | diffusion | diffusion | wave transmission | wave transmissionLicense

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

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The basic objective of Unified Engineering is to give a solid understanding of the fundamental disciplines of aerospace engineering, as well as their interrelationships and applications. These disciplines are Materials and Structures (M); Computers and Programming (C); Fluid Mechanics (F); Thermodynamics (T); Propulsion (P); and Signals and Systems (S). In choosing to teach these subjects in a unified manner, the instructors seek to explain the common intellectual threads in these disciplines, as well as their combined application to solve engineering Systems Problems (SP). Throughout the year, the instructors emphasize the connections among the disciplines.Technical RequirementsMicrosoft® Excel software is recommended for viewing the .xls files The basic objective of Unified Engineering is to give a solid understanding of the fundamental disciplines of aerospace engineering, as well as their interrelationships and applications. These disciplines are Materials and Structures (M); Computers and Programming (C); Fluid Mechanics (F); Thermodynamics (T); Propulsion (P); and Signals and Systems (S). In choosing to teach these subjects in a unified manner, the instructors seek to explain the common intellectual threads in these disciplines, as well as their combined application to solve engineering Systems Problems (SP). Throughout the year, the instructors emphasize the connections among the disciplines.Technical RequirementsMicrosoft® Excel software is recommended for viewing the .xls filesSubjects

Unified | Unified | Unified Engineering | Unified Engineering | aerospace | aerospace | CDIO | CDIO | C-D-I-O | C-D-I-O | conceive | conceive | design | design | implement | implement | operate | operate | team | team | team-based | team-based | discipline | discipline | materials | materials | structures | structures | materials and structures | materials and structures | computers | computers | programming | programming | computers and programming | computers and programming | fluids | fluids | fluid mechanics | fluid mechanics | thermodynamics | thermodynamics | propulsion | propulsion | signals | signals | systems | systems | signals and systems | signals and systems | systems problems | systems problems | fundamentals | fundamentals | technical communication | technical communication | graphical communication | graphical communication | communication | communication | reading | reading | research | research | experimentation | experimentation | personal response system | personal response system | prs | prs | active learning | active learning | First law | First law | first law of thermodynamics | first law of thermodynamics | thermo-mechanical | thermo-mechanical | energy | energy | energy conversion | energy conversion | aerospace power systems | aerospace power systems | propulsion systems | propulsion systems | aerospace propulsion systems | aerospace propulsion systems | heat | heat | work | work | thermal efficiency | thermal efficiency | forms of energy | forms of energy | energy exchange | energy exchange | processes | processes | heat engines | heat engines | engines | engines | steady-flow energy equation | steady-flow energy equation | energy flow | energy flow | flows | flows | path-dependence | path-dependence | path-independence | path-independence | reversibility | reversibility | irreversibility | irreversibility | state | state | thermodynamic state | thermodynamic state | performance | performance | ideal cycle | ideal cycle | simple heat engine | simple heat engine | cycles | cycles | thermal pressures | thermal pressures | temperatures | temperatures | linear static networks | linear static networks | loop method | loop method | node method | node method | linear dynamic networks | linear dynamic networks | classical methods | classical methods | state methods | state methods | state concepts | state concepts | dynamic systems | dynamic systems | resistive circuits | resistive circuits | sources | sources | voltages | voltages | currents | currents | Thevinin | Thevinin | Norton | Norton | initial value problems | initial value problems | RLC networks | RLC networks | characteristic values | characteristic values | characteristic vectors | characteristic vectors | transfer function | transfer function | ada | ada | ada programming | ada programming | programming language | programming language | software systems | software systems | programming style | programming style | computer architecture | computer architecture | program language evolution | program language evolution | classification | classification | numerical computation | numerical computation | number representation systems | number representation systems | assembly | assembly | SimpleSIM | SimpleSIM | RISC | RISC | CISC | CISC | operating systems | operating systems | single user | single user | multitasking | multitasking | multiprocessing | multiprocessing | domain-specific classification | domain-specific classification | recursive | recursive | execution time | execution time | fluid dynamics | fluid dynamics | physical properties of a fluid | physical properties of a fluid | fluid flow | fluid flow | mach | mach | reynolds | reynolds | conservation | conservation | conservation principles | conservation principles | conservation of mass | conservation of mass | conservation of momentum | conservation of momentum | conservation of energy | conservation of energy | continuity | continuity | inviscid | inviscid | steady flow | steady flow | simple bodies | simple bodies | airfoils | airfoils | wings | wings | channels | channels | aerodynamics | aerodynamics | forces | forces | moments | moments | equilibrium | equilibrium | freebody diagram | freebody diagram | free-body | free-body | free body | free body | planar force systems | planar force systems | equipollent systems | equipollent systems | equipollence | equipollence | support reactions | support reactions | reactions | reactions | static determinance | static determinance | determinate systems | determinate systems | truss analysis | truss analysis | trusses | trusses | method of joints | method of joints | method of sections | method of sections | statically indeterminate | statically indeterminate | three great principles | three great principles | 3 great principles | 3 great principles | indicial notation | indicial notation | rotation of coordinates | rotation of coordinates | coordinate rotation | coordinate rotation | stress | stress | extensional stress | extensional stress | shear stress | shear stress | notation | notation | plane stress | plane stress | stress equilbrium | stress equilbrium | stress transformation | stress transformation | mohr | mohr | mohr's circle | mohr's circle | principal stress | principal stress | principal stresses | principal stresses | extreme shear stress | extreme shear stress | strain | strain | extensional strain | extensional strain | shear strain | shear strain | strain-displacement | strain-displacement | compatibility | compatibility | strain transformation | strain transformation | transformation of strain | transformation of strain | mohr's circle for strain | mohr's circle for strain | principal strain | principal strain | extreme shear strain | extreme shear strain | uniaxial stress-strain | uniaxial stress-strain | material properties | material properties | classes of materials | classes of materials | bulk material properties | bulk material properties | origin of elastic properties | origin of elastic properties | structures of materials | structures of materials | atomic bonding | atomic bonding | packing of atoms | packing of atoms | atomic packing | atomic packing | crystals | crystals | crystal structures | crystal structures | polymers | polymers | estimate of moduli | estimate of moduli | moduli | moduli | composites | composites | composite materials | composite materials | modulus limited design | modulus limited design | material selection | material selection | materials selection | materials selection | measurement of elastic properties | measurement of elastic properties | stress-strain | stress-strain | stress-strain relations | stress-strain relations | anisotropy | anisotropy | orthotropy | orthotropy | measurements | measurements | engineering notation | engineering notation | Hooke | Hooke | Hooke's law | Hooke's law | general hooke's law | general hooke's law | equations of elasticity | equations of elasticity | boundary conditions | boundary conditions | multi-disciplinary | multi-disciplinary | models | models | engineering systems | engineering systems | experiments | experiments | investigations | investigations | experimental error | experimental error | design evaluation | design evaluation | evaluation | evaluation | trade studies | trade studies | effects of engineering | effects of engineering | social context | social context | engineering drawings | engineering drawings | 16.01 | 16.01 | 16.02 | 16.02 | 16.03 | 16.03 | 16.04 | 16.04License

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

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Includes audio/video content: AV selected lectures, AV faculty introductions, AV special element video. The basic objective of Unified Engineering is to give a solid understanding of the fundamental disciplines of aerospace engineering, as well as their interrelationships and applications. These disciplines are Materials and Structures (M); Computers and Programming (C); Fluid Mechanics (F); Thermodynamics (T); Propulsion (P); and Signals and Systems (S). In choosing to teach these subjects in a unified manner, the instructors seek to explain the common intellectual threads in these disciplines, as well as their combined application to solve engineering Systems Problems (SP). Throughout the year, the instructors emphasize the connections among the disciplines. Includes audio/video content: AV selected lectures, AV faculty introductions, AV special element video. The basic objective of Unified Engineering is to give a solid understanding of the fundamental disciplines of aerospace engineering, as well as their interrelationships and applications. These disciplines are Materials and Structures (M); Computers and Programming (C); Fluid Mechanics (F); Thermodynamics (T); Propulsion (P); and Signals and Systems (S). In choosing to teach these subjects in a unified manner, the instructors seek to explain the common intellectual threads in these disciplines, as well as their combined application to solve engineering Systems Problems (SP). Throughout the year, the instructors emphasize the connections among the disciplines.Subjects

Unified | Unified | Unified Engineering | Unified Engineering | aerospace | aerospace | CDIO | CDIO | C-D-I-O | C-D-I-O | conceive | conceive | design | design | implement | implement | operate | operate | team | team | team-based | team-based | discipline | discipline | materials | materials | structures | structures | materials and structures | materials and structures | computers | computers | programming | programming | computers and programming | computers and programming | fluids | fluids | fluid mechanics | fluid mechanics | thermodynamics | thermodynamics | propulsion | propulsion | signals | signals | systems | systems | signals and systems | signals and systems | systems problems | systems problems | fundamentals | fundamentals | technical communication | technical communication | graphical communication | graphical communication | communication | communication | reading | reading | research | research | experimentation | experimentation | personal response system | personal response system | prs | prs | active learning | active learning | First law | First law | first law of thermodynamics | first law of thermodynamics | thermo-mechanical | thermo-mechanical | energy | energy | energy conversion | energy conversion | aerospace power systems | aerospace power systems | propulsion systems | propulsion systems | aerospace propulsion systems | aerospace propulsion systems | heat | heat | work | work | thermal efficiency | thermal efficiency | forms of energy | forms of energy | energy exchange | energy exchange | processes | processes | heat engines | heat engines | engines | engines | steady-flow energy equation | steady-flow energy equation | energy flow | energy flow | flows | flows | path-dependence | path-dependence | path-independence | path-independence | reversibility | reversibility | irreversibility | irreversibility | state | state | thermodynamic state | thermodynamic state | performance | performance | ideal cycle | ideal cycle | simple heat engine | simple heat engine | cycles | cycles | thermal pressures | thermal pressures | temperatures | temperatures | linear static networks | linear static networks | loop method | loop method | node method | node method | linear dynamic networks | linear dynamic networks | classical methods | classical methods | state methods | state methods | state concepts | state concepts | dynamic systems | dynamic systems | resistive circuits | resistive circuits | sources | sources | voltages | voltages | currents | currents | Thevinin | Thevinin | Norton | Norton | initial value problems | initial value problems | RLC networks | RLC networks | characteristic values | characteristic values | characteristic vectors | characteristic vectors | transfer function | transfer function | ada | ada | ada programming | ada programming | programming language | programming language | software systems | software systems | programming style | programming style | computer architecture | computer architecture | program language evolution | program language evolution | classification | classification | numerical computation | numerical computation | number representation systems | number representation systems | assembly | assembly | SimpleSIM | SimpleSIM | RISC | RISC | CISC | CISC | operating systems | operating systems | single user | single user | multitasking | multitasking | multiprocessing | multiprocessing | domain-specific classification | domain-specific classification | recursive | recursive | execution time | execution time | fluid dynamics | fluid dynamics | physical properties of a fluid | physical properties of a fluid | fluid flow | fluid flow | mach | mach | reynolds | reynolds | conservation | conservation | conservation principles | conservation principles | conservation of mass | conservation of mass | conservation of momentum | conservation of momentum | conservation of energy | conservation of energy | continuity | continuity | inviscid | inviscid | steady flow | steady flow | simple bodies | simple bodies | airfoils | airfoils | wings | wings | channels | channels | aerodynamics | aerodynamics | forces | forces | moments | moments | equilibrium | equilibrium | freebody diagram | freebody diagram | free-body | free-body | free body | free body | planar force systems | planar force systems | equipollent systems | equipollent systems | equipollence | equipollence | support reactions | support reactions | reactions | reactions | static determinance | static determinance | determinate systems | determinate systems | truss analysis | truss analysis | trusses | trusses | method of joints | method of joints | method of sections | method of sections | statically indeterminate | statically indeterminate | three great principles | three great principles | 3 great principles | 3 great principles | indicial notation | indicial notation | rotation of coordinates | rotation of coordinates | coordinate rotation | coordinate rotation | stress | stress | extensional stress | extensional stress | shear stress | shear stress | notation | notation | plane stress | plane stress | stress equilbrium | stress equilbrium | stress transformation | stress transformation | mohr | mohr | mohr's circle | mohr's circle | principal stress | principal stress | principal stresses | principal stresses | extreme shear stress | extreme shear stress | strain | strain | extensional strain | extensional strain | shear strain | shear strain | strain-displacement | strain-displacement | compatibility | compatibility | strain transformation | strain transformation | transformation of strain | transformation of strain | mohr's circle for strain | mohr's circle for strain | principal strain | principal strain | extreme shear strain | extreme shear strain | uniaxial stress-strain | uniaxial stress-strain | material properties | material properties | classes of materials | classes of materials | bulk material properties | bulk material properties | origin of elastic properties | origin of elastic properties | structures of materials | structures of materials | atomic bonding | atomic bonding | packing of atoms | packing of atoms | atomic packing | atomic packing | crystals | crystals | crystal structures | crystal structures | polymers | polymers | estimate of moduli | estimate of moduli | moduli | moduli | composites | composites | composite materials | composite materials | modulus limited design | modulus limited design | material selection | material selection | materials selection | materials selection | measurement of elastic properties | measurement of elastic properties | stress-strain | stress-strain | stress-strain relations | stress-strain relations | anisotropy | anisotropy | orthotropy | orthotropy | measurements | measurements | engineering notation | engineering notation | Hooke | Hooke | Hooke's law | Hooke's law | general hooke's law | general hooke's law | equations of elasticity | equations of elasticity | boundary conditions | boundary conditions | multi-disciplinary | multi-disciplinary | models | models | engineering systems | engineering systems | experiments | experiments | investigations | investigations | experimental error | experimental error | design evaluation | design evaluation | evaluation | evaluation | trade studies | trade studies | effects of engineering | effects of engineering | social context | social context | engineering drawings | engineering drawingsLicense

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

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This course models multi-domain engineering systems at a level of detail suitable for design and control system implementation. Topics include network representation, state-space models; multi-port energy storage and dissipation, Legendre transforms; nonlinear mechanics, transformation theory, Lagrangian and Hamiltonian forms; and control-relevant properties. Application examples may include electro-mechanical transducers, mechanisms, electronics, fluid and thermal systems, compressible flow, chemical processes, diffusion, and wave transmission. This course models multi-domain engineering systems at a level of detail suitable for design and control system implementation. Topics include network representation, state-space models; multi-port energy storage and dissipation, Legendre transforms; nonlinear mechanics, transformation theory, Lagrangian and Hamiltonian forms; and control-relevant properties. Application examples may include electro-mechanical transducers, mechanisms, electronics, fluid and thermal systems, compressible flow, chemical processes, diffusion, and wave transmission.Subjects

Modeling multi-domain engineering systems | Modeling multi-domain engineering systems | design and control system implementation | design and control system implementation | Network representation | Network representation | state-space models | state-space models | dissipation | dissipation | Legendre transforms | Legendre transforms | Nonlinear mechanics | Nonlinear mechanics | transformation theory | transformation theory | Hamiltonian forms | Hamiltonian forms | Control-relevant properties | Control-relevant properties | electro-mechanical transducers | electro-mechanical transducers | mechanisms | mechanisms | electronics | electronics | thermal systems | thermal systems | compressible flow | compressible flow | chemical processes | chemical processes | diffusion | diffusion | wave transmission | wave transmissionLicense

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

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ESD.83 Doctoral Seminar in Engineering Systems examines the core theory and contextual applications of the emerging field of Engineering Systems. There is a focus 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 of the course 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. ESD.83 Doctoral Seminar in Engineering Systems examines the core theory and contextual applications of the emerging field of Engineering Systems. There is a focus 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 of the course 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 | 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 evaluationLicense

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

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Engineering systems design must have the flexibility to take advantage of new opportunities while avoiding disasters. This subject develops "real options" analysis to create design flexibility and measure its value so that it can be incorporated into system optimization. It builds on essential concepts of system models, decision analysis, and financial concepts. Emphasis is placed on calculating value of real options with special attention given to efficient analysis and practical applications. The material is organized and presented to deal with the contextual reality of technological systems, that substantially distinguishes the analysis of real options in engineering systems from that of financial options. Note This MIT OpenCourseWare site is based on the materials from Profes Engineering systems design must have the flexibility to take advantage of new opportunities while avoiding disasters. This subject develops "real options" analysis to create design flexibility and measure its value so that it can be incorporated into system optimization. It builds on essential concepts of system models, decision analysis, and financial concepts. Emphasis is placed on calculating value of real options with special attention given to efficient analysis and practical applications. The material is organized and presented to deal with the contextual reality of technological systems, that substantially distinguishes the analysis of real options in engineering systems from that of financial options. Note This MIT OpenCourseWare site is based on the materials from ProfesSubjects

real options | real options | flexibility | flexibility | flexible design | flexible design | engineering systems | engineering systems | complex projects | complex projects | evaluation over time | evaluation over time | risk | risk | uncertainty | uncertainty | valuation | valuation | timing | timing | uncertainty modeling | uncertainty modeling | flexibility valuation | flexibility valuation | methods | methods | design analysis | design analysis | lattice analysis | lattice analysis | monte carlo simulation | monte carlo simulation | flexibility identification. | flexibility identification.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.htmSite sourced from

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See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

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See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

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See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

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See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

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See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

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Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

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Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

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See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataESD.04J Frameworks and Models in Engineering Systems / Engineering System Design (MIT)

Description

This class provides an introduction to quantitative models and qualitative frameworks for studying complex engineering systems. Also taught is the art of abstracting a complex system into a model for purposes of analysis and design while dealing with complexity, emergent behavior, stochasticity, non-linearities and the requirements of many stakeholders with divergent objectives. The successful completion of the class requires a semester-long class project that deals with critical contemporary issues which require an integrative, interdisciplinary approach using the above models and frameworks.Subjects

frameworks and models in engineering systems | quantitative models | qualitative frameworks | complex engineering systems | analysis and design | emergent behavior | stochasticity | non-linearities | architectural system configurationLicense

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

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

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See all metadata