System-of-Systems Engineering - Liophant Simulation
System-of-Systems Engineering - Liophant Simulation System-of-Systems Engineering - Liophant Simulation
Mathematical Modeling Techniques• There are a variety ofmathematical modelingtechniques that areapplicable to SoS• Markov Chains– Used to model stochasticprocesses which adhere tothe Markov Property• Graph Theory– Basis of many networkmodels– Can also be used to studythe complexity andstructure of a SoSblog.purevisibility.comblog.purevisibility.comDeveloping Methods and Techniques for System of Systems EngineeringDr. Dimitri Mavris, dimitri.mavris@ae.gatech.eduEetimes.com38discovery.bits-pilani.ac.in
Enablers for Complex SoS• Design of ComputerSimulations– Space Filling Designs– Adaptive DoE• Modeling and SimulationTechniques– Agent-based modeling andconstructive simulations– System Dynamics Modeling– Discrete Event Simulation– Mathematical Modeling Techniques• Non-linear SurrogateModeling– Neural Networks– Kriging/Gaussian– Stepwise RSE• Probabilistic Theory– Stochastic modeling– Surrogate modeling of stochasticprocesses– Monte Carlo Simulation• Visual AnalyticsDeveloping Methods and Techniques for System of Systems EngineeringDr. Dimitri Mavris, dimitri.mavris@ae.gatech.edu39
- Page 1 and 2: Developing Methods and Techniques f
- Page 3 and 4: The Aerospace Systems Design Labora
- Page 5 and 6: Motivation- Emphasis on “Early-Ph
- Page 7 and 8: What is a system?“A set of functi
- Page 9 and 10: System of Systems• “A set or ar
- Page 11 and 12: What is SoSE?• System of Systems
- Page 13 and 14: The Evolution of New Ideas“All tr
- Page 15 and 16: What is needed for this New Paradig
- Page 17 and 18: An Architecture-based Approach to S
- Page 19 and 20: The System Alternative Space• The
- Page 21 and 22: The Architecture-based Technology E
- Page 23 and 24: Extension to Systems-of-Systems Ana
- Page 25 and 26: Fundamental Properties of a Complex
- Page 27 and 28: Enablers for Complex SoS• Design
- Page 29 and 30: Design of Experiments• Design of
- Page 31 and 32: Design of Computer Simulation• Co
- Page 33 and 34: Agent-Based Behavioral Modeling•
- Page 35 and 36: System Dynamics Modeling• System
- Page 37: Discrete Event Simulations• Discr
- Page 41 and 42: Surrogate ModelsWhy do we use surro
- Page 43 and 44: Challenges to Surrogate Modeling fo
- Page 45 and 46: Fitting Modal ResponsesDeveloping M
- Page 47 and 48: Enablers for Complex SoS• Design
- Page 49 and 50: Enablers for Complex SoS• Design
- Page 51 and 52: Pareto Optimal Solutions in Many Di
- Page 53 and 54: Interactive Electronic Design Revie
- Page 55 and 56: Collaboration and Integration in So
- Page 57 and 58: Concluding Remarks• System of Sys
- Page 59 and 60: Selecting a DesignDeveloping Method
- Page 61 and 62: A New Paradigm Shift: Simulation Ba
- Page 63 and 64: Which are simple? Which arecomplica
- Page 65 and 66: What is a Markov Chain• Markov Ch
- Page 67 and 68: Markov Chains• The transition pro
Mathematical Modeling Techniques• There are a variety <strong>of</strong>mathematical modelingtechniques that areapplicable to SoS• Markov Chains– Used to model stochasticprocesses which adhere tothe Markov Property• Graph Theory– Basis <strong>of</strong> many networkmodels– Can also be used to studythe complexity andstructure <strong>of</strong> a SoSblog.purevisibility.comblog.purevisibility.comDeveloping Methods and Techniques for <strong>System</strong> <strong>of</strong> <strong>System</strong>s <strong>Engineering</strong>Dr. Dimitri Mavris, dimitri.mavris@ae.gatech.eduEetimes.com38discovery.bits-pilani.ac.in
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