System-of-Systems Engineering - Liophant Simulation

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Surrogate Modeling Comes of Age• In the 1990s, surrogate models were seen as amathematical curiosity in the designcommunity• Response surface equations, Kriging models,and neural networks have been crossfertilizedand their use is now widespread• Automated tools for creation and validationare needed• A library of surrogates and the underlyingassumptions for their use must be constructedR 2Surrogate modeling for systems analysis is now a standard technique in the fieldDeveloping Methods and Techniques for System of Systems EngineeringDr. Dimitri Mavris, dimitri.mavris@ae.gatech.edu40
Surrogate ModelsWhy do we use surrogate models?• Statistical analysis of contributing factors, includinginteractions and high order effects• Closed-form mathematical characterization of “blackbox”• Dynamic / interactive visualization of model space• Computer evaluation time is multiple orders ofmagnitude less than legacy “black box” codes,enables Monte Carlo simulations and probabilisticanalysis• Share model of systemic behavior without sharingsensitive tools and models.Training data setV&V data setError checkingComputer model / Legacy code / Black boxWhat do we need to create surrogate models?• A carefully selected data set for regression or“training”, may imply a significant allocation ofresources (Design of Experiments)• A sufficiently broad data set for Validation &Verification (V&V) through and error checkingSecure sharingDeveloping Methods and Techniques for System of Systems EngineeringDr. Dimitri Mavris, dimitri.mavris@ae.gatech.edu41
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 and 38: Discrete Event Simulations• Discr
Page 39: Enablers for Complex SoS• Design
Page 43 and 44: Challenges to Surrogate Modeling fo
Page 45 and 46: Fitting Modal ResponsesDeveloping M
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

System-of-Systems Engineering - Liophant Simulation

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