System-of-Systems Engineering - Liophant Simulation

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Motivation - Increasing need for moreinteroperable, cost-effective systems• Military systems are becomingincreasingly complex as informationand communications technology surges• Distribution of operations is creating aneed for aerospace systems to becomeincreasingly interoperablehttps://nasea.faa.gov/architecture/main/display/2• Despite their complexity, aerospacesystems must be cost effectiveThese trends have resulted in an increasedfocus on System-of-Systems Engineering incivil, military, and space applicationsDeveloping Methods and Techniques for System of Systems EngineeringDr. Dimitri Mavris, dimitri.mavris@ae.gatech.edu4http://www.ibm.com
Motivation- Emphasis on “Early-Phase” SE• Systems Engineering (SE)– An interdisciplinary approach to derive, evolve, and verify a life-cycle balancedsystem solution that satisfies customer expectations and meets publicacceptability (IEEE 1220-1994)• The most fundamental (and most difficult and costly to reverse) decisionsare made in the early phases of design and architecture definition– This is doubly true for System of SystemsVerification andValidation“Early-Phase” SEAdapted From INCOSE HandbookDeveloping Methods and Techniques for System of Systems EngineeringDr. Dimitri Mavris, dimitri.mavris@ae.gatech.edu5
Page 1 and 2: Developing Methods and Techniques f
Page 3: The Aerospace Systems Design Labora
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 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 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
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System-of-Systems Engineering - Liophant Simulation

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