Accounting for Epistemic and Aleatory Uncertainty in Early System Design

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNL06AA40P
Agency Tracking Number: 054481
Amount: $69,427.00
Phase: Phase I
Program: SBIR
Awards Year: 2006
Solicitation Year: 2005
Solicitation Topic Code: S2.07
Solicitation Number: N/A
Small Business Information
100 North Country Road, Setauket, NY, 11733-1300
DUNS: 178047015
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Scott Ferson
 Principal Investigator
 (631) 751-4350
Business Contact
 Lev Ginzburg
Title: President
Phone: (631) 751-4350
Research Institution
The proposed work extends Probability Bounds Analysis to model epistemic and aleatory uncertainty during early design of engineered systems in an Integrated Concurrent Engineering environment. This method uses efficient analytic and semi-analytic calculations, is more rigorous than probabilistic Monte Carlo simulation, and provides comprehensive and (often) best possible bounds on mission-level risk as a function of uncertainty in each parameter. Phase I will demonstrate the capability to robustly model variability (aleatory uncertainty) and incertitude (epistemic uncertainty) during early design. The demonstrated methods will (1) allow rapid, rigorous, and more complete exploration of alternate designs in the mission- and engineering-constrained trade space; (2) provide a rigorous rationale for risk-based margin determination that is robust to surprise; (3) facilitate the incorporation of qualitatively described risks in quantitative risk analysis; (4) support the integration of physics and non-physics based risks in mission-wide risk analysis; and (5) permit sensitivity analysis at the mission, system, subsystem, and component levels that identifies the importance of specific uncertainties to uncertainty at higher levels and allows the rapid exploration of alternate strategies and designs. This suite of capabilities is not currently available to systems engineers and cannot be provided by more traditional probabilistic risk assessment methods.

* Information listed above is at the time of submission. *

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