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M&S Uncertainty Quantification

Award Information

Department of Defense
Missile Defense Agency
Award ID:
Program Year/Program:
2013 / STTR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
Applied Biomathematics
100 North Country Road Setauket, NY 11733-1354
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 1
Fiscal Year: 2013
Title: M&S Uncertainty Quantification
Agency / Branch: DOD / MDA
Contract: HQ0147-13-C-7401
Award Amount: $99,266.00


An emerging consensus in engineering holds that aleatory uncertainty should be propagated by traditional methods of probability theory but that epistemic uncertainty may require methods that do not confuse incertitude with variability by requiring every possibility be associated with a probability that it occurs. Therefore, although Monte Carlo shells that re-run calculations many times while varying input values according to specified distributions are useful, they are insufficient to properly account for epistemic and aleatory uncertainty. Three things are needed to build on the new consensus. The first is a clear and comprehensive roadmap for how various important problems (e.g., arithmetic and logical evaluations, backcalculations, sensitivity analyses, etc.) can be solved under this view. The second is software that enables analysts to automatically propagate through simulations the uncertainty implied by the significant digits of the numbers specifying a model. Such software would require very little training in uncertainty analysis to be useful to analysts. The third need is a software library of recommended methods for common calculations that is usable by modelers and analysts who may not themselves be experts in uncertainty quantification but who recognize the need for and benefits from it.

Principal Investigator:

Scott D. Ferson
(631) 751-4350

Business Contact:

Lev R. Ginzburg
(631) 751-4350
Small Business Information at Submission:

Applied Biomathematics
100 North Country Rd. Setauket, NY 11733-1354

EIN/Tax ID: 112596502
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Research Institution Information:
Los Alamos National Laboratory
P.O. Box 1663
Los Alamos, NM 87545-
Contact: Kari Sentz
Contact Phone: (505) 667-3320