Probabilistic Error Estimation In Model-Based Predictions

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$449,029.00
Award Year:
2005
Program:
SBIR
Phase:
Phase II
Contract:
N00014-05-C-0267
Award Id:
70182
Agency Tracking Number:
N041-137-0921
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
3916 Trade Center Drive, Ann Arbor, MI, 48108
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
134722656
Principal Investigator:
NickolasVlahopoulos
Operating Manager
(734) 355-0084
nv@miengsrv.com
Business Contact:
ChristinaVlahopoulos
President
(734) 358-0777
christinavl@miengsrv.com
Research Institute:
n/a
Abstract
Modern ship designs can only be successful if the ship can survive in a hostile environment. External threats for a ship can originate from underwater detonations, anti-ship missiles, and even low tech weapons like in the terrorist attack on USS Cole. These threats become even more important as the focal point for naval operations has shifted towards littoral areas, where ships are exposed to a higher risk. Current analysis methods do not provide levels of confidence and large structural design safety factors are used. Thus, ships are heavier and more expensive to construct and maintain than may actually be required. Models that quantify the level of confidence are required in order to provide meaningful and reliable information during the ship design stage. The Completed Phase I effort demonstrated the feasibility of performing model update and error estimation in UNDEX simulation using FEA models with a large number of elements. In the proposed Phase II effort additional computational capabilities will be developed in order to create a complete capability for model update and error estimation. The new developments will be utilized in full scale modeling/testing application for a surface ship with the collaboration of NSWC/IHD, and in automotive crash analysis simulations with the participation of TNO.

* information listed above is at the time of submission.

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