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Modeling to Support Damage Control Assessment and Decision-making in Shipboard Environments - Smoke

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N65538-05-M-0154
Agency Tracking Number: N051-050-1127
Amount: $69,988.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N05-050
Solicitation Number: 2005.1
Timeline
Solicitation Year: 2005
Award Year: 2005
Award Start Date (Proposal Award Date): 2005-05-05
Award End Date (Contract End Date): 2005-11-04
Small Business Information
4695 Millennium Drive
Belcamp, MD 21017
United States
DUNS: 035414697
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 W. Keith Bowman
 Senior Analyst
 (410) 273-7722
 keith.bowman@survice.com
Business Contact
 Jeffrey Foulk
Title: VP, Business Operations
Phone: (410) 273-7722
Email: jeff.foulk@survice.com
Research Institution
N/A
Abstract

As the Navy moves to reduce shipboard manning, automated damage control systems are necessary to evaluate real-time data and provide the crew with proper situational awareness and predictive capability. Existing computer models for estimating smoke spread are not designed to model confined compartments, are complex in operation, and generally require long periods of time to set up and process. An accurate, yet fast-running computer model is needed to input shipboard sensor and baseline target configuration data to simulate the smoke spread in a shipboard environment. The SURVICE Engineering Company, with our team members Enthalpy Corporation and Northrop Grumman Ship Systems, proposes the development of a smoke spread analysis model that can fill the gap between over-simplified empirical relationships in zone based fire/smoke models and the ultra-high-resolution computational fluid dynamics type field models. The smoke spread prediction model will be fast running and sufficiently accurate while capable of simulating all the key processes involved in smoke spread dynamics and interfacing with the shipboard sensor network. To develop such a model, and to minimize development risk, the basis for this proposed model will be the existing Fire Prediction Model (FPM) and its inherent methodology.

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

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