NASA SBIR 2005 Solicitation

SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
Applied Biomathematics
100 North Country Road
Setauket ,NY 11733 - 1300
(631) 751 - 4350

PRINCIPAL INVESTIGATOR/PROJECT MANAGER (Name, E-mail, Mail Address, City/State/Zip, Phone)
Scott   Ferson
scott@ramas.com
100 North Country Road
Setauket, NY  11733 -1300
(631) 751 - 4350

TECHNICAL ABSTRACT (LIMIT 200 WORDS)
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.

POTENTIAL NASA COMMERCIAL APPLICATIONS (LIMIT 150 WORDS)
The primary application envisioned for the extended PBA technology at NASA is the analysis of uncertainty and risk in subsystem, system, and mission design in an Integrated Concurrent Engineering environment like that used by Team X at JPL. The methods, algorithms, libraries, and software developed will be of use in a wide variety of commercial activities that involve physics- or non-physics-based systems design, reliability assessment, or risk analysis. Applications where NASA may use the technology while serving as a vendor include: (1) Uncertainty and risk analysis during commercial spacecraft subsystem component, subsystem, system, and/or mission early design, (2) Integrated analysis of qualitative and quantitative uncertainty during commercial operations and organization design, restructuring and/or risk and reliability analysis, (3) Commercial organizational and/or mission risk reduction modeling, (4) Incorporation of quantitative uncertainty and risk analysis in commercial system optimization and constraint satisfaction operations, and (5) Development of quantitative system-wide, mission-wide, and/or organization-wide probabilistic risk-based margin determination metrics and management procedures.

POTENTIAL NON-NASA COMMERCIAL APPLICATIONS (LIMIT 150 WORDS)
The successful completion of Phase II research and development will result in a library of functions for performing Probability Bounds Analysis in Microsoft Excel, a software add-on implementing those functions, a software application that guides engineers in constructing uncertain input parameters using available information, and methods for applying these technologies in an Integrated Concurrent Engineering early design environment. Potential commercial applications include: (1) A Microsoft Excel application for analyzing risk using PBA and uncertain numbers. Highly successful commercial risk analysis applications based on Excel exist (e.g., Crystal Ball), but all rely on Monte Carlo simulation and are thus limited in comprehensiveness and applicability to near real time design environments. (2) A commercial software application implementing PBA technology using quantitative and qualitative uncertainty information to perform system optimization, constraint satisfaction, and organizational risk reduction modeling. (3) Methods and software for developing system- or organization-wide probabilistic risk-based margin determination metrics and management procedures. This product could be implemented as a book with accompanying software, or as a training workshop.

NASA's technology taxonomy has been developed by the SBIR-STTR program to disseminate awareness of proposed and awarded R/R&D in the agency. It is a listing of over 100 technologies, sorted into broad categories, of interest to NASA.

TECHNOLOGY TAXONOMY MAPPING

Data Acquisition and End-to-End-Management Expert Systems Human-Computer Interfaces Operations Concepts and Requirements Simulation Modeling Environment Software Development Environments Software Tools for Distributed Analysis and Simulation