ENGINEERING CASE STUDIES

Accounting for epistemic and aleatory uncertainty in early system design NASA SBIR Phase 2 Final Report

 

Software: RAMAS/GIS

Funding: Electric Power Research Institute and Carolina Power and Light

Authors: Scott Ferson

Location of study: Applied Biomathematics 100 North Country Road Setauket, NY

Project description

This project 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 1 demonstrated the capability to robustly model uncertainty during early design. Phase 2 will build on the Phase 1 work by 1) Implementing the PBA technology in Excel-mediated computing tools, 2) Fashioning an interface for these tools that enables fast and robust elicitation of expert knowledge, 3) Initiating the development of a library of such elicitations, 4) Demonstrating the application of the tools, interface and library in an interactive, distributedcomputing environment, 5) Developing case studies, and 6) Creating tutorial documentation. Important applications of these new tools include the ability to rapidly and rigorously explore uncertainty regarding alternate designs, determine risk-based margins that are robust to surprise, and incorporate qualitatively described risks in quantitative analyses. This suite of capabilities is not currently available to systems engineers and cannot be provided by more traditional probabilistic risk assessment methods. 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 the IDC at LaRC. The methods, algorithms, libraries, and software developed will be of use in a wide variety of commercial activities that involve physicsor 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, and (4) Incorporation of quantitative uncertainty and risk analysis in quantitative system-wide, mission-wide, and/or organization-wide probabilistic risk-based margin determination metrics and management procedures.

2. Identification and Significance of the Innovation The proposed work extends Probability Bounds Analysis (PBA) to model epistemic and aleatory uncertainty during early design of engineered systems in an Integrated Concurrent Engineering (ICE) environment. This method uses efficient analytic and semi-analytic calculations, is more rigorous than Monte Carlo simulation, and provides comprehensive and (often) best possible bounds on mission-level risk as a function of uncertainty in each parameter. Phase 1 demonstrated the capability to robustly model variability (aleatory uncertainty) and incertitude (epistemic uncertainty) during early design. The new methods are intended to (1) allow rapid, rigorous, and more complete exploration of alternate designs in the mission- and engineeringconstrained 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 PBA capabilities is not currently available to systems engineers and cannot be provided by more traditional probabilistic risk assessment methods.

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