NASA SBIR 2006 Phase I Solicitation
X1 Systems Analysis and Integration
Definition of large, complex systems requires an understanding of system performance, cost and risk during each
of the system's lifecycle phases (i.e., design, development, testing, deployment and operations). Accurate
representations of the system's: (1) functional and physical interfaces are required to facilitate the analysis, design,
and integration of the system and its elements; (2) costs, operational plans, and risks are required to balance the
programmatic aspects of the system; and (3) performance projections and margins are required to understand
payload options. Achieving an understanding of these complex interactions requires the development, analysis and
refinement of models and simulations (M&S) across the lifecycle of the system in order to support a variety of
analysis activities. Models currently being developed for Exploration Systems and Space Operations are
categorized as subjective, constructive, operator-in-the-loop, hardware- and software-in-the-loop, and in-service
operations. These models and simulations are used to address requirements generation, design definition,
verification of requirements, testing and sustaining engineering. SBIR Topic X1 is aimed at addressing pressing
issues that are still lingering in the area of analysis and M&S. Data required to perform analysis and execute
models/simulations must be consistent, valid and cohesive across the analyses. Approaches to dealing with
analysis data management and manipulation through the lifecycle are sought. The integration of cost and risk
models early in the lifecycle of a system's analyses must be achieved to ensure that programmatic factors drive our
plans. Modeling and simulation is key to achieving NASA's vision by providing the data required for early key
decision-making.
Subtopics
X1.01 Full Data Coherency Systems for Engineering Systems Modeling and Simulation
Lead Center: MSFC
Participating Center(s): ARC, GRC, JPL, LaRC
In addressing the accuracy of analysis results, which are used to make program/project decisions, we typically
assess the data, the models/simulations, and the analysts. This subtopic area will address the first of these
concerns. Verification and validation approaches typically address the validity of the data used to perform the
analysis. However, they do not address the issue associated with data cohesiveness and consistency. An issue in
the development of integrated modeling/simulation for complex engineering systems arises when information is fed
to the models with inconsistent coherency, where "coherency" is defined as appropriate versions,
semantics/syntax, abstraction/resolution, and sequence. When, for example, serial/parallel simulations are run with
revised input data from one source, other sources may or may not need to be held constant; similarly, input data of
varying heritage, semantics, resolution, etc., may result in unexpected and inaccurate simulations. Proposals are
sought for systems that manage full data coherency (not just version or sequence control) in modeling and
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