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The Composable Object (COB) Knowledge Representation: Enabling Advanced Collaborative Engineering Environments (CEEs)

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  • Georgia Tech - Atlanta, Georgia
  • NASA Goddard Space Flight Center - Greenbelt, Maryland (sponsor)
  • NASA JPL - Pasadena, California
  • Lockheed Martin - Fairfax, Virginia


The teams of engineers and scientists who develop and deploy NASA's complex space missions need tools that can provide clear and intuitive visualization of the parametric relationships and constraints among the diverse models used in the analysis, simulation, and visualization of physical assemblies, firmware, software, device components, and human factors. The capability to generate these diverse models efficiently, to capture their relationships in a standardized, intelligent, computer-sensible form, and to provide collaborative, GUI-based access to these relationships is absent in the current state of the art.

The work proposed herein will develop a methodology and software tools that implement a broadly applicable formalism called composable objects (COBs). Next-generation COBs will enable a user to identify, represent, visualize, and navigate the relationships among the diverse types of models used to analyze and simulate space mission systems. (The COB formalism is currently a proposed extension to the OMG's Unified Modeling Language [UML], and is expected to be one component of the new "Systems Modeling Language" UML profile [SysML].) This methodology and toolset will support collaborative analysis and decision-making by enabling the intelligent linkage and regeneration of model variants and parameters. Such models will support an entire spectrum of "what-if" scenarios used in a series of mission analyses, the execution and observation of these simulations in a networked collaboration space, and the capture of all models, constraints, and results in a distributed repository and knowledgebase of mission analysis and modeling information.

Research products will include: (1) an intuitive visualization language ("constraint schematics") for rigorously specifying non-causal and algorithmic relationships between physical assembly parameters and corresponding idealized analysis model parameters; (2) a graphical tool for creating, editing, and navigating constraint schematics; (3) a constraint graph manager which interconnects diverse models based on their COB lexical specification; and (4) integration of these capabilities within a standards-based, distributed interaction space and repository framework. This framework will enable next-generation system lifecycle management (SLiM) including model sharing and interaction with existing COTS tools and in-house codes.

This approach will provide capabilities (a) during system development: to capture comprehensive analysis and simulation scenarios, the associated models and context, and related documentation, and (b) during operations: to drive real-time displays of system parameters and their relationships to analysis and simulation models.


R. Peak, S. Friedenthal, A. Moore, R. Burkhart, S. Waterbury, M. Bajaj, I. Kim (2005) Experiences Using SysML Parametrics to Represent Constrained Object-based Analysis Templates . 2005 NASA-ESA Workshop on Product Data Exchange (PDE), Atlanta.

R. Peak (2005) GIT SysML Parametrics Work . Update to OMG SE DSIG , Atlanta.

D. Tamburini, R. Peak, C. Paredis, et al. (Oct. 31, 2005) Composable Objects (COB) Requirements & Objectives v1.0 . Technical Report, Georgia Tech, Atlanta.

RS Peak, RM Burkhart, SA Friedenthal, MW Wilson, M Bajaj, I Kim (2007) Simulation-Based Design Using SysML—Part 1: A Parametrics Primer. INCOSE Intl. Symposium, San Diego.

RS Peak, RM Burkhart, SA Friedenthal, MW Wilson, M Bajaj, I Kim (2007) Simulation-Based Design Using SysML—Part 2: Celebrating Diversity by Example. INCOSE Intl. Symposium, San Diego.

Bajaj M, Peak RS, Paredis CJJ (2007) Knowledge Composition for Efficient Analysis Problem Formulation - Part 1: Motivation and Requirements. Paper DETC2007-35049, Proc ASME CIE Intl Conf, Las Vegas.

Bajaj M, Peak RS, Paredis CJJ (2007) Knowledge Composition for Efficient Analysis Problem Formulation - Part 2: Approach and Analysis Meta-Model. Paper DETC2007-35050, Proc ASME CIE Intl Conf, Las Vegas.