NAFEMS Webinar Series
Abstract Modeling Enables Aerospace Corporation Project to Reap Benefits of Collaborative Engineering Process
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(Note: This broadcast is part of the NAFEMS vendor series that allows various solutions providers the opportunity to deliver technical information to the NAFEMS community. NAFEMS does not endorse any vendor, but tries to provide an unbiased view of the marketplace.)
About one-quarter of all space-borne sensors being developed for NASA and Security Space applications are overrunning their budget and schedule allocations by factors of 2X or more. A substantial improvement in the cycle time of development for these systems is needed while retaining adequate system performance levels with high reliability. Collaborative engineering practices based on new abstract modeling technology promise significant reductions in project cost and delivery time.
This presentation describes how a multi-disciplinary design team from The Aerospace Corporation utilized a unified performance engineering workspace powered by abstract modeling to support a collaborative engineering process for the design of space optical systems while still leveraging their off-the-shelf CAD and CAE (simulation) tools for evaluating structural, thermal and optical performance. The author will present results of use of this approach on a current flight hardware program, with an emphasis on the significant productivity improvements that were realized. Comparison of simulation results to empirical test results will also be discussed.
What Is Abstract Modeling
An abstract model is a functional model containing all the engineering data (performance requirements/metrics, material properties, boundary conditions, and loads) for a part or assembly that is independent of the particular design geometry. With an abstract model, engineering analysis data is reapplied to the model when the geometry changes, and you easily re-run multiple “what if” conceptual analyses. Teams can document engineering “best practices” workflows abstractly step-by-step, and capture that domain knowledge in reusable and modifiable templates. Abstract modeling enables discipline engineers to assess the effects of their design modifications on the other discipline aspects of the design without having to be able to run the underlying codes of those disciplines themselves. Multiple versions of the CAD geometry become the inputs that drive the abstract model and the resulting performance simulation models are automatically built, analyzed and results generated with little additional work by the simulation domain experts. Entire project teams are able to quickly view the system level engineering results versus the design requirements in an easy-to-comprehend project dashboard. Work in process data for an entire project cutting across multiple organizational disciplines is automatically captured via the abstract model enabling model re-use as well as results traceability throughout the life of the project.
Design of Space Borne Sensors - Abstract Modeling In Use
An Aerospace Corporation project engineering team comprised of optical, mechanical, structural, and thermal engineers utilized recent advances in abstract modeling to augment and accelerate the evaluation of thermally-induced structural deformations on the optical performance of a flight sensor.
By utilizing an abstract model approach, the team had access to CAD and CAE information across multiple engineering disciplines and tools without the need for each simulation discipline to have direct knowledge of how to run all the underlying existing CAD and CAE packages. The domain experts utilized an abstract model to evaluate multi-physics interactions in a very complex opto-mechanical assembly in a near-real time manner that would be impossible with traditional tools and approaches. The abstract model, along with the single engineering workspace, provided the team with a work in progress simulation environment that is independent of the underlying CAD/CAE tools used in the design process. Because the abstract model tracks requirements and results independent of geometry, the team had access to a dashboard view of performance data/results for each design iteration. Abstract modeling technology gave the whole team including simulation domain experts, design engineers, program management, and financial representatives the ability to complete “real time” design reviews. These design reviews were performed with the full quantitative and visualization power of the robust multi-disciplinary design and simulation data rather than the fragmented and thin results abstractions typically captured via PowerPoint snapshots, Excel spreadsheets and Word/HTML/PDF reports.
Specific results of the project will be shared during webinar and a detailed white paper will be made available to attendees.
Welcome & Introduction
Matthew Ladzinski, NAFEMS North America
Multi-Disciplinary Product Development
David A. Thomas, The Aerospace Corporation
Q & A Session
David A. Thomas, The Aerospace Corporation
Malcolm Panthaki, Comet Solutions
Event Type: Webinar
Location: Online USA
Date: October 24, 2008
David A. Thomas
PhD in Optical Sciences from the University of Arizona.
28 years of experience, primarily with the optical engineering of space-borne electro-optical sensors for NASA and national defense applications
Current position / tasks
Senior optical project engineer for a space-borne reconnaisance sensor program
BS in Civil Engineering from the Indian Institute of Technology in India, and MS in Structural Engineering and Computer Graphics from Cornell University.
Mr. Panthaki has been at the cutting edge of CAE software development since 1987.
He started his career as a CAE software engineer at an engineering consulting firm
He moved to ABAQUS Inc., where he led the effort to develop the interactive environment, ABAQUS/CAE."
Mr. Panthaki left ABAQUS in 1994 to build a technology framework that could handle the complexity of CAE data, processes and results in one common data model.
Mr. Panthaki provided software consulting services for CAE projects including Sandia National Labs and NASA.
He formed Comet Solutions in 2001.