NASA SBIR 2006 Solicitation


SUBTOPIC TITLE:Aircraft Systems Analysis, Design and Optimization
PROPOSAL TITLE:Cumulative Metamodeling with Uncertainty Estimation: a New Approach to Optimization of Highly Integrated Flight Vehicles

SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
Nielsen Engineering & Research, Inc.
605 Ellis Street, Suite 200
Mountain View, CA 94043-2241
(650) 968-9457

PRINCIPAL INVESTIGATOR/PROJECT MANAGER (Name, E-mail, Mail Address, City/State/Zip, Phone)
Patrick H. Reisenthel
605 Ellis Street, Suite 200
Mountain View, CA  94043-2241
(650) 968-9457

TECHNICAL ABSTRACT ( Limit 2000 characters, approximately 200 words)
Future adaptive, smart air vehicles will continually tune themselves using sophisticated on-board health management and on-the-fly optimization of performance parameters. To support these dynamic, complex/nonlinear, and multidisciplinary optimization tasks requires novel methodologies. These new methodologies must be capable of assimilating data from disparate (heterogeneous) sources in a potentially high-dimensional parameter space, yet provide robust and updatable predictions. Recent progress in cumulative metamodel technology suggests new optimization methodologies capable of combining a priori mathematical models, numerical predictions, and noisy experimental data. The resulting representations can be constructed on-the-fly and are cumulatively enriched as more data become available. Nielsen Engineering & Research (NEAR) proposes to investigate the use of Cumulative Global Metamodels (CGM) in novel optimization techniques for conceptual design of highly integrated flight vehicle and air space concepts. The Phase I will investigate the feasibility of an orders-of-magnitude acceleration in nonlinear multidimensional design by combining existing search techniques with adaptive CGMs. A special emphasis of the work will be to capitalize on NEAR's CGM uncertainty estimation capabilities to monitor the quality of the metamodel and provide confidence estimates which can be used to guide optimization in a rational and systematic way.

POTENTIAL NASA COMMERCIAL APPLICATIONS ( Limit 1500 characters, approximately 150 words)
NEAR's CGM module for formulating and communicating metamodel information, including the visualization of uncertainty in multiple dimensions, will support decision making in complex multidisciplinary environments. The proposed CGM technology is innovative and has the potential to accelerate future design methods, particularly when the number of design variable is large. This reduction in time and cost will result in the designer's ability to handle larger problems or increase the scope of parametric studies. This technology will help NASA's mission by reducing risk and incorporating high-fidelity analyses early in conceptual design of highly-integrated flight and space vehicles.

POTENTIAL NON-NASA COMMERCIAL APPLICATIONS ( Limit 1500 characters, approximately 150 words)
In the aerospace field, the uncertainty-enhanced CGM technology will benefit reusable launch vehicles, UAVs, commercial aircraft, military aircraft, missiles and armaments. The commercial benefits of developing the CGM technology reach far beyond the defense and aerospace sectors, however. Numerous technical activities in the automotive, chemical, and pharmaceutical industries stand to benefit from the proposed innovation. Banks, the insurance industry, and the Department of Homeland Security are also potential customers for this technology.

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.

Aircraft Engines
Control Instrumentation
Database Development and Interfacing
Launch and Flight Vehicle
On-Board Computing and Data Management
Sensor Webs/Distributed Sensors
Simulation Modeling Environment
Software Tools for Distributed Analysis and Simulation
Structural Modeling and Tools

Form Printed on 09-08-06 18:19