SBIR/STTR Research Award

Development of Multi-Frequency Multi-Scale Radiation Transport Modeling

Award identifier 2b726a399197dc5cbabd6e748fa7adc3ca55fab0d254dd05db962217fbd2b3c6Awarding agency Department of Defense · Air Force

Award amount

$750,000

Program and phase

STTR · Phase II

Award year

2010

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
Prism Computational Sciences, Inc.
Proposal award date
2010-01-12
Contract end date
2012-01-12
UEI
XYGNAVLZ1KW8
Solicitation number
2008.A
Topic code
AF08-T020

Research abstract

The objective of this proposal is to develop advanced radiation transport modeling techniques that accurately and efficiently treat transport in media having widely varying optical properties; in particular, hot gases and plasmas with optical depths ranging from the optically thin to the optically thick regimes. We will develop a hybrid diffusion-Monte Carlo (HDMC) model that efficiently transports multi-frequency radiation on multi-dimensional grids. During Phase I, we have successfully developed algorithms for the HDMC package, and demonstrated their accuracy and efficiency on simple 1-D grids. We have also investigated variance reduction, escape probability, and domain decomposition techniques for improving the efficiency and accuracy of the HDMC modeling. Algorithms developed during Phase I will be extended to support simulations on multi-dimensional grids during Phase II. Advanced techniques for treating: the interfacing between the diffusion and Monte Carlo models on non-orthogonal grids; domain decomposition for large-scale 3-D grids; and escape probability-based line transport will be developed and implemented. The models will be benchmarked against known solutions, and tested for efficiency and scalability to many-processor systems. Successful completion of this work will result in an efficient multi-scale multi-dimensional radiation transport package that accurately treats radiation flow in materials with realistic frequency-dependent radiative properties. BENEFIT: This project will develop state-of-the-art tools that numerically simulate the radiative properties of hot gases and plasmas. This capability is of substantial interest to a number of government laboratory research programs, including those supported by DOD and DOE. In addition, this project will lead to the development of tools that accurately simulate plasma spectral and radiative properties. Such tools are of significant value in developing commercial systems related to laser-induced breakdown spectroscopy (LIBS) and plasma radiation sources, such as those used in EUV lithography and medical research and technology.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

9 SBIR/STTR records share this UEI (2005–2013). Reported award amounts total $4,499,992. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, Department of Energy, National Science Foundation

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.