SBIR/STTR Research Award

Modeling and Empiricizing the Decomposition of HAN-Based Monopropellant and Associated Catalysts, Phase II

Award identifier 002b4af0aa696e6c6d54519101c7b92c82acee29da5f99165b651ff85fe43f3bAwarding agency Department of Defense

Award amount

$849,889

Program and phase

SBIR · Phase II

Award year

2012

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
Not reported
Recipient company
ULTRAMET
Proposal award date
2012-07-30
Contract end date
2016-10-26
UEI
N8ZRMWX85NZ6
Solicitation number
2009.3
Topic code
AF093-189

Research abstract

ABSTRACT: The decomposition of hydroxylammonium nitrate (HAN)-based monopropellants is a complex process that involves scores of unimolecular and bimolecular reaction steps and dozens of species. Chemical reactions between these species and the catalyst, as well as thermal effects, can all have a profound impact on the life of the catalyst. In Phase I, Ultramet performed rigorous heat, mass, and momentum balances to develop a model that describes the transient temperature and chemical composition profiles that result when AF-M315E monopropellant is decomposed in a packed bed of either catalytic or non-catalytic material. The model predictions, which agree well with empirical data, were used to predict the iridium recession rate throughout the bed. In Phase II, Ultramet will use ab initio data to better model the decomposition pathways of hydroxyethylhydrazinium nitrate (HEHN) (as reliable data already exist for HAN) via finite rate kinetics, the overall model for the ignition system will be refined, and key pieces of empirical data will be obtained for anchoring the model and verifying its predictions. As was the case in the Phase I model, the effects of chamber pressure, bed loading, propellant composition, bed preheat temperature, and the nature of the bed packing (catalytic or non-catalytic) will all be taken into account. Each of these variables will be investigated empirically to isolate their effect and to anchor that specific element of the model. The result will be a model that can predict engine performance over an extremely wide parameter space. Equally as important, it will also predict the thermochemical environment at any location within the bed as a function of time, thus providing key information on the various environments that the ignition system materials, the bed plate, and the chamber itself will need to endure. BENEFIT: Being able to predict the temperature and chemical composition of HAN-based monopropellant decomposition products at any location in a thruster will enable catalysts, combustion chambers, and bed plates to all be designed more rigorously and rely less on trial-and-error empiricism. This will greatly accelerate the implementation of HAN-based thrusters in both military and commercial applications. Military applications include reaction control systems for launch vehicles, attitude control systems and main engines for satellites, and divert and attitude control systems for missiles and missile defense systems. Commercial applications include similar launch vehicle and satellite applications, as well as main engines and attitude control systems for interplanetary spacecraft and sample return missions.

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

380 SBIR/STTR records share this UEI (1983–2025). Reported award amounts total $105,154,309. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Energy, National Science Foundation, Department of Transportation, Department of Health and Human Services

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.