OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Hypersonics; Sustainment; Trusted AI and Autonomy
The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.
OBJECTIVE: Develop a general purpose fragment mass estimation library that complements high-speed 3D stereoscopic data for use in high-fidelity multiphysics hydrocodes.
DESCRIPTION: High Speed Video (HSV) systems (hardware and software) have evolved significantly over the past 10 years. One relatively new area of study and application involves Three Dimensional (3D) stereoscopic systems based on HSV hardware, which are then utilized to identify fragments in-flight emanating from a warhead. These 3D stereoscopic systems have been evaluated by the DoD for use in fragment characterization tests, usually referred to as “arena tests” with varying degrees of success depending on the metric of interest. Fragment position, speed, and vector information offers the greatest confidence; however, fragment mass remains an elusive parameter in such assessments. This parameter is a key measure in the U.S. Navy’s and DoD’s vision of leveraging advanced diagnostics, and the data generated from these, in the calibration of High Fidelity Multiphysics hydrocodes currently in use.
Given these challenges, there is a need for innovative engineering solutions that allows the U.S. Navy and the DoD to bridge the last data gap related to 3D stereoscopic HSV systems by creating a general purpose fragment mass estimation library for use in high-fidelity codes.
Solutions (e.g., General Purpose Mass Estimation Library) must be able to leverage the 3D stereoscopic raw data independent of intrinsic hardware used. Additionally, the solution must generate verifiable and validated fragment mass data from said 3D stereoscopic raw data. The solution must work for all possible types, namely natural (e.g., random shapes), pre-scored and preformed fragments, as well as multiple materials such as—but not limited to—steel, aluminum, titanium, or tungsten compositions. The solution must be able to create accurate mass assessment for fragments in the range of 10 to 2500 grains, traveling at speeds ranging from 500–9000 ft/s (152.4–2743.2 m/s). Mass estimate generated from the solution must be calibrated to have uncertainties less than +/- 4% for fragments at 2500 grains, and less than +/- 20% for fragments at 10 grain levels (e.g., Mass Estimate threshold) from verifiable and validated data source(s). Based on this, the mass tolerance threshold would follow a linear relationship (e.g., Mass Tolerance Threshold [fragment mass, in grains] = 0.0394 * fragment mass + 1.604, Mass Tolerance Threshold has units of grains as well).
Verifiable and validated data sources for calibrating the proposed solution may be, but are not limited to, experimental or other empirical datasets, including any other representative Modeling and Simulation (M&S) techniques. Calibration must be performed at laboratory scale to include full mass scale. The solution may leverage precomputed data/regressions and/or any Machine Learning (ML) techniques. If ML techniques are utilized, open source tools/methods must be leveraged to the greatest extent possible. As part of the solution, a verification and validation package on the general purpose mass estimation library must be created along with any other required SBIR reporting, allowing full transparency to Subject Matter Experts (SME) in the U.S. Navy and DoD.
The solution must be able to generate mass estimates within seconds on a per fragment basis and within minutes for an entire populated 3D stereoscopic raw data set potentially consisting of thousands of fragments. The solution must have an appropriate and well-documented interface or Application Programming Interface (API) if relevant, so that other software tools may be able to leverage it effectively. The solution must be compatible with use inside modern Operating Systems (OS) such as Microsoft Windows and Linux. The solution must provide clear text data output consisting of estimated mass, as well as any ancillary graphical depiction of the post-processing results including statistical uncertainties in output values.
PHASE I: Identify and evaluate potential technologies/methodologies applicable for the solution. The feasibility study may include limited/initial lab scale test or M&S efforts that help provide grounding to a proposal/study. A preliminary design of the general purpose library and methodology will be performed that includes identification of current/future resources in the form of existing software packages and/or empirical or M&S datasets. Create (1) a preliminary engineering development plan that includes an evaluation of potential numerical/ML methodologies, calibration plans, and testing program needed and (2) a preliminary post-processing and analysis plan for the general purpose library that includes the proposed analysis/computational logic flow needed in order to meet the mass estimate uncertainties across the range of parameters indicated. The Phase I effort will include prototype plans to be developed under Phase II.
PHASE II: Develop a working prototype. Demonstrate the prototype, including applicable testing of any post-processing features, and with laboratory scenarios/data including full scale scenarios, with comparison of the output data and associated uncertainties. Proposed solution must demonstrate capability for expansion in light of new test or M&S data enhancing the verification and validation package. Integrate the solution into a larger software package as directed by the Government or provide technical support in the event that the Government integrates it. Deliver source code, binaries, libraries, trained ML, verification and validation package, design specifications, configuration and user’s manual for Government evaluation. Provide technical support for Government use of prototype libraries within a larger Community of Interest of Subject Matter Experts (SMEs).
PHASE III DUAL USE APPLICATIONS: Transition the updated solution to the U.S. Navy. Receive feedback from users and perform/release updates addressing feature requests and bug fixes. Enhance the text and visual capabilities per user feedback along with the verification and validation package expanding into further fragment ranges. Provide continuing technical support for Government use of libraries within a larger Community of Interest of SMEs. Update the technical report and user’s manuals as required.
Commercial applications involve DoD contractors supporting the Tri-Service community, the Department of Homeland Security, the U.S. Coast Guard, the FBI, and other Government Agencies interested in fragment/debris flyout. Additional interest in this technology includes, but is not limited to, the motion picture industry, chemical manufacturing, the oil and gas industry or any other organization that utilizes high-pressure vessels, and is concerned about accurate characterization of flying debris or fragments from industrial accidents.
- Lines, J. A., Tillett, R. D., Ross, L. G., Chan, D., Hockaday, S., & McFarlane, N. J. B. (2001). An automatic image-based system for estimating the mass of free-swimming fish. Computers and Electronics in Agriculture, 31(2), 151-168. https://doi.org/10.1016/S0168-1699(00)00181-2
- Gaich, A., Poetsch, M., & Schubert, W. (2006, June). Acquisition and assessment of geometric rock mass features by true 3D images. In ARMA US Rock Mechanics/Geomechanics Symposium (pp. ARMA-06). ARMA. https://onepetro.org/ARMAUSRMS/proceedings-abstract/ARMA06/All-ARMA06/115985
- Nicholson, J. I. (2022). Deep learning techniques to estimate 3D position in stereoscopic imagery. Air Force Institute of Technology. Wright-Patterson AFB, OH. Accession Number: AD1166906. DoD Dist. A, Approved for Public Release. https://apps.dtic.mil/sti/pdfs/AD1166906.pdf
KEYWORDS: munitions; warhead characterization; fragments; mass estimation, hydrocodes; Machine Learning