The Department of Defense, specifically the Navy, is seeking proposals for the Small Business Innovation Research (SBIR) topic titled "Environmental Parameters and Transmission Loss Modeling Framework." The objective is to develop a modular software framework that integrates environmental data ingestion, geospatial machine learning, sediment physics models, and acoustic simulations to assess transmission and bottom loss, particularly in support of anti-submarine warfare (ASW). This initiative is critical for enhancing the Navy's capabilities in producing and evaluating acoustic information databases, addressing both forward and inverse problems in acoustic modeling. Interested parties must submit their proposals by May 21, 2025, with the opportunity to work on classified aspects of the project in later phases. For more details, visit the solicitation link at https://www.sbir.gov/topics/11983.

OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Advanced Computing and Software 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: Establish a modular software framework encompassing environmental data ingestion, geospatial machine learning, sediment physics models, acoustic simulations, and evaluation metrics for assessing transmission and/or bottom loss in support of anti-submarine warfare (ASW). DESCRIPTION: To evaluate current and future methods of producing databases of acoustic information, in particular bottom loss, the Navy needs a flexible framework where different datasets, machine learning algorithms, and/or simulations can be “plugged-in” to evaluate their predictive skill. The Naval Research Laboratory (NRL) has produced a codebase, the Global Predictive Seabed Model (GPSM), [Ref 1], that utilizes a subset of methods to produce and evaluate bottom loss databases utilizing environmental observations. However, this framework as it currently exists is strict in its formulation, uses a non-standardized interface, and is less modular than necessary to allow other datasets, methods, and/or models to be easily utilized. Further, the GPSM codebase currently solves the acoustic “forward problem” (environmental observations -- simulation -- acoustic observations) and lacks the flexibility to solve the “inverse problem” (acoustic observations -- simulation -- environmental observations). This gap in capability allows for opportunity to incorporate innovative inversion methodologies, such as trans-dimensional geoacoustic inversion [Ref 2] in the codebase. This innovation will allow acoustic data holdings, such as The Naval Oceanographic Office-collected transmission loss data, to be incorporated into environmental models within a single framework. The formation of a new framework with a standardized interface is necessary for the development of novel methods and collaboration within the wider scientific and Naval community. The transition of the forward-solver in the current GPSM codebase and the new inversion methodology into this new framework will set the basis of a new system for other researchers to provide data and evaluate methods on an even playing field. Specifically, this SBIR topic requires: 1) a modularized framework in which the updated GPSM codebase fits; 2) a standardized interface that other researchers can use to formulate code to fit into the new framework; 3) a framework flexible enough to solve both the “forward” and “inverse” problems; and 4) proper documentation and code examples so that future users can utilize the new framework to evaluate past and future methods and datasets. Note: A Controlled Unclassified Information (CUI) version of the GPSM codebase (able to solve the forward problem) will be provided for use during Phase I. Work produced in Phase II may become classified. Note: The prospective contractor(s) must be U.S. owned and operated with no foreign influence as defined by 32 U.S.C. § 2004.20 et seq., National Industrial Security Program Executive Agent and Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Counterintelligence and Security Agency (DCSA) formerly Defense Security Service (DSS). The selected contractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances. This will allow contractor personnel to perform on advanced phases of this project as set forth by DCSA and ONR in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement. The selected company will be required to safeguard classified material during the advanced phases of this contract IAW the National Industrial Security Program Operating Manual (NISPOM), which can be found at Title 32, Part 2004.20 of the Code of Federal Regulations. PHASE I: Develop a software framework with a standardized interface for the quantitative assessment of global acoustic databases that includes the ability to start with sparse environmental observations and produce transmission loss at various frequencies and evaluate their fit to observed values. Additionally, any innovation plan to solve the inverse problem must fit within this standardized framework. Establish data formats for incoming datasets and dataset outputs to make the framework tractable. Design an interface and glossary to work within the framework and be flexible enough to not dissuade potential future users and researchers. Develop a Phase II plan for 1) incorporating innovative inversion methodologies into the standardized software framework, and 2) implementing, testing, and evaluating the software framework. PHASE II: Implement the software framework developed in Phase I for the current GPSM codebase. Develop an inverse solution to the acoustic problem, such as trans-dimensional geoacoustic inversion, that fits within the software framework. This updated codebase will serve as the basis for future development and will be the first test of the framework. Evaluate the framework (e.g., ability of others to develop methods to “plug into” the framework). Test and evaluate both inverse and forward methods. Assess documentation to determine usability and flexibility of the framework. Tests between at least two competing data sets and/or geoacoustic models in specific regions of interest, over a wide range of frequencies. This will not only demonstrate the value of the system(s) produced as a part of this SBIR, but also serve to recommend one or more data sets or numerical simulations to the Navy. It is probable that the work under this effort will be classified under Phase II (see Description section for details). PHASE III DUAL USE APPLICATIONS: Incorporate a wide variety of Navy-standard and publicly available datasets into the new framework and determine their usability within the framework. These datasets include but are not limited to: acoustic transmission loss, backscatter, and geotechnical data like multi-beam and sub-bottom profiler data. The final test of the framework will be an end-to-end evaluation of multiple methods and datasets to evaluate and recommend a new methodology to produce a Low Frequency Bottom Loss (LFBL) to NAVO NP5. The framework developed here will continue to be used to evaluate methods and datasets beyond this SBIR to improve prediction capabilities into the future. Although the specific GPSM codebase would not be available for public use, the software framework and standardized interface developed in Phase I can be applied by the performers to other applications in the private and academic sectors. REFERENCES: 1. Graw, Jordan H.; Wood, Warren T. and Phrampus. Benjamin J. "Predicting marine in situ heat flow using a geospatial machine learning conformal prediction." Geochemistry, Geophysics, Geosystems 24(6), e2023GC010913, 2023. https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2023GC010913 2. Dettmer, Jan; Dosso, Stan E. and Holland, Charles W. "Trans-dimensional geoacoustic inversion." The Journal of the Acoustical Society of America 128(6). 2010, pp. 3393-3405. https://www.researchgate.net/publication/49740570_Trans-dimensional_geoacoustic_inversion 3. Harvey, David W.; Lowrie, Allen and Filipczyk, R.D. “The generation of N-layered geoacoustic descriptions of the sub bottom using NAVOCEANO-collected environmental data.” Oceans ’02 MTS/IEE, vol. 1, pp. 358-362. https://ieeexplore.ieee.org/document/1193298 4. Ruppel, Timothy H. "Generating acoustic provinces for the U.S. Navy's Low frequency bottom loss database using geographic information systems." OCEANS 2009, pp. 1-4. https://apps.dtic.mil/sti/tr/pdf/ADA527359.pdf KEYWORDS: Sonar; Submarine; Sensor; Bottom loss; Environment; Inverse modeling; Forward modeling; Geology; Sediment

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