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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. Automating the Application of Deception Detection Heuristics to Unstructured Data

    SBC: STOTTLER HENKE ASSOCIATES, INC            Topic: N10AT029

    We propose to construct a deception detection system which will exploit scaffolding provided by a collection of largely domain-independent deception detection heuristics. These heuristics, integrated through a novel evidential reasoning system, will provide the proposed system, called Skeptic, with a significant advantage over purely inductive methods by allowing it to exploit the adversarial natu ...

    STTR Phase I 2010 Department of DefenseNavy
  2. Mitigation of USV Motions via Wave Sensing and Prediction

    SBC: ADVANCED SCIENTIFIC CONCEPTS, LLC            Topic: N10AT036

    Advanced Scientific Concepts, Inc. (ASC) has teamed with the Department of Ocean Engineering at The University of Rhode Island to devise a sensor suite and computer algorithm to predict ocean waves to aid autonomous boat navigation in heavy weather. The centerpiece of the sensor suite is a Lidar designed by ASC that is adapted to image the ocean at glancing angles. It’s ability to acquire a 3D s ...

    STTR Phase I 2010 Department of DefenseNavy
  3. Complex Event Detection in Video and Communications

    SBC: SOAR TECHNOLOGY, LLC            Topic: N10AT040

    We will demonstrate the feasibility of detecting tactically meaningful complex events in sensor input streams using an efficient pattern matching technology embodied in the Soar cognitive architecture. Our focus in Phase I will be on video streams, such as those that might be produced by unattended ground sensors or unmanned aerial systems. To reduce risk, we propose devoting a portion of our effo ...

    STTR Phase I 2010 Department of DefenseNavy
  4. High Efficiency Gain Media for Eye-Safer 1.55 µm Ultrafast Fiber Amplifiers

    SBC: KAPTEYN-MURNANE LABORATORIES, INC            Topic: N10AT012

    We propose to design a high average power Er:Fiber ultrafast laser system which is pumped at 14xxnm, and at the same time solve other problems related to ultrashort pulses in fiber lasers. The advantage of using 14xxnm pumping is the reduction of the standard quantum defect from 37% to 5%, thus greatly reducing the thermal load on the system, which makes it inherently more efficient. We also inten ...

    STTR Phase I 2010 Department of DefenseNavy
  5. Advanced Real Time Battery Monitoring and Management System

    SBC: TECHNOLOGY SERVICE CORP            Topic: N10AT013

    TSC and Purdue University will demonstrate a lab prototype of software and hardware capable of doing high speed monitoring of a Lithium-Ion cell. This monitoring needs to be specifically designed to predict failures. When a predictive failure is indicated a defensive countermeasure needs to be implemented. Our specific project goals are to: 1) Select a Lithium-Ion battery that consists of multiple ...

    STTR Phase I 2010 Department of DefenseNavy
  6. Development of Surface Reaction Mechanism for C-SiC-SiO2-Rubber Composite Oxidation in Extreme Oxidizing Condition

    SBC: CFD RESEARCH CORPORATION            Topic: N10AT005

    The purpose of this STTR is to develop comprehensive detailed kinetics for oxidation of C-SiC-SiO2-rubber in extreme oxidizing environment. This material is used as a coating on the outer surface of Navy weapon systems. In order to predict the fate of this material under extreme conditions and mitigate the degradation of the coating, a comprehensive oxidation mechanism is required. In Phase I, CFD ...

    STTR Phase I 2010 Department of DefenseNavy
  7. Analysis and Modeling of Foreign Object Damage (FOD) in Ceramic Matrix Composites (CMCs)

    SBC: N&R ENGNERING MGT SUPPORT SVCS            Topic: N10AT010

    The Phase I deliverable will be a physic-based model which represents a CMC gas turbine component concomitantly at the material level and the structural level. This model will be probabilistically analyzed to account for the uncertainties in material properties and the uncertainties in the size and impact velocities of possible foreign objects (FOD). A ceramic material must display sufficient capa ...

    STTR Phase I 2010 Department of DefenseNavy
  8. Development of a Computational Method for Prediction of After-Burning Effect

    SBC: BUSA Engineering Consulting            Topic: N10AT002

    This proposal is being submitted in response to the solicitation topic N10A-T002 (Development of a Computational Method for Prediction of After Burning Effect) by BUSA Engineering Consulting (Dr. Jianghui Chao) in collaboration with University of Florida (PI: Prof. S. Balachandar). The overall objective of the proposed effort is to contribute to national defense and security by advancing the state ...

    STTR Phase I 2010 Department of DefenseNavy
  9. Advanced Materials for the Design of Lightweight JP5/JP8/DS2 Fueled Engines for Unmanned Aerial Vehicles (UAVs)

    SBC: Northwest Uld, Inc.            Topic: N10AT001

    Northwest UAV Propulsion Systems proposes using our purpose built heavy fuel engine designed and built in the USA for small unmanned aerial systems in the tier 2 & 3 class. We will be adding a lightweight ceramic material set combined with FEA (Finite Element Analysis) and heavy fuel atomizer (IRAD Project) to create a lightweight engine for a SUAS or STUAS class UAVs. The Ceramic material set is ...

    STTR Phase I 2010 Department of DefenseNavy
  10. Adaptive Learning for Stall Pre-cursor Identification and General Impending Failure Prediction

    SBC: FRONTIER TECHNOLOGY INC.            Topic: N10AT008

    Frontier Technology, Inc. (FTI) and Northeastern University propose to investigate and develop an innovative approach to predict stall events of aircraft engines prior to occurrence and in sufficient time to allow the FADEC controller to adjust engine variables. The team will utilize vector quantization and neural network techniques to develop accurate models of engine behavior that will be used t ...

    STTR Phase I 2010 Department of DefenseNavy
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