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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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TAIGR's Technical and Cognitive Red Teaming Approach
This slide deck will be presented in a virtual workshop where AI risks and challenges will be discussed with different stakeholders from the energy sector.
Measuring Expert and Novice Performance within Computer Security Incident Response Teams.
Abstract not provided.
Transfemoral Aortic Valve Replacement (TAVR): Is Incorporation of Interventional Radiologists into the Team Beneficial?
No abstract prepared.
Expert protocol teams enhance patient centered cardiac testing and care
No abstract prepared.
Optimal composition of heterogeneous multi-agent teams for coverage problems with performance bound guarantees
Not Available
Photons, Protons, SBRT, Brachytherapy—What Is Leading the Charge for the Management of Prostate Cancer? A Perspective From the GU Editorial Team
No abstract prepared.
Multiple-robot drug delivery strategy through coordinated teams of microswimmers
Untethered robotic microswimmers are very promising to significantly improve various types of minimally invasive surgeries by offering high accuracy at extremely small scales. A prime example is drug delivery, for which a large number of microswimmers is required to deliver sufficient dosages to target sites. For this reason, the controllability of groups of microswimmers is essential. In this paper, we demonstrate simultaneous control of multiple geometrically similar but magnetically different microswimmers using a single global rotating magnetic field. By exploiting the differences in their magnetic properties, we triggered different swimming behaviors from the microswimmers by controlling the frequency and the strength of the global field, for example, one swim and the other does not while exposed to the same control input. Our results show that the balance between the applied magnetic torque and the hydrodynamic torque can be exploited for simultaneous control of two microswimmers to swim in opposite directions, with different velocities, and with similar velocities. This work will serve to establish important concepts for future developments of control systems to manipulate multiple magnetically actuated microswimmers and a step towards using swarms of microswimmers as viable workforces for complex operations.
Building a Diverse and Inclusive HPC Community for Mission-Driven Team Science
The U.S. Department of Energy (DOE) has been a long-standing leader in driving advances in science and technology through advanced computing. However, DOE laboratories are currently facing urgent workforce challenges, particularly in terms of underrepresentation from key communities, including people of color, women, persons with disabilities, and first-generation scholars. This paper introduces the work carried out as part of the Exascale Computing Project (ECP) Broadening Participation Initiative, which aims to address workforce challenges through a lens that considers the distinct needs and culture of high-performance computing (HPC). The work focuses on three main efforts: hosting Intro to HPC Bootcamps, expanding the Sustainable Research Pathways (SRP) internship and workforce development program, and establishing an HPC Workforce Development and Retention Action Group. Finally, the paper also highlights various workforce efforts throughout the computational science community and explores opportunities for future work aimed at broadening participation in HPC.
Cooperative Routing for an Air–Ground Vehicle Team—Exact Algorithm, Transformation Method, and Heuristics
This paper considers a cooperative vehicle routing problem for an intelligence, surveillance, and reconnaissance mission in the presence of communication constraints between the vehicles. The proposed framework uses a ground vehicle and an unmanned aerial vehicle (UAV) that travel cooperatively and visit a set of targets while satisfying the communication constraints. The problem is formulated as a mixed-integer linear program, and a branch-and-cut algorithm is developed to solve the problem to optimality. Furthermore, a transformation method and a heuristic are also developed for the problem. The effectiveness of all the algorithms is corroborated through extensive computational experiments on several randomly generated instances. Furthermore, this paper is motivated by an intelligence, surveillance, and reconnaissance mission involving a single unmanned aerial vehicle (UAV) and a ground vehicle, where the vehicles must coordinate their activity in the presence of communication constraints. The combination of a small UAV and a ground vehicle is an ideal platform for such missions, since small UAVs can fly at low altitudes and can avoid obstacles or threats that would be problematic for the ground vehicle alone. This paper addresses the coordinated routing problem involving these two vehicles and presents an algorithm to obtain an optimal solution for this problem, fast heuristics to obtain good feasible solutions, and also a transformation method to transform any instance of this cooperative vehicle routing problem to an instance of the one-in-a-set traveling salesman problem.
AEGIS autonomous targeting for ChemCam on Mars Science Laboratory: Deployment and results of initial science team use
Autonomous target selection and pointing refinement steer a remote geochemical LIBS instrument on Mars, increasing data return.
TEAM-TDM: A Tool for Evaluating an Array of Machine Learning Travel Demand Models [SWR-18-64]
This is a package for easy application of multiple machine learning models to a single problem, and comparison via various metrics. For a pretty detailed description of the models that are available in the tool, and a quite detailed description of the metrics that it pumps out, see the paper, "A Machine Learning Decision Support Tool for Travel Demand Modeling". Accessible at: https://github.com/NREL/TEAM-TDM/blob/master/paper/team_tdm.pdf
SaS4D Home Team Ul
This software allows for a lidar-generated point cloud to be converted to a water-tight geometry, and finally an MCNP radiation transport input deck automatically. This includes the automatic registration of detectors and placement of pre-generated radiation transport models of these detectors in the scene.
Simulation of Workflow and Threat Characteristics for Cyber Security Incident Response Teams.
Abstract not provided.