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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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There is a lack of state-of-the-art quantum computing simulation software that scales on heterogeneous systems like Titan. Tensor Network Quantum Virtual Machine (TNQVM) provides a quantum simulator that leverages a distributed network of GPUs to simulate quantum circuits in a manner that leverages recent results from tensor network theory.
This 2-minute animation shows a virtual walk through the large caverns of the Long-Baseline Neutrino Facility, which will house the Deep Underground Neutrino Experiment. To create the caverns for the huge DUNE particle detectors, construction crews will excavate more than 800,000 tons of rock a mile underground at the Sanford Underground Research Facility in South Dakota. Scientists and dignitaries broke ground for this project on July 21, 2017. When construction is complete, DUNE scientists will send an intense neutrino beam through 1,300 kilometers of rock from the Department of Energy’s Fermilab to the DUNE particle detectors to understand the role that neutrinos – the most abundant matter particles in the universe – play in our cosmos. About 1,000 scientists from more than 160 institutions in 30 countries work on the Deep Underground Neutrino Experiment.
A building thermal model is an essential component for achieving optimal control of a building’s heating, ventilation, and air conditioning (HVAC). A self-learning grey-box model has been developed by implementing data-driven techniques and utilizing limited available information about the building. In previous research, detailed foreknown knowledge/information, e.g. physical and thermal properties of building materials, as well as sufficient number of observation points, e.g. indoor temperature sensors in different zones, are available for making the decision of model structure and parameters searching range easier. The availability of measured data and a narrowed searching range of model parameters, e.g. resistance and capacity for each wall, made the adopted algorithms quickly achieve near optimal values, which closely approximate the actual heat transfer of a building. Meanwhile, the details of pre-processing of the key inputs were seldom explained. Compared to the previous research, in this study, the available information is assumed to be limited which can fill the requirement for large scale virtual storage control of real residential community in near future, where it may be impractically or over time-consuming to acquire the detailed information for each single house. The developed model is validated by comparing the results to measured data in a recently-built home typical of the southeastern United States.
Arrays of position-sensitive virtual Frisch-grid CdZnTe (CZT) detectors with enhanced energy resolution have been proposed for spectroscopy and imaging of gamma-ray sources in different applications. The flexibility of the array design, which can employ CZT crystals with thicknesses up to several centimeters in the direction of electron drift, allows for integration into different kinds of field-portable instruments. These can include small hand-held devices, compact gamma cameras and large field-of-view imaging systems. In this work, we present results for a small linear array of such detectors optimized for the low-energy region, 50-400 keV gamma-rays, which is principally intended for incorporation into hand-held instruments. There are many potential application areas for such instruments, including uranium enrichment measurements, storage monitoring, dosimetry and other safeguards-related tasks that can benefit from compactness and isotope-identification capability. The array described here provides a relatively large area with a minimum number of readout channels, which potentially allows the developers to avoid using an ASIC-based electronic readout by substituting it with hybrid preamplifiers followed by digitizers. The array prototype consists of six (5x5.7x25 mm3) CZT detectors positioned in a line facing the source to achieve a maximum exposure area (~10 cm2). Each detector is furnished with 5 mm-wide charge-sensing pads placed near the anode. The pad signals are converted into X-Y coordinates for each interaction event, which are combined with the cathode signals (for determining the Z coordinates) to give 3D positional information for all interaction points. This information is used to correct the response non-uniformity caused by material inhomogeneity, which therefore allows the usage of standard-grade (unselected) CZT crystals, while achieving high-resolution spectroscopic performance for the instrument. In this presentation we describe the design of the array, the results from detailed laboratory tests, and preliminary results from measurements taken during a field test.
Systems, apparatuses, and methods for implementing an asynchronous router with virtual channel (VC) control. The asynchronous router may support multiple VCs for connections to other routers. The asynchronous router may include an interface unit on each switch boundary, with each interface unit including a data merge unit. The data merge unit may include a full detector unit for each VC, with the full detector unit counting the number of flits sent out on a respective VC and counting the number of credits released by the successor router. Whenever the successor router has no credits available, the full detector unit will assert the full signal to prevent any input requests from requesting to transmit over that particular VC. When the full signal is asserted, a timer unit may be activated to repeatedly check if any credits have been released in the successor router.
The U.S. power system is going through significant shifts in the value of energy and services, largely driven by increased generation in intermittent renewables (e.g, wind and solar). The increased utilization of these resources is shifting power markets and requiring other participants to consider changes in their operations to meet market needs. A large stock of existing run-of-river (ROR) hydropower infrastructure in the U.S. (29% of all hydropower capacity in the U.S.) is ROR, without the flexibility to regulate operations independent of daily water flows. This research is assessing the potential of integrated hybrid energy storage systems (HESS) as virtual reservoir for ROR flexibility enhancement. Different combinations of high energy storage (e.g., battery) and high power storage (e.g., flywheel, supercapacitor) devices with single/multi converter configuration are being considered for ROR integration. This poster summarizes the various ancillary services that are being investigated for all possible ROR integrated HESS configurations.
An incident simulation system supports an incident exercise in a virtual environment. The incident simulation system accesses a simulation plan defining an incident within a theater of operation. The incident simulation system simulates the incident exercise by displaying, to a participant in the incident exercise, images representing what the participant would see within the theater of operation as the participant moves within the theater of operation. The incident simulation system further simulates the incident by generating incident data indicating effects of the incident at target locations and at target times as the participant moves within the theater of operation. The incident simulation system further simulates the incident by displaying to the participant images representing the user experience that a detector would provide based on the generated incident data.
We present a neural virtual machine that can be trained to perform algorithmic tasks. Rather than combining a neural controller with non-neural memory storage as has been done in the past, this architecture is purely neural and emulates tape-based memory via fast associative weights (onestep learning). Here we formally define the architecture, and then extend the system to learn programs using recurrent policy gradient reinforcement learning based on examples of program inputs labeled with corresponding output targets, which are compared against actual output to generate a sparse reward signal. We describe the policy gradient training procedure used, and report its empirical performance on a number of smallscale list processing tasks, such as finding the maximum list element, filtering out certain elements, and reversing the order of the elements. These results show that program induction via reinforcement learning is possible using sparse rewards and solely neural computations.
Watch this video to learn how NREL researchers are evaluating the interdependencies between power systems and network communication flows when cyber and physical threats to the grid occur. NREL’s cybersecurity researchers have developed an emulated, multilayer grid environment at the ESIF, where they can safely launch attacks in the virtual world on both emulated and actual physical devices throughout the facility—and evaluate how they would respond to an attack in the real world.
National Virtual Biotechnology Laboratory (NVBL) Symposium Opening Remarks, Harriet Kung, Deputy Director for Science, DOE Office of Science
National Virtual Biotechnology Laboratory (NVBL) Symposium Co-Lead Stephen Streiffer, Argonne National Laboratory, Moderator for NVBL Project Leads Working Group Progress and Q&A
National Virtual Biotechnology Laboratory (NVBL) Symposium - Project Leads Working Group Progress, Lonnie Love
National Virtual Biotechnology Laboratory (NVBL) Symposium - COVID-19 Testing R&D, J. Patrick Fitch, Los Alamos National Laboratory
National Virtual Biotechnology Laboratory (NVBL) Symposium - Molecular Design for Medical Therapeutics, Martha (Marti) Head, Oak Ridge National Laboratory
National Virtual Biotechnology Laboratory (NVBL) Symposium - Viral Fate and Transport, Katrina Waters, Pacific Northwest National Laboratory
National Virtual Biotechnology Laboratory (NVBL) Symposium - Project Leads Working Group Progress, Epidemiological Modeling - Budhu Bhaduri, Oak Ridge National Laboratory
National Virtual Biotechnology Laboratory (NVBL) Symposium - Feature Speaker, Dr. William A. Bookless, Principal Deputy Administrator of the National Nuclear Security Administration
National Virtual Biotechnology Laboratory (NVBL) Symposium - Bruce Tromberg, Director, National Institute of Biomedical Imaging & Bioengineering, National Institutes of Health, “Future S&T Needs: Future of Testing & Surveillance”