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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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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Control of matrix converters using machine learning

A method of controlling a matrix converter system is provided. The method includes receiving an operating condition and consulting a trained Q-data structure for reward values associated with respective switching states of the switching matrix for an operating state that corresponds to the operating condition. The Q-data structure is trained using Q-learning to map a reward value predicted for respective switching states to respective discrete operating states. The method further includes sorting the reward values predicted for the respective switching states mapped to the operating state that corresponds to the operating condition, selecting a subset of the set of the mappings as a function of a result of sorting the reward values associated with the switching states of the operating state, evaluating each switching state included in the subset, and selecting an optimal switching state for the operating condition based on a result of evaluating the switching states of the subset.

Chamie, Mahmoud El↗
DOE OSTI2023

Identifying location of data granules in global virtual address space

An approach is disclosed that identifies a home node of a data granule. The process is performed by an information handling system (a local node) that retrieves a global virtual address directory. The global virtual address directory maps shared virtual addresses to a number nodes that includes the local node with one of the nodes being the home node. The shared virtual addresses correspond to a plurality of memory addresses that are stored in a shared virtual memory that is shared amongst the plurality of nodes. The approach receives a selected shared virtual address, retrieves, from the global virtual address directory, the home node associated with the selected shared virtual address, and accesses the data granule corresponding to the selected shared virtual address from the home node.

Johns, Charles R.↗
DOE OSTI2023

Systems and methods for vehicle cruise speed recommendation

A method for providing a cruising speed recommendation to an operator of a vehicle includes determining a projected route; receiving route characteristic data including route elevation data; determining a sampling resolution; sampling the route elevation data at the sampling resolution to generate sampled route elevation data; determining at least one start of uphill position and at least one start of downhill position; determining at least one cruise speed route segment based at least in part on the at least one start of uphill position and the at least one start of downhill position; determining a corresponding cruising speed for the at least one cruise speed route segment based at least in part on one or more of the route elevation data and the sampled route elevation data; and communicating the corresponding cruising speed for the at least one cruise speed route segment.

Aggoune, Karim↗
DOE OSTI2023

System and method of making an enhanced cast iron crankshaft

A method and system for manufacturing a cast iron crankshaft for a vehicle are provided. The system comprises a molding unit arranged to form a negative sand cast mold of the cast iron crankshaft. The mold comprising at least one molded cavity having a pattern with dimensions of the cast iron crankshaft. The system further comprises a feeding mechanism comprising a riser having a connector through which molten metallic material flows to the cast mold. The feeding mechanism feeds the molten metallic material at a riser connection angle in the at least one mold cavity. The riser connection angle corresponds to a connector modulus. The connector modulus is 20% greater than a cast modulus. The riser geometry corresponds to a riser modulus. The riser modulus is 20% greater than the connector modulus. The system further comprises a furnace, a cooling area, a separation unit, a controller and a power source.

Wang, Liang↗
DOE OSTI2024

Object Detection and Recognition with PointPillars in LiDAR Point Clouds – Comparisions

In the field of autonomous systems, neural networks have been leveraged for object detection and recognition in 2-dimensional images captured by cameras. Other types of sensors are available for sensing surroundings, including LiDAR sensors, and corresponding networks have been developed to perform detection and recognition in the point clouds generated by these sensors. The approaches are similar, both perform convolutions, but have distinct characteristics and challenges. In designing and configuring autonomous systems, a variety of LiDAR sensors are available, along with configurable deep neural networks to leverage their data. This work presents a review of the PointPillars network, an evolution of the seminal PointNet, comparing accuracy and training time relative to different LiDAR sensors, network and training parameters, CPU and GPU hardware, and the criticality of the use of reflective intensity as a feature. The value of using reflectivity as a predictive feature is explored and quantified to determine if it makes a significant difference in accuracy of the PointPillars network. Two separate LiDAR sensors are utilized, a 16-plane and a 32-plane, and corresponding accuracies and training times with the PointPillars network are evaluated.

LiDAR, machine learning, neural network, object re↗
DOE OSTI2023

Anomalous behavior detection by an artificial intelligence-enabled system with multiple correlated sensors

Multi-metric artificial intelligence (AI)/machine learning (ML) models for detection of anomalous behavior of a machine/system are disclosed. The multi-metric AI/ML models are configured to detect anomalous behavior of systems having multiple sensors that measure correlated sensor metrics such as coolant distribution units (CDUs). The multi-metric AI/ML models perform the anomalous system behavior detection in a manner that enables both a reduction in the amount of sensor instrumentation needed to monitor the system's operational behavior as well as a corresponding reduction in the complexity of the firmware that controls the sensor instrumentation. As such, AI-enabled systems and corresponding methods for anomalous behavior detection disclosed herein offer a technical solution to the technical problem of increased failure rates of existing multi-sensor systems, which is caused by the presence of redundant sensor instrumentation that necessitates complex firmware for controlling the sensor instrumentation.

Serebryakov, Sergey↗
DOE OSTI2023

Power converter having a gate drive circuit and method of operating

A power converter apparatus comprises a set of switching elements communicatively coupled with a set of gate drive circuits. Each gate drive circuit is configured to provide a respective drive signal to a corresponding switching element, each switching element being switchably responsive to the respective drive signal. The apparatus includes a controller module configured to control an output state of the power converter, and selectively change one of a respective gate resistance and a respective gate current of a corresponding subset of the gate drive circuits based on the output state of the power converter.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Synthetic nucleic acids for information storage and transmission

The present invention relates to method for storing and transmitting information by employing a nucleic acid construct. The nucleic acid construct can include a lock region; a translation key region that corresponds to the identity of a key; and a message region including a nucleic sequence that corresponds to an encrypted message.

Bachand, George↗
DOE OSTI2020

Development of a Model Correlating Axial HEPA Filter Performance Between Elevated and Standard Conditions

The ASME AG-1 Code specifies minimum rated airflow based on standard cubic feet per minute (SCFM) for axial high efficiency particulate air (HEPA) filters and actual cubic feet per minute (ACFM) for radial HEPA filters with corresponding maximum pressure drop. A quantitative analysis can be performed to demonstrate the variation in filter efficiency and develop a correlation of performance between axial filters subjected to ACFM and SCFM. This study illustrates the variation in filter efficiency of axial HEPA filters subjected to ACFM and SCFM flow rate conditions at varying atmospheric pressures. It also presents the methods used to calculate correction factors to convert filter efficiency and pressure drop from elevated to standard conditions. The Axial Large Scale Test Stand (ALSTS) in the Institute for Clean Energy Technology (ICET) at Mississippi State University has been utilized to control aerosol concentration, flowrate, atmospheric pressure, relative humidity, and temperature. The filter test matrix consists of axial HEPA filters rated at 1,000 and 1,500 CFM with varying filter pack types. Each filter is subjected to varying pressures of 14.70 psi, 13.55 psi, 12.40 psi, and 11.25 psi, temperatures of 70 deg. F, 110 deg. F, and 150 deg. F, and relative humidities of 50% and 80%, resulting in twenty-four unique testing points. The corresponding SCFM flow rates are computed for each point in order to form a comparison. Evaluation of the effects of designating ACFM or SCFM will be based upon the filter efficiencies of generated Dioctyl Phthalate (DOP) particles at a diameter of 0.3 micrometers. The results show filter efficiency decreasing as atmospheric pressure decreases due to increased filter face velocity. A correlation model is developed to convert filter efficiency and pressure drop at elevated conditions to those of standard pressure, relative humidity, and temperature.

42 ENGINEERING↗
DOE OSTI2022

Fourier analysis of continuous fractional diffusion synthetic acceleration schemes in slab geometry

We propose two fractional extensions of continuous diffusion synthetic acceleration (DSA) with fractional derivative order α varying over the interval 2 ≥ α ≥ 1 . We investigate the spectral properties of the corresponding continuous families of fractional preconditioners by performing Fourier analysis for a model infinite homogeneous medium problem in slab geometry. The first family results in a fractional acceleration scheme, FrDSAo, that reduces to traditional DSA for .α = 2 and scattering ratio c limiting to a unit value (c → 1) but is otherwise optimized via the Fourier analysis, to obtain the smallest possible spectral radius, for c < 1 and 2 ≥ α ≥ 1. The second family corresponds to a fractional acceleration scheme, FrDSAs, that reduces to traditional DSA for α = 2 for all values of c. The latter scheme is not optimized but has the advantage of lending itself to a more straightforward implementation. For high values of c, the results of the Fourier analysis point to the existence of an interval 2 > α > ∼1.8 where both FrDSAo and FrDSAs can achieve a lower spectral radius than DSA. For example, DSA has a spectral radius of ∼0.2246 for c = 0.9999 while FrDSAo produces a value of ∼0.1616 at α = 1.92 and FrDSAs results in ∼0.2116 at α =1.93. (author)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Overview of collaborative research between UNICAMP in Brazil and Fermilab in cryogenics

The Long-Baseline Neutrino Facility (LBNF) situated at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, serves as the host for the Deep Underground Neutrino Experiment (DUNE), employing cryostats with nearly 70,000 metric tons of high purity liquid argon (LAr). The integrity of LAr quality is pivotal in determining the electron lifetime within DUNE, directly impacting its signal-to-noise ratio. Specifically, Far Detector 1 (FD-1) in cryostat 1 requires an electron lifetime over 3 ms within its 3.5 m drift, corresponding to less than 100 parts-per-trillion (ppt) Oxygen equivalent contamination. Far Detector 2 (FD-2) in cryostat 2 demands over 6 ms electron lifetime within its 6.0 m drift, corresponding to less than 50 ppt Oxygen equivalent contamination. Nitrogen (N$_2$) absorption of LAr scintillation light, known as quenching, necessitates N$_2$ contamination in LAr to remain below 1 ppm to minimize photon loss and enhance energy reconstruction. Studies indicate that at 1 ppm N$_2$, approximately 20% of scintillation light is lost, highlighting the importance of minimizing N$_2$ contamination.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 $\mu$m$^2$ in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e$^-$ and a total dispersion of $\sim$100e$^-$ The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4% - 75.4% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm$^2$ staying within the experimental constraints.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Measurements of the Neutron Magnetic Form Factor and the Two-Photon Exchange Contribution to the Electron-Neutron Elastic Scattering Cross Section

The Super BigBite Spectrometer (SBS) program in Experimental Hall A of Jefferson Lab is a series of high-precision, large ?2 , electromagnetic form factor experiments. GMn and nTPE were the first two experiments of the SBS program and ran from Oc?tober 2021 through February 2022. Both experiments detect neutron-tagged ?(?, ???) and proton-tagged ?(?, ???) quasi-elastic electrons scattering from a deuterium tar?get. The GMn experiment is a measurement of the magnetic form factor of the neutron, ?? ?, via the ratio method over a ?2 range of 3.5 to 13.5 (GeV/c)2 . The nTPE experiment ran in-parallel with the GMn experiment and shared an overlap?ping kinematic point with GMn. nTPE extends the GMn experiment to assess the differences between Rosenbluth Slop and the single-photon exchange approximation. The nTPE experiment had two kinematic settings corresponding to different electron scatting angles at a fixed ?2 of 4.5 (GeV/c)? . Comparisons of nucleon form factor ratio measurements acquired through polarization transfer and LT separation reveal discrepancies as ?2 increases. Two-photon exchange is strongly favored as the reason for this discrepancy. ?? ? has been extracted at two kinematic settings corresponding to ?2 values of 3.0 and 4.5 (GeV/c)2 . Additionally, I will present an assessment of the differences between Rosenbluth Separation and single-photon exchange measure?ments.

Boyd III, John Alan↗
DOE OSTI2024

Chiral symmetry and Atiyah-Patodi-Singer index theorem for staggered fermions

We consider the Atiyah-Patodi-Singer (APS) index theorem corresponding to the chiral symmetry of a continuum formulation of staggered fermions called Kähler-Dirac fermions, which have been recently investigated as an ingredient in lattice constructions of chiral gauge theories. We point out that there are two notions of chiral symmetry for Kähler-Dirac fermions, both having a mixed perturbative anomaly with gravity leading to index theorems on closed manifolds. By formulating these theories on a manifold with boundary, we find the APS index theorems corresponding to each of these symmetries, necessary for a complete picture of anomaly inflow, using a recently discovered physics-motivated proof. We comment on a fundamental difference between the nature of these two symmetries by showing that a sensible local, symmetric boundary condition only exists for one of the two symmetries. This sheds light on how these symmetries behave under lattice discretization, and in particular on their use for recent symmetric-mass generation proposals.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting

Many existing object counting methods rely on density map estimation (DME) of the discrete grid representation by decoding extracted image semantic features from designed convolutional neural networks (CNNs). Relying on discrete density maps not only leads to information loss dependent on the original image resolution, but also has a scalability issue when analyzing high-resolution images with cubically increasing memory complexity. Furthermore, none of the existing methods can offer reliable uncertainty quantification (UQ) for the derived count estimates. To overcome these limitations, we design UNcertainty-aware, hypernetwork-based Implicit neural representations for Counting (UNIC) to assign probabilities and the corresponding counting confidence over continuous spatial coordinates. We derive a sampling-based Bayesian counting loss function and develop the corresponding model training algorithm. UNIC outperforms existing methods on the Remote Sensing Object Counting (RSOC) dataset with reliable UQ and improved interpretability of the derived count estimates. Our code is available at https://github.com/SiyuanXu-tamu/UNIC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Memory access statistics monitoring

Systems, apparatuses, and methods related to memory access statistics monitoring are described. A host is configured to map pages of memory for applications to a number of memory devices coupled thereto. A first memory device comprises a monitoring component configured to monitor access statistics of pages of memory mapped to the first memory device. A second memory device does not include a monitoring component capable of monitoring access statistics of pages of memory mapped thereto. The host is configured to map a portion of pages of memory for an application to the first memory device in order to obtain access statistics corresponding to the portion of pages of memory upon execution of the application despite there being space available on the second memory device and adjust mappings of the pages of memory for the application based on the obtained access statistics corresponding to the portion of pages.

Roberts, David A.↗
DOE OSTI2024

Systems and methods for application performance profiling and improvement

Methods for analyzing and improving a target computer application and corresponding systems and computer-readable mediums. A method includes receiving the target application. The method includes generating a parallel control flow graph (ParCFG) corresponding to the target application. The method includes analyzing the ParCFG by the computer system. The method includes generating and storing the modified ParCFG for the target application.

Leidel, John D.↗
DOE OSTI2024

Fabrication method for a component having magnetic and non-magnetic dual phases

Methods for forming a dual-phase magnetic component from an initial component comprising a non-magnetic austenite composition are provided. The method may include: forming a coating on a portion of the surface of the initial component to form a masked area while leaving an unmasked area thereon. Thereafter the initial component may be heated to a treatment temperature such that nitrogen diffuses out of the unmasked area of the initial component to transform the non-magnetic austenite composition to a magnetic phase in the unmasked area. Thereafter, the initial component may be cooled from the treatment temperature to form a dual-phase magnetic component having a magnetic region corresponding to the unmasked area and a non-magnetic region corresponding to the masked area.

Huang, Shenyan↗