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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hybrid Analytics Solution to Improve Coal Power Plant Operations

This project focused on developing advanced methods for thermal performance monitoring of a coal-fueled power plant. The specific goal was to develop and demonstrate a new thermal performance monitoring approach using a hybrid model that integrates a physics-based heat balance model with a machine learning-based pattern recognition model. The hybrid model enables increased accuracy and scope of the thermal analysis and an improved ability to monitor and detect changes in plant operation. This new approach takes full advantage of the individual model capabilities and creates an important new set of capabilities not previously possible using the two types of models separately. Using the heat balance model, a rich set of derived parameters (virtual sensors) are calculated from the measured plant operating data at each time point. The combined measured and derived data values are used by machine learning algorithms to create pattern recognition models over the range of normal unit operation. To create the monitoring models, historical data from normal operation of the plant is first processed by the heat balance model to compute the derived parameter data. The result is a greatly expanded set of normal operating data that can be used as input to create the pattern recognition model. Once the models are calibrated for normal operation, the hybrid model is suitable for use in continuous online monitoring. During online monitoring, new plant operating data is processed first by the heat balance model and then by the pattern recognition model. Results from the pattern recognition model quantify the deviation of each measured or derived parameter from its expected value in normal operation. The hybrid models can detect abnormal changes in plant operating data with very high accuracy and sensitivity. When abnormal behavior is detected, alerts are generated automatically for evaluation by the plant monitoring staff. The new hybrid solution product was developed and verified in the performance of the project. The hybrid solution was tested first in a simulation environment that mimicked the plant data systems and infrastructure used by U.S. power generating plants and utilities. The hybrid solution was then deployed for real-time, online monitoring of an operating coal-fueled power plant at a field test site. Field testing demonstrated that all hybrid solution development objectives were accomplished. The project work was based on combining the capabilities of two existing software products to create the new hybrid solution product. One of these was the existing MapEx® heat balance product and the other was the existing SureSense® advanced pattern recognition product. Each of these separate products was assessed to be at a Technology Readiness Level (TRL) of 9 at the start of the effort. The hybrid solution product was assessed to be at a TRL of 2 at the start of the project based on early feasibility work by the project team. At completion of the field testing performed in the project, the hybrid solution product was assessed to be at a TRL of 7. The project team expects that the hybrid solution product will be deployed commercially and will achieve a TRL of 9 within one year after completion of the project.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Fault detection in a three-phase dab converter

A system and method of fault detection based on a detailed waveform analysis is presented for transient and steady-state fault operation of 3-Φ DAB converter. Main symptoms of the converter during normal and fault conditions have been identified and a unique pattern in DC bias of phase currents under fault mode is noted. The logic-based fault diagnosis scheme is used to detect the fault and identify the faulty transistor.

Rastogi, Sagar K.↗
DOE OSTI2020

HIDES: Hybrid Intrusion Detector for Energy Systems

The establishment of a resilient electric grid accompanied by a secure communications network is an ongoing battle as advanced persistent threats continue to exploit existing vulnerabilities in legacy supervisory control and data acquisition system (SCADA) infrastructure. Traditional intrusion detection systems (IDSs) lack consistent performance because of the continuously evolving attack surface of SCADA systems. These shortcomings can be overcome by integrating logical system behavior, protocol-specific knowledge, and data-based learning to develop a comprehensive IDS solution. In this paper, we present a Hybrid Intrusion Detector for Energy Systems by integrating a network-based IDS, state-of-the-art machine learning-based IDS, and model-based IDS to detect unknown and stealthy cyberattacks targeting the SCADA networks. The proposed IDS uses synchrophasor measurements and cyber logs to learn patterns of different scenarios based on spatiotemporal behaviors of power systems. As a proof of concept, we implement and validate the proposed IDS by leveraging resources available at the National Renewable Energy Laboratory's Energy Systems Integration Facility test bed. Experimental results show promising performance in detecting cyberattacks while providing realtime visualization of power system measurements and cyber logs.

machine-learning intrusion detection system↗
DOE OSTI2019

MR findings of uterine PEComa in patients with tuberous sclerosis: report of two cases

Tuberous sclerosis complex (TSC), a rare autosomal dominant neurocutaneous disorder, is characterized by the presence of benign congenital tumors in multiple organs. Neoplasms with perivascular epithelioid cell differentiation (PEComas), including angiomyolipoma (AML) and lymphangioleiomyomatosis (LAM), can occur in association with TSC. This report describes two cases of uterine PEComas presenting characteristic MR imaging features reflecting pathological findings. From MR images, both cases showed single or multiple large, irregularly shaped or lobulated hemorrhagic lesions within the myometrium. They differed from typical adenomyotic cysts in their large size and irregular margins. Histopathologic analysis revealed that the hemorrhage was caused by adenomyosis and tumor cells that proliferated in surrounding stroma of the hemorrhagic lesions, compatible with PEComas. Microscopic observation revealed an infiltrative growth pattern of PEComas, with small nodules formed. The tumor lesions, however, were difficult to detect on MR images. The myometrium showed normal appearance on both T1-weighted and T2-weighted images in both cases. We speculate that PEComas may infiltrate extensively into the myometrium even when the myometrium shows almost normal radiologic appearance.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Controlling single rare earth ion emission in an electro-optical nanocavity

Abstract Rare earth emitters enable critical quantum resources including spin qubits, single photon sources, and quantum memories. Yet, probing of single ions remains challenging due to low emission rate of their intra-4 f optical transitions. One feasible approach is through Purcell-enhanced emission in optical cavities. The ability to modulate cavity-ion coupling in real-time will further elevate the capacity of such systems. Here, we demonstrate direct control of single ion emission by embedding erbium dopants in an electro-optically active photonic crystal cavity patterned from thin-film lithium niobate. Purcell factor over 170 enables single ion detection, which is verified by second-order autocorrelation measurement. Dynamic control of emission rate is realized by leveraging electro-optic tuning of resonance frequency. Using this feature, storage, and retrieval of single ion excitation is further demonstrated, without perturbing the emission characteristics. These results promise new opportunities for controllable single-photon sources and efficient spin-photon interfaces.

42 ENGINEERING↗
DOE OSTI2019

Widespread inhibition of daytime ecosystem respiration

The global land surface absorbs about a third of anthropogenic emissions each year, due to the difference between two key processes: ecosystem photosynthesis and respiration. Despite the importance of these two processes, it is not possible to measure either at the ecosystem scale during the daytime. Eddy-covariance measurements are widely used as the closest 'quasi-direct' ecosystem-scale observation from which to estimate ecosystem photosynthesis and respiration. Recent research, however, suggests that current estimates may be biased by up to 25%, due to a previously unaccounted for process: the inhibition of leaf respiration in the light. Yet the extent of inhibition remains debated, and implications for estimates of ecosystem-scale respiration and photosynthesis remain unquantified. Here, we quantify an apparent inhibition of daytime ecosystem respiration across the global FLUXNET eddy-covariance network and identify a pervasive influence that varies by season and ecosystem type. We develop partitioning methods that can detect an apparent ecosystem-scale inhibition of daytime respiration and find that diurnal patterns of ecosystem respiration might be markedly different than previously thought. The results call for the re-evaluation of global terrestrial carbon cycle models and also suggest that current global estimates of photosynthesis and respiration may be biased, some on the order of magnitude of anthropogenic fossil fuel emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Multi-MHz time-of-flight electronic bandstructure imaging of graphene on Ir(111)

In the quest for detailed spectroscopic insight into the electronic structure at solid surfaces in a large momentum range, we have developed an advanced experimental approach. It combines the 3D detection scheme of a time-of-flight momentum microscope with an optimized filling pattern of the BESSY II storage ring. Here, comprehensive data sets covering the full surface Brillouin zone have been used to study faint substrate-film hybridization effects in the electronic structure of graphene on Ir(111), revealed by a pronounced linear dichroism in angular distribution. The method paves the way to 3D electronic bandmapping with unprecedented data recording efficiency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

MTUQ: a framework for estimating moment tensors, point forces, and their uncertainties

SUMMARY We introduce MTUQ, an open-source Python package for seismic source estimation and uncertainty quantification, emphasizing flexibility and operational scalability. MTUQ provides MPI-parallelized grid search and global optimization capabilities, compatibility with 1-D and 3-D Green’s function database formats, customizable data processing, C-accelerated waveform and first-motion polarity misfit functions, and utilities for plotting seismic waveforms and visualizing misfit and likelihood surfaces. Applicability to a range of full- and constrained-moment tensor, point force, and centroid inversion problems is possible via a documented application programming interface, accompanied by example scripts and integration tests. We demonstrate the software using three different types of seismic events: (1) a 2009 intraslab earthquake near Anchorage, Alaska; (2) an episode of the 2021 Barry Arm landslide in Alaska; and (3) the 2017 Democratic People’s Republic of Korea underground nuclear test. With these events, we illustrate the well-known complementary character of body waves, surface waves, and polarities for constraining source parameters. We also convey the distinct misfit patterns that arise from each individual data type, the importance of uncertainty quantification for detecting multimodal or otherwise poorly constrained solutions, and the software’s flexible, modular design.

58 GEOSCIENCES↗
DOE OSTI2020

Jet Substructure in Fireworks Emission from Nonuniform and Rotating Bose-Einstein Condensates

Here, we show that jet emission from a Bose condensate with periodically driven interactions, also known as “Bose fireworks”, contains essential information on the condensate wave function, which is difficult to obtain using standard detection methods. We illustrate the underlying physics with two examples. When condensates acquire phase patterns from external potentials or from vortices, the jets display novel substructure, such as oscillations or spirals, in their correlations. Through a comparison of theory, numerical simulations, and experiments, we show how one can quantitatively extract the phase and the helicity of a condensate from the emission pattern. Our work, demonstrating the strong link between jet emission and the underlying quantum system, bears on the recent emphasis on jet substructure in particle physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Directional Laplacian Centrality for Cyber Situational Awareness

Cyber operations is drowning in diverse, high-volume, multi-source data. To get a full picture of current operations and identify malicious events and actors, analysts must see through data generated by a mix of human activity and benign automated processes. Although many monitoring and alert systems exist, they typically use signature-based detection methods. We introduce a general method rooted in spectral graph theory to discover patterns and anomalies without a priori knowledge of signatures. We derive and propose a new graph-theoretic centrality measure based on the derivative of the graph Laplacian matrix in the direction of a vertex. To build intuition about our measure, we show how it identifies the most central vertices in standard network datasets and compare to other graph centrality measures. Finally, we focus our attention on studying its effectiveness in identifying important IP addresses in network flow data. Using both real and synthetic network flow data, we conduct several experiments to test our measure’s sensitivity to two types of injected attack profiles and show that vertices participating in injected attack profiles exhibit noticeable changes in our centrality measures, even when the injected anomalies are relatively small, and in the presence of simulated network dynamics.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Master State Threat Identifier (masti)

The MSE cyber sensor offers a novel approach for scalable network monitoring using heterogeneous computing. Packet data is collected, analyzed, and stored by a stand alone cyber sensor. Machine learning algorithms are run to discover patterns in the communication without the need for deep packet inspection. Tuning of the detection algorithms happens automatically, without need for an engineer to manually create detection rules.

Russell, PierceL↗
DOE OSTI2023

Update to the Microcontroller Benchmark for Radiation Testing

LANL developed a benchmark of software code for radiation testing of microprocessors several years ago, and it was published under an open-source license on GitHub. Publishing the software is necessary for other researchers to adopt and implement this benchmark for radiation testing of other microprocessors to standardize test practices so that test data can be compared across different microprocessors. The original codes have been used several times by other organizations to test a wide range of microcontrollers and microprocessors. After several years of research, LANL is ready to update the benchmark. Changes include: 1. Addition of new codes that allow common software codes to be tested, 2. Addition of new codes that instrument more microprocessor circuitry, 3. Addition of input patterns that allow for a more compressive understanding of how the memory layout affects the sensitivity to radiation-induced faults and better use of automated test pattern generation standards, and 4. Modification of current codes for faster and more resilient detection, reporting and correction of radiation-induced faults. These codes have been tested by LANL researchers over the last few years, which has been published in the open literature. As the code base for the new benchmarks are stable, it is time to release the update to the GitHub repository, where the original codes were released.

Quinn, Heather↗
DOE OSTI2022

Internal 2-D Surface Temperature Measurements for Large Complex Geometries

For 2D-temperature monitoring applications, a variant of EIT (Electrical Impedance Tomography) is evaluated computationally in this work. Literature examples of poor sensor performance in the center of the 2D domains away from the side electrodes motivated this study which seeks to overcome some of the previously noted shortcomings. In particular, the use of ‘sensing skins’ with novel tailored baseline conductivities were examined using the EIDORS package for EIT. It was found that the best approach for detecting a hot spot depends on several factors such as the current injection (stimulation) patterns, the measurement patterns, and the reconstruction algorithms. For a well-performing combination of these factors, tailored baseline conductivities were assessed and compared to the baseline uniform conductivity. It was discovered that for some EIT applications, a tailored distribution needs to be smooth and that sudden changes in the conductivity gradients should be avoided. Still, the benefits in terms of improved EIT performance were small for conditions for which the EIT measurements had been ‘optimized’ for the uniform baseline case. Within the limited scope of this study, only two specific cases showed benefits from tailored distributions. For one case, a smooth tailored distribution with increased baseline conductivity in the center provided a better separation of two centrally located hot spots. For another case, a smooth tailored distribution with reduced conductivity in the center provided better estimates of the magnitudes of two hot spots near the center of the sensing skin.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

The High-resolution Transmission Spectrum of HD 189733b Interpreted with Atmospheric Doppler Shifts from Three-dimensional General Circulation Models

The signature of wind patterns caused by the interplay of rotation and energy redistribution in hot Jupiters is detectable at high spectral resolution, yet no direct comparison has been attempted between predictions from general circulation models (GCMs) and observed high-resolution spectra. We present the first such comparison on near-infrared transmission spectra of the hot Jupiter HD 189733b. Exploring 12 rotation rates and two chemical regimes, we have created model spectra from 3D GCMs and cross-correlated them with the observed spectra. Comparing our models against those of HD 189733b, we obtain three key results: (1) we confirm CO and H{sub 2}O in the planet’s atmosphere at a detection significance of 8.2σ; (2) we recover the signature of day-to-night winds with speeds of several km s{sup −1} at pressures of several millibars; and (3) we constrain the rotation period of the planet to between 1.2 and 4.69 days (synchronous rotation (2.2 days) remains consistent with existing observations). Our results do not suffer from the shortcomings of 1D models as cross-correlation templates—these models mainly tend to overconstrain the slower rotation rates and show evidence for anomalous blueshifts. Our 3D models instead match the observed line-of-sight velocity of this planet by self-consistently including the effects of high-altitude day-to-night winds. Overall, we find a high degree of consistency between observations of HD 189733b and our GCM-based spectra, implying that the physics and chemistry are adequately described in current 3D forward models for the purpose of interpreting observations at high spectral resolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

R-process-rich Stellar Streams in the Milky Way*

We present high-resolution Magellan/MIKE spectra of 22 bright (9 < V < 13.5) metal-poor stars (-3.18 < [Fe/H] < -1.37) in three different stellar streams, the Helmi debris stream, the Helmi trail stream, and the ω Centauri progenitor stream. We augment our Helmi debris sample with results for 10 stars by Roederer et al. for a total of 32 stars. Detailed chemical abundances of light elements as well as heavy neutron-capture elements have been determined for our 22 stars. All three streams contain carbon-enhanced stars. For 13 stars, neutron-capture element lines were detectable, and they all show signatures in agreement with the scaled solar r -process pattern, albeit with a large spread of -0.5 < [Eu/Fe] < +1.3. Eight of these stars show an additional small s -process contribution superposed onto their r -process pattern. This could be discerned because of the relatively high signal-to-noise ratio of the spectra given that the stars are close by in the halo. Our results suggest that the progenitors of these streams experienced one or more r -process events early on, such as a neutron star merger or another prolific r -process source. This widely enriched these host systems before their accretion by the Milky Way. The small s -process contribution suggests the presence of asymptotic giant branch stars and associated local (inhomogeneous) enrichment as part of the ongoing chemical evolution by low-mass stars. Stars in stellar streams may thus be a promising avenue for studying the detailed history of large dwarf galaxies and their role in halo assembly with easily accessible targets for high-quality spectra of many stars.

Astronomy & Astrophysics↗
DOE OSTI2015

Nanogels from Metal-Chelating Crosslinkers as Versatile Platforms Applied to Copper-64 PET Imaging of Tumors and Metastases

Metals are essential in medicine for both therapy and diagnosis. We recently created the first metal-chelating nanogel imaging agent, which employed versatile, reproducible chemistry that maximizes chelation stability. Here we demonstrate that our metal chelating crosslinked nanogel technology is a powerful platform by incorporating 64 Cu to obtain PET radiotracers. Polyacrylamide-based nanogels were crosslinked with three different polydentate ligands (DTPA, DOTA, NOTA). NOTA-based nanogels stably retained 64 Cu in mouse serum and accumulated in tumors in vivo as detected by PET/CT imaging. Measurement of radioactivity in major organs ex vivo confirmed this pattern, revealing a high accumulation (12.3% ID/g and 16.6% ID/g) in tumors at 24 and 48 h following administration, with lower accumulation in the liver (8.5% ID/g at 24 h) and spleen (5.5% ID/g). Nanogels accumulated even more efficiently in metastases (29.9% and 30.4% ID/g at 24 and 48 h). These metal-chelating nanogels hold great promise for future application as bimodal PET/MRI agents; chelation of β-emitting radionuclides could enable radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Data analysis for valve leak detection of nuclear power plant safety critical components - 336

A nuclear plant consists of several safety-related components. These safety-related components are tested periodically in order to verify their functionality when they are called upon to perform. The data acquired during periodic testing provides information about possible degradation of the equipment or device under test. This research is focused on leak monitoring techniques to provide diagnostic information on the determination of valve aging and degradation. Several commercially available valve diagnostic-monitoring methods are evaluated, especially for the techniques based on measurements of acoustic emission, and accelerometer. The check valve is one of typical components being extensively used in safety systems of nuclear power plants. The failures of check valves have resulted in significant maintenance efforts, on occasion, have resulted in water hammer, over-pressurization of low-pressure systems, and damage to flow system components. In this paper, acoustic emission signals due to leak from check valves with artificial leakage and worn parts are investigated both analytically and experimentally. The results of advanced signal processing and de-noising techniques also have been identified. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Interferometric mapping of magnetic fields: the ALMA view of the massive star-forming clump W43-MM1

Here, we present the first results from ALMA observations of 1 mm polarized dust emission toward the W43-MM1 high-mass star-forming clump. We have detected a highly fragmented filament with source masses ranging from 14 M {sub ⊙} to 312 M {sub ⊙}, where the largest fragment, source A, is believed to be one of the most massive in our Galaxy. We found a smooth, ordered, and detailed polarization pattern throughout the filament, which we used to derived magnetic field morphologies and strengths for 12 out of the 15 fragments detected ranging from 0.2 to 9 mG. The dynamical equilibrium of each fragment was evaluated finding that all the fragments are in a super-critical state that is consistent with previously detected infalling motions toward W43-MM1. Moreover, there are indications suggesting that the field is being dragged by gravity as the whole filament is collapsing.

79 ASTRONOMY AND ASTROPHYSICS↗