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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Multiagent-Based Dynamic Voltage Support of Power Converters During Fault Ride-Through

Reference point of applicability (RPA) is a predefined point in a distribution network that performance requirements shall apply. As RPA is not directly controlled by a dedicated distributed energy resource (DER), it requires an aggregate response of multiple DERs over a complex meshed network. Here, this article presents a multiagent-based distributed dynamic voltage support (DDVS) method for coordinated aggregate response of multiple DER units to support RPA voltage profile during and after fault ride-through. DDVS implements a multiagent-based leader target tracking scheme with velocity matching and flock centering features to avoid uncoordinated current injections of cooperative DERs. The DDVS is an event-based approach based on RPA requirements. Two-dimensional voltage support objective is handled: 1) coordinated positive sequence current injection for voltage magnitude boosting and 2) coordinated negative sequence current injection for unbalance voltage mitigation. The results demonstrate that the proposed DDVS algorithm addresses emerging coordinated DVS requirement of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

MatCal Users Guide: Release 1.3.0

Any continuum mechanics model will require three components: (1) a discretized geometry of the boundary value problem being studied, (2) the partial differential equations to be solved, and (3) the initial conditions and boundary conditions for the problem. To describe material behavior in these computational models, material models contribute to (2) the underlying equations and, occasionally, to (3) the initial conditions for the simulation. These material models can exhibit a mathematical form that is empirically based, based on first principles, or developed from both empirical observations and known physics. In general, these models are meant to represent a class of materials with well understood behavior. As a result, material models have parameters that must be tuned or calibrated so that the model response matches characterization data available for the specific material it is intended to represent when used to simulate a specific system. For simple models, such as isotropic, linear elastic materials in solid mechanics, this calibration process can be a simple analytical calculation directly extracting the parameters from experimental measurements. For complex models that have many inputs and require many characterization datasets to adequately identify the material behavior, the model calibration process can require an inverse problem approach where an optimization is performed to tune the model parameters to the available data.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Efficient excitation and control of integrated photonic circuits with virtual critical coupling

Critical coupling in integrated photonic devices enables the efficient transfer of energy from a waveguide to a resonator, a key operation for many applications. This condition is achieved when the resonator loss rate is equal to the coupling rate to the bus waveguide. Carefully matching these quantities is challenging in practice, due to variations in the resonator properties resulting from fabrication and external conditions. Here, we demonstrate that efficient energy transfer to a non-critically coupled resonator can be achieved by tailoring the excitation signal in time. We rely on excitations oscillating at complex frequencies to load an otherwise overcoupled resonator, demonstrating that a virtual critical coupling condition is achieved if the imaginary part of the complex frequency equals the mismatch between loss and coupling rate. We probe a microring resonator with tailored pulses and observe a minimum intensity transmission T = 0.11 in contrast to a continuous-wave transmission T = 0.58, corresponding to 8 times enhancement of intracavity intensity. Our technique opens opportunities for enhancing and controlling on-demand light-matter interactions for linear and nonlinear photonic platforms.

42 ENGINEERING↗
DOE OSTI2026

Revisiting the three-kaon interaction and its relation with 𝐾⁡(1460)

Here, we test the hypothesis of 𝐾⁡(1460) being a hadronic 𝐽 𝑃 = 0 − molecule through nonperturbative 𝑆-wave $KK\bar{⁢K}$, 𝐾⁢𝜋⁢𝜋, 𝐾⁢𝜋⁢𝜂 coupled-channel dynamics in a three-body unitary isobar approach. The scalar two-body coupled-channel resonances 𝑓 0 ⁡(500), 𝑓 0 ⁡(980), 𝑎 0 ⁡(980), and 𝐾$^*_0$⁡(700) are generated in the subsytems in amplitudes that match phase shifts from experiment. In a first step, previous results in the limit of mass-degenerate, stable 𝑓 0 and 𝑎 0 isobars are reproduced. Once the full seven-coupled channel model is switched on, other 𝑆-matrix effects obscure and modify the resonance signal, including complex thresholds, a two-body cusp, and a triangle singularity at threshold.

Döring, M. [George Washington Univ., Washington, D↗
DOE OSTI2026

Machine Learning-Enabled Wearable Piezoelectric Acoustic Sensor for Real-Time Breast Abnormality Detection

In contemporary society, breast health has become a significant public health concern, particularly among women. According to statistics from the World Health Organization, both the incidence and mortality rates of breast tumors have steadily increased in recent years. Therefore, effective early-stage screening and postoperative monitoring are essential for maintaining breast health. However, conventional clinical diagnostic modalities are typically bulky, operationally complex, and unsuitable for continuous real-time monitoring, which limits their use in portable and everyday health management applications. To address these limitations, this study proposes a machine learning-integrated wearable piezoelectric sensing platform as an auxiliary tool for breast health assessment. The device consists of a PDMS matching layer embedded with flexible silver nanowires, a P(VDF-TrFE) piezoelectric layer, and a multi-channel low-noise signal acquisition circuit. It is capable of acquiring acoustic echo signals from tissue-mimicking environments and automatically evaluating signal validity using a convolutional neural network (CNN). By integrating piezoelectric sensing with deep learning-based signal analysis, the proposed system achieves a signal-to-noise ratio exceeding 70 dB and a real-time classification accuracy above 96% under controlled conditions. These results demonstrate that the platform provides a compact, portable, and intelligent approach for wearable sensing of mechanical heterogeneity and highlight its potential for future development in continuous biomedical monitoring technologies.

He, Shuaitong↗
DOE OSTI2022

Porting the Kitten Lightweight Kernel Operating System to RISC-V

Hardware design in high-performance computing (HPC) is often highly experimental. Exploring new designs is difficult and time-consuming, requiring lengthy vendor cooperation. RISC-V is an open-source processor ISA that improves the accessibility of chip design, including the ability to do hardware/software co-design using open-source hardware and tools. Co-design allows design decisions to easily flow across the hardware/software boundary and influence future design ideas. However, new hardware designs require corresponding software to drive and test them. Conventional operating systems like Linux are massively complex and modification is time-prohibitive. In this paper, we describe our port of the Kitten lightweight kernel operating system to RISC-V in order to provide an alternative to Linux for conducting co-design research. Kitten's small code base and simple resource management policies are well matched for quickly exploring new hardware ideas that may require radical operating system modifications and restructuring. Our evaluation shows that Kitten on RISC-V is functional and provides similar performance to Linux for single-core benchmarks. This provides a solid foundation for using Kitten in future co-design research involving RISC-V.

Gordon, Nick↗
DOE OSTI2020

Imaging of a fluid injection process using geophysical data — A didactic example

In many subsurface industrial applications, fluids are injected into or withdrawn from a geologic formation. It is of practical interest to quantify precisely where, when, and by how much the injected fluid alters the state of the subsurface. Routine geophysical monitoring of such processes attempts to image the way that geophysical properties, such as seismic velocities or electrical conductivity, change through time and space and to then make qualitative inferences as to where the injected fluid has migrated. The more rigorous formulation of the time-lapse geophysical inverse problem forecasts how the subsurface evolves during the course of a fluid-injection application. Using time-lapse geophysical signals as the data to be matched, the model unknowns to be estimated are the multiphysics forward-modeling parameters controlling the fluid-injection process. Properly reproducing the geophysical signature of the flow process, subsequent simulations can predict the fluid migration and alteration in the subsurface. The dynamic nature of fluid-injection processes renders imaging problems more complex than conventional geophysical imaging for static targets. This work intents to clarify the related hydrogeophysical parameter estimation concepts.

58 GEOSCIENCES↗
DOE OSTI2022

LDRD 226360 Final Project Report: Simulated X-ray Diffraction and Machine Learning for Optimizing Dynamic Experiment Analysis

This report is the final documentation for the one-year LDRD project 226360: Simulated X-ray Diffraction and Machine Learning for Optimizing Dynamic Experiment Analysis. As Sandia has successfully developed in-house X-ray diffraction tools for study of atomic structure in experiments, it has become increasingly important to develop computational analysis methods to support these experiments. When dynamically compressed lattices and orientations are not known a priori, the identification requires a cumbersome and sometimes intractable search of possible final states. These final states can include phase transition, deformation and mixed/evolving states. Our work consists of three parts: (1) development of an XRD simulation tool and use of traditional data science methods to match XRD patterns to experiments; (2) development of ML-based models capable of decomposing and identifying the lattice and orientation components of multicomponent experimental diffraction patterns; and (3) conducting experiments which showcase these new analysis tools in the study of phase transition mechanisms. Our target material has been cadmium sulfide, which exhibits complex orientation-dependent phase transformation mechanisms. In our current one-year LDRD, we have begun the analysis of high-quality c-axis CdS diffraction data from DCS and Thor experiments, which had until recently eluded orientation identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Strain-Induced Lateral Heterostructures in Patterned Semiconductor Nanomembranes for Micro- and Optoelectronics

The ability to tailor the energy band lineup of semiconductor materials plays a key role in the development of many electronic and optoelectronic devices and normally relies on heteroepitaxy. In this work, we report a different method, based on strain engineering, for the controlled introduction of variations in bandgap energy with lateral position in thin films. External stress is applied on Ge nanomembranes stacked with an array of amorphous-Si pillars in order to create a non-uniform strain (and therefore bandgap energy) distribution commensurate with the sample thickness variations. The resulting strain profiles are mapped using Bragg diffraction with a hard X-ray probe featuring nanoscale spatial resolution. Compared with traditional heterostructures grown by epitaxial techniques, these strain-engineered samples involve a single chemical composition and are not limited in the choice of compatible materials by any restriction imposed by lattice-matching requirements. Furthermore, their energy band lineups can be patterned in nearly arbitrary shapes using nanolithography to control the thickness profile and can be tuned actively by varying the applied stress. As a result, these structures are attractive for a wide range of device applications (including lasers, LEDs, solar cells, and thermoelectrics) that require complex heterostructure lineups with multiple bandgap energies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

M-STAR: Magnetism second target advanced reflectometer at the Spallation Neutron Source

M-STAR is a next generation polarized neutron reflectometer with advanced capabilities. A new focusing guide concept is optimized for samples with dimensions down to a millimeter range. A proposed hybrid pulse-skipping chopper will enable experiments at constant geometry at one incident angle in a broad range of wavevector transfer Q up to 0.3 A –1 for specular, off-specular, and GISANS measurements. M-STAR will empower nanoscience and spintronics studies routinely on small samples (~2 × 2 mm 2 ) and of atomic-scale thickness using versatile experimental conditions of magnetic and/or electric fields, light, and temperature applied in situ to novel complex device-like nanosystems with multiple buried interfaces. M-STAR will enable improved grazing incidence diffraction measurements, as a surface-sensitive depth-resolved probe of, e.g., the out-of-plane component of atomic magnetic moments in ferromagnetic, antiferromagnetic, and more complex structures as well as in-plane atomic-scale structures inaccessible with contemporary diffractometry and reflectometry. New horizons will be opened by the development of an option to probe near-surface dynamics with inelastic grazing incidence scattering in the time-of-flight mode. These novel options in combination with ideally matched parameters of the second target station will place M-STAR in the world’s leading position for high resolution polarized reflectometry.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Cross-reactive sarbecovirus antibodies induced by mosaic RBD nanoparticles

Broad immune responses are needed to mitigate viral evolution and escape. To induce antibodies against conserved receptor-binding domain (RBD) regions of SARS-like betacoronavirus (sarbecovirus) spike proteins that recognize SARS-CoV-2 variants of concern and zoonotic sarbecoviruses, we developed mosaic-8b RBD nanoparticles presenting eight sarbecovirus RBDs arranged randomly on a 60-mer nanoparticle. Mosaic-8b immunizations protected animals from challenges from viruses whose RBDs were matched or mismatched to those on nanoparticles. Here, we describe neutralizing mAbs isolated from mosaic-8b-immunized rabbits, some on par with Pemgarda, the only currently FDA-approved therapeutic mAb. Deep mutational scanning, in vitro selection of spike resistance mutations, and single-particle cryo-electron microscopy structures of spike–antibody complexes demonstrated targeting of conserved RBD epitopes. Rabbit mAbs included critical D-gene segment RBD-recognizing features in common with human anti-RBD mAbs, despite rabbit genomes lacking an equivalent human D-gene segment, thus demonstrating that the immune systems of humans and other mammals can utilize different antibody gene segments to arrive at similar modes of antigen recognition. These results suggest that animal models can be used to elicit anti-RBD mAbs with similar properties to those raised in humans, which can then be humanized for therapeutic use, and that mosaic RBD nanoparticle immunization coupled with multiplexed screening represents an efficient way to generate and select broadly cross-reactive therapeutic pan-sarbecovirus and pan-SARS-CoV-2 variant mAbs.

Science & Technology - Other Topics↗
DOE OSTI2022

Inverse Analysis with Variational Autoencoders: A Comparison of Shallow and Deep Networks

Inverse problems are applied to determine unknown properties by matching observational data with a physical model that often takes many parameters as input. To overcome the underconstrained nature of inverse problems and achieve good performance, an approach is presented involving regularization with a technique known as a variational autoencoder (VAE), which is trained to map a high-dimensional parameter space with a complex structure to a low-dimensional latent space with a simple structure. We apply this approach to unconditioned realizations of the parameters (heterogeneous hydraulic fields) for a hydrogeological inverse problem. Two types of hydraulic conductivity fields are used to evaluate the characterization for the different levels of heterogeneity complexity of the physical inputs. This approach keeps the computational cost of generating the training data low. The reason is unconditioned realizations neither rely on the observational data used to perform the inverse analysis nor require any groundwater flow model forward runs. In addition, this approach applies regularization on a low-dimensional latent space from the VAE and increases optimization efficiency through automatic differentiation. Furthermore, two different neural network (NN) structures are tested for their utility in using the VAE for inverse analysis. The performance of a deep, convolutional neural network strongly depends on the dimensionality of the latent space, which requires tuning. In contrast, a shallow, dense neural network provides consistently accurate characterization without tuning. Furthermore, our approach evaluates the advantages of the shallow, dense neural network over the deep, convolutional one and enables future application to a wide range of inverse problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Understanding the Effects of Vehicle Platoons on Crash Type and Severity

Crash type is an informative indicator to infer driving behaviors and conditions that cause a crash. For example, rear-end and side-swipe crashes are typically caused by improper vehicle interaction such as sudden lane-changing or speed control while hit-object crashes are likely the result of a single driver’s mistake. This study investigated the impact of vehicles travelling as a group (platoon) and its configuration (i.e., types of vehicles consisting of the platoon) on crash type and severity since the vehicles could affect each other when travelling in close proximity. This study applied Generalized Structure Equation Modeling (GSEM) to capture the complex relationships among the various crash factors such as traffic condition, driver characteristics, environmental conditions, and vehicle interaction to the crash attributes including type and severity. This study collected over 3 million individual vehicle data from 39 traffic count sites in California to estimate the vehicle interactions and driving behaviors. The microscopic traffic data are matched to 1417 crash reports. Results showed that vehicles traveling in platoons are associated with more rear-end and side-swipe crashes. Speed difference in the platoon had a positive effect on hit-object crashes if the platoon comprises vehicles of homogeneous type – either trucks or non-trucks. In addition, human factors such as age and gender were identified as significant influential factors in all type of crashes, however truck involvement particularly played an important role amongst side-swipe crashes. Crash severity was negatively affected by total flow, and rear-end crashes were more likely to be severe compared with hit-object crashes. Based on findings, this study suggests practical operational strategies to reduce traffic instability associated with platooned vehicle patterns. Understanding the high-risk factors for different crash types and severities would provide valuable insights for decision-makers and transportation engineers to develop targeted intervention strategies in consideration of road users and traffic conditions such as fleet mix and speed.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Functional properties of Yttrium Iron Garnett thin films on graphene-coated Gd 3 Ga 5 O 12 for remote epitaxial transfer

Remote epitaxial growth via a graphene interlayer and subsequent mechanical exfoliation of a free-standing membrane is a recently developed technique used to transfer complex oxide thin films onto non-native substrates to form heterogeneously integrated structures for various device applications. One such oxide is Yttrium Iron Garnet (YIG), a material of choice for a wide range of magnetoelectric and spintronic devices owing to its strong magnetic properties and low microwave losses. YIG is predominantly grown on lattice matched Gadolinium Gallium Garnet (GGG) substrates, but by utilizing the remote epitaxy technique, high quality YIG films can be transferred from GGG onto another substrate such as piezoelectric Lithium Niobate (LN). Mechanical strain coupling between the layers and magnetostrictive nature of YIG would allow for the investigation of the interplay in YIG/LN structures leading to the design of novel frequency agile magneto-acoustic devices. In this study functional properties of a YIG film grown using PLD on graphene-coated GGG substrate were investigated and compared to traditional YIG on GGG. Both materials were characterized in terms of crystal structure, surface morphology, FMR and Gilbert damping, and Raman and XAS spectroscopy. Further, it was found that YIG on graphene-coated GGG exhibits significantly higher microwave losses than standard YIG on GGG (FMR linewidth 30.9 vs 2.1 Oe at 10 GHz, and Gilbert damping coefficient 15.4x10 -4 vs 3.4x10 -4 respectively), which was attributed to increased concentration of Fe 2+ cations in YIG/Graphene/GGG. While the damping is higher in these studied films compared to YIG grown directly on GGG, the resulting properties are still very favorable compared to many other competing materials which can be grown without the need for lattice matched substrates, such as metallic ferromagnets.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A source of gamma rays coincident with the shell of the supernova remnant CTB 80

ABSTRACT CTB 80 (G69.0+2.7) is a relatively old (50–80 kyr) supernova remnant (SNR) with a complex radio morphology showing three extended radio arms and a radio and X-ray nebula near the location of the pulsar PSR B1951+32. We report on a study of the GeV emission in the region of CTB 80 with Fermi-Large Area Telescope data. An extended source with a size of 1.3°, matching the size of the infrared shell associated to the SNR, was discovered. The GeV emission, detected up to an energy of ∼20 GeV, is more significant at the location of the northern radio arm where previous observations imply that the SNR shock is interacting with ambient material. Both hadronic and leptonic scenarios can reproduce the multiwavelength data reasonably well. The hadronic cosmic ray energy density required is considerably larger than the local Galactic value and the gamma-ray leptonic emission is mainly due to bremsstrahlung interactions. We conclude that GeV particles are still trapped or accelerated by the SNR producing the observed high-energy emission when interacting with ambient material.

Araya, M.↗
DOE OSTI2024

Stimulated emission tomography for efficient characterization of spatial entanglement

Stimulated-emission tomography (SET) is an excellent tool for characterizing the process of spontaneous parametric down conversion (SPDC), which is commonly used to create pairs of entangled photons for use in quantum information protocols. The use of stimulated emission increases the average number of detected photons by several orders of magnitude compared to the spontaneous process. In a SET measurement, the parametric down conversion is seeded by an intense signal field prepared with specified mode properties rather than by broadband multimodal vacuum fluctuations, as is the case for the spontaneous process. The SET process generates an intense idler field in a mode that is the complex conjugate to the signal mode. In this work we use SET to estimate the joint spatial mode distribution (JSMD) in the Laguerre-Gaussian (LG) basis of the two photons of an entangled photon pair. The pair is produced by parametric down conversion in a beta barium borate (BBO) crystal with type-II phase matching pumped at a wavelength of 405 nm along with a 780 nm seed signal beam prepared in a variety of LG modes to generate an 842 nm idler beam of which the spatial mode distribution is measured. We observe strong idler production and good agreement with the theoretical prediction of its spatial mode distribution. Our experimental procedure should enable the efficient determination of the photon-pair wavefunctions produced by low-brightness SPDC sources and the characterization of high-dimensional entangled-photon pairs. Published by the American Physical Society 2024

Xu, Yang (ORCID:0009000954547320)↗
DOE OSTI2023

Acute Ozone-Induced Transcriptional Changes in Markers of Oxidative Stress and Glucocorticoid Signaling in the Rat Hippocampus and Hypothalamus Are Sex-Specific

Exposure to a prototypic air pollutant ozone (O 3 ) has been associated with the activation of neuroendocrine stress response along with neural changes in oxidative stress (OS), inflammation, and Alzheimer’s disease-like pathologies in susceptible animal models. We hypothesized that neural oxidative and transcriptional changes induced by O 3 in stress responsive regions are sex-dependent. Male and female adult Long–Evans rats were exposed to filtered air or O 3 for two consecutive days (0.8 ppm, 4 h/day) and brain regions were flash-frozen. Activities of cerebellar OS parameters and mitochondrial complex I, II, and IV enzymes were assessed to confirm prior findings. We assessed transcriptional changes in hypothalamus (HYP) and hippocampus (HIP) for markers of OS, microglial activity and glucocorticoid signaling using qPCR. Although there were no O 3 or sex-related differences in the cerebellar activities of OS and mitochondrial enzymes, the levels of protein carbonyls and complex II activities were higher in females regardless of O 3 . There were no statistical differences in baseline expression of genes related to OS (Cat, Dhcr24, Foxm1, Gpx1, Gss, Nfe2l2, Sod1) except for lower HYP Sod1 expression in air-exposed females than males, and higher HIP Gss expression in O 3 -exposed females relative to matched males. Microglial marker Aif1 expression was higher in O 3 -exposed females relative to males; O 3 inhibited Itgam only in males. The expression of Bdnf in HIP and HYP was inhibited by O 3 in both sexes. Genes related to glucocorticoid signaling (Fkbp4, Fkbp5, Hsp90aa1, Hspa4, nr3c1, nr3c2) showed sex-specific effects due to O 3 exposure. Baseline expression of HIP Fkbp4 was higher in females relative to males. O 3 inhibited Nr3c1 in female HIP and male HYP, but Nr3c2 was inhibited in male HYP. Fkbp4 expression was higher in O 3 -exposed females when compared to matched males, whereas Fkbp5 was expressed at higher levels in both brain regions of males and females. These results indicate that sex-specific brain region responses to O 3 might, in part, be caused by OS and regulation of glucocorticoid signaling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

An effective matrix model for dynamical end of the world branes in Jackiw-Teitelboim gravity

We study Jackiw-Teitelboim gravity with dynamical end of the world branes in asymptotically nearly AdS2 spacetimes. We quantize this theory in Lorentz signature, and compute the Euclidean path integral summing over topologies including dynamical branes. The latter will be seen to exactly match with a modification of the SSS matrix model. The resolution of UV divergences in the gravitational instantons involving the branes will lead us to understand the matrix model interpretation of the Wilsonian effective theory perspective on the gravitational theory. We complete this modified SSS matrix model nonperturbatively by extending the integration contour of eigenvalues into the complex plane. Furthermore, we give a new interpretation of other phases in such matrix models. We derive an effective W(Φ) dilaton gravity, which exhibits similar physics semiclassically. In the limit of a large number of flavors of branes, the effective extremal entropy S0,eff has the form of counting the states of these branes.

2D Gravity↗