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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Floquet engineering of polaritonic amplification in dispersive photonic time crystals

In this study, we investigate the dynamics of dispersive photonic time crystals (PTCs) and their potential applications for controlling light-matter interaction. Using the Lorentz-Drude as dispersive material model, we analyze the effects of periodic modulation of dispersion parameters through both theoretical and numerical analysis, revealing the emergence of hybrid bandgaps from the interaction of polaritonic branches with distinctive characteristics. Our study demonstrates that dispersive PTCs offer novel excitation channels and amplification possibilities, that require lower modulation frequencies compared to nondispersive systems thus alleviating experimental challenges for the realization of PTCs in the optical regime. These findings pave the way for advancements in polaritonic lasing and resonant Raman scattering.

Classical optics↗
DOE OSTI2013

Single site-specific integration targeting coupled with embryonic stem cell differentiation provides a high-throughput alternative to in vivo enhancer analyses

Comprehensive analysis of cis-regulatory elements is key to understanding the dynamic gene regulatory networks that control embryonic development. While transgenic animals represent the gold standard assay, their generation is costly, entails significant animal usage, and in utero development complicates time-course studies. As an alternative, embryonic stem (ES) cells can readily be differentiated in a process that correlates well with developing embryos. Here, we describe a highly effective platform for enhancer assays using an Hsp68/ Venus reporter cassette that targets to the Hprt locus in mouse ES cells. This platform combines the flexibility of Gateway H cloning, live cell trackability of a fluorescent reporter, low background and the advantages of single copy insertion into a defined genomic locus. We demonstrate the successful recapitulation of tissue-specific enhancer activity for two cardiac and two haematopoietic enhancers. In addition, we used this assay to dissect the functionality of the highly conserved Ets/Ets/Gata motif in the Scl+19 enhancer, which revealed that the Gata motif is not required for initiation of enhancer activity. We further confirmed that Gata2 is not required for endothelial activity of the Scl+19 enhancer using Gata2 -/- Scl+19 transgenic embryos. We have therefore established a valuable toolbox to study gene regulatory networks with broad applicability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Enabling the First Ever Measurement of Coherent Neutrino Scattering Through Background Neutron Measurements.

Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation/Completion of Episodic Information - Sandia researchers developed novel methods and metrics for studying the computational function of neurogenesis,thus generating substantial impact to the neuroscience and neural computing communities. This work could benefit applications in machine learning and other analysis activities. The purpose of this project was to computationally model the impact of neural population dynamics within the neurobiological memory system in order to examine how subareas in the brain enable pattern separation and completion of information in memory across time as associated experiences.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Sierra/SolidMechanics for Target Pulse Analysis

Sierra is a Multiphysics engineering simulation software suite developed and maintained by Sandia National Laboratories. Created for nuclear weapon needs, it is available to national laboratories with a foreign national restriction. The STS Target Systems analysis team is interested in using Sierra to perform explicit dynamics simulations of the tantalum clad tungsten target blocks as a response to sudden temperature changes induced by proton beam pulses. The capability already exists with Abaqus|Explicit, however, there are time and cost limitations due to licensing. The following document serves as a “quick-start” guide to the successful setup, simulation, and post-processing of a target model in Sierra on the OZ3 computing cluster at the Spallation Neutron Source.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Training Ultrasound Image Classification Deep-Learning Algorithms for Pneumothorax Detection Using a Synthetic Tissue Phantom Apparatus

Ultrasound (US) imaging is a critical tool in emergency and military medicine because of its portability and immediate nature. However, proper image interpretation requires skill, limiting its utility in remote applications for conditions such as pneumothorax (PTX) which requires rapid intervention. Artificial intelligence has the potential to automate ultrasound image analysis for various pathophysiological conditions. Training models require large data sets and a means of troubleshooting in real-time for ultrasound integration deployment, and they also require large animal models or clinical testing. Here, we detail the development of a dynamic synthetic tissue phantom model for PTX and its use in training image classification algorithms. The model comprises a synthetic gelatin phantom cast in a custom 3D-printed rib mold and a lung mimicking phantom. When compared to PTX images acquired in swine, images from the phantom were similar in both PTX negative and positive mimicking scenarios. We then used a deep learning image classification algorithm, which we previously developed for shrapnel detection, to accurately predict the presence of PTX in swine images by only training on phantom image sets, highlighting the utility for a tissue phantom for AI applications.

Boice, Emily N. (ORCID:0000000171802842)↗
DOE OSTI2015

Assessment of model estimates of land-atmosphere CO 2 exchange across Northern Eurasia

A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO 2 ) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO 2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m⁻² yr⁻², equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO 2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO 2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO 2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Analysis of brain patterns using temporal measures

A set of brain data representing a time series of neurophysiologic activity acquired by spatially distributed sensors arranged to detect neural signaling of a brain (such as by the use of magnetoencephalography) is obtained. The set of brain data is processed to obtain a dynamic brain model based on a set of statistically-independent temporal measures, such as partial cross correlations, among groupings of different time series within the set of brain data. The dynamic brain model represents interactions between neural populations of the brain occurring close in time, such as with zero lag, for example. The dynamic brain model can be analyzed to obtain the neurophysiologic assessment of the brain. Data processing techniques may be used to assess structural or neurochemical brain pathologies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Dynamic recovery in silicate-apatite structures under irradiation and implications for long-term immobilization of actinides

The irradiation responses of Ca2La8(SiO4)6O2 and Sr2Nd8(SiO4)6O2 with the apatite structure are investigated to predict their long-term behaviour as host phases for immobilization of actinide elements from the nuclear fuel cycle. Different ions and energies are used to study the effects of dose, temperature, atomic displacement rate and ionization rate on irradiation-induced amorphization and recrystallization. The dose for amorphization increases with temperature in two stages, below and above 150 K. In the high temperature stage relevant to actinide immobilization, the increase of amorphization dose with temperature exhibits a strong dependence on the ratio of ionization rate to displacement rate for the different ions. Data analysis using a dynamic model for amorphization reveals that ionization-induced processes, with activation energy of 0.15 0.02 eV, dominate dynamic recovery for ions from Ne through Xe. For heavier Au ions or for alpha-recoil nuclei emitted in alpha decay of actinides, ionization becomes less dominant and dynamic recovery is controlled primarily by thermally-driven processes. In post-irradiation annealing studies of amorphous samples, epitaxial thermal recrystallization is observed at 1123 K, and irradiation-enhanced nucleation of nanocrystallites is observed under irradiation with heavier ions. The recrystallization temperature under irradiation decreases with increasing ion mass to a value of ~ 823 K, which also defines the thermally-driven critical temperature for amorphization under irradiation with heavy ions. Some partial recovery due to alpha particle irradiation at 300 K is observed that suggests a self-healing mechanism in apatite phases containing actinides. Based on the results and dynamic model, the temperature and time dependences of amorphization in silicate-apatite host phases for actinide immobilization are predicted.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Dynamic Probabilistic Safety Assessment Studies for Advanced Reactor Using RAVEN

Probabilistic Safety Assessment (PSA) is used extensively to evaluate the risks associated with complex engineering systems like Nuclear Power Plants (NPPs). Current PSA models are based on the Event-Tree/Fault-Tree (ET/FT) methodology. ET and FT models are static and are based on Boolean logic approaches. In the past, concerns have been raised in the literature regarding the capability of the traditional static modelling approaches to adequately account for the impact of process, hardware, software, firmware and human interactions on the stochastic system behaviour. To overcome the limitations of the traditional approach to PSA, several dynamic PSA methodologies have been proposed. One of the dynamic PSA methodologies used for dynamic evaluations is Dynamic Event Tree (DET) framework which can be used to assess the impact of the parameter variability and scenario dynamics on the PSA model for the initiating event. The DET framework couples the stochastic model (number of component/trains that start on demand, operator action timing, etc.) with a Thermal-Hydraulic (TH) model of the plant. This paper explores the use of DET along with a case study on advanced reactor. The initiating event selected for the study was Class IV power supply failure event. The TH analysis considering uncertainty in various parameters was performed using RELAP5 and Reactor Analysis and Virtual control ENvironment (RAVEN) tool. Based on the uncertainty analysis, it is concluded that the peak clad temperatures (PCT) are within the limits in all the code runs implying a high-degree of safety margin. However, variation in time to reach the PCT was observed among the code runs and the mean time to reach the PCT was found to be around 8590sec (approximately 2.4 hours). Hence, sufficient time margin is available for human intervention and the operator might have a relatively stress-free state during such an accident scenario. Due to the static nature of the traditional PSA models, the safety margin available was lesser, whereas, with the help of dynamic PSA models, one can demonstrate that the actual available safety margin is more in the present case study and is valuable input from the design point of view.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Interpreting dynamic-compression experiments to uncover the time dependence of freezing: Application to gallium

Using pulsed-power magnetic field sources to compress gallium to gigapascal pressures on nanosecond timescales, we report here experiments on shockless dynamic compression of a liquid metal. Time-resolved velocimetry data reveal signatures of rapid freezing from a metastable liquid state, and we demonstrate that the kinetics of this nonequilibrium solidification can be accurately simulated with a computational modeling framework we have developed in previous studies, where classical nucleation theory is coupled with hydrodynamics. Notably, velocity traces in some of our experiments show evidence of a phase transition, while others do not, even though other types of evidence suggest that solidification may be occurring in all of them. We explain how predictions made by our models regarding the presence or absence of these phase-transition signatures motivated additional experiments that later confirmed the theoretical predictions. Our analysis shows that due to the rapid, quasi-isentropic nature of the loading path, our experiments were able to compress liquid gallium to metastable states that are undercooled below the equilibrium melt temperature by more than 300 K and exhibit pressures that approach five times the equilibrium melt pressure. The understanding gained in this study should form the basis for future dynamic-compression experiments aimed at interrogating melt curves at high pressures.

gallium↗
DOE OSTI2012

NON-THERMAL RESPONSE OF THE CORONA TO THE MAGNETIC FLUX DISPERSAL IN THE PHOTOSPHERE OF A DECAYING ACTIVE REGION

We analyzed Solar Dynamics Observatory line-of-sight magnetograms for a decaying NOAA active region (AR) 11451 along with co-temporal Extreme-Ultraviolet Imaging Spectrometer (EIS) data from the Hinode spacecraft. The photosphere was studied via time variations of the turbulent magnetic diffusivity coefficient, {eta}(t), and the magnetic power spectrum index, {alpha}, through analysis of magnetogram data from the Helioseismic and Magnetic Imager (HMI). These measure the intensity of the random motions of magnetic elements and the state of turbulence of the magnetic field, respectively. The time changes of the non-thermal energy release in the corona was explored via histogram analysis of the non-thermal velocity, v {sub nt}, in order to highlight the largest values at each time, which may indicate an increase in energy release in the corona. We used the 10% upper range of the histogram of v {sub nt} (which we called V {sup upp} {sub nt}) of the coronal spectral line of Fe XII 195 A. A 2 day time interval was analyzed from HMI data, along with the EIS data for the same field of view. Our main findings are the following. (1) The magnetic turbulent diffusion coefficient, {eta}(t), precedes the upper range of the v {sub nt} with the time lag of approximately 2 hr and the cross-correlation coefficient of 0.76. (2) The power-law index, {alpha}, of the magnetic power spectrum precedes V {sup upp} {sub nt} with a time lag of approximately 3 hr and the cross-correlation coefficient of 0.5. The data show that the magnetic flux dispersal in the photosphere is relevant to non-thermal energy release dynamics in the above corona. The results are consistent with the nanoflare mechanism of the coronal heating, due to the time lags being consistent with the process of heating and cooling the loops heated by nanoflares.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Water Film Structure during Rupture as Revealed by MDS Image Analysis

The structure of thin water films during the rupture process was investigated by a new approach, which combines molecular dynamics simulation (MDS) with image processing analysis. The analysis procedure was developed to convert MDS trajectories to readable 3D images. The water films were studied at different thicknesses by MDS to determine the critical thickness at which the film ruptures. The potential energy of each specific film thickness during the simulation time was analyzed, and the results showed that the potential energy of stable films remained unchanged while the potential energy kept decreasing for films which ruptured during the simulation time. By applying the new procedure, the molecular porosity, which is defined as the void fraction between the volume of molecular pores in the water film and the total volume of the water film, was calculated. The results of molecular porosity for different film thicknesses during the simulation time suggested a critical molecular porosity as 49%. In other words, stable films have a molecular porosity of less than 49%. If a water film has a molecular porosity greater than 49%, rupture occurs during the simulation. This research was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences.

molecular dynamics simulation, film stability, ima↗
DOE OSTI2020

Computational Analysis of Water Film Thickness During Rain Events for Assessing Hydroplaning Risk Part 2: Rough Road Surfaces

Hydroplaning occurs when a water film forms on a road during a rain event and vehicles are traveling at a speed that does not provide sufficient time for the tires to push the water film out of the tire path. Under these conditions, the tire loses contact with the road and the driver may lose control over the vehicle. The present study is a part of a multiyear research effort aimed at gaining a better understanding of the factors that contribute to hydroplaning risk in order to minimize the occurrence of hydroplaning accidents. Three-dimensional computational fluid dynamics (CFD) analysis was used to investigate the water film thickness on multilane roads, one of the key parameters in evaluating hydroplaning risk. In the first part of the study, water films forming on wide roadways, i.e. multilane highways with 2, 4, and 6 lanes per side, were analyzed, with varying cross slope, longitudinal slope, and rainfall rate. Roadways with and without curbs and drainage were included in the analysis. The analysis in the first part was limited to nearly smooth asphalt or concrete surfaces because the maximum roughness height that can be specified in a CFD model using wall functions to determine shear stress at the road surface boundary is one half the thickness of computational cell layer adjacent to the boundary and the need to resolve the vertical velocity distribution in a thin water film requires cell layers that are a fraction of a millimeter thick. In this part of the study, the analysis was extended to consider the influence of pavement roughness over a range extending up 3.6 mm on the development of water film thickness. Various methods of modeling roughness were investigated and are presented: the roughness height model, a meshed-out geometry of the macrotexture of the pavement, and a porous region model. The computational results were analyzed and compared with experimental measurements performed by Gallaway et al.

42 ENGINEERING↗
DOE OSTI2024

Entropy Analysis of FPGA Interconnect and Switch Matrices for Physical Unclonable Functions

Random variations in microelectronic circuit structures represent the source of entropy for physical unclonable functions (PUFs). In this paper, we investigate delay variations that occur through the routing network and switch matrices of a field-programmable gate array (FPGA). The delay variations are isolated from other components of the programmable logic, e.g., look-up tables (LUTs), flip-flops (FFs), etc., using a feature of Xilinx FPGAs called dynamic partial reconfiguration (DPR). A set of partial designs is created to fix the placement of a time-to-digital converter (TDC) and supporting infrastructure to enable the path delays through the target interconnect and switch matrices to be extracted by subtracting out common-mode delay components. Delay variations are analyzed in the different levels of routing resources available within FPGAs, i.e., local routing and across-chip routing. Data are collected from a set of Xilinx Zynq 7010 devices, and a statistical analysis of within-die variations in delay through a set of the randomly-generated and hand-crafted interconnects is presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-C-303-02: Correlating Metabolic Response to Radiation Therapy with HIF-1alpha Expression

Purpose: To understand radiation induced alterations in cellular metabolism which could be used to assess treatment or normal tissue response to aid in patient-specific adaptive radiotherapy. This work aims to compare the metabolic response of two head and neck cell lines, one malignant (UM-SCC-22B) and one benign (Normal Oral Keratinocyte), to ionizing radiation. Responses are compared to alterations in HIF-1alpha expression. These dynamics can potentially serve as biomarkers in assessing treatment response allowing for patient-specific adaptive radiotherapy. Methods: Measurements of metabolism and HIF-1alpha expression were taken before and X minutes after a 10 Gy dose of radiation delivered via an orthovoltage x-ray source. In vitro changes in metabolic activity were measured via fluorescence lifetime imaging (FLIM) to assess the mean lifetime of NADH autofluorescence following a dose of 10 Gy. HIF-1alpha expression was measured via immunohistochemical staining of in vitro treated cells and expression was quantified using the FIJI software package. Results: FLIM demonstrated a decrease in the mean fluorescence lifetime of NADH by 100 ps following 10 Gy indicating a shift towards glycolytic pathways for malignant cells; whereas this benign cell line showed little change in metabolic signature. Immunohistochemical analysis showed significant changes in HIF-1alpha expression in response to 10 Gy of radiation that correlate to metabolic profiles. Conclusion: Radiation induces significant changes in metabolic activity and HIF-1alpha expression. These alterations occur on time scales approximating the duration of common radiation treatments (approximately tens of minutes). Further understanding these dynamics has important implications with regard to improvement of therapy and biomarkers of treatment response.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Comparing the Performance of Three Land Models in Global C Cycle Simulations: A Detailed Structural Analysis: Structural Analysis of Land Models

Land models are valuable tools to understand the dynamics of global carbon (C) cycle. Various models have been developed and used for predictions of future C dynamics but uncertainties still exist. Diagnosing the models’ behaviors in terms of structures can help to narrow down the uncertainties in prediction of C dynamics. In this study three widely used land surface models, namely CSIRO’s Atmosphere Biosphere Land Exchange (CABLE) with 9 C pools, Community Land Model (version 3.5) combined with Carnegie-Ames-Stanford Approach (CLM-CASA) with 12 C pools and Community Land Model (version 4) (CLM4) with 26 C pools were driven by the observed meteorological forcing. The simulated C storage and residence time were used for analysis. The C storage and residence time were computed globally for all individual soil and plant pools, as well as net primary productivity (NPP) and its allocation to different plant components’ based on these models. Remotely sensed NPP and statistically derived HWSD, and GLC2000 datasets were used as a reference to evaluate the performance of these models. Results showed that CABLE exhibited better agreement with referenced C storage and residence time for plant and soil pools, as compared with CLM-CASA and CLM4. CABLE had longer bulk residence time for soil C pools and stored more C in roots, whereas, CLM-CASA and CLM4 stored more C in woody pools due to differential NPP allocation. Overall, these results indicate that the differences in C storage and residence times in three models are largely due to the differences in their fundamental structures (number of C pools), NPP allocation and C transfer rates. Our results have implications in model development and provide a general framework to explain the bias/uncertainties in simulation of C storage and residence times from the perspectives of model structures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Combining RAVEN, RELAP5-3D, and PHISICS for Fuel Cycle and Core Design Analysis for New Cladding Criteria

The Nuclear Regulatory Commission (NRC) has considered revision of 10 CFR 50.46C rule to account for the effects of burn-up rate in future analysis of reactor accident scenarios so that safety margins may evolve with the operation and reloading of the reactor as dynamic limits. In order to find these limiting conditions, both cladding oxidation and maximum temperature must be cast as functions of fuel exposure. It is computationally intensive to run a plant model through a long duration operational transient to the time of fuel reload, and this must be repeated for each reload until the time of the accident scenario. Moreover, fuel reload patterns may differ in many ways so that calculations with many different core configurations must be considered. To perform such new analyses in a reasonable amount of computational time with good accuracy, Idaho National Laboratory (INL) has developed new multi-physics tools by combining existing codes and adding new capabilities. The Parallel Highly Innovative Simulation INL Code System (PHISICS) toolkit for neutronic and reactor physics is coupled with the Reactor Excursion and Leak Analysis Program (RELAP5-3D) for the Loss of Coolant Accident (LOCA) analysis and RAVEN for the Probabilistic Risk Assessment (PRA) and margin characterization analysis. Expansion of code capability was also necessary. For RELAP5-3D to process a single sequence of cores in a continuous run required modification of RELAP5-3D to restart a sequence of input decks, each with a slightly modified neutronics model or thermal-hydraulic flow region and culminating in an accident scenario. A new multi-deck input processing capability was developed and verified for this analysis. In conclusion, the combined RAVEN/PHISICS/RELAP5-3D tool is used to analyze a typical Pressurized Water Reactor (PWR).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

SUPERGRANULES AS PROBES OF THE SUN'S MERIDIONAL CIRCULATION

Recent analysis revealed that supergranules (convection cells seen at the Sun's surface) are advected by the zonal flows at depths equal to the widths of the cells themselves. Here we probe the structure of the meridional circulation by cross-correlating maps of the Doppler velocity signal using a series of successively longer time lags between maps. We find that the poleward meridional flow decreases in amplitude with time lag and reverses direction to become an equatorward return flow at time lags >24 hr. These cross-correlation results are dominated by larger and deeper cells at longer time lags. (The smaller cells have shorter lifetimes and do not contribute to the correlated signal at longer time lags.) We determine the characteristic cell size associated with each time lag by comparing the equatorial zonal flows measured at different time lags with the zonal flows associated with different cell sizes from a Fourier analysis. This association gives a characteristic cell size of {approx}50 Mm at a 24 hr time lag. This indicates that the poleward meridional flow returns equatorward at depths >50 Mm-just below the base of the surface shear layer. A substantial and highly significant equatorward flow (4.6 {+-} 0.4 m s{sup -1}) is found at a time lag of 28 hr corresponding to a depth of {approx}70 Mm. This represents one of the first positive detections of the Sun's meridional return flow and illustrates the power of using supergranules to probe the Sun's internal dynamics.

79 ASTRONOMY AND ASTROPHYSICS↗