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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Chromatin Folding, Fragile Sites, and Chromosome Aberrations Induced by Low- and High- LET Radiation

We previously demonstrated non-random distributions of breaks involved in chromosome aberrations induced by low- and high-LET radiation. To investigate the factors contributing to the break point distribution in radiation-induced chromosome aberrations, human epithelial cells were fixed in G1 phase. Interphase chromosomes were hybridized with a multicolor banding in situ hybridization (mBAND) probe for chromosome 3 which distinguishes six regions of the chromosome in separate colors. After the images were captured with a laser scanning confocal microscope, the 3-dimensional structure of interphase chromosome 3 was reconstructed at multimega base pair scale. Specific locations of the chromosome, in interphase, were also analyzed with bacterial artificial chromosome (BAC) probes. Both mBAND and BAC studies revealed non-random folding of chromatin in interphase, and suggested association of interphase chromatin folding to the radiation-induced chromosome aberration hotspots. We further investigated the distribution of genes, as well as the distribution of breaks found in tumor cells. Comparisons of these distributions to the radiation hotspots showed that some of the radiation hotspots coincide with the frequent breaks found in solid tumors and with the fragile sites for other environmental toxins. Our results suggest that multiple factors, including the chromatin structure and the gene distribution, can contribute to radiation-induced chromosome aberrations.

Zhang, Ye↗
DOE OSTI2023

Shedding light on the 239Pu fission source term with new high-precision experiments and advanced fission modeling

In the last decade, there has been a renaissance of fission research resulting in new high-precision experiments and advanced fission modeling. For instance, the Chi-Nu and CEA teams supplied, for the first time, the 239 Pu prompt fission neutron spectrum (PFNS) for broad ranges of incident and outgoing neutron energies. The CEA team also measured 239 Pu average prompt neutron multiplicities, ν ̄ p , with lower statistical uncertainties and a technique significantly different than the one used in the past. The NIFFTE collaboration provided 239 Pu( n ,f)/ 235 U( n ,f) cross section shape ratios with uncertainties below 1% utilizing a novel detector type. Advanced fission event generators were developed, among them CGMF, FIFRELIN, FREYA, and GEF, which calculate post-scission fission observables in a correlated manner. These new experimental data and more consistent fission models change the evaluated PFNS, ν ̄ p , and ( n ,f) cross sections, some only modestly, compared to ENDF/B-VIII.0. In turn, the individual new nuclear data distinctly change simulated effective neutron multiplication factors of fast critical assemblies, but their combined impact is small, while affecting the prediction of LLNL pulsed sphere neutron leakage spectra and reaction rates only within experimental uncertainties. Also, the parameters obtained from fitting to ν ̄ p reproduce various post-scission fission observables within the uncertainties of experimental data. This indicates that new differential experiments and consistent fission modeling reduce compensating errors present in ENDF/B-VIII.0.

fission cross section↗
DOE OSTI2011

J/{psi} production and elliptic flow in relativistic heavy-ion collisions

Using the two-component model for charmonium production, which includes contributions from both initial hard nucleon-nucleon scattering and from regeneration in the quark-gluon plasma, we study the nuclear modification factor R{sub AA} and elliptic flow v{sub 2} of J/{psi} in relativistic heavy-ion collisions. For the expansion dynamics of produced hot, dense matter, we introduce a schematic fireball model with its transverse acceleration determined from the pressure gradient inside the fireball and azimuthally anisotropic expansion parametrized to reproduce measured v{sub 2} of light hadrons. We assume that light hadrons freeze out at the temperature of 120 MeV while charmonia freeze out at 160 MeV, similar to the kinetic and chemical freeze-out temperatures in the statistical model, respectively. For the properties of charmonia in the quark-gluon plasma, we use the screening mass between their charm and anticharm quarks and their dissociation cross sections given by the perturbative quantum chromodynamical (pQCD) calculations in the leading order and up to the next-to-leading order, respectively. For the relaxation time of charm and anticharm quarks in the quark-gluon plasma, we also use the one calculated in the leading-order pQCD. Modeling the effect of higher-order corrections in pQCD by introducing multiplicative factors to the dissociation cross sections of charmonia and the elastic scattering cross sections of charm and anticharm quarks, we find that this effect is small for the R{sub AA} of J/{psi} as they suppress the number of initially produced J/{psi} but enhance the number of regenerated ones. The higher-order corrections increase, however, the v{sub 2} of J/{psi}. Our results suggest that the v{sub 2} of J/{psi} can play an important role in discriminating between J/{psi} production from initial hard collisions and from regeneration in the quark-gluon plasma.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Multi-fidelity modeling to predict the rheological properties of a suspension of fibers using neural networks and Gaussian processes

Unveiling the rheological properties of fiber suspensions is of paramount interest to many industrial applications. There are multiple factors, such as fiber aspect ratio and volume fraction, that play a significant role in altering the rheological behavior of suspensions. Three-dimensional (3D) numerical simulations of coupled differential equations of the suspension of fibers are computationally expensive and time-consuming. Machine learning algorithms can be trained on the available data and make predictions for the cases where no numerical data are available. However, some widely used machine learning surrogates, such as neural networks, require a relatively large training dataset to produce accurate predictions. Multi-fidelity models, which combine high-fidelity data from numerical simulations and less expensive lower fidelity data from resources such as simplified constitutive equations, can pave the way for more accurate predictions. Here, we focus on neural networks and the Gaussian processes with two levels of fidelity, i.e., high and low fidelity networks, to predict the steady-state rheological properties, and compare them to the single-fidelity network. High-fidelity data are obtained from direct numerical simulations based on an immersed boundary method to couple the fluid and solid motion. The low-fidelity data are produced by using constitutive equations. Multiple neural networks and the Gaussian process structures are used for the hyperparameter tuning purpose. Results indicate that with the best choice of hyperparameters, both the multi-fidelity Gaussian processes and neural networks are capable of making predictions with a high level of accuracy with neural networks demonstrating marginally better performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Extension of Large Fire Emissions From Summer to Autumn and Its Drivers in the Western US

Abstract Burned areas in the western US have increased ten‐fold since 1980s, which are attributable to multiple factors, including increasing heat, changing precipitation patterns, and extended drought. To better understand how these factors contribute to large fire emissions (gridded monthly fire emissions >95th percentile of all the fire emissions in the western US; 0.009 Gg/month), we build a machine learning model to predict fire emissions (PM 2.5 ) over the western US at 0.25° resolution, interpreted using explainable artificial intelligence (XAI). From the predictor contributions derived from XAI, we conduct k‐means clustering analysis to identify four clusters of predictor variables representing different drivers of large fire emissions. The four clusters feature the contributions of fuel load (Cluster 1) and different levels of dryness (Cluster 2–4), controlled by fuel moisture, drought condition, and fire‐favorable large‐scale meteorological patterns featuring high temperature, high pressure, and low relative humidity. In the past two decades, large fire emissions peak in summer. However, large fire emissions increased significantly in September and October in 2010–2020 relative to 2000–2009, extending the peak large fire emissions from summer to autumn. The larger enhancements of large fire emissions during autumn compared to summer are contributed by decreased fuel moisture, along with more frequent concurrent fire‐favorable large‐scale meteorological patterns and drought. These results highlight fuel drying as a common driver supported by multiple drivers, such as warmer temperature and more frequent synoptic patterns favorable for fires, in increasing the autumn risk of large fire emissions across the western US.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

A Multi-Scale Sampling Strategy for Detecting Physiologically Significant Signals in AVIRIS Imagery

Models of photosynthetic production at ecosystem and global scales require multiple input parameters specifying physical and physiological surface features. While certain physical parameters (e.g., absorbed photosynthetically active radiation) can be derived from current satellite sensors, other physiologically relevant measures (e.g., vegetation type, water status, carboxylation capacity, or photosynthetic light-use efficiency), are not generally directly available from current satellite sensors at the appropriate geographic scale. Consequently, many model parameters must be assumed or derived from independent sources, often at an inappropriate scale. An abundance of ecophysiological studies at the leaf and canopy scales suggests strong physiological control of vegetation-atmosphere CO2 and water vapor fluxes, particularly in evergreen vegetation subjected to diurnal or seasonal stresses. For example hot, dry conditions can lead to stomatal closure, and associated "downregulation" of photosynthetic biochemical processes, a phenomenon often manifested as a "midday photosynthetic depression". A recent study with the revised simple biosphere (SiB2) model demonstrated that photosynthetic downregulation can significantly impact global climate. However, at the global scale, the exact significance of downregulation remains unclear, largely because appropriate physiological measures are generally unavailable at this scale. Clearly, there is a need to develop reliable ways of extracting physiologically relevant information from remote sensing. Narrow-band spectrometers offer many opportunities for deriving physiological parameters needed for ecosystem and global scale photosynthetic models. Experimental studies on the ground at the leaf- to stand-scale have indicated that several narrow-band features can be used to detect plant physiological status. One physiological signal is caused by xanthophyll cycle pigment activity, and is often expressed as the Photochemical Reflectance Index (PRI). Because the xanthophyll cycle pigments are photoregulatory pigments closely linked to photosynthetic function, this index can be used to derive relative photosynthetic rates. An additional signal with physiological significance is the 970 nm water absorption band, which provides a measure of liquid water content. This feature has been quantified both using a simple 2-band ratio (900/970 nm, here referred to as the "Water Band Index" or WBI;), and using the "continuum removal" method. Current atmospheric correction methods for AVIRIS imagery also obtain quantitative expressions of surface liquid water absorption based on the 970 nm water band and may be comparable to ground-based estimates of water content using this feature. However, physiological interpretations of both the PRI and the WBI are best understood at the leaf and canopy scales, where complications of atmospheric interference and complex stand and landscape features can be minimized, and where experimental manipulations can be readily applied. Currently it is not known whether these physiological indices can be used to derive meaningful physiological information from AVIRIS imagery. In addition to the problem of atmospheric interference, another challenge is that any simple physiological index can be confounded by multiple factors unrelated to physiology, and this problem can become more severe at progressively larger spatial scales. For example, previous work has suggested that both the PRI and the WBI, are strongly correlated with other optical measures of canopy structure (e.g., the Normalized Difference Vegetation Index or green vegetation fraction), indicating a confounding effect of structure on physiological signals at the larger, landscape scale. Furthermore, the normal operating mode of most imaging spectrometers does not allow simultaneous, ground truthing at a level of detail needed for physiological sampling. Additionally, manipulative experiments of physiology are difficult to apply at a geographic scale suitable for comparison with remote imagery, which often works at spatial scales that are several orders of magnitude larger than those typically used for physiological studies. These limitations require the consideration of alternative approaches to validating physiological information derived from AVIRIS data. In this report, we present a multi-scale sampling approach to detecting physiologically significant signals in narrow-band spectra. This approach explores the multi-dimensional data space provided by narrow-band spectrometry, and combines AVIRIS imagery at a large scale, with ground spectral sampling at an intermediate scale, and detailed ecophysiological measurements at a fine scale, to examine seasonally and spatially changing relationships between multiple structural and physiological variables. Examples of this approach are provided by simultaneous sampling of the Normalized Difference Vegetation Index (NDVI), an index of fractional PAR interception and green vegetation cover, the Water Band Index (WBI, an index of liquid water absorption, and the Photochemical Reflectance Index (PRI, an index of xanthophyll cycle pigment activity and photosynthetic light-use efficiency. By directly linking changing optical properties sampled on the ground with measurable physiological states, we hope to develop a basis for interpreting similar signals in AVIRIS imagery.

Gamon, John A.↗
DOE OSTI2022

A compendium and meta-analysis of flatband potentials for TiO2, ZnO, and SnO2 semiconductors in aqueous media

Semiconductor/electrolyte interfaces are of great interest to numerous scientific fields including renewable energy, (photo)electrochemistry, and energy storage. The semiconductor flatband potential is a key parameter in locating the conduction band minimum or valence band maximum of the semiconductor material in electrolyte. Despite its importance for quantifying the energetic location of the semiconductor bands, literature reports for the same material demonstrate significant variability in the flatband potential. In this compendium and meta-analysis, reported flatband potentials of the common semiconductor materials TiO2, SnO2, and ZnO in aqueous electrolyte were compiled and assessed to quantify the spread in literature flatband potentials as well as determine the factors that lead to the significant spread. For TiO2, SnO2, and ZnO, literature flatband potentials referenced to the reversible hydrogen electrode span a range of nearly 2 V each. Flatband potential tabulations were separated by variables such as the solution pH, the crystalline polymorph, the crystal facet, the morphology, and the dimensions or combinations of these variables to assess the factors that contribute to the observed spread. Important and surprising findings from these categorizations are summarized: (1) Even for the narrowest categorizations, the spread in flatband potential is still large. (2) Flatband potentials of TiO2 and SnO2 follow the expected Nernstian dependence with solution pH. ZnO materials deviate from this Nernstian dependence. (3) In the aggregate, there is no statistically significant difference in the reported flatband potentials of anatase and rutile TiO2. Single crystal tabulations were the only distributions to have statistically significant differences in the flatband potential between anatase and rutile TiO2. (4) Anatase TiO2 materials with a nanotube morphology appear to have a +400 mV difference in mean flatband potential compared to all other morphologies, but we argue that this is likely due to widespread misuse of the Mott–Schottky analysis. Other interesting findings are revealed within the spread of literature flatband potentials, and possible explanations are provided to generate discussion. We also briefly review and discuss common techniques that were used to determine the flatband potential and the pitfalls/criticisms of these techniques. Last, we discuss some ways in which future research on the determination of the flatband potential can be performed to improve the reliability of reported values and the quality of the work. In total, the results from this meta-analysis suggest multiple factors can affect the measured flatband potential and that an abundance of caution should be applied when attempting to quantify the flatband potential of complex or nanostructured systems.

Patel, Milan Y. (ORCID:0000000291948141)↗
DOE OSTI2022

Evaluated 238 U(n,f) Average Prompt Fission Neutron Multiplicities Including the CGMF Model

This report documents an evaluation of the average prompt fission neutron multiplicity, $\overline{v}_p$, of 238 U from 800 keV to MeV. This evaluation had to be re-done from “scratch” as the input to previous $\overline{v}_p$ evaluations, specifically ENDF/B-VIII.0, was not found. That means that all available experimental data were re-analyzed and uncertainties were re-estimated. The new evaluated 238 U $\overline{v}_p$ based on only experimental data differs distinctly from ENDF/B-VIII.0 $\overline{v}_p$ from 2 to 4.5 MeV, and from 6 to 7 MeV, and is otherwise similar. The difference from 2 to 4.5 MeV stems from the fact that ENDF/B-VIII.0 was tweaked in this energy range to data of Frehaut, while two other, equally trustworthy, data sets would indicate an evaluated 238 U $\overline{v}_p$ that is up to 2% higher. Also, second chance fission in ENDF/B-VIII.0 was smoothed over from 6–7 MeV. Another major difference to ENDF/B-VIII.0 is that one of the evaluations presented here includes model information from the Hauser-Feshbach fission fragment decay code CGMF, while ENDF/B-VIII.0 is based purely on experimental data. CGMF links several fission quantities with each other; $\overline{v}_p$ is predicted by assumptions made on, e.g., pre-neutron emission yields as a function of mass, the total kinetic energy, or spin and parity of fission fragments. This allows to validate the new 238 U $\overline{v}_p$ by using CGMF parameters obtained from fitting to experimental 238 U $\overline{v}_p$ to predict yields as a function of mass, the average total kinetic energy, or the mean energy of the prompt fission neutron spectrum. These model-predicted values can then be compared to experimental and evaluated data. The model-predicted fission-observable values using evaluated parameters obtained here are reasonably close to experimental data for some observables, but are farther away from experimental data related to TKE observables. In addition to that, the evaluated 238 U(n,f) $\overline{v}_p$ shows similar deviations from ENDF/B-VIII.0 as for the evaluation with only experimental data. This difference is expected to lead to changes in simulated effective neutron multiplication factor, $k_{eff}$ of ICSBEP critical assemblies that are sensitive to 238 U in the fast range (BigTen, Flattop, Flattop-Pu). These changes in $k_{eff}$ need to be counter-balanced. Chi-Nu PFNS experimental data are expected to be released in the next few months that might lead to the needed changes in the PFNS. Until then, we hold off in benchmarking the new 238 U(n,f) $\overline{v}_p$ as well as submitting it to ENDF/B-VIII.1. Also, new high-precision 238 U $\overline{v}_p$ are expected to be measured by the CEA in the next two years that will shed further light on question on 238 U $\overline{v}_p$ from 2–4.5 and 6–7 MeV.

238U↗
DOE OSTI2018

Improving Land-Surface Modeling of Evapotranspiration Processes in Tropical Forests (Final Report)

Land surface models are used to represent terrestrial processes that shape global climate; examples of these processes include evaporation, plant water use, and photosynthesis. While much progress has been made to improve and refine these models, some hydrological processes are not well captured, which hinders our ability to understand land-atmosphere interactions and ultimately to predict impacts of climate change on water resources. The inadequate representation of evapotranspiration may partly explain why global climate models do not match observed precipitation patterns. Multiple factors contribute to this problem. In moist tropical regions, high humidity, leaf wetness, and cloud cover combine to suppress forest water use and possibly reduce forest growth in ways that are poorly understood. Mountainous areas pose additional difficulties, as standard modeling and measurement techniques are not readily applied in rough terrain. In this project, we aimed to improve our understanding and modeling of fluxes of water vapor and carbon dioxide to and from tropical forests. To do this, we collected a suite of data from the mountainous rainforest surrounding the Texas A&M Soltis Center in San Ramon, Costa Rica. From 2014 to 2018, a suite of variables were measured, including: in-canopy profiles of water vapor, carbon dioxide, temperature, light, and leaf wetness; transpiration, evapotranspiration, carbon flux, and soil respiration; and local weather conditions. Leaf-scale measurements were used to find photosynthesis rates and derive their parameters. Using this data set, we were able to better quantify the relationships between assimilation and transpiration and their main drivers in tropical forests. These variables were namely available light, vapor pressure deficit, and leaf wetness, but not soil moisture, which exerted no detectable control. We also showed the vertical variability in canopy microclimates and how neglecting forest layers in models may misrepresent overall fluxes. The data were then used to test and refine evapotranspiration and energy budget formulations in the Community Land Model. Fluxes and energy budget components were compared to simulated values from CLM4.5 and CLM.5. The biggest discrepancies arose from hillslope shading effects, particularly mismatches in afternoon carbon fluxes, with notable differences in transpiration rates and sap flux due to capacitance in large trees. Secondary, but still significant issues included unrealistic leaf wetness and leaf drying rates, as well as air and vegetation temperatures, both of which were likely linked to CLM’s formulations controlling wet leaf and sunlit/shaded leaf fractions. Modeling multiple layers in the canopy via the newly released CLM-ml and making adjustments to existing parameters both show promise in resolving these issues. In total, the project has produced 5 peer-reviewed articles, 24 presentations, 2 theses, 4 public outreach items, and 4 publically available datasets, to date. Additional products are expected pending the completion of an additional thesis. Data has also been shared with several collaborative networks, including PHENOCAM and SAPFLUXNET.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Active Mixing of Disparate Inks for Multimaterial 3D Printing

3D printing of multimaterial parts relies upon efficient mixing of the ink components and a rapid response to composition changes. However, at low Reynolds numbers and large Peclet numbers, mixing disparate viscosity and density inks poses a challenge. In this study, the performance of active micromixers for disparate non-Newtonian inks is evaluated using both experiments and computational fluid dynamics simulations. The mixing efficiencies are compared with scaling relationships for active micromixers. Using detailed simulation results, multiple factors are identified that can impact the micromixer response time during a composition change. Finally, an active micromixer is proposed and evaluated to efficiently mix arbitrary multimaterial ink compositions and produce fine composition gradients within printed parts.

3D printing↗
DOE OSTI2017

Elucidating the Irreversible Mechanism and Voltage Hysteresis in Conversion Reaction for High-Energy Sodium-Metal Sulfide Batteries

We present that irreversible electrochemical behavior and large voltage hysteresis are commonly observed in battery materials, in particular for materials reacting through conversion reaction, resulting in undesirable round-trip energy loss and low coulombic efficiency. Seeking solutions to these challenges relies on the understanding of the underlying mechanism and physical origins. Here, this study combines in operando 2D transmission X-ray microscopy with X-ray absorption near edge structure, 3D tomography, and galvanostatic intermittent titration techniques to uncover the conversion reaction in sodium–metal sulfide batteries, a promising high-energy battery system. This study shows a high irreversible electrochemistry process predominately occurs at first cycle, which can be largely linked to Na ion trapping during the first desodiation process and large interfacial ion mobility resistance. Subsequently, phase transformation evolution and electrochemical reaction show good reversibility at multiple discharge/charge cycles due to materials' microstructural change and equilibrium. The origin of large hysteresis between discharge and charge is investigated and it can be attributed to multiple factors including ion mobility resistance at the two-phase interface, intrinsic slow sodium ion diffusion kinetics, and irreversibility as well as ohmic voltage drop and overpotential. In conclusion, this study expects that such understandings will help pave the way for engineering design and optimization of materials microstructure for future-generation batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Effective gravitational couplings of four-dimensional $ \mathcal{N} $ = 2 supersymmetric gauge theories

The low energy effective couplings of a four-dimensional N = 2 supersymmetric gauge theory to topological invariants of the background gravitational field are described by two functions A and B. These two functions play an important role in the study of topologically twisted four-dimensional N = 2 supersymmetric gauge theories and in the computation of central charges of N = 2 superconformal theories. In this paper, we compute A and B from the partition function in the Ω-background for SU(2) gauge theories. Our results not only confirm the predicted expressions of the effective gravitational couplings, but also give the previously undetermined overall multiplicative factors. We also analyze A and B for the SU(N) super-Yang-Mills theory, and confirm all the previous predictions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Muon g -2 from millicharged hidden confining sector

We provide a novel explanation to the muon g - 2 excess with new physics contributions at the two-loop level. In this scenario, light millicharged particles are introduced to modify the photon vacuum polarization that contributes to muon g - 2 at one additional loop. The muon g - 2 excess can be explained with the millicharged particle mass m χ around 10 MeV and the product of the multiplicity factor and millicharge squared of N χ ε 2 ~ 10 -3 . The minimal model faces severe constraints from direct searches at fixed-target experiments and astrophysical observables. However, if the millicharged particles are also charged under a hidden confining gauge group SU(N χ ) with a confinement scale of MeV, hidden-sector hadrons are unstable and can decay into neutrinos, which makes this scenario consistent with existing constraints. This explanation can be well tested at low-energy lepton colliders such as BESIII and Belle II as well as other proposed fixed-target experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Method for assessing coal-floor water-inrush risk based on the variable-weight model and unascertained measure theory

Water inrush from coal-seam floors greatly threatens mining safety in North China and is a complex process controlled by multiple factors. This study presents a mathematical assessment system for coal-floor water-inrush risk based on the variable-weight model (VWM) and unascertained measure theory (UMT). In contrast to the traditional constant-weight model (CWM), which assigns a fixed weight to each factor, the VWM varies with the factor-state value. The UMT employs the confidence principle, which is more effective in ordered partition problems than the maximum membership principle adopted in the former mathematical theory. The method is applied to the Datang Tashan Coal Mine in North China. First, eight main controlling factors are selected to construct the comprehensive evaluation index system. Subsequently, an incentive-penalty variable-weight model is built to calculate the variable weights of each factor. Then, the VWM-UMT model is established using the quantitative risk-grade divide of each factor according to the UMT. On this basis, the risk of coal-floor water inrush in Tashan Mine No. 8 is divided into five grades. For comparison, the CWM is also adopted for the risk assessment, and a differences distribution map is obtained between the two methods. Finally, the verification of water-inrush points indicates that the VWM-UMT model is powerful and more feasible and reasonable. The model has great potential and practical significance in future engineering applications.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2018

Hydrogen Embrittlement Susceptibility and Safety Control of Reheated CGHAZ in X80 Welded Pipeline

Coarse-grained heat-affected zone (CGHAZ) exhibits the highest hydrogen embrittlement (HE) susceptibility, which changes under the influence of thermal cycle. In this study, slow strain rate tension (SSRT) tests were conducted to investigate the HE susceptibility of reheated CGHAZs and the critical hydrogen pressure for fracture failure. Results show that intercritically reheated CGHAZ (ICCGHAZ) possesses the lowest HE resistance. Analyses of HE index and fracture indicate that the critical hydrogen pressure is 3.5 MPa. Microstructure analysis reveals that HE susceptibility is associated with multiple factors, such as phase composition, grain coarsening, HAB density, and MA constituent. Blocky necklace-like MA constituent along prior austenite boundaries plays a predominant role in intensifying the HE susceptibility of ICCGHAZ.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Performance and accuracy of criticality calculations performed using WARP – A framework for continuous energy Monte Carlo neutron transport in general 3D geometries on GPUs

In this companion paper to "Algorithmic Choices in WARP - A Framework for Continuous Energy Monte Carlo Neutron Transport in General 3D Geometries on GPUs" (doi:10.1016/j.anucene.2014.10.039), the WARP Monte Carlo neutron transport framework for graphics processing units (GPUs) is benchmarked against production-level central processing unit (CPU) Monte Carlo neutron transport codes for both performance and accuracy. We compare neutron flux spectra, multiplication factors, runtimes, speedup factors, and costs of various GPU and CPU platforms running either WARP, Serpent 2.1.24, or MCNP 6.1. WARP compares well with the results of the production-level codes, and it is shown that on the newest hardware considered, GPU platforms running WARP are between 0.8 to 7.6 times as fast as CPU platforms running production codes. Also, the GPU platforms running WARP were between 15% and 50% as expensive to purchase and between 80% to 90% as expensive to operate as equivalent CPU platforms performing at an equal simulation rate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗