SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Not Available
High fidelity kinetic equilibria are crucial for tokamak modeling and analysis. Manual workflows for constructing kinetic equilibria are time consuming and subject to user error, motivating development of automated equilibrium reconstruction tools to provide accurate and consistent reconstructions for downstream physics analysis. These automated tools also provide access to kinetic equilibria at large database scales, which enables the quantification of general uncertainties arising from equilibrium reconstruction techniques. In this paper, we compare a large database of DIII-D kinetic equilibria generated manually by physics experts to equilibria from automated kinetic reconstruction tools, assessing the impact of reconstruction method on equilibrium parameters and resulting magnetohydrodynamic stability calculations. We find agreement among scalar parameters, whereas profile quantities, such as the bootstrap current, show larger disagreements. We analyze ideal kink and classical tearing stability with DCON and STRIDE respectively, finding that the kink stability calculation is generally more robust than the tearing index Δ' calculation. We find that in 90% of cases, both kink stability classifications are unchanged between the manual expert and automated kinetic equilibria.
Direct laser acceleration (DLA) enables energy transfer from an ultra-high-intensity laser to plasma electrons and underpins many laser-driven particle and radiation-source concepts. A laser-driven azimuthal plasma magnetic field is a key player in this process: it confines energetic electrons, induces betatron oscillations, and makes possible a resonant interaction between the betatron motion and the laser field. While this betatron resonance can enhance electron energy gain, the gain itself generally drives frequency detuning and promotes largely reversible energy exchange that limits net acceleration. Here we show, using a test-electron model with prescribed fields, that a slow longitudinal increase of the quasi-static plasma magnetic field qualitatively changes DLA by introducing hysteresis in the ratio of the betatron frequency to the laser frequency experienced by the electron, so that this ratio depends on the prior evolution of the electron even at the same energy. This hysteresis enables phase control of the electron-laser energy exchange and suppresses the usual reversibility of DLA, allowing electrons to retain the acquired energy and sustain energy gain without intermittent losses.
Experiments in DIII-D show that a particle source location inside the top of the H-mode pedestal (pellets) maintains a higher pedestal pressure than an edge source (gas fueling) through a widening of the electron temperature pedestal with reduction of the temperature gradient. The effect of these two fueling schemes on the H-mode pedestal structure was examined in DIII-D by comparing controlled pellet-fueled and gas-fueled discharges across a fueling scan up to 40 torr 1 s –1 . High resolution electron profiles reveal that gas fueling lowers the pedestal pressure as the density profile shifts radially outwards and the separatrix density increases, while pellet fueling maintains a constant pedestal pressure. The neutral source locations from pellets and gas are determined with the PELLET and UEDGE codes, respectively, and quantify the particle source localization. Pellets provide significant ionization inside the pedestal top while gas puffing localizes ionization in the scrape-off-layer and pedestal foot, broadly consistent with the density profile structure influenced by the source. ELMs are observed to increase in frequency and reduce impurity content as fueling is increased. Stability analysis with ELITE shows that both conditions are near the type-I ELM corner of the peeling–ballooning stability diagram, which is altered significantly by the introduction of pellets. Since transport mechanisms are not observed to change substantially with particle source location, wider pedestals allow the pellet-fueled discharges to retain higher pedestal temperatures at similar pedestal densities. EPED1 is tested to capture the pedestal pressure, under-predicting the height with pellets and over-predicting the height with gas by ~15%. Overall, these results have important implications for future reactors where pellet fueling will be the primary particle source due to an opaque scrape-off-layer by showing that the neutral source location plays a role in setting the structure of the H-mode pedestal.
The eigenfunction of an instability contains information about energy flow in the wave. Here, the amplitude and phase of electron cyclotron emission radiometer data from hundreds of DIII-D reversed shear Alfvén eigenmodes (RSAE) and toroidicity-induced Alfvén eigenmodes (TAE) are analyzed along the outboard horizontal midplane. The radial phase profile can be flat, linearly rising or falling, convex or concave; in other words, a wide variety of shapes is observed. For a particular mode, often the radial phase profile remains approximately constant as the mode evolves in time but sometimes it changes rapidly. Many TAEs and some RSAEs have phase profiles that are rather flat where the mode amplitude is largest but rise steadily by ~2π at large major radius. Rapid phase changes are observed when the frequencies of an RSAE and TAE overlap and the modes couple. The phase profile depends weakly on the fast-ion gradient that would appear in the absence of wave-induced transport. Linear and quadratic fits to the phase profiles, together with many plasma parameters, are assembled into RSAE and TAE databases. In both cases, large variability is observed. For RSAEs, the strongest phase dependencies are on electron temperature T e , RSAE mode frequency, and the density of carbon impurities. For TAEs, the strongest dependencies are on beam power and major radius of the mode. In general, the average RSAE radial phase profile is essentially flat but the TAE profile has non-zero slope and curvature.
The Brassicaceae family comprises more than 3,700 species with a diversity of phenotypic characteristics, including seed oil content and composition. Recently, the global interest in Thlaspi arvense L. (pennycress) has grown as the seed oil composition makes it a suitable source for biodiesel and aviation fuel production. However, many wild traits of this species need to be domesticated to make pennycress ideal for cultivation. Molecular breeding and engineering efforts require the availability of an accurate genome sequence of the species. Here, we describe pennycress genome annotation improvements, using a combination of long- and short-read transcriptome data obtained from RNA derived from embryos of 22 accessions, in addition to public genome and gene expression information. Our analysis identified 27,213 protein-coding genes, as well as on average 6,188 biallelic SNPs. In addition, we used the identified SNPs to evaluate the population structure of our accessions. The data from this analysis support that the accession Ames 32872, originally from Armenia, is highly divergent from the other accessions, while the accessions originating from Canada and the United States cluster together. When we evaluated the likely signatures of natural selection from alternative SNPs, we found 7 candidate genes under likely recent positive selection. These genes are enriched with functions related to amino acid metabolism and lipid biosynthesis and highlight possible future targets for crop improvement efforts in pennycress.
Switchgrass is a potential crop for bioenergy or carbon capture schemes, but further yield improvements through selective breeding are needed to encourage commercialization. To identify promising switchgrass germplasm for future breeding efforts, we conducted multisite and multitrait genomic prediction with a diversity panel of 630 genotypes from 4 switchgrass subpopulations (Gulf, Midwest, Coastal, and Texas), which were measured for spaced plant biomass yield across 10 sites. Our study focused on the use of genomic prediction to share information among traits and environments. Specifically, we evaluated the predictive ability of cross-validation (CV) schemes using only genetic data and the training set (cross-validation 1: CV1), a subset of the sites (cross-validation 2: CV2), and/or with 2 yield surrogates (flowering time and fall plant height). We found that genotype-by-environment interactions were largely due to the north–south distribution of sites. The genetic correlations between the yield surrogates and the biomass yield were generally positive (mean height r = 0.85; mean flowering time r = 0.45) and did not vary due to subpopulation or growing region (North, Middle, or South). Genomic prediction models had CV predictive abilities of –0.02 for individuals using only genetic data (CV1), but 0.55, 0.69, 0.76, 0.81, and 0.84 for individuals with biomass performance data from 1, 2, 3, 4, and 5 sites included in the training data (CV2), respectively. To simulate a resource-limited breeding program, we determined the predictive ability of models provided with the following: 1 site observation of flowering time (0.39); 1 site observation of flowering time and fall height (0.51); 1 site observation of fall height (0.52); 1 site observation of biomass (0.55); and 5 site observations of biomass yield (0.84). The ability to share information at a regional scale is very encouraging, but further research is required to accurately translate spaced plant biomass to commercial-scale sward biomass performance.
Abstract Previous studies have found that maximum quantum yield of CO2 assimilation (Φ CO2,max,app) declines in lower canopies of maize and miscanthus, a maladaptive response to self-shading. These observations were limited to single genotypes, leaving it unclear whether the maladaptive shade response is a general property of this C4 grass tribe, the Andropogoneae. We explored the generality of this maladaptation by testing the hypothesis that erect leaf forms (erectophiles), which allow more light into the lower canopy, suffer less of a decline in photosynthetic efficiency than drooping leaf (planophile) forms. On average, Φ CO2,max,app declined 27% in lower canopy leaves across 35 accessions, but the decline was over twice as great in planophiles than in erectophiles. The loss of photosynthetic efficiency involved a decoupling between electron transport and assimilation. This was not associated with increased bundle sheath leakage, based on 13C measurements. In both planophiles and erectophiles, shaded leaves had greater leaf absorptivity and lower activities of key C4 enzymes than sun leaves. The erectophile form is considered more productive because it allows a more effective distribution of light through the canopy to support photosynthesis. We show that in sorghum, it provides a second benefit, maintenance of higher Φ CO2,max,app to support efficient use of that light resource.
Abstract Chronic vulvovaginal candidosis results either from reinfection or from the ability of Candida spp. to persist in the vulva and/or vagina. Persistence is usually associated with increased antifungal (mainly azoles) resistance rates, which can explain treatment failure, and/or increased expression of virulence factors by Candida spp. The aim of this study was to assess the mechanisms leading to Candida spp persistence, by studying sequential isolates from women with chronic vulvovaginal candidosis, focusing on strains genotypes, azole resistance, and ability to form biofilms along the period of clinical evaluation. The strains were identified at species level by automated analysis of biochemical profiles and molecular typing evaluated by polymorphic DNA analysis. The capacity to form biofilm was assessed with a microtiter plate assay. Fluconazole susceptibility was determined by the microdilution broth assay at both pH 7 (following the recommended guideline) and pH 4.5 (as representative of vaginal pH). We studied samples from 17 clinically recurrent cases. In 53% of the chronic cases there were two or more isolates that had a phylogenetic relationship while the remaining (47%) were caused by different species. In those cases where related strains were involved in recurrence, we verified an increase in MIC at pH 7 and also an increased capacity to form biofilms over time. Significant correlation between these two parameters was observed only in cases caused by C. glabrata, evidencing the importance of these two factors to enhance persistence in the vaginal mucosa for this particular species.
ABSTRACT HATS-18 b is a transiting planet with a large mass and a short orbital period, and is one of the best candidates for the detection of orbital decay induced by tidal effects. We present extensive photometry of HATS-18 from which we measure 27 times of mid-transit. Two further transit times were measured from data from the Transiting Exoplanet Survey Satellite (TESS) and three more taken from the literature. The transit timings were fitted with linear and quadratic ephemerides and an upper limit on orbital decay was determined. This corresponds to a lower limit on the modified stellar tidal quality factor of $Q_\star ^{\, \prime } \gt 10^{5.11 \pm 0.04}$. This is at the cusp of constraining the presence of enhanced tidal dissipation due to internal gravity waves. We also refine the measured physical properties of the HATS-18 system, place upper limits on the masses of third bodies, and compare the relative performance of TESS and the 1.54 m Danish Telescope in measuring transit times for this system.
ABSTRACT Type Ia supernovae (SNe Ia) are used as standardizable candles to measure cosmological distances, but differences remain in their corrected luminosities which display a magnitude step as a function of host galaxy properties such as stellar mass and rest-frame U−R colour. Identifying the cause of these steps is key to cosmological analyses and provides insight into SN physics. Here we investigate the effects of SN progenitor ages on their light-curve properties using a galaxy-based forward model that we compare to the Dark Energy Survey 5-yr SN Ia sample. We trace SN Ia progenitors through time and draw their light-curve width parameters from a bimodal distribution according to their age. We find that an intrinsic luminosity difference between SNe of different ages cannot explain the observed trend between step size and SN colour. The data split by stellar mass are better reproduced by following recent work implementing a step in total-to-selective dust extinction ratio (RV) between low- and high-mass hosts, although an additional intrinsic luminosity step is still required to explain the data split by host galaxy U−R. Modelling the RV step as a function of galaxy age provides a better match overall. Additional age versus luminosity steps marginally improve the match to the data, although most of the step is absorbed by the width versus luminosity coefficient α. Furthermore, we find no evidence that α varies with SN age.
ABSTRACT Type Ia supernovae (SNe Ia) are powerful tools for measuring the expansion history of the Universe, but the impact of dust around SNe Ia remains unknown and is a critical systematic uncertainty. One way to improve our empirical description of dust is to analyse highly reddened SNe Ia [E(B − V) > 0.4, roughly equivalent to the fitted SALT2 light-curve parameter c > 0.3]. With the recently released Pantheon+ sample, there are 57 SNe Ia that were removed because of their high colour alone (with colours up to c = 1.61), which can provide enormous leverage on understanding line-of-sight RV. Previous studies have claimed that RV decreases with redder colour, though it is unclear if this is due to limited statistics, selection effects, or an alternative explanation. To test this claim, we fit two separate colour–luminosity relationships, one for the main cosmological sample (c < 0.3) and one for highly reddened (c > 0.3) SNe Ia. We find the change in the colour–luminosity coefficient to be consistent with zero. Additionally, we compare the data to simulations with different colour models, and find that the data prefers a model with a flat dependence of RV on colour over a declining dependence. Finally, our results strongly support that line-of-sight RV to SNe Ia is not a single value, but forms a distribution.
Core-collapse supernovae, occurring at the end of massive star evolution, produce heavy elements, including those in the iron peak. Although the explosion mechanism is not yet fully understood, theoretical models can reproduce optical observations and observed elemental abundances. However, many nuclear reaction rates involved in explosive nucleosynthesis have large uncertainties, impacting the reliability of abundance predictions. To address this, we have previously developed a Monte Carlo-based nucleosynthesis code that accounts for reaction rate uncertainties and has been applied to nucleosynthesis processes beyond iron. Our framework is also well suited for studying explosive nucleosynthesis in supernovae. In this paper, we investigate 1D explosion models using the ‘PUSH method’ , focusing on progenitors with varying metallicities and initial masses around $M_{\rm ZAMS} = 16\, {\rm M}_{\odot }$. Detailed post-process nucleosynthesis calculations and Monte Carlo analyses are used to explore the effects of reaction rate uncertainties and to identify key reaction rates in explosive nucleosynthesis. We find that many reactions have little impact on the production of iron-group nuclei, as these elements are primarily synthesized in the nuclear statistical equilibrium. However, we identify a few ‘key reactions’ that significantly influence the production of radioactive nuclei, which may affect astrophysical observables. In particular, for the production of ${}^{44}{\rm Ti}$, we confirm that several traditionally studied nuclear reactions have a strong impact. However, determining a single reaction rate is insufficient to draw a definitive conclusion.
ABSTRACT Identifying the thresholds of drought that, if crossed, suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and change. We present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning 2001–2018. The thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress, and as a warning signal for substantial vegetation impacts. Drought thresholds varied geographically, with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests, corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ecosystems. Generally, those lower thresholds are detected in more humid climates. State-of-the-art land models, however, overestimated thresholds of soil moisture (i.e. overestimating drought impacts), especially in more humid areas with higher forest covers and arid areas with few forest covers. Based on climate model projections, we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia, Europe, Amazon, southern Australia and eastern and southern Africa. Our data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.
Flooding poses a substantial challenge to plant survival and productivity, particularly in riparian genus like Populus. This study examines the physiological, morphological, metabolic, and molecular responses of Populus deltoides ‘D-124’ and P. trichocarpa x P. deltoides hybrid clone ‘52–225’ under control and inundated conditions to identify differences in flooding tolerance. Under flooding conditions, physiological and cellular stress was more pronounced in P. deltoides ‘D-124’ than in the hybrid clone ‘52–225,’ as evidenced by lower transpiration (E), photosynthesis (A), and chlorophyll content. In contrast, ‘52–225’ showed reduced ROS accumulation suggesting better cellular function under stress. Morphologically, ‘52–225’ produced more shoot-born roots, which likely enhance oxygen transport and metabolic activity during flooding. Metabolite profiling revealed both overlapping and distinct patterns of sugar and amino acid accumulation between genotypes. Gene expression analysis revealed that flooding-responsive genes, including ALCOHOL DEHYDROGENASE 1 and HYPOXIA RESPONSIVE ERF 2, were activated in both genotypes, with a more pronounced response noted in ‘52–225.’ These findings extend our understanding of flooding tolerance mechanisms in Populus by connecting physiological traits, stress responses, and genetic regulation. This research contributes to the development of more flooding-resilient poplar varieties, with potential applications in breeding and restoration programs for flooding-prone environments.
The multiple crystalline terminations in magnetic Weyl semimetal Co 3 Sn 2 S 2 display distinct topological and trivial surface states, which have successfully been distinguished experimentally. However, a model of pure terminations is known to be inadequate because these surfaces exhibit a high degree of spatial heterogeneity and point disorder. Here, in this study, we perform a spectromicroscopy study of the surface chemistry and surface electronic structure using photoemission measurements in combination with first-principles calculations of core levels. We identify an intermediate region with properties distinct from both the sulfur and tin terminations, and demonstrate that the spectral features in this region can be associated with a disordered termination with a varying density of surface tin vacancies. This work establishes heuristics for identifying variable surface disorder using photoemission, an important prerequisite to experimentally establishing the behavior of momentum-space topological surface features subject to variable surface disorder on a single cleave.
Quantum process learning is a fundamental primitive that draws inspiration from machine learning with the goal of better studying the dynamics of quantum systems. One approach to quantum process learning is quantum compilation, whereby an analog quantum operation is digitized by compiling it into a series of basic gates. While there has been significant focus on quantum compiling for discrete-variable systems, the continuous-variable (CV) framework has received comparatively less attention. We present an experimental implementation of a CV quantum compiler that uses two-mode squeezed light to learn a Gaussian unitary operation. We demonstrate the compiler by learning a parameterized linear phase unitary through the use of target and control phase unitaries to demonstrate a factor of 5.4 increase in the precision of the phase estimation and a 3.6-fold acceleration in the time-to-solution metric when leveraging quantum resources. We further show how our approach can be extended to higher-dimensional compilation tasks. Our results are enabled by the tunable control of our cost landscape via variable squeezing, thus providing a critical framework to simultaneously increase precision and reduce time-to-solution.