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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Numerical integration of stochastic contact Hamiltonian systems via stochastic Herglotz variational principle

Within this work, we establish a stochastic contact variational integrator and its discrete version via stochastic Herglotz variational principle for stochastic contact Hamiltonian systems. A general structure-preserving stochastic contact method is provided to seek the stochastic contact variational integrators. Numerical experiments are performed to verify the validity of this approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Characterizing the gene–environment interaction underlying natural morphological variation in Neurospora crassa conidiophores using high-throughput phenomics and transcriptomics

Abstract Neurospora crassa propagates through dissemination of conidia, which develop through specialized structures called conidiophores. Recent work has identified striking variation in conidiophore morphology, using a wild population collection from Louisiana, United States of America to classify 3 distinct phenotypes: Wild-Type, Wrap, and Bulky. Little is known about the impact of these phenotypes on sporulation or germination later in the N. crassa life cycle, or about the genetic variation that underlies them. In this study, we show that conidiophore morphology likely affects colonization capacity of wild N. crassa isolates through both sporulation distance and germination on different carbon sources. We generated and crossed homokaryotic strains belonging to each phenotypic group to more robustly fit a model for and estimate heritability of the complex trait, conidiophore architecture. Our fitted model suggests at least 3 genes and 2 epistatic interactions contribute to conidiophore phenotype, which has an estimated heritability of 0.47. To uncover genes contributing to these phenotypes, we performed RNA-sequencing on mycelia and conidiophores of strains representing each of the 3 phenotypes. Our results show that the Bulky strain had a distinct transcriptional profile from that of Wild-Type and Wrap, exhibiting differential expression patterns in clock-controlled genes (ccgs), the conidiation-specific gene con-6, and genes implicated in metabolism and communication. Combined, these results present novel ecological impacts of and differential gene expression underlying natural conidiophore morphological variation, a complex trait that has not yet been thoroughly explored.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Variational quantum and neural quantum states algorithms for the linear complementarity problem

Variational quantum algorithms (VQAs) are promising hybrid quantum-classical methods designed to leverage the computational advantages of quantum computing while mitigating the limitations of current noisy intermediate-scale quantum (NISQ) hardware. Although VQAs have been demonstrated as proofs of concept, their practical utility in solving real-world problems—and whether quantum-inspired classical algorithms can match their performance—remains an open question. We present a novel application of the variational quantum linear solver (VQLS) and its classical neural quantum states-based counterpart, the variational neural linear solver (VNLS), as key components within a minimum map Newton solver for a complementarity-based rigid-body contact model. We demonstrate using the VNLS that our solver accurately simulates the dynamics of rigid spherical bodies during collision events. These results suggest that quantum and quantum-inspired linear algebra algorithms can serve as viable alternatives to standard linear algebra solvers for modelling certain physical systems.

neural quantum states↗
DOE OSTI2023

Variational Monte Carlo calculations of n + H 3 scattering

A paramount goal in nuclear physics is to unify ab initio treatments of bound and unbound states. The position-space quantum Monte Carlo (QMC) methods have a long history of successful bound-state calculations in light systems but have seen minimal implementation in unbound systems. Here, we introduce a numerical method to improve the efficiency and accuracy of unbound-state calculations in QMC. As an initial application, we compute scattering observables for the smallest system available to probe three-body forces, the neutron-triton system, using variational Monte Carlo (VMC) wave functions. The method involves inferring long-range amplitudes in the wave function from integrals over the short-range region where all the particles interact. This approach using integral relations is well established in the literature; here, we develop it for the QMC framework. We validate our approach with a consistency check between short-range spectroscopic overlap functions computed from direct evaluation and from the integral relations; scattering amplitudes are long-range asymptotics of those overlaps. Comparison against published benchmark calculations using the same potential demonstrates that when applied to the current VMC wave functions, the integral method produces more accurate scattering observables than direct evaluation from the same variational wave function. However, it still differs noticeably from the exact results. Using additional interactions, we then present phase shifts and mixing parameters for the n + 3 H system. In particular, we present one of the first applications of the Norfolk family of local coordinate-space chiral potentials in unbound systems of A > 2. The Norfolk results accurately describe s-wave scattering but predict p-wave cross sections too large. Compared with previous QMC scattering calculations, the integral method avoids difficulties associated with the precise computation of energy differences and with convergence outside the interaction region, which is particularly severe in the variational calculation. Application of the integral method here paves the way for its use in Green's function Monte Carlo (GFMC) calculations. In GFMC, the wave functions are more accurate, but the high-precision convergence of their tails is slow, and there are additional difficulties in reading out amplitudes. Here, the integral methods will address both of those remaining problems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Variational quantum algorithm for estimating the quantum Fisher information

The quantum Fisher information (QFI) quantifies the ultimate precision of estimating a parameter from a quantum state and can be regarded as a reliability measure of a quantum system as a quantum sensor. However, estimation of the QFI for a mixed state is in general a computationally demanding task. In this paper we present a variational quantum algorithm called variational quantum Fisher information estimation (VQFIE) to address this task. By estimating lower and upper bounds on the QFI, based on bounding the fidelity, VQFIE outputs a range in which the actual QFI lies. This result can then be used to variationally prepare the state that maximizes the QFI, for the application of quantum sensing. In contrast to previous approaches, VQFIE does not require knowledge of the explicit form of the sensor dynamics. We simulate the algorithm for a magnetometry setup and demonstrate the tightening of our bounds as the state purity increases. For this example, we compare our bounds with literature bounds and show that our bounds are tighter.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Ensemble approximate control variate estimators: Applications to multi-fidelity importance sampling.

The recent growth in multifidelity uncertainty quantification has given rise to a large set of variance reduction techniques that leverage information from model ensembles to provide variance reduction for estimates of the statistics of a high-fidelity model. In this paper we provide two contributions: (1) we utilize an ensemble estimator to account for uncertainties in the optimal weights of approximate control variate (ACV) approaches and derive lower bounds on the number of samples required to guarantee variance reduction; and (2) we extend an existing multifidelity importance sampling (MFIS) scheme to leverage control variates. Our approach directly addresses a limitation of many multifidelity sampling strategies that require the usage of pilot samples to estimate covariances. As such we make significant progress towards both increasing the practicality of approximate control variates—for instance, by accounting for the effect of pilot samples—and using multifidelity approaches more effectively for estimating low-probability events. The numerical results indicate our hybrid MFIS-ACV estimator achieves up to 50% improvement in variance reduction over the existing state-of-the-art MFIS estimator, which had already shown an outstanding convergence rate compared to the Monte Carlo method, on several problems of computational mechanics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Covariance-Free Bifidelity Control Variates Importance Sampling for Rare Event Reliability Analysis

Multifidelity modeling has been steadily gaining attention as a tool to address the problem of exorbitant model evaluation costs that makes the estimation of failure probabilities a significant computational challenge for complex real-world problems, particularly when failure is a rare event. To implement multifidelity modeling, estimators that efficiently combine information from multiple models/sources are necessary. In past works, the variance reduction techniques of control variates (CV) and importance sampling (IS) have been leveraged for this task. In this paper, we present the CVIS framework—a creative take on a coupled CV and IS estimator for bifidelity reliability analysis. The framework addresses some of the practical challenges of the CV method by using an estimator for the control variate mean and sidestepping the need to estimate the covariance between the original estimator and the control variate through a clever choice for the tuning constant. Furthermore, the task of selecting an efficient IS distribution is also considered, with a view towards maximally leveraging the bifidelity structure and maintaining expressivity. Additionally, a diagnostic is provided that indicates both the efficiency of the algorithm as well as the relative predictive quality of the models utilized. Finally, the behavior and performance of the framework is explored through analytical and numerical examples.

Markov chain Monte Carlo↗
DOE OSTI2023

Soil fertility and drought interact to determine large variations in wood production for a hyperdominant Amazonian tree species

The productivity of the Amazon Rainforest is related to climate and soil fertility. However, the degrees to which these interactions influence multiannual to decadal variations in tree diameter growth are still poorly explored. To fill this gap, we used radiocarbon measurements to evaluate the variation in tree growth rates over the past decades in an important hyperdominant species, Eschweilera coriacea (Lecythidaceae), from six sites in the Brazilian Amazon that span a range of soil properties and climate. Using linear mixed-effects models, we show that temporal variations in mean annual diameter increment evaluated over a specific time period reflect interactions between soil fertility and the drought index (SPEI-Standardized Precipitation and Evapotranspiration Index). Our results indicate that the growth response of trees to drought is strongly dependent on soil conditions, a facet of forest productivity that is still underexplored, and which has great potential for improving predictions of future tropical tree growth in the face of projected climate change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Variation in sulfide tolerance of photosystem II in phylogenetically diverse cyanobacteria from sulfidic habitats

Physiological and molecular phylogenetic approaches were used to investigate variation among 12 cyanobacterial strains in their tolerance of sulfide, an inhibitor of oxygenic photosynthesis. Cyanobacteria from sulfidic habitats were found to be phylogenetically diverse and exhibited an approximately 50-fold variation in photosystem II performance in the presence of sulfide. Whereas the degree of tolerance was positively correlated with sulfide levels in the environment, a strain's phenotype could not be predicted from the tolerance of its closest relatives. These observations suggest that sulfide tolerance is a dynamic trait primarily shaped by environmental variation. Despite differences in absolute tolerance, similarities among strains in the effects of sulfide on chlorophyll fluorescence induction indicated a common mode of toxicity. Based on similarities with treatments known to disrupt the oxygen-evolving complex, it was concluded that sulfide toxicity resulted from inhibition of the donor side of photosystem II.

Phylogeny↗
NASA NTRS2003

Precision Clocks in Space and alpha-Variations

Important developments of both in theoretical and observational cosmology have fueled considerable interest in searches for variations of the fine structure constant. Experimentally, Webb et. al. have found evidence for a cosmological variation of the fine structure constant through an analysis of the absorption lines in galactic halos from quasar-emitted light. Recently developed small ion atomic clocks enable Solar System tests for equivalence principle (EP) violating (alpha)-variations by way of rate-comparisons of three ultra-stable atomic clocks near-to and far-from the sun where gravitational red-shift changes are more than 10(exp 4) larger than in low Earth orbit. No space tests of the EP have been made in nearly 30 years, since the GP-A hydrogen maser reached a 10,000 km apogee confirming EP red-shift predictions ~1 part in 10(exp 4). Today's small ion clocks, nearly 100x more stable and 100x smaller then the GP-A H-maser, could probe for EP violating scalar fields near the sun for mission costs comparable to low Earth orbiters and improve the GP-A sensitivity by 5 to 6 orders of magnitude.

(alpha)-variation↗
NASA NTRS2014

Effects of Extreme Obliquity Variations on the Habitability of Exoplanets

We explore the impact of obliquity variations on planetary habitability in hypothetical systems with high mutual inclination. We show that large-amplitude, high-frequency obliquity oscillations on Earth-like exoplanets can suppress the ice-albedo feedback, increasing the outer edge of the habitable zone. We restricted our exploration to hypothetical systems consisting of a solar-mass star, an Earth-mass planet at 1 AU, and 1 or 2 larger planets. We verified that these systems are stable for 108 years with N-body simulations and calculated the obliquity variations induced by the orbital evolution of the Earth-mass planet and a torque from the host star. We ran a simplified energy balance model on the terrestrial planet to assess surface temperature and ice coverage on the planet's surface, and we calculated differences in the outer edge of the habitable zone for planets with rapid obliquity variations. For each hypothetical system, we calculated the outer edge of habitability for two conditions: (1) the full evolution of the planetary spin and orbit and (2) the eccentricity and obliquity fixed at their average values. We recovered previous results that higher values of fixed obliquity and eccentricity expand the habitable zone, but we also found that obliquity oscillations further expand habitable orbits in all cases. Terrestrial planets near the outer edge of the habitable zone may be more likely to support life in systems that induce rapid obliquity oscillations as opposed to fixed-spin planets. Such planets may be the easiest to directly characterize with space-borne telescopes.

habitability of exoplanets↗
NASA NTRS2016

Role of Surface Wind and Vegetation Cover in Multi-decadal Variations of Dust Emission in the Sahara and Sahel

North Africa, the world's largest dust source, is non-uniform, consisting of a permanently arid region (Sahara), a semi-arid region (Sahel), and a relatively moist vegetated region (Savanna), each with very different rainfall patterns and surface conditions. This study aims to better understand the controlling factors that determine the variation of dust emission in North Africa over a 27-year period from 1982 to 2008, using observational data and model simulations. The results show that the model-derived Saharan dust emission is only correlated with the 10-m winds (W10m) obtained from reanalysis data, but the model-derived Sahel dust emission is correlated with both W10m and the Normalized Difference Vegetation Index (NDVI) that is obtained from satellite. While the Saharan dust accounts for 82 of the continental North Africa dust emission (1340-1570 Tg year(exp -1) in the 27-year average, the Sahel accounts for 17 with a larger seasonal and inter-annual variation (230-380 Tg year(exp -1), contributing about a quarter of the transatlantic dust transported to the northern part of South America. The decreasing dust emission trend over the 27-year period is highly correlated with W10m over the Sahara (R equals 0.92). Over the Sahel, the dust emission is correlated with W10m (R 0.69) but is also anti-correlated with the trend of NDVI (R equals 0.65). W10m is decreasing over both the Sahara and the Sahel between 1982 and 2008, and the trends are correlated (R equals 0.53), suggesting that Saharan Sahelian surface winds are a coupled system, driving the inter-annual variation of dust emission.

Inter-annual variation↗
NASA NTRS2014

Development of Dynamic Sub-Grid Models for Variational Multiscale Methods

A dynamic Variational Multiscale Method (Hughes et al. 1998) is developed by leveraging the Germano procedure from classical Large-eddy Simulations (LES). The similarity between the classical and variational approaches is analyzed in the context of incompressible flow. This analysis leads to a consistent modeling approach for both incompressible and compressible flows, the latter being demonstrated in a priori testing for low-speed attached and separated boundary layers. Similar to the classical LES procedure from which it is derived, the variational dynamic procedure does not guarantee a positive semi-definite coefficient in the general case. However, reproducing the behavior of the classical LES dynamic approach is seen as a necessary first step to develop a VMM that automatically adjusts to the local resolution and flow physics.

Variational multiscale↗
DOE OSTI2021

Genetic dissection of natural variation in oilseed traits of camelina by whole‐genome resequencing and QTL mapping

Abstract Camelina [ Camelina sativa (L.) Crantz] is an oilseed crop in the Brassicaceae family that is currently being developed as a source of bioenergy and healthy fatty acids. To facilitate modern breeding efforts through marker‐assisted selection and biotechnology, we evaluated genetic variation among a worldwide collection of 222 camelina accessions. We performed whole‐genome resequencing to obtain single nucleotide polymorphism (SNP) markers and to analyze genomic diversity. We also conducted phenotypic field evaluations in two consecutive seasons for variations in key agronomic traits related to oilseed production such as seed size, oil content (OC), fatty acid composition, and flowering time. We determined the population structure of the camelina accessions using 161,301 SNPs. Further, we identified quantitative trait loci (QTL) and candidate genes controlling the above field‐evaluated traits by genome‐wide association studies (GWAS) complemented with linkage mapping using a recombinant inbred line (RIL) population. Characterization of the natural variation at the genome and phenotypic levels provides valuable resources to camelina genetic studies and crop improvement. The QTL and candidate genes should assist in breeding of advanced camelina varieties that can be integrated into the cropping systems for the production of high yield of oils of desired fatty acid composition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Genomic variation within the maize stiff-stalk heterotic germplasm pool

The stiff-stalk heterotic group in Maize (Zea mays L.) is an important source of inbreds used in U.S. commercial hybrid production. Founder inbreds B14, B37, B73, and, to a lesser extent, B84, are found in the pedigrees of a majority of commercial seed parent inbred lines. We created high-quality genome assemblies of B84 and four expired Plant Variety Protection (ex-PVP) lines LH145 representing B14, NKH8431 of mixed descent, PHB47 representing B37, and PHJ40, which is a Pioneer Hi-Bred International (PHI) early stiff-stalk type. Sequence was generated using long-read sequencing achieving highly contiguous assemblies of 2.13-2.18 Gbp with N50 scaffold lengths >200 Mbp. Inbred-specific gene annotations were generated using a core five-tissue gene expression atlas, whereas transposable element (TE) annotation was conducted using de novo and homology-directed methodologies. Compared with the reference inbred B73, synteny analyses revealed extensive collinearity across the five stiff-stalk genomes, although unique components of the maize pangenome were detected. Comparison of this set of stiff-stalk inbreds with the original Iowa Stiff Stalk Synthetic breeding population revealed that these inbreds represent only a proportion of variation in the original stiff-stalk pool and there are highly conserved haplotypes in released public and ex-Plant Variety Protection inbreds. Despite the reduction in variation from the original stiff-stalk population, substantial genetic and genomic variation was identified supporting the potential for continued breeding success in this pool. The assemblies described here represent stiff-stalk inbreds that have historical and commercial relevance and provide further insight into the emerging maize pangenome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Little vertical and circumferential variations in stem xylem water Δ 2 H and Δ 18 O in three tree species

Vertical and circumferential patterns of xylem water isotope signatures in large trees are rarely characterized but may influence interpretation of water source investigations and soil/xylem water isotope offsets. Furthermore, to examine vertical and circumferential variation in xylem water δ 2 H and δ 18 O, we collected xylem tissue at 5 heights (0, 1, 4, 7 and 10 m) from three replicate trees of three species with contrasting xylem anatomy, two angiosperms (Liquidambar styraciflua and Quercus nigra) and one gymnosperm (Pinus taeda). Concurrently, we also determined δ 2 H and δ 18 O of groundwater, soil water, and recent precipitation. On a different day, we collected circumferential samples at 1 m from the same trees to test for sectorality effects. Water from stem and soil samples were cryogenically extracted and analyzed for δ 2 H and δ 18 O. Mean xylem water δ 2 H and δ 18 O were significantly different between species, both vertically and circumferentially. We did not find significant (p = 0.05) systematic variation in δ 2 H or δ 18 O with height. We found no significant evidence for sectorality effects on δ 2 H, δ 18 O. Variances of vertical synoptic xylem water δ 2 H or δ 18 O were similar between species, 7.2–10.4‰ for δ 2 H and 0.58–0.81‰ for δ 18 O. Circumferential variances were also similar between species, 4.0–6.0 for δ 2 H and 0.37–0.44 for δ 18 O. A mixing model showed that sweetgum, water oak and loblolly pine, were drawing most of their water from deep soil from 45 to 190 cm (84.7, 68.4 and 53.2%, respectively) however, soil water-excess values indicate δ 2 H fractionation effects on these estimates. Dual isotope mixing model evaluation with single and multiple sample configurations showed that source water estimates were not affected by within tree variability of xylem water signatures. Xylem water δ 2 H and δ 18 O variability with height or circumference, was 3.2 and 2.7 times less than between tree variation because of transient temporal and spatial processes and is, therefore, not likely to affect interpretations of water sourcing in these three species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Type II Hamiltonian Variational Principle and Adjoint Systems for Lie Groups

We present a novel Type II variational principle on the cotangent bundle of a Lie group which enforces Type II boundary conditions, i.e., fixed initial position and final momentum. In general, such Type II variational principles are only globally defined on vector spaces or locally defined on general manifolds; however, by left translation, we are able to define this variational principle globally on cotangent bundles of Lie groups. Type II boundary conditions are particularly important for adjoint sensitivity analysis, which is our motivating application. As such, we additionally discuss adjoint systems on Lie groups, their properties, and how they can be used to solve optimization problems subject to dynamics on Lie groups.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

What explains the year-to-year variation in growing season timing of boreal black spruce forests?

Amplified climate warming in high latitudes is expected to affect growing season timing of the vast boreal biome. It is unclear whether the presence of permafrost (perennially frozen ground) might have an influence on changes in growing season timing. Here, this study examined how different environmental variables explained, either directly or indirectly, the variation in growing season timing of boreal forest stands with and without permafrost. We expected that environmental variables explaining the variation in growing season timing differed or had different explanatory power depending on permafrost presence or absence. The growing season was delineated from daily gross primary productivity (GPP) time series derived from 40 site-year data of net ecosystem carbon dioxide exchange measured with eddy covariance techniques over five black spruce (Picea mariana [Mill.])-dominated boreal forest stands in North America. In permafrost-free forest stands, a combination of start in canopy ‘green-up’ in spring and the timing of air and soil temperature increasing above freezing explained the start-of-season (SOS GPP ). Results from commonality analysis and structural equation modeling suggest that canopy ‘green-up’ and air temperature directly affected SOS GPP in permafrost-free forest stands. In addition, soil temperature acted as mediator for an indirect effect of air temperature on SOS GPP . In contrast, none of the environmental variables, or their combination, explained the variation in SOS GPP in forest stands with permafrost. The explanatory power of environmental variables was more consistent regarding the end-of-season (EOS GPP ). In both, forest stands with and without permafrost, EOS GPP was directly explained by mean soil water content in the fall and the first day of continuous snowpack formation. A better understanding how environmental variables control SOS GPP and EOS GPP in forest stands with and without permafrost will help to refine parameterizations of the boreal biome in Earth system models.

54 ENVIRONMENTAL SCIENCES↗