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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Mineralogical, Elemental, and Tomographic Reconnaissance Investigation for CLPS (METRIC): A Proposed Mission to the Lunar South Pole-Aitken Basin

The global Lunar Magma Ocean (LMO) hypothesis is based on analyses of ferroan anorthosites (FAN), magnesian plutonic rocks (Mg-suite), and KREEPy (Potassium - K; Rare Earth Elements - REE; Phosphorous - P) material present at the Apollo landing sites and the assumed global distribution of these lithologies. However, orbital spacecraft data over the last two decades have highlighted that the location of the Apollo missions within and near the Procellarum KREEP Terrane (PKT) is compositionally anomalous and not representative of the entire lunar surface and suggests that Apollo samples provide a biased view of the Moon. Further, meteorites, which originate from random areas on the lunar surface, including those not visited by Apollo, Luna, or Chang’E-5, provide complementary datasets that reveal a more complex lunar formation and evolution than the simple LMO onion skin model. While many recent investigations support and refine the LMO model, other recent studies have questioned whether this mechanism alone is responsible for the primordial differentiation of the Moon. Thus, relating the distinct and asymmetrically distributed geochemical terranes on the Moon, especially KREEP which is a predicted global LMO product, to lunar formation and differentiation remains a fundamental goal of lunar science. The South Pole-Aitken (SPA) impact carved a two-and-a-half thousand-kilometer basin into the Moon’s ancient crust, excavating material from as deep as the upper mantle. Orbital remote sensing of the basin indicates compositions with elevated thorium (Th) contents and unique mineralogies that provide a window into early lunar structure and LMO processes. We propose to land a powerful characterization laboratory at Birkeland crater on the far side of the Moon–where Th-rich SPA ejecta have been re-exposed near the surface–in order to address outstanding questions about the evolution of the Moon.

K M Cannon↗
DOE OSTI2026

Efficient many-jet event generation with flow matching

We apply for the first time, to the best of our knowledge, the flow matching method to the problem of phase-space sampling for event generation in high-energy collider physics. By training the model to remap the random numbers used to generate the momenta and helicities of the scattering matrix elements as implemented in the portable partonic event generator pepper, we find substantial efficiency improvements in the studied processes. We focus our study on the highest final-state multiplicities in Drell-Yan and top-antitop pair production used in simulated samples for the Large Hadron Collider, which computationally are the most relevant ones. We find that the unweighting efficiencies improve by factors of 184 and 25, respectively, when compared to the standard approach of using a vegas-based optimization. We also compare continuous normalizing flows trained with flow matching against the previously studied normalizing flows based on coupling layers and find that the former leads to better results, faster training and a better scaling behavior across the studied multiplicity range, while the latter evaluate faster. When combining the advantages of both methods using the regflow approach, we find parton-level unweighted event generation walltime gains of about a factor of 10 at the highest final-state multiplicities.

Bothmann, E. [CERN; Gottingen U.] (ORCID:000000016↗
NASA NTRS2012

Geochemistry of Lunar Highland Meteorites Mil, 090034, 090036 AND 090070

Apollo and Luna samples were collected from a restricted area on the near side of the Moon, while the source craters of the lunar meteorites are randomly distributed. For example, Takeda et al. [1] and Yamaguchi et al. [2] found a variety of lithic clasts in Dho 489 and Y 86032 which were not represented by Apollo samples, and some of these clasts have lower rare earth elements (REE) and FeO abundances than Apollo anorthosites, respectively. Takeda et al. [1] and Yamaguchi et al. [2] concluded that Dho 489 and Y 86032 originated from the lunar farside. Therefore, lunar meteorites provide an opportunity to study lunar surface rocks from areas not sampled by Apollo and Luna missions. Three lunar anorthitic breccias (MIL 090034, 090036 and 090070) were found on the Miller Range Ice Field in Antarctica during the 2009-2010 ANSMET season [3]. In this study, we determined elemental abudnances for MIL 090034, 090036 and 090070 by using INAA and aimed to characterize these meteorites in chemical compositions in comparison with those for other lunar meteorites and Apollo samples.

Shirai, N.aoki↗
NASA NTRS1977

Testing the accuracy of remote sensing land use maps

Some of the main aspects that need to be considered in a remote sensing sampling design are: (1) the frequency that any one land use type (on the ground) is erroneously attributed to another class by the interpreter; (2) the frequency that the wrong land use (as observed on the ground) is erroneously included in any one class by the remote sensing interpreter; (3) the proportion of all land (as determined in the field) that is mistakenly attributed by the interpreter; and (4) the determination of whether the mistakes are random (so that the overall proportions are approximately correct) or subject to a persistent bias. A sampling and statistical testing procedure is presented which allows an approximate answer to each of these aspects. The concept developed and described incorporates the probability of making incorrect interpretations at particular prescribed accuracy levels, for a certain number of errors, for a particular sample size. It is considered that this approach offers a meaningful explanation of the interpretation accuracy level of an entire remote sensing land use survey.

Vangenderen, J. L.↗
DOE OSTI2025

The polarized-signal density matrix: A practical way to recover molecular frame information from isotropic samples

We present a novel approach to model ultrafast time-dependent nonlinear optical polarization sensitive signals emitted from randomly oriented molecules. By projecting the laboratory-frame analyzer polarization axis into the molecular-frame and linking that axis with the density matrix through a tensor product, we demonstrate an approach to find a specific molecular orientation that yields a good approximation to simulated four-wave mixing signals produced by the same model but with averaging over molecular orientation.

Thurston, Richard L↗
DOE OSTI2021

An adaptive Hessian approximated stochastic gradient MCMC method

Bayesian approaches have been successfully integrated into training deep neural networks. One popular family is stochastic gradient Markov chain Monte Carlo methods (SG-MCMC), which have gained increasing interest due to their ability to handle large datasets and the potential to avoid overfitting. Although standard SG-MCMC methods have shown great performance in a variety of problems, they may be inefficient when the random variables in the target posterior densities have scale differences or are highly correlated. Here, we present an adaptive Hessian approximated stochastic gradient MCMC method to incorporate local geometric information while sampling from the posterior. The idea is to apply stochastic approximation (SA) to sequentially update a preconditioning matrix at each iteration. The preconditioner possesses second-order information and can guide the random walk of a sampler efficiently. Instead of computing and saving the full Hessian of the log posterior, we use limited memory of the samples and their stochastic gradients to approximate the inverse Hessian-vector multiplication in the updating formula. Moreover, by smoothly optimizing the preconditioning matrix via SA, our proposed algorithm can asymptotically converge to the target distribution with a controllable bias under mild conditions. To reduce the training and testing computational burden, we adopt a magnitude-based weight pruning method to enforce the sparsity of the network. Our method is user-friendly and demonstrates better learning results compared to standard SG-MCMC updating rules. The approximation of inverse Hessian alleviates storage and computational complexities for large dimensional models. Numerical experiments are performed on several problems, including sampling from 2D correlated distribution, synthetic regression problems, and learning the numerical solutions of heterogeneous elliptic PDE. The numerical results demonstrate great improvement in both the convergence rate and accuracy.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2007

Non-Random Spatial Distribution of Impacts in the Stardust Cometary Collector

In January 2004, the Stardust spacecraft flew through the coma of comet P81/Wild2 at a relative speed of 6.1 km/sec. Cometary dust was collected at in a 0.1 sq m collector consisting of aerogel tiles and aluminum foils. Two years later, the samples successfully returned to earth and were recovered. We report the discovery that impacts in the Stardust cometary collector are not distributed randomly in the collecting media, but appear to be clustered on scales smaller than approx.10 cm. We also report the discovery of at least two populations of oblique tracks. We evaluated several hypotheses that could explain the observations. No hypothesis was consistent with all the observations, but the preponderance of evidence points toward at least one impact on the central Whipple shield of the spacecraft as the origin of both clustering and low-angle oblique tracks. High-angle oblique tracks unambiguously originate from a noncometary impact on the spacecraft bus just forward of the collector. Here we summarize the observations, and review the evidence for and against three scenarios that we have considered for explaining the impact clustering found on the Stardust aerogel and foil collectors.

Westphal, Andrew J.↗
NASA NTRS2003

Estimating Terrestrial Carbon Exchange from Space: How Often and How Well?

Data from a new space mission measuring integrated light-use efficiency could provide a breakthrough in understanding of global carbon, water, and energy dynamics, and greatly improve the accuracy of model predictions for terrestrial carbon cycles and climate. Over the past decade, Gamon and others have shown that changes in photo-protective pigments are sensitive indicators of declines in light-use efficiency of plants and plant canopies. The requirements for integrated diurnal measurements from space need to be defined, before a space mission can be formulated successfully using this concept. We used towerbased CO 2 flux data as idealized proxies for remote measurements, examining their sampling properties. Thousands of half-hourly CO 2 flux measurements are needed before their average begins to converge on an average annual net CO 2 exchange. Estimates of daily integrated fluxes (i.e., diurnal curves) are more statistically efficient, especially if the spacing between measured days is quasiregular, rather than random. Using a few measurements per day one can distinguish among days with different net CO 2 exchanges. Fluxes sampled between mid-morning to mid-afternoon are more diagnostic than early morning or late afternoon measurements. Similar results (correlation >0.935) were obtained using 2 measurements per day with high accuracy ([:plusmn:]5%), 3 measurements per day with medium accuracy ([:plusmn:] 10%), or 5 measurements per day at lower accuracy ([:plusmn:]20%). An observatory in a geosynchronous or near-geosynchronous orbit could provide appropriate observations, as could a multi-satellite constellation in polar orbits, but there is a potential trade-off between the required number of observations per day and quality of each observation.

Knox, Robert G.↗
NASA NTRS2006

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part II: Evaluation of Estimates Using Independent Data

Rainfall rate estimates from spaceborne microwave radiometers are generally accepted as reliable by a majority of the atmospheric science community. One of the Tropical Rainfall Measuring Mission (TRMM) facility rain-rate algorithms is based upon passive microwave observations from the TRMM Microwave Imager (TMI). In Part I of this series, improvements of the TMI algorithm that are required to introduce latent heating as an additional algorithm product are described. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, 0.5 deg. -resolution estimates of surface rain rate over ocean from the improved TMI algorithm are well correlated with independent radar estimates (r approx. 0.88 over the Tropics), but bias reduction is the most significant improvement over earlier algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly 2.5 -resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data is limited, TMI-estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain-rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with (a) additional contextual information brought to the estimation problem and/or (b) physically consistent and representative databases supporting the algorithm. A model of the random error in instantaneous 0.5 deg. -resolution rain-rate estimates appears to be consistent with the levels of error determined from TMI comparisons with collocated radar. Error model modifications for nonraining situations will be required, however. Sampling error represents only a portion of the total error in monthly 2.5 -resolution TMI estimates; the remaining error is attributed to random and systematic algorithm errors arising from the physical inconsistency and/or nonrepresentativeness of cloud-resolving-model-simulated profiles that support the algorithm.

Yang, Song↗
NASA NTRS1998

Development of a Probabilistic Dynamic Synthesis Method for the Analysis of Nondeterministic Structures

Accounting for the statistical geometric and material variability of structures in analysis has been a topic of considerable research for the last 30 years. The determination of quantifiable measures of statistical probability of a desired response variable, such as natural frequency, maximum displacement, or stress, to replace experience-based "safety factors" has been a primary goal of these studies. There are, however, several problems associated with their satisfactory application to realistic structures, such as bladed disks in turbomachinery. These include the accurate definition of the input random variables (rv's), the large size of the finite element models frequently used to simulate these structures, which makes even a single deterministic analysis expensive, and accurate generation of the cumulative distribution function (CDF) necessary to obtain the probability of the desired response variables. The research presented here applies a methodology called probabilistic dynamic synthesis (PDS) to solve these problems. The PDS method uses dynamic characteristics of substructures measured from modal test as the input rv's, rather than "primitive" rv's such as material or geometric uncertainties. These dynamic characteristics, which are the free-free eigenvalues, eigenvectors, and residual flexibility (RF), are readily measured and for many substructures, a reasonable sample set of these measurements can be obtained. The statistics for these rv's accurately account for the entire random character of the substructure. Using the RF method of component mode synthesis, these dynamic characteristics are used to generate reduced-size sample models of the substructures, which are then coupled to form system models. These sample models are used to obtain the CDF of the response variable by either applying Monte Carlo simulation or by generating data points for use in the response surface reliability method, which can perform the probabilistic analysis with an order of magnitude less computational effort. Both free- and forced-response analyses have been performed, and the results indicate that, while there is considerable room for improvement, the method produces usable and more representative solutions for the design of realistic structures with a substantial savings in computer time.

Brown, A. M.↗
DOE OSTI2024

Sampling Size Optimization for Bioburden Density Estimation in Planetary Protection

Planetary protection (PP) is a discipline that focuses on minimizing the biological contamination of spacecraft to ensure compliance with international policy. Precise estimation of bioburden - the total number of microbes in or on spacecraft hardware – and the bioburden density are of utmost importance for PP. Such estimation is the way concordance with requirements is demonstrated, and it is critical for quantifying the potential risk of inadvertently contaminating other planetary bodies. Although a suite of molecular techniques have been used to thoroughly characterize and profile the microbiome of various cleanroom environments and spacecraft, the gold standard remains the physical enumeration of microbes via culturing of samples directly taken from spacecraft and associated surfaces. However, due to technical, budgetary, and programmatic constraints, only a manageable portion (around 10%) of the entire spacecraft surface is directly sampled with cotton swabs or wipes. To generate the bioburden current best estimate (CBE) for components not directly verifiable, the accepted approach is to apply a NASA-defined bioburden estimate based on the components’ manufacturing or assembly environment. This approach utilizes a prespecified bioburden density estimation that applies a maximum value across the total surface area of the specified component. For hardware components that underwent similar assembly processes, an implied bioburden is adopted for all components, based on a direct verification of a representative component within the same lot. Once all components have a CBE, the bioburden estimates are generated. In previous publication [ 1], we have shown that statistical risks quantifying the accuracy of the estimates for sampled, prespecified, and implied components can be derived and ranked. For mean squared error (MSE) function, the risks are available analytically and hence a cost function can be obtained to optimize the risks with respect to the sampling area and sampling cost. Since the sampling area and sampling cost are two complimentary variables, their sum will have a well-defined minimum. This paper presents the multivariate optimization of the integrated risk of an empirical Bayes estimator to determine the optimal sampling schedule for a given number of components. It is assumed that given a number of components, N, the bioburden density for each component can either be sampled, implied, or prespecified. The multivariate optimization searches through different options to sample, imply or prespecify the bioburden density for a component, and account for the component’s surface area and cost of sampling. The idea of the optimization is based on the observation that the statistical risk of using an estimator is a monotonically decreasing function of the sampled area. The larger the sampled area, the lower the risk of using the estimator as the estimator becomes more and more accurate as the sampling area increases. On the other hand, the cost of sampling is monotonically increasing as the sampled surface grows. This makes the risk and total cost of sampling complimentary variables which can be counterbalanced to achieve an optimal overall value with respect to the sampled surface. In this paper, the integrated risk has been used to quantify the accuracy of the estimator. This risk has been selected because it depends on neither the true value of the parameter nor on the collected data. The cost of each sample was also available to obtain the total cost of sampling of N components. The paper will present the results based on computer-simulated data as well as the data collected during the InSight mission. The computer-simulated data have N components with randomly generated total areas and each component assigned to one of the three categories according to the method of estimating of bioburden density: sampled, implied, or prespecified. The cost of sampling is also available. The cost of sampling is estimated based on a cost model provided by the planetary protection group at JPL. For this paper, the overall cost was assumed to be a linear function of exposure. The optimization process finds the allocation of the components to the three categories that minimizes the tradeoff between integrated risk and total cost. For the InSight data, a set of components is selected representing all three categories, and optimization is performed to determine if the performed allocation was optimal or if a better allocation could have been obtained. To the best of our knowledge, this work is the first attempt not only perform an accurate estimation of bioburden density but also do it in an optimal way.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Distributionally Safe Path Planning: Wasserstein Safe RRT

In this paper, we propose a Wasserstein metric-based random path planning algorithm. Wasserstein Safe RRT (W-Safe RRT) provides finite-sample probabilistic guarantees on the safety of a returned path in an uncertain obstacle environment. Vehicle and obstacle states are modeled as distributions based upon state and model observations. Additionally, we define limits on distributional sampling error so the Wasserstein distance between a vehicle state distribution and obstacle distributions can be bounded. This enables the algorithm to return safe paths with a confidence bound through combining finite sampling error bounds with calculations of the Wasserstein distance between discrete distributions. W-Safe RRT is compared against a baseline minimum encompassing ball algorithm, which ensures balls that minimally encompass discrete state and obstacle distributions do not overlap. The improved performance is verified in a 3D environment using single, multi, and rotating non-convex obstacle cases, with and without forced obstacle error in adversarial directions, showing that W-Safe RRT can handle poorly modeled complex environments.

42 ENGINEERING↗
DOE OSTI2022

Do Machine Learning Approaches Offer Skill Improvement for Short-Term Forecasting of Wind Gust Occurrence and Magnitude?

Abstract Wind gusts, and in particular intense gusts, are societally relevant but extremely challenging to forecast. This study systematically assesses the skill enhancement that can be achieved using artificial neural networks (ANNs) for forecasting of wind gust occurrence and magnitude. Geophysical predictors from the ERA5 reanalysis are used in conjunction with an autoregressive term in regression and ANN models with different predictors, and varying model complexity. Models are derived and assessed for the warm (April–September) and cold (October–March) seasons for three high passenger volume airports in the United States. Model uncertainty is assessed by deriving models for 1000 different randomly selected training (70%) and testing (30%) subsets. Gust prediction fidelity in independent test samples is critically dependent on inclusion of an autoregressive term. Gust occurrence probabilities derived using five-layer ANNs exhibit consistently higher fidelity than those from regression models and shallower ANNs. Inclusion of the autoregressive term and increasing the number of hidden layers in ANNs from 1 to 5 also improve the model performance for gust magnitudes (lower RMSE, increased correlation, and model standard deviations that more closely approximate observed values). Deeper ANNs (e.g., 20 hidden layers) exhibit higher skill in forecasting strong (17–25.7 m s −1 ) and damaging (≥25.7 m s −1 ) wind gusts. However, such deep networks exhibit evidence of overfitting and still substantially underestimate (by 50%) the frequency of strong and damaging wind gusts at the three airports considered herein. Significance Statement Improved short-term forecasting of wind gusts will enhance aviation safety and logistics and may offer other societal benefits. Here we present a rigorous investigation of the relative skill of models of wind gust occurrence and magnitude that employ different statistical methods. It is shown that artificial neural networks (ANNs) offer considerable skill enhancement over regression methods, particularly for strong and damaging wind gusts. For wind gust magnitudes in particular, application of deeper learning networks (e.g., five or more hidden layers) offers tangible improvements in forecast accuracy. However, deeper networks are vulnerable to overfitting and exhibit substantial variability with the specific training and testing data subset used. Also, even deep ANNs reproduce only half of strong and damaging wind gusts. These results indicate the need for future work to elucidate the dynamical mechanisms of intense wind gusts and advance solutions to their prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Single-shot imaging with randomized structured illumination at a free electron laser

Stroboscopic nanoscale imaging with free electron laser light is revolutionizing our understanding of fast dynamics in heterogeneous systems. The short wavelength of X-ray and extreme ultraviolet radiation makes it possible to achieve nanoscale resolution, while resonance with atomic transitions gives access to electronic and magnetic degrees of freedom. Here, we report on our implementation of a recently developed imaging method, randomized probe imaging, at a free electron laser. The advantage of randomized probe imaging over existing methods is its compatibility with extended and strongly scattering samples. Our implementation delivers robust single-shot reconstructions at up to a full-pitch resolution of 400 nm over a field of view with a 40 µm diameter. We also demonstrate single-shot imaging of magnetic domain structures using circular dichroism at resonance, paving the way to future time-resolved studies of magnetic dynamics, shock physics, and the dynamics of collective electronic phases.

47 OTHER INSTRUMENTATION↗
NASA NTRS1973

Plasma electrolytes, pH, and ECG during and after exhaustive exercise.

Ten men worked on a bicycle ergometer at increasing work loads to exhaustion in 15 min. Each performed one test breathing air and another with added CO2 in random sequence. ECG was recorded during exercise and for 30 min of recovery. Arterial samples for blood gases, pH, and electrolytes were drawn at rest, in the last minute of exercise and at 1, 4, 10, 20, and 30 min thereafter. A striking increase in the amplitude of T and P waves was observed reaching a maximum in the first 2 min after exercise. All electrolytes measured were increased at the end of exercise, most markedly potassium (60%) and phosphorus (53%). Potassium dropped faster than all others to below resting values in 4 min coinciding with the lowest levels in plasma bicarbonate. ECG alterations were not closely related in time with any single factor such as potassium, but appeared to reflect an interaction of the transient mineral and acid-base imbalance during and immediately following exhaustive exercise.

Coester, N.↗
NASA NTRS1979

Radar error statistics for the space shuttle

Radar error statistics of C-band and S-band that are recommended for use with the groundtracking programs to process space shuttle tracking data are presented. The statistics are divided into two parts: bias error statistics, using the subscript B, and high frequency error statistics, using the subscript q. Bias errors may be slowly varying to constant. High frequency random errors (noise) are rapidly varying and may or may not be correlated from sample to sample. Bias errors were mainly due to hardware defects and to errors in correction for atmospheric refraction effects. High frequency noise was mainly due to hardware and due to atmospheric scintillation. Three types of atmospheric scintillation were identified: horizontal, vertical, and line of sight. This was the first time that horizontal and line of sight scintillations were identified.

Lear, W. M.↗
NASA NTRS1983

Some methods of estimating a coverage parameter

To demonstrate the high reliability of fault-tolerant computing systems, experimental testing can be performed by injecting faults into their hardware and observing the times needed to detect and isolate failed components and reconfigure the good components. Coverage, a parameter measuring continued system success, is the probability that recovery occurs before other, perhaps catastrophic, component failures occur. Methods of estimating coverage are given for the case of randomly selecting a subset of the pins or chips for testing. Pin-level samples of times to recovery are treated by the Type I censoring model often used in life testing.

Lee, L. D.↗