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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

An Advanced Machine Learning and Artificial Intelligence System for Demonstrating Radiation Regulatory Compliance in DOE Accelerator Facilities

In this Phase II proposal, Applied Research LLC (ARLLC), Thomas Jefferson National Accelerator Facility (Jefferson Lab), and Old Dominion University (ODU) propose the combination of domain knowledge (beam characteristics, fixed structural shielding, earthen burden (the soil and foliage added to the dome of the experimental halls as additional shielding), etc.), machine learning (ML) and/or artificial intelligence (AI) to correlate a variety of multi-modal onsite signals and the radiation fields seen in accessible areas of the accelerator site and the site boundary. The ML/AI will consider the complex influence of environmental parameters affecting the radon contribution of the measurements, focusing on actual data obtained from Jefferson Lab. In Phase I, the coded beam and location data were fed into a deep learning model to predict doses at several designated locations in Jefferson Lab’s facility. Moreover, a dense radiation map was generated using only a sparse collection of the samples in a facility. In Phase II, we will develop a software prototype containing a radiation prediction algorithm, dense radiation map algorithms, and background noise prediction algorithms, with actual data used to evaluate the prototype. This work will provide a framework for evaluation of radiation measurement results around the site based on learned responses. In addition, the proposed approach allows more granular mapping of radiation levels. Better understanding and communication of these levels is related to the overall approach in keeping doses to personnel ALARA.

43 PARTICLE ACCELERATORS↗
NASA NTRS1998

[Activities of Space Telescope Science Institute with the Hubble Space Telescope]

A number of studies, especially in recent years with the Hubble Space Telescope's (HST) Goddard High Resolution Spectrograph (GHRS), have been presented on the UV line profiles of late-type stars. Generally, these consist of a few "snapshot" spectra of several different key diagnostic emission lines. From this it has become clear that many active stars possess non-gaussian line profiles. Unlike the case with AR Lac, observed with IUE, no assymetric profile has been clearly identified that results from an inhomogeneous surface temperature or density distribution. In 1993 we attempted to observe the RS CVn binary V711 Tau at several phases with the GHRS in a number of UV bandpasses in order to study profile variations as a function of phase. Unfortunately, scheduling problems, pointing errors, continuous flaring and the sparse and uneven phase sampling prevented us from achieving the primary goal. However, it is clear that a number of UV lines in the system, notably C IV, Si IV and Mg II show very extended emission out to several hundred km/s. The profiles were also clearly variable. Vilhu et al. (1997) and Walter et al. (1995) conducted a campaign on the rapidly rotating, single star AB Dor, where they observed C IV continuously for 14 hours. They found extended, non-gaussian emission in the C IV doublet and that Doppler images derived from these images were remarkably similar to the simultaneous spot-image. In a follow up study of V711 Tau we have observed another RS CVn with complete phase coverage in three key wavelength bandpasses, utilizing the ability of HST to observe some stars at high latitudes in uninterrupted fashion. Generally classified as an RS CVn, V824 Ara (HD 155555) consists of a G5 IV star in a short period orbit (P=ld.68) with a K0 V-IV companion. However, the system does not eclipse and therefore does not rigorously fit the Hall (1976) definition. There is also a visual M star companion (LDS587B) 33 arcsec away. The space velocities of the stars suggests that the binary is part of the young disk population which agrees with the high Li I lambda 6708 abundance. With the M star companion showing very high levels of activity it seems likely that the V824 Ara +LDS587B system is pre-main sequence. With rotational velocities of 37 km/s and 29 km/s for the G and K star components respectively, the system is very similar to V711 Tau. Photometric observations by Cutispoto (1993) show an amplitude, delta V approx. = 0.12 with a period equal to the orbital value derived by Pasquini et at. (1991). Dempsey et al. (1993a) found a PSPC X-ray luminosity of 2.74 x 10(exp 30)erg/s. Two-temperature coronal models were applied to the PSPC X-ray pulse-height spectra by Dempsey et al. (1993b). They found that the lower temperature component was consistent with the full sample of RS CVn binaries studied but that the hot component was slightly lower than the sample as a whole. Moderate Ca II H and K emission, filled in H alpha and radio emission are also consistent with this being a fairly active, short period binary system.

Dempsey, Robert C.↗
NASA NTRS1997

A Comparison of Soil Moisture Retrieval Models Using SIR-C Measurements over the Little Washita River Watershed

Six SIR-C L-band measurements over the Little Washita River watershed in Chickasha, Oklahoma during 11-17 April 1994 have been analyzed for studying the change of soil moisture in the region. Two algorithms developed recently for estimation of moisture content in bare soil were applied to these measurements and the results were compared with those sampled on the ground. There is a good agreement between the values of soil moisture estimated by either one of the algorithms and those measured from ground sampling for bare or sparsely vegetated fields. The standard error from this comparison is on the order of 0.05-0.06 cu cm/cu cm, which is comparable to that expected from a regression between backscattering coefficients and measured soil moisture. Both algorithms provide a poor estimation of soil moisture or fail to give solutions to areas covered with moderate or dense vegetation. Even for bare soils the number of pixels that bear no numerical solution from the application of either one of the two algorithms to the data is not negligible. Results from using one of these algorithms indicate that the fraction of these pixels becomes larger as the bare soils become drier. The other algorithm generally gives a larger fraction of these pixels when the fields are vegetation-covered. The implication and impact of these features are discussed in this article.

Wang, J. R.↗
NASA NTRS1997

Biodosimetry of ionizing radiation by selective painting of prematurely condensed chromosomes in human lymphocytes

Painting of interphase chromosomes can be useful for biodosimetric purposes in particular cases such as radiation therapy, accidental exposure to very high radiation doses and exposure to densely ionizing radiation, for example during space missions. Biodosimetry of charged-particle radiation is analyzed in the present paper. Target cells were human peripheral blood lymphocytes irradiated in vitro with gamma rays, protons and iron ions. After exposure, lymphocytes were incubated for different times to allow repair of radiation-induced damage and then fused to mitotic hamster cells to promote premature condensation in the interphase chromosomes. Chromosome spreads were then hybridized with whole-chromosome DNA probes labeled with fluorescent stains. Dose-response curves for the induction of chromatin fragments shortly after exposure, as well as the kinetics of rejoining and misrejoining, were not markedly dependent on linear energy transfer. However, after exposure to heavy ions, more aberrations were scored in the interphase cells after incubation for repair than in metaphase samples harvested at the first postirradiation mitosis. On the other hand, no significant differences were observed in the two samples after exposure to sparsely ionizing radiation. These results suggest that interphase chromosome painting can be a useful tool for biodosimetry of particle radiation.

NASA Center JSC↗
NASA NTRS2005

Olivine and Ca-Phosphate in the Diogenites Manegaon and Roda

The textural relationships between the different primary minerals in igneous rocks provide one of the most fundamental pieces of evidence available for inferring the crystallization history of their parent magmas. Unfortunately, the high degree of brecciation that characterizes most diogenites, along with the low modal abundance and small grain sizes of minerals other than orthopyroxene, combine to make identifying and interpreting such textural relationships extremely difficult in this class of meteorites. A few descriptions of primary igneous contacts between orthopyroxene and chromite, troilite, and to a lesser extent, olivine in diogenites have been provided in the literature. In addition to these, in previous work, our research group has characterized several types of igneous contacts between Ca-pyroxene, plagioclase and orthopyroxene in the Bilanga diogenite. We have also described primary igneous inclusions of troilite + kamacite + chromite + Ca-pyroxene +/- Ca-phosphate in orthopyroxene (i.e. Metal/Troilite- Ball inclusions) in the diogenites Bilanga, Manegaon, Johnstown, Roda, Shalka, and Tatahouine. However, for the most part, detailed data on igneous textural relations between minerals other than orthopyroxene in diogenites are still sparse. Of the diogenite samples that we have examined,

Domanik, K. J.↗
NASA NTRS2013

An Indirect System Identification Technique for Stable Estimation of Continuous-Time Parameters of the Vestibulo-Ocular Reflex (VOR)

The vestibulo-ocular reflex (VOR) is a well-known dual mode bifurcating system that consists of slow and fast modes associated with nystagmus and saccade, respectively. Estimation of continuous-time parameters of nystagmus and saccade models are known to be sensitive to estimation methodology, noise and sampling rate. The stable and accurate estimation of these parameters are critical for accurate disease modelling, clinical diagnosis, robotic control strategies, mission planning for space exploration and pilot safety, etc. This paper presents a novel indirect system identification method for the estimation of continuous-time parameters of VOR employing standardised least-squares with dual sampling rates in a sparse structure. This approach permits the stable and simultaneous estimation of both nystagmus and saccade data. The efficacy of this approach is demonstrated via simulation of a continuous-time model of VOR with typical parameters found in clinical studies and in the presence of output additive noise.

Kukreja, Sunil L.↗
NASA NTRS2015

A Formal Messaging Notation for Alaskan Aviation Data

Data exchange is an increasingly important aspect of the National Airspace System. While many data communication channels have become more capable of sending and receiving data at higher throughput rates, there is still a need to use communication channels efficiently with limited throughput. The limitation can be based on technological issues, financial considerations, or both. This paper provides a complete description of several important aviation weather data in Abstract Syntax Notation format. By doing so, data providers can take advantage of Abstract Syntax Notation's ability to encode data in a highly compressed format. When data such as pilot weather reports, surface weather observations, and various weather predictions are compressed in such a manner, it allows for the efficient use of throughput-limited communication channels. This paper provides details on the Abstract Syntax Notation One (ASN.1) implementation for Alaskan aviation data, and demonstrates its use on real-world aviation weather data samples as Alaska has sparse terrestrial data infrastructure and data are often sent via relatively costly satellite channels.

communications↗
NASA NTRS2017

Large-scale product of forest height using a new approach from spaceborne repeat-pass SAR interferometry and LIDAR

Spaceborne SAR interferometry (InSAR) has the potential of mapping the forest height on a global scale and a monthly/weekly basis under all weather conditions, which can improve our understanding of the global carbon dynamics. In previous work, repeatpass SAR interferometry from spaceborne sensors is utilized to create large-scale forest height maps (that are particularly interested for large-scale ecological research) based on a newly developed approach. This paper thus serves as a summary paper and also sheds light on the future directions with improved results. In particular, it will be shown that repeat-pass SAR interferometry is able to create a large-scale forest height mosaic product with RMSE 4 m for forest stands on the order of 20 hectares through using the past spaceborne repeat-pass InSAR observations (i.e. JAXA’s ALOS-1 and ALOS-2) combined with sparse airborne lidar training samples over the forested areas in New England, US. Moreover, the results and performance of this approach can be remarkably improved with several enhancement techniques that can be easily satisfied with use of future spaceborne repeat-pass InSAR and lidar missions (e.g. NASA-ISRO’s NISAR and NASA’s GEDI). The methodology described in this paper can be considered as a complimentary tool to the existing PolInSAR technique and also serves as an observing prototype for the future spaceborne missions of repeatpass InSAR in fusion with lidar (e.g. NISAR and GEDI).

Treuhaft, Robert↗
NASA NTRS2012

Monitoring Ocean CO2 Fluxes from Space: GOSAT and OCO-2

The ocean is a major component of the global carbon cycle, emitting over 330 billion tons of carbon dioxide (CO2) into the atmosphere each year, or about 10 times that emitted fossil fuel combustion and all other human activities [1, 2]. The ocean reabsorbs a comparable amount of CO2 each year, along with ~25% of the CO2 emitted by these human activities. The nature and geographic distribution of the processes controlling these ocean CO2 fluxes are still poorly constrained by observations. A better understanding of these processes is essential to predict how this important CO2 sink may evolve as the climate changes.While in situ measurements of ocean CO2 fluxes can be very precise, the sampling density is far too sparse to quantify ocean CO2 sources and sinks over much of the globe. One way to improve the spatial resolution, coverage, and sampling frequency is to make observations of the column averaged CO2 dry air mole fraction, XCO2, from space [4, 5, 6]. Such measurements could provide global coverage at high resolution (< 100 km) on monthly time scales. High precision (< 1 part per million, ppm) is essential to resolve the small, near-surface CO2 variations associated with ocean fluxes and to better constrain the CO2 transport over the ocean. The Japanese Greenhouse gases Observing Satellite (GOSAT) and the NASA Orbiting Carbon Observatory (OCO) were first two space based sensors designed specifically for this task. GOSAT was successfully launched on January 23, 2009, and has been returning measurements of XCO2 since April 2009. The OCO mission was lost in February 2009, when its launch vehicle malfunctioned and failed to reach orbit. In early 2010, NASA authorized a re-flight of OCO, called OCO-2, which is currently under development.

GOSAT↗
DOE OSTI2017

A two-stage adaptive stochastic collocation method on nested sparse grids for multiphase flow in randomly heterogeneous porous media

A new computational method is proposed for efficient uncertainty quantification of multiphase flow in porous media with stochastic permeability. For pressure estimation, it combines the dimension-adaptive stochastic collocation method on Smolyak sparse grids and the Kronrod–Patterson–Hermite nested quadrature formulas. For saturation estimation, an additional stage is developed, in which the pressure and velocity samples are first generated by the sparse grid interpolation and then substituted into the transport equation to solve for the saturation samples, to address the low regularity problem of the saturation. Numerical examples are presented for multiphase flow with stochastic permeability fields to demonstrate accuracy and efficiency of the proposed two-stage adaptive stochastic collocation method on nested sparse grids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Analysis of sparse recovery for Legendre expansions using envelope bound

We provide novel sufficient conditions for the uniform recovery of sparse Legendre expansions using ℓ 1 minimization, where the sampling points are drawn according to orthogonalization (uniform) measure. So far, conditions of the form m ≳ Θ 2 s x log factors have been relied on to determine the minimum number of samples m that guarantees successful reconstruction of s-sparse vectors when the measurement matrix is associated to an orthonormal system. However, in case of sparse Legendre expansions, the uniform bound Θ of Legendre systems is so high that these conditions are unable to provide meaningful guarantees. Here, in this paper, we present an analysis which employs the envelop bound of all Legendre polynomials instead, and prove a new recovery guarantee for s-sparse Legendre expansions, m ≳ Θs 2 x log factors, which is independent of Θ. Arguably, this is the first recovery condition established for orthonormal systems without assuming the uniform boundedness of the sampling matrix. The key ingredient of our analysis is an extension of chaining arguments, recently developed in Bourgain and Chkifa et al., to handle the envelope bound. Furthermore, our recovery condition is proved via restricted eigenvalue property, a less demanding replacement of restricted isometry property which is perfectly suited to the considered scenario. Along the way, we derive simple criteria to detect good sample sets. Our numerical tests show that sets of uniformly sampled points that meet these criteria will perform better recovery on average.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Joint cosmic density reconstruction from photometric and spectroscopic samples

ABSTRACT We reconstruct the dark matter density field from spatially overlapping spectroscopic and photometric redshift catalogues through a field-level forward modelling approach. Instead of directly inferring the underlying density field, we find the best-fitting initial Gaussian fluctuations that will evolve into the observed cosmic volume. To account for the substantial uncertainty of photometric redshifts we employ a differentiable continuous Poisson process. As an initial test, we construct a mock based on the upcoming Prime Focus Spectrograph combined with photometric sample modelled on the Subaru Hyper Suprime-Cam. Depending on the statistic of interest, we find improvements in cosmic structure classification equivalent to 50–100 per cent more spectroscopic targets by combining relatively sparse spectroscopic with dense photometric samples.

Horowitz, B.↗
DOE OSTI2023

3′ RNA-seq is superior to standard RNA-seq in cases of sparse data but inferior at identifying toxicity pathways in a model organism

The application of RNA-sequencing has led to numerous breakthroughs related to investigating gene expression levels in complex biological systems. Among these are knowledge of how organisms, such as the vertebrate model organism zebrafish (Danio rerio), respond to toxicant exposure. Recently, the development of 3' RNA-seq has allowed for the determination of gene expression levels with a fraction of the required reads compared to standard RNA-seq. While 3' RNA-seq has many advantages, a comparison to standard RNA-seq has not been performed in the context of whole organism toxicity and sparse data. Here, we examined samples from zebrafish exposed to perfluorobutane sulfonamide (FBSA) with either 3' or standard RNA-seq to determine the advantages of each with regards to the identification of functionally enriched pathways. We found that 3' and standard RNA-seq showed specific advantages when focusing on annotated or unannotated regions of the genome. We also found that standard RNA-seq identified more differentially expressed genes (DEGs), but that this advantage disappeared under conditions of sparse data. We also found that standard RNA-seq had a significant advantage in identifying functionally enriched pathways via analysis of DEG lists but that this advantage was minimal when identifying pathways via gene set enrichment analysis of all genes. These results show that each approach has experimental conditions where they may be advantageous. Our observations can help guide others in the choice of 3' RNA-seq vs standard RNA sequencing to query gene expression levels in a range of biological systems.

3’ RNA-seq↗
DOE OSTI2015

Spectrotemporal CT data acquisition and reconstruction at low dose

Purpose: X-ray computed tomography (CT) is widely used, both clinically and preclinically, for fast, high-resolution anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. The authors propose and demonstrate a projection acquisition and reconstruction strategy for 5D CT (3D + dual energy + time) which recovers spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. Methods: The authors approach the 5D reconstruction problem within the framework of low-rank and sparse matrix decomposition. Unlike previous work on rank-sparsity constrained CT reconstruction, the authors establish an explicit rank-sparse signal model to describe the spectral and temporal dimensions. The spectral dimension is represented as a well-sampled time and energy averaged image plus regularly undersampled principal components describing the spectral contrast. The temporal dimension is represented as the same time and energy averaged reconstruction plus contiguous, spatially sparse, and irregularly sampled temporal contrast images. Using a nonlinear, image domain filtration approach, the authors refer to as rank-sparse kernel regression, the authors transfer image structure from the well-sampled time and energy averaged reconstruction to the spectral and temporal contrast images. This regularization strategy strictly constrains the reconstruction problem while approximately separating the temporal and spectral dimensions. Separability results in a highly compressed representation for the 5D data in which projections are shared between the temporal and spectral reconstruction subproblems, enabling substantial undersampling. The authors solved the 5D reconstruction problem using the split Bregman method and GPU-based implementations of backprojection, reprojection, and kernel regression. Using a preclinical mouse model, the authors apply the proposed algorithm to study myocardial injury following radiation treatment of breast cancer. Results: Quantitative 5D simulations are performed using the MOBY mouse phantom. Twenty data sets (ten cardiac phases, two energies) are reconstructed with 88 μm, isotropic voxels from 450 total projections acquired over a single 360° rotation. In vivo 5D myocardial injury data sets acquired in two mice injected with gold and iodine nanoparticles are also reconstructed with 20 data sets per mouse using the same acquisition parameters (dose: ∼60 mGy). For both the simulations and the in vivo data, the reconstruction quality is sufficient to perform material decomposition into gold and iodine maps to localize the extent of myocardial injury (gold accumulation) and to measure cardiac functional metrics (vascular iodine). Their 5D CT imaging protocol represents a 95% reduction in radiation dose per cardiac phase and energy and a 40-fold decrease in projection sampling time relative to their standard imaging protocol. Conclusions: Their 5D CT data acquisition and reconstruction protocol efficiently exploits the rank-sparse nature of spectral and temporal CT data to provide high-fidelity reconstruction results without increased radiation dose or sampling time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Measurement of the small-scale 3D Lyman- α forest power spectrum

Small-scale correlations measured in the Lyman-α (Lyα) forest encode information about the intergalactic medium and the primordial matter power spectrum. In this article, we present and implement a simple method to measure the 3-dimensional power spectrum, P 3D , of the Lyα forest at wavenumbers k corresponding to small, ~ Mpc scales. In order to estimate P 3D from sparsely and unevenly distributed data samples, we rely on averaging 1-dimensional Fourier Transforms, as previously carried out to estimate the 1-dimensional power spectrum of the Lyα forest, P 1D . Further, this methodology exhibits a very low computational cost. We confirm the validity of this approach through its application to Nyx cosmological hydrodynamical simulations. Subsequently, we apply our method to the eBOSS DR16 Lyα forest sample, providing as a proof of principle, a first P 3D measurement averaged over two redshift bins z = 2.2 and z = 2.4. This work highlights the potential for forthcoming P 3D measurements, from upcoming large spectroscopic surveys, to untangle degeneracies in the cosmological interpretation of P 1D .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Wavefront shaping with a Hadamard basis for scattering soil imaging

Here, soil is a scattering medium that inhibits imaging of plant-microbial-mineral interactions that are essential to plant health and soil carbon sequestration. However, optical imaging in the complex medium of soil has been stymied by the seemingly intractable problems of scattering and contrast. Here, we develop a wavefront shaping method based on adaptive stochastic parallel gradient descent optimization with a Hadamard basis to focus light through soil mineral samples. Our approach allows a sparse representation of the wavefront with reduced dimensionality for the optimization. We further divide the used Hadamard basis set into subsets and optimize a certain subset at once. Simulation and experimental optimization results demonstrate our method has an approximately seven times higher convergence rate and overall better performance compared to that with optimizing all pixels at once. The proposed method can benefit other high-dimensional optimization problems in adaptive optics and wavefront shaping.

47 OTHER INSTRUMENTATION↗
NASA NTRS1992

Time-dependent inhomogeneous jet models for BL Lac objects

Relativistic beaming can explain many of the observed properties of BL Lac objects (e.g., rapid variability, high polarization, etc.). In particular, the broadband radio through X-ray spectra are well modeled by synchrotron-self Compton emission from an inhomogeneous relativistic jet. We have done a uniform analysis on several BL Lac objects using a simple but plausible inhomogeneous jet model. For all objects, we found that the assumed power-law distribution of the magnetic field and the electron density can be adjusted to match the observed BL Lac spectrum. While such models are typically unconstrained, consideration of spectral variability strongly restricts the allowed parameters, although to date the sampling has generally been too sparse to constrain the current models effectively. We investigate the time evolution of the inhomogeneous jet model for a simple perturbation propagating along the jet. The implications of this time evolution model and its relevance to observed data are discussed.

Marlowe, A. T.↗