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All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

The case for planetary sample return missions. 2. History of Mars

Principal science goals for exploration of Mars are to establish the chemical, isotopic, and physical state of Martian material, the nature of major surface-forming processes and their time scales, and the past and present biological potential of the planet. Many of those goals can only be met by detailed analyses of atmospheric gases and carefully selected samples of fresh rocks, weathered rocks, soils, sediments, and ices. The high-fidelity mineral separations, complex chemical treatments, and ultrasensitive instrument systems required for key measurements, as well as the need to adapt analytical strategies to unanticipated results, point to Earth-based laboratory analyses on returned Martian samples as the best means for meeting the stated objectives.

NASA Center ARC↗
DOE OSTI2016

SEARCHING FOR BINARY Y DWARFS WITH THE GEMINI MULTI-CONJUGATE ADAPTIVE OPTICS SYSTEM (GeMS)

The NASA Wide-field Infrared Survey Explorer (WISE) has discovered almost all the known members of the new class of Y-type brown dwarfs. Most of these Y dwarfs have been identified as isolated objects in the field. It is known that binaries with L- and T-type brown dwarf primaries are less prevalent than either M-dwarf or solar-type primaries, they tend to have smaller separations and are more frequently detected in near-equal mass configurations. The binary statistics for Y-type brown dwarfs, however, are sparse, and so it is unclear if the same trends that hold for L- and T-type brown dwarfs also hold for Y-type ones. In addition, the detection of binary companions to very cool Y dwarfs may well be the best means available for discovering even colder objects. We present results for binary properties of a sample of five WISE Y dwarfs with the Gemini Multi-Conjugate Adaptive Optics System. We find no evidence for binary companions in these data, which suggests these systems are not equal-luminosity (or equal-mass) binaries with separations larger than ∼0.5–1.9 AU. For equal-mass binaries at an age of 5 Gyr, we find that the binary binding energies ruled out by our observations (i.e., 10{sup 42} erg) are consistent with those observed in previous studies of hotter ultra-cool dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗
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↗
DOE OSTI2015

SU-E-J-127: Implementation of An Online Replanning Tool for VMAT Using Flattening Filter-Free Beams

Purpose: This is to report the implementation of an online replanning tool based on segment aperture morphing (SAM) for VMAT with flattening filter free (FFF) beams. Methods: Previously reported SAM algorithm modified to accommodate VMAT with FFF beams was implemented in a tool that was interfaced with a treatment planning system (Monaco, Elekta). The tool allows (1) to output the beam parameters of the original VMAT plan from Monaco, and (2) to input the apertures generated from the SAM algorithm into Monaco for the dose calculation on daily CT/CBCT/MRI in the following steps:(1) Quickly generating target contour based on the image of the day, using an auto-segmentation tool (ADMIRE, Elekta) with manual editing if necessary; (2) Morphing apertures based on the SAM in the original VMAT plan to account for the interfractional change of the target from the planning to the daily images; (3) Calculating dose distribution for new apertures with the same numbers of MU as in the original plan; (4) Transferring the new plan into a record & verify system (MOSAIQ, Elekta); (5) Performing a pre-delivery QA based on software; (6) Delivering the adaptive plan for the fraction.This workflow was implemented on a 16-CPU (2.6 GHz dual-core) hardware with GPU and was tested for sample cases of prostate, pancreas and lung tumors. Results: The online replanning process can be completed within 10 minutes. The adaptive plans generally have improved the plan quality when compared to the IGRT repositioning plans. The adaptive plans with FFF beams have better normal tissue sparing as compared with those of FF beams. Conclusion: The online replanning tool based on SAM can quickly generate adaptive VMAT plans using FFF beams with improved plan quality than those from the IGRT repositioning plans based on daily CT/CBCT/MRI and can be used clinically. This research was supported by Elekta Inc. (Crawley, UK)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Enhancing adaptive sparse grid approximations and improving refinement strategies using adjoint-based a posteriori error estimates

In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical discretization error and the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity of the sparse grid. Utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Application of adaptive hierarchical sparse grid collocation to the uncertainty quantification of nuclear reactor simulators

Recent efforts in the application of uncertainty quantification to nuclear systems have utilized methods based on generalized perturbation theory and stochastic sampling. While these methods have proven to be effective they both have major drawbacks that may impede further progress. A relatively new approach based on spectral elements for uncertainty quantification is applied in this paper to several problems in reactor simulation. Spectral methods based on collocation attempt to couple the approximation free nature of stochastic sampling methods with the determinism of generalized perturbation theory. The specific spectral method used in this paper employs both the Smolyak algorithm and adaptivity by using Newton-Cotes collocation points along with linear hat basis functions. Using this approach, a surrogate model for the outputs of a computer code is constructed hierarchically by adaptively refining the collocation grid until the interpolant is converged to a user-defined threshold. The method inherently fits into the framework of parallel computing and allows for the extraction of meaningful statistics and data that are not within reach of stochastic sampling and generalized perturbation theory. This paper aims to demonstrate the advantages of spectral methods-especially when compared to current methods used in reactor physics for uncertainty quantification-and to illustrate their full potential. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Application of an Evolutionary Algorithm for Parameter Optimization in a Gully Erosion Model

Herein we demonstrate how to use model optimization to determine a set of best-fit parameters for a landform model simulating gully incision and headcut retreat. To achieve this result we employed the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an iterative process in which samples are created based on a distribution of parameter values that evolve over time to better fit an objective function. CMA-ES efficiently finds optimal parameters, even with high-dimensional objective functions that are non-convex, multimodal, and non-separable. We ran model instances in parallel on a high-performance cluster, and from hundreds of model runs we obtained the best parameter choices. This method is far superior to brute-force search algorithms, and has great potential for many applications in earth science modeling. We found that parameters representing boundary conditions tended to converge toward an optimal single value, whereas parameters controlling geomorphic processes are defined by a range of optimal values.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Note: A method for minimizing oxide formation during elevated temperature nanoindentation

A standardized method to protect metallic samples and minimize oxide formation during elevated-temperature nanoindentation was adapted to a commercial instrument. Nanoindentation was performed on Al (100), Cu (100), and W (100) single crystals submerged in vacuum oil at 200 °C, while the surface morphology and oxidation was carefully monitored using atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS). The results were compared to room temperature and 200 °C nanoindentation tests performed without oil, in order to evaluate the feasibility of using the oil as a protective medium. Extensive surface characterization demonstrated that this methodology is effective for nanoscale testing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Graph convolutional networks applied to unstructured flow field data

Abstract Many scientific and engineering processes produce spatially unstructured data. However, most data-driven models require a feature matrix that enforces both a set number and order of features for each sample. They thus cannot be easily constructed for an unstructured dataset. Therefore, a graph based data-driven model to perform inference on fields defined on an unstructured mesh, using a graph convolutional neural network (GCNN) is presented. The ability of the method to predict global properties from spatially irregular measurements with high accuracy is demonstrated by predicting the drag force associated with laminar flow around airfoils from scattered velocity measurements. The network can infer from field samples at different resolutions, and is invariant to the order in which the measurements within each sample are presented. The GCNN method, using inductive convolutional layers and adaptive pooling, is able to predict this quantity with a validation R 2 above 0.98, and a Normalized Mean Squared Error below 0.01, without relying on spatial structure.

Ogoke, Francis (ORCID:0000000224327783)↗
DOE OSTI2024

GalaxyFlow: upsampling hydrodynamical simulations for realistic mock stellar catalogues

ABSTRACT Cosmological N-body simulations of galaxies operate at the level of ‘star particles’ with a mass resolution on the scale of thousands of solar masses. Turning these simulations into stellar mock catalogues requires ‘upsampling’ the star particles into individual stars following the same phase-space density. In this paper, we introduce two new upsampling methods. First, we describe GalaxyFlow, a sophisticated upsampling method that utilizes normalizing flows to both estimate the stellar phase-space density and sample from it. Secondly, we improve on existing upsamplers based on adaptive kernel density estimation (KDE), using maximum likelihood estimation to fine-tune the bandwidth for such algorithms in a way that improves both the density estimation accuracy and upsampling results. We demonstrate our upsampling techniques on a neighbourhood of the Solar location in two simulated galaxies: Auriga 6 and h277. Both yield smooth stellar distributions that closely resemble the stellar densities seen in the Gaia DR3 catalogue. Furthermore, we introduce a novel multimodel classifier test to compare the accuracy of different upsampling methods quantitatively. This test confirms that GalaxyFlow more accurately estimates the density of the underlying star particles than methods based on KDE, at the cost of being more computationally intensive.

Lim, Sung Hak (ORCID:0000000330981092)↗
DOE OSTI2016

Giant clumps in simulated high- z Galaxies: properties, evolution and dependence on feedback

Here, we study the evolution and properties of giant clumps in high- z disc galaxies using adaptive mesh refinement cosmological simulations at redshifts z ∼ 6–1. Our sample consists of 34 galaxies, of halo masses 10 11 –10 12 M⊙ at z = 2, run with and without radiation pressure (RP) feedback from young stars. While RP has little effect on the sizes and global stability of discs, it reduces the amount of star-forming gas by a factor of ∼2, leading to a similar decrease in stellar mass by z ∼ 2. Both samples undergo extended periods of violent disc instability continuously forming giant clumps of masses 10 7 –10 9 M ⊙ at a similar rate, though RP significantly reduces the number of long-lived clumps (LLCs). When RP is (not) included, clumps with circular velocity ≲ 40 (20) km s -1 , baryonic surface density ≲ 200 (100)M ⊙ pc -2 and baryonic mass ≲ 10 8.2 (10 7.3 ) M ⊙ are short-lived, disrupted in a few free-fall times. More massive and dense clumps survive and migrate towards the disc centre over a few disc orbital times. In the RP simulations, the distribution of clump masses and star formation rates (SFRs) normalized to their host disc is similar at all redshifts, exhibiting a truncated power law with a slope slightly shallower than -2. The specific SFR (sSFR) of the LLCs declines with age as they migrate towards the disc centre, producing gradients in mass, stellar age, gas fraction, sSFR and metallicity that distinguish them from the short-lived clumps which tend to populate the outer disc. Ex situ mergers comprise ~37 percent of the mass in clumps and ~29 percent of the SFR. They are more massive and with older stellar ages than the in situ clumps, especially near the disc edge. Lastly, roughly half the galaxies at redshifts z = 4–1 are clumpy, with ~3–30 percent of their SFR and ~0.1–3 percent of their stellar mass in clumps.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

TU-F-18C-03: X-Ray Scatter Correction in Breast CT: Advances and Patient Testing

Purpose: To further develop and perform patient testing of an x-ray scatter correction algorithm for dedicated breast computed tomography (BCT). Methods: A previously proposed algorithm for x-ray scatter signal reduction in BCT imaging was modified and tested with a phantom and on patients. A wireless electronic positioner system was designed and added to the BCT system that positions a tungsten plate in and out of the x-ray beam. The interpolation used by the algorithm was replaced with a radial basis function-based algorithm, with automated exclusion of non-valid sampled points due to patient motion or other factors. A 3D adaptive noise reduction filter was also introduced to reduce the impact of scatter quantum noise post-reconstruction. The impact on image quality of the improved algorithm was evaluated using a breast phantom and seven patient breasts, using quantitative metrics such signal difference (SD) and signal difference-to-noise ratios (SDNR) and qualitatively using image profiles. Results: The improvements in the algorithm resulted in a more robust interpolation step, with no introduction of image artifacts, especially at the imaged object boundaries, which was an issue in the previous implementation. Qualitative evaluation of the reconstructed slices and corresponding profiles show excellent homogeneity of both the background and the higher density features throughout the whole imaged object, as well as increased accuracy in the Hounsfield Units (HU) values of the tissues. Profiles also demonstrate substantial increase in both SD and SDNR between glandular and adipose regions compared to both the uncorrected and system-corrected images. Conclusion: The improved scatter correction algorithm can be reliably used during patient BCT acquisitions with no introduction of artifacts, resulting in substantial improvement in image quality. Its impact on actual clinical performance needs to be evaluated in the future. Research Agreement, Koning Corp., Hologic Inc., Barco Corp Consultant Agreement, Fujifilm Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Cloud Condensation Nuclei Particle Counter Instrument Handbook - Airborne Version

The cloud condensation nuclei counter (CCN) is a U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility instrument for measuring the concentration of aerosol particles that can act as cloud condensation nuclei. Note: ARM deploys both ground and airborne versions of this instrument. This handbook covers only the airborne instrument; the ground version is covered by DOE/SC-ARM-TR-168. The main differences between the two are that the airborne CCN operates at fixed supersaturation and adapts thermal efficiency calculation in the data process. The CCN draws sample aerosol through a column with thermodynamically unstable supersaturated water vapor that can condense onto aerosol particles. Particles that are activated, i.e., grown larger in this process, are counted (and sized) by an optical particle counter (OPC). Thus, activated ambient aerosol particle number concentration as a function of supersaturation is measured. Models CCN-100 and CCN- 200 differ only in the number of humidifier columns and related subsystems: CCN-100 has one column and CCN-200 has two columns along with dual flow systems and electronics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High Throughput Genome Releaser

In this study, we present the development of a High Throughput Genome Releaser, an innovative device addressing common challenges in screening PCR. This genome DNA releaser is designed for rapid, cost-effective, and efficient DNA extraction, optimized for subsequent PCR reactions. Our experimentation with various synthetic materials led us to select a particular type of plastic that mirrors the properties of glass cover slides, providing a smooth surface and effective compression capabilities. We engineered a 96-well device equipped with a 96-well plate and a top rod, operable both manually and automatically, which is compatible with widely used liquid-handling robot decks. This compatibility enhances ease of use in high-throughput PCR setups. Additionally, we developed software to support its automatic functions. The genome releaser facilitates the extraction of PCR-amplifiable genomic DNA from 96 samples within minutes, eliminates the need for extraction buffers, and is adaptable to a wide range of microorganisms and cells. This versatility could significantly advance biomanufacturing processes.

42 ENGINEERING↗
DOE OSTI2025

An Innovative High Throughput Genome Releaser for Rapid and Efficient PCR Screening

High-throughput PCR screening is vital in synthetic biology and metabolic engineering as it allows researchers to rapidly analyze and detect numerous targeted genetic mutation in the genome. Current challenges for high-throughput PCR screening in synthetic biology include efficiently preparing genomic DNA, optimizing protocols for diverse sample types, managing contamination risks, and effectively analyzing the large volumes of data generated while ensuring consistent and accurate results. In this study, we present the development of a High Throughput Genome Releaser (HTGR), an innovative device addressing common challenges in screening PCR. This genome DNA releaser is designed based on a squash method for rapid, cost-effective, and efficient DNA release, optimized for subsequent PCR reactions. After experimenting with various synthetic materials, we selected a plastic that closely replicates the smooth surface and compression properties of microscope slides, ensuring reliable performance. We engineered a device featuring a 96-Well Plate and a shear applicator, operable both manually and automatically, and compatible with standard liquid-handling robot platform. This compatibility enhances ease of use in high-throughput PCR workflows. Additionally, we developed software to support its automatic functions. Our results demonstrated that the specially engineered 96-Well Plate and HTGR can effectively squash fungal spores , which release enough genome DNA for PCR screening. The genome releaser facilitates the preparation of PCR-amplifiable genomic DNA substrate from 96 samples within minutes, eliminates the need for extraction buffers, and is adaptable to a wide range of microorganisms and cells, which could significantly advance biomanufacturing processes.

Yuan, Guoliang [BATTELLE (PACIFIC NW LAB)]↗
NASA NTRS1972

ALLMAG, GDALMG, LINTRA: Computer programs for geomagnetic field and field-line calculations

A set of computer programs has been developed for the calculation of the geomagnetic field and the tracing of field lines in space. The basic subroutine, geocentric ALLMAG, contains coefficients for seven recently-published field models as built-in data statements. At execution time the user can vary the model and/or the time period by simply changing input parameters. Subroutine GDALMG is adapted for input and output in geodetic coordinates. ALLMAG and GDALMG are equivalent to Cain's FIELD and FIELDG, with the added flexibility of the choice of seven models. LINTRA traces field lines from any point in space to a specified altitude intersect in the same or opposite hemisphere, using any of the models contained in ALLMAG. Input is in either geocentric or geodetic coordinates, and output is returned in both. McIlwain's INVAR package, which calculates B and L, has been adapted to use ALLMAG. All programs are described in detail, and sample calculations are given.

Stassinopoulos, E. G.↗
NASA NTRS1971

A variable-step-size robust delta modulator.

Description of an analytically obtained optimum adaptive delta modulator-demodulator configuration. The device utilizes two past samples to obtain a step size which minimizes the mean square error for a Markov-Gaussian source. The optimum system is compared, using computer simulations, with a linear delta modulator and an enhanced Abate delta modulator. In addition, the performance is compared to the rate distortion bound for a Markov source. It is shown that the optimum delta modulator is neither quantization nor slope-overload limited. The highly nonlinear equations obtained for the optimum transmitter and receiver are approximated by piecewise-linear equations in order to obtain system equations which can be transformed into hardware. The derivation of the experimental system is presented.

Song, C. L.↗