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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Synthesis of bulk reactive Ni–Al composites using high pressure torsion

Self-propagating exothermic reactions, for instance in the nickel-aluminum (Ni-Al) system, have been widely studied to create high performance intermetallic compounds or for in-situ welding. Their easy ignition once the phase spacing is reduced below the micron scale, makes top-down methods like high-energy ball milling, ideal to fabricate such reactive nanostructures. A major drawback of ball milling is the need of a sintering step to form bulk pieces of the reactive material. However, this is not possible, as the targeted reactions would already proceed. Therefore, we investigate the ability of high pressure torsion as an alternative process, capable to produce bulk nanocomposites from powder mixtures. Severe straining of powder mixtures with a composition of 50 wt% Ni and 50 wt% Al enables fabrication of self-reactive bulk samples with microstructures similar to those obtained from ball milling or magnetron sputtering. Additionally, samples deformed at ambient temperature are highly reactive and can be ignited significantly below the Al melting point, finally predominantly consisting of Al 3 Ni 2 and Al 3 Ni, independent of the applied strain. Although the reaction proceeds first at the edge of the disk, the strain gradient present in the disks does not prevent reaction of the whole sample.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Predictive Prescription Framework for Stochastic Unit Commitment Using Boosting Ensemble Learning Algorithms

To take unit commitment (UC) decisions under uncertain load, most existing stochastic optimization (SO) frameworks adopt a generic representation of uncertainty. While load levels that materialize on a particular day are influenced by various covariates (such as the day of the week or temperature), SO frameworks typically disregard such side observations, wasting actionable information that could significantly enhance decision quality. Here, this article proposes a contextual SO (CSO) framework for UC under uncertain load, which can effectively exploit covariate observations in conjunction with a class of machine learning (ML) algorithms to improve the out-of-sample performance of UC decisions. It shows how three ML algorithms, adaptive boosting, gradient boosted trees, and extreme gradient boosting, can be used to this end, constituting the first application of these algorithms in any CSO framework. Using real-world data harvested from the New York ISO grid, we measure the out-of-sample performance of the framework in terms of total operation cost, shed load values, locational marginal prices, and total payments by the loads, against several benchmark methods proposed in the literature. The article has an online companion (Yurdakul et al.), wherein we present additional results and lay out further mathematical formulations used in this work.

42 ENGINEERING↗
DOE OSTI2024

Experimental and Computational Studies of Crystal Nucleation in Composition Gradients (Final Report)

The major goals of this project were to develop and validate a predictive nucleation model that incorporates composition gradients and is applicable to a large range of metallic systems which form both stochiometric and non-stochiometric compounds. Computationally we planned to expand the extent of thermodynamics-based theories and lay the groundwork to improve the general understanding and predictive capabilities of the role that gradients play in phase formation, glass formability and stability, and nucleation and growth events. To address these goals, we used Molecular Dynamics (MD) simulations and both isothermal and isochronal nanocalorimetric experiments on amorphous phases with a controlled composition gradient with the hopes of validating and improving the classical nucleation model and its use in solid solutions. While the computations were successful and identified ways to improve the classical nucleation model, the in situ nanocalorimetry studies proved very challenging due to unexpected difficulties in fabricating effective calorimeters and samples. Thus, we could not experimentally validate our predicted influence of composition gradients on nucleation. Nonetheless, important insights were gained and modifications to the classical nucleation theory were suggested.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Gas-phase metallicity determinations in nearby AGNs with SDSS-IV MaNGA: evidence of metal-poor accretion

ABSTRACT We derive the metallicity (traced by the O/H abundance) of the narrow-line region (NLR) of 108 Seyfert galaxies as well as radial metallicity gradients along their galaxy discs and of these of a matched control sample of no active galaxies. In view of that, observational data from the SDSS-IV MaNGA survey and strong emission-line calibrations taken from the literature were considered. The metallicity obtained for the NLRs was compared to the value derived from the extrapolation of the radial oxygen abundance gradient, obtained from H ii region estimates along the galaxy disc, to the central part of the host galaxies. We find that, for most of the objects ($\sim 80\, {{\ \rm per\ cent}}$), the NLR metallicity is lower than the extrapolated value, with the average difference ($\langle$D$\rangle$) between these estimates ranging from 0.16 to 0.30 dex. We suggest that $\langle$D$\rangle$ is due to the accretion of metal-poor gas to the AGN that feeds the nuclear supermassive black hole (SMBH), which is drawn from a reservoir molecular and/or neutral hydrogen around the SMBH. Additionally, we look for correlations between D and the electron density (Ne), [O iii]λ5007, and H α luminosities, extinction coefficient (AV) of the NLRs, as well as the stellar mass (M*) of the host galaxies. Evidence of an inverse correlation between the D and the parameters Ne, M*, and Av was found.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Absence of Barren Plateaus and Scaling of Gradients in the Energy Optimization of Isometric Tensor Network States

Abstract Vanishing gradients can pose substantial obstacles for high-dimensional optimization problems. Here we consider energy minimization problems for quantum many-body systems with extensive Hamiltonians and finite-range interactions, which can be studied on classical computers or in the form of variational quantum eigensolvers on quantum computers. Barren plateaus correspond to scenarios where the average amplitude of the energy gradient decreases exponentially with increasing system size. This occurs, for example, for quantum neural networks and for brickwall quantum circuits when the depth increases polynomially in the system size. Here we prove that the variational optimization problems for matrix product states, tree tensor networks, and the multiscale entanglement renormalization ansatz are free of barren plateaus. The derived scaling properties for the gradient variance provide an analytical guarantee for the trainability of randomly initialized tensor network states (TNS) and motivate certain initialization schemes. In a suitable representation, unitary tensors that parametrize the TNS are sampled according to the uniform Haar measure. We employ a Riemannian formulation of the gradient based optimizations which simplifies the analytical evaluation.

Barthel, Thomas↗
NASA NTRS2001

Thermal Modeling and Analysis of a Sub-Compact Seebeck Furnace

The Sub-Compact Seebeck Furnace (SCSF) is a third generation furnace designed as an experimental facility to study the phenomena of undercooling associated with directional solidification. It is intended to provide a double peak temperature profile along the axial direction with gradient zones at each end. By keeping the temperature in the central portion above the melting point of the sample, and cooling the ends of the furnace, a solid/liquid (S/L) interface can be maintained in each one of the gradient zones. A motorized motion control provides a motion to one-half of the furnace. The undercooling associated with the interface being directionally solidified can thus be studied. Modeling of the temperature profile is important to help assure that the furnace design provides the correct thermal characteristics. The furnace is designed with two halves that telescope. Results of thermal analysis based on an analytical solution using simple assumptions will be presented. The resulting temperature profile will show the salient features of the desired thermal profile and provide the general directions for thermal design. Experimental results will be used to compare with the analytical profile. Approach for numerical modeling to provide more detailed information such as two-dimensional effects will be discussed.

Wang, Francis C.↗
DOE OSTI2022

Estimating Drizzle Parameters by Aircraft Sampling

In-cloud supersaturation is calculated from aircraft derived measurements of the in-cloud vertical gradient of liquid water content, vertical velocity, the pt and 3 rd cloud droplet radius moments and a parameter related to the heat and mass transport during condensation and evaporation of cloud droplets. The aircraft data where taken during the VOCALS 2008 study in marine stratocumulus clouds off the coast of Chile. Approximately 16000 discrete samples, 2.5 meter in length, were used in the present analysis of in-cloud supersaturation and its variability, both of which are indicative of turbulent processes within the cloud and their significant impact on drizzle formation. Two additional drizzle parameters, the eddy persistence time and the variance of fluctuations in in-cloud droplet growth rate were also estimated from this data set. These results will help to constrain parameterizations of underlying turbulent microphysical processes of clouds and thereby advance the future development of warm cloud and precipitation models for climate simulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Scalable Techniques for Stochastic Power Flow Problems (Final Report)

The proposed research focuses on developing scalable algorithms for two-stage security-constrained OPF problems with AC power flow constraints, a class of problems complicated by (i) scale arising from a scenario representation; and (ii) the presence of nonlinearity, nonconvexity, and possibly second-stage discreteness or complementarity. Unfortunately, most existing solvers cannot contend with both challenges simultaneously; accordingly, the proposed research focuses on developing solution techniques that can both scale with the number of scenarios and contend with nonconvexity and second-stage complementarity. We consider three avenues for addressing such problems: (i) Variable sample-size SQP (VS-SQP) methods that combine sparse Quasi-Newton updates with a scalable variance-reduced stochastic gradient scheme for stochastic QP subproblems, allowing for contending with second-stage complementarity via regularization; (ii) Variable sample-size stochastic Interior-point (VS-sIP) schemes that propose a sampling-based regularized (to allow for contending with complementarity) interior-point schemes in which a Schur-complement technique is employed for decomposing the Newton direction computation step; (iii) Variable sample-size tractable ADMM (VS-tADMM) schemes combine variable sample-sizes with carefully designed techniques for resolving each of the nonconvex updates (by leveraging the QCQP structures). We intend to compare the three schemes using performance profiles in terms of solution quality, scalability, etc. and then select one scheme which will then be developed and further refined in Python for purposes of the GO competition.

42 ENGINEERING↗
DOE OSTI2023

Gray matter volume drives the brain age gap in schizophrenia: a SHAP study

Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML) predictions. The brain age gap (BAG) is typically defined as the difference between the predicted brain age and chronological age. Studies have consistently reported a positive BAG in individuals with schizophrenia (SCZ). However, there is little understanding of which specific factors drive the ML-based brain age predictions, leading to limited biological interpretations of the BAG. We gathered data from three publicly available databases - COBRE, MCIC, and UCLA - and an additional dataset (TOPSY) of early-stage schizophrenia (82.5% untreated first-episode sample) and calculated brain age with pre-trained gradient-boosted trees. Then, we applied SHapley Additive Explanations (SHAP) to identify which brain features influence brain age predictions. We investigated the interaction between the SHAP score for each feature and group as a function of the BAG. These analyses identified total gray matter volume (group × SHAP interaction term β = 1.71 [0.53; 3.23]; p corr < 0.03) as the feature that influences the BAG observed in SCZ among the brain features that are most predictive of brain age. Other brain features also presented differences in SHAP values between SCZ and HC, but they were not significantly associated with the BAG. We compared the findings with a non-psychotic depression dataset (CAN-BIND), where the interaction was not significant. This study has important implications for the understanding of brain age prediction models and the BAG in SCZ and, potentially, in other psychiatric disorders.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Nonlinear dimension reduction for surrogate modeling using gradient information

We introduce a method for the nonlinear dimension reduction of a high-dimensional function $u:{\mathbb{R}}^d\rightarrow{\mathbb{R}}$, $d\gg 1$. Our objective is to identify a nonlinear feature map $g:{\mathbb{R}}^d\rightarrow{\mathbb{R}}^m$, with a prescribed intermediate dimension $m\ll d$, so that $u$ can be well approximated by $f\circ g$ for some profile function $f:{\mathbb{R}}^m\rightarrow{\mathbb{R}}$. We propose to build the feature map by aligning the Jacobian $\nabla g$ with the gradient $\nabla u$, and we theoretically analyze the properties of the resulting $g$. Once $g$ is built, we construct $f$ by solving a gradient-enhanced least squares problem. Our practical algorithm uses a sample $\{{\textbf{x}}^{(i)},u({\textbf{x}}^{(i)}),\nabla u({\textbf{x}}^{(i)})\}_{i=1}^N$ and builds both $g$ and $f$ on adaptive downward-closed polynomial spaces, using cross validation to avoid overfitting. We numerically evaluate the performance of our algorithm across different benchmarks, and explore the impact of the intermediate dimension $m$. We show that building a nonlinear feature map $g$ can permit more accurate approximation of $u$ than a linear $g$, for the same input data set.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Deep Neural Network Informed Markov Chain Monte Carlo Methods

In subsurface flow modeling, quantifying the uncertainty of model parameters and the corresponding uncertainly on output quantities is a crucial task for groundwater management. Markov chain Monte Carlo (MCMC) methods can take advantage of observed data to estimate parameters in a Bayesian setting. However, MCMC can be slow to converge and produce highly correlated samples when the dimensions of the parameters is high. Using gradients for the posterior distribution can help samplers explore the parameter space more efficiently, but obtaining gradients can be computationally challenging.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

In Situ Non-Destructive Temporal Measurements of the Rhizosphere Microbiome ‘Hot-Spots’ Using Metaproteomics

Rhizosphere arguably embodies the most diverse microbial ecosystem on the planet, yet it is largely a functional ‘black box’ of belowground plant-microbiome interactions. The rhizosphere is the primary site of entry for subsurface injection of fixed carbon (C) into soil with impacts on local to global scale C biogeochemistry and ultimately Earth’s climate. While spatial organization of rhizosphere is central to its function, small scale and steep microbial and geochemical gradients within this dynamic region make it easily disrupted by sampling. The significant challenge presented by sampling blocks elucidation of discreet functions, drivers, and interactions within rhizosphere ecosystems. Here, we describe a non-destructive sampling method linked to metaproteomic analysis in order to measure temporal shifts in the microbial composition and function of rhizosphere. A robust, non-destructive method of sampling microbial hotspots within rhizosphere provides an unperturbed window into the elusive functional interactome of this system over time and space.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1987

Preparative electrophoresis for space

A premise of continuous flow electrophoresis is that removal of buoyancy-induced thermal convection caused by axial and lateral temperature gradients results in ideal performance of these instruments in space. Although these gravity dependent phenomena disturb the rectilinear flow in the separation chamber when high voltage gradients or thick chambers are used, distortion of the injected sample stream due to electrohydrodynamic effects cause major broadening of the separated bands. The electrophoresis separation process is simple, however flow local to the sample filament produced by the applied electric field have not been considered. These electrohydrodynamic flows distort the sample stream and limit the separation. Also, electroosmosis and viscous flow combine to further distort the process. A moving wall concept is being proposed for space which will eliminate and control the disturbances. The moving wall entrains the fluid to move as a rigid body and produces a constant residence time for all samples distributed across the chamber thickness. The moving wall electrophoresis chamber can only be operated in space because there is no viscous flow in the chamber to stabilize against thermal convection.

Rhodes, Percy H.↗
NASA NTRS1988

Preparative electrophoresis for space

A premise of continuous flow electrophoresis is that removal of buoyance-induced thermal convection caused by axial and lateral temperature gradients results in ideal performance of these instruments in space. Although these gravity dependent phenomena disturb the rectilinear flow in the separation chamber when high voltage gradients or thick chamber are used, distortion of the injected sample stream due to electrodynamic effects cause major broadening of the separated bands. The electrophoresis separation process is simple, however flow local to the sample filament produced by the applied electric field were not considered. These electrohydrodynamic flows distort the sample stream and limit the separation. Also, electroosmosis and viscous flow combine to further distort the process. A moving wall concept is being proposed for space which will eliminate and control the disturbances. The moving wall entrains the fluid to move as a rigid body and produces a constant residence time for all samples distributed across the chamber thickness. The moving wall electrophoresis chamber can only be operated in space because there is no viscous flow in the chamber to stabilize against thermal convection.

Rhodes, Percy H.↗
NASA NTRS1991

A 3-D upwind Euler solver for unstructured meshes

A three-dimensional finite-volume upwind Euler solver is developed for unstructured meshes. The finite-volume scheme solves for solution variables at vertices of the mesh and satisfies the integral conservation law on nonoverlapping polyhedral control volumes surrounding vertices of the mesh. The schene achieves improved solution accuracy by assuming a piecewise linear variation of the solution in each control volume. This improved spatial accuracy hinges heavily upon the calculation of the solution gradient in each control volume given pointwise values of the solution at vertices of the mesh. Several algorithms are discussed for obtaining these gradients. Details concerning implementation procedures and data structures are discussed. Sample calculations for inviscid Euler flow about isolated aircraft wings at subsonic and transonic speeds are compared with established Euler solvers as well as experiment.

Barth, Timothy J.↗
NASA NTRS1992

In vitro measurement of nucleus pulposus swelling pressure: A new technique for studies of spinal adaptation to gravity

Swelling of the intervertebral disc nucleus pulposus is altered by posture and gravity. We have designed and tested a new osmometer for in vitro determination of nucleus pulposus swelling pressure. The functional principle of the osmometer involves compressing a sample of nucleus pulposus with nitrogen gas until saline pressure gradients across a 0.45 microns Millipore filter are eliminated. Swelling pressure of both pooled dog and pooled pig lumbar disc nucleus pulposus were measured on the new osmometer and compared to swelling pressures determined using the equilibrium dialysis technique. The osmometer measured swelling pressures comparable to those obtained by the dialysis technique. This osmometer provides a rapid, direct, and accurate measurement of swelling pressure of the nucleus pulposus.

Hargens, A. R.↗
NASA NTRS1992

SAYANI'91 - A joint United States/Commonwealth of Independent States field campaign to investigate forest decline damage in the Krasnoyarsk region of southcentral Siberia

The field experiment described took place in the Sayani Mountains of Siberia. The purpose of the joint field campaign was to observe and exchange methodologies with Russian scientists with regard to the development of remote sensing techniques for the early detection and assessment of forest decline damage believed to be associated with atmospheric deposition and/or insect and disease infestations. Several types of passive and active remote sensing measurements were made in conjunction with biophysical measurements on vegetative samples collected from four study sites representing a strong elevational gradient. Relatively cloud-free SPOT data were also acquired over the study area. Moderate canopy damage was recorded at the mid-elevation site (3400 ft/1037 m). The lowest levels of damage were recorded at the lowest elevation site (2300 ft/701 m.) At all sites, east versus west flagging of the canopy was noted (i.e., full canopy on the west-facing side of the canopy, significantly less foliage on the east-facing side).

Williams, D. L.↗
NASA NTRS2007

A Comprehensive Characterization of Microorganisms and Allergens in Spacecraft Environment

The determination of risk from infectious disease during long-duration missions is composed of several factors including (1) the host#s susceptibility, (2) the host#s exposure to the infectious disease agent, and (3) the concentration of the infectious agent, and (4) the characteristics of the infectious agent. While stringent steps are taken to minimize the transfer of potential pathogens to spacecraft, several medically significant organisms have been isolated from both the Mir and International Space Station (ISS). Historically, the method for isolation and identification of microorganisms from spacecraft environmental samples depended upon their growth on culture media. Unfortunately, only a fraction of the organisms may grow on a culture medium, potentially omitting those microorganisms whose nutritional and physical requirements for growth are not met. Thus, several pathogens may not have been detected, such as Legionella pneumophila, the etiological agent of Legionnaire#s disease. We hypothesize that environmental analysis using non-culture-based technologies will reveal microorganisms, allergens, and microbial toxins not previously reported in spacecraft, allowing for a more complete health assessment. The development of techniques for this flight experiment, operationally named SWAB, has already provided advances in NASA laboratory processes and beneficial information toward human health risk assessment. The first accomplishment of the SWAB experiment was the incorporation of 16S ribosomal DNA sequencing for the identification of bacteria. The use of this molecular technique has increased bacterial speciation of environmental isolates from previous flights three fold compared to conventional methodology. This increased efficiency in bacterial speciation provides a better understanding of the microbial ecology and the potential risk to the crew. Additional SWAB studies focused on the use of molecular-based DNA fingerprinting using repetitive sequencebased polymerase chain reaction (rep-PCR). This technology has allowed contamination tracking of microorganisms between crewmembers and their environment. This study not only demonstrated that ISS has a greater diversity of organisms than originally expected, but also provided insight into possible routes of infection to the crew. Additional ground-based studies used rep-PCR and protein based assays to determine the potential of methicillin resistant Staphylococcus aureus (MRSA) aboard ISS. MRSA has become increasingly common on Earth and pose a treatment problem for infections during flight. While no MRSA have been isolated from ISS to date, the mecA gene product that is responsible for methicillin resistance was isolated in other Staphylococcus species aboard ISS suggesting a potential of MRSA through gene transfer. Using improved sample collection technologies, flight sampling for SWAB was initiated in August 2006 and should continue through spring of 2007. The focus of these flight samples is the collection of DNA for evaluation by Denaturing Gradient Gel Electrophoresis (DGGE). Unlike other techniques, DGGE does not depend on any microbial growth on culture media allowing a more comprehensive assessment of the spacecraft interior. This study should provide insight into the true microbial ecology that is experienced by the crew during flight. This information will lead toward an accurate microbial risk assessment to help set flight requirements to protect the safety, health, and performance of the crew.

Ott, C. M.↗