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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

Produced Water DNA Database (PW-DNA): Utilizing KBase to generate an environmental specific curated molecular database

The deep subsurface is estimated to host the majority of Earth’s microbial biomass yet remains one of the most challenging environments to access and study. One common approach to investigate these microbial communities is through the analysis of produced water from subsurface reservoirs, where researchers can assess water and gas chemistry along with molecular (DNA/RNA) sequence data. Advances in high-throughput sequencing have greatly expanded our understanding of these environments and their biotechnological potential. However, further progress requires large-scale, integrative meta-analyses across diverse datasets. To address this need, we developed the Produced Water-DNA (PW-DNA) Database, a curated, publicly available resource that consolidates microbial DNA/RNA sequences, geochemical data, and relevant metadata from in situ hydrocarbon environments such as coal beds, oil reservoirs, and natural gas systems. The PW-DNA database delivers three core benefits to the research community: (1) it improves data sharing by linking environmental microbial datasets with corresponding geochemical parameters, enabling more robust filtering and analysis; (2) it connects with complementary research databases to promote broader dissemination and interoperability; and (3) it supports technological innovation by serving as a resource for identifying microbial trends and exploring genetic potential. While individual studies have highlighted basin-specific microbial communities and functional redundancy in biogeochemical cycling, a comprehensive, system-wide perspective is needed to better understand connectivity and novelty across subsurface ecosystems. By designing the PW-DNA in the KBase platform, we provide a reproducible, visual framework for integrating large-scale genomic and geochemical data, enabling researchers to perform more informed analyses and experimental design. Ultimately, this resource enhances the ability to identify, characterize, and interpret microbial functions across diverse subsurface environments, thereby accelerating discovery in subsurface microbiology and biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Exact isovector pairing in a shell-model framework: Role of proton-neutron correlations in isobaric analog states

Here, we utilize a nuclear shell model Hamiltonian with only two adjustable parameters to generate, for the first time, exact solutions for pairing correlations for light to medium-mass nuclei, including the challenging proton-neutron pairs, while also identifying the primary physics involved. In addition to single-particle energy and Coulomb potential terms, the shell model Hamiltonian consists of an isovector T = 1 pairing interaction and an average proton-neutron isoscalar T = 0 interaction, where the T = 0 term describes the average interaction between nonpaired protons and neutrons. This Hamiltonian is exactly solvable, where, utilizing three to seven single-particle energy levels, we reproduce experimental data for 0 + state energies for isotopes with mass A = 10 through A = 62 exceptionally well including isotopes from He to Ge. Additionally, we isolate effects due to like-particle and proton-neutron pairing, provide estimates for the total and proton-neutron pairing gaps, and reproduce N (neutron) = Z (proton) irregularity. These results provide a further understanding for the key role of proton-neutron pairing correlations in nuclei, which is especially important for waiting-point nuclei on the $\mathcal{rp}$ path of nucleosynthesis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Self-Secure Inverters Against Malicious Setpoints

The next generation of grid-interactive inverters brings a communication feature that allows data sharing from utility supervisory controllers and smart devices that are connected to the same network. This feature enhances the control capabilities of grid-interactive inverters to provide services beyond active power injection. However, communication networks entail more vulnerable surfaces to malicious attacks that may result in modifying active and reactive power setpoints and causing weak-grid conditions or abnormal inverter operation. In this paper, steady-state and the dynamic behavior of the inverter for the incoming setpoints are analyzed to detect false data injection attacks and provide device-level security. The steady-state behavior of the inverter in the operating region is determined from the grid parameters such as the grid voltage and the grid impedance. These estimations are accomplished by the proposed self-security technique through a low-frequency signal injection-based approach combined with the recursive least square method. Moreover, a reduced fourth-order inverter model is used as the dynamic reference model, and grid parameters as well as the incoming setpoints are implemented to the reference model to verify whether the dynamic behavior of the inverter is inside the permissible region of operation. The validity and performance of the proposed method are verified experimentally through Allen-Bradley Powerflex 755 three-phase inverter and a 12 kW NHR 9410 regenerative power grid emulator. The results show that the self-secure smart-inverter is able to accept or reject the incoming commands and thus is protected from malicious cyber-physical attacks.

Hossen, Tareq↗
DOE OSTI2017

Comparative study on neutronics characteristics of a 1500 MWe metal fuel sodium-cooled fast reactor

Under the cooperative effort of the Civil Nuclear Energy R&D Working Group within the framework of the U.S.-Japan bilateral, Argonne National Laboratory (ANL) and Japan Atomic Energy Agency (JAEA) have been performing benchmark study using Japan Sodium-cooled Fast Reactor (JSFR) design with metal fuel. In this benchmark study, core characteristic parameters at the beginning of cycle were evaluated by the best estimate deterministic and stochastic methodologies of ANL and JAEA. The results obtained by both institutions show a good agreement with less than 200 pcm of discrepancy on the neutron multiplication factor, and less than 3% of discrepancy on the sodium void reactivity, Doppler reactivity, and control rod worth. The results by the stochastic and deterministic approaches were compared in each party to investigate impacts of the deterministic approximation and to understand potential variations in the results due to different calculation methodologies employed. From the detailed analysis of methodologies, it was found that the good agreement in multiplication factor from the deterministic calculations comes from the cancellation of the differences on the methodology (0.4%) and nuclear data (0.6%). The different treatment in reflector cross section generation was estimated as the major cause of the discrepancy between the multiplication factors by the JAEA and ANL deterministic methodologies. Impacts of the nuclear data libraries were also investigated using a sensitivity analysis methodology. Furthermore, the differences on the inelastic scattering cross sections of U-238, ν values and fission cross sections of Pu-239 and µ-average of Na-23 are the major contributors to the difference on the multiplication factors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Comprehensive Neural Posterior Estimation for Galaxy-Galaxy Strong Lensing

We present a deep learning model based on neural posterior estimation (NPE) for comprehensive extraction of astrophysical parameters from galaxy-scale strong gravitational lenses. The unprecedentedly large amount of galaxy-scale strong lenses expected in future cosmological surveys (${\cal O}(10^5)$) promises to enable valuable statistical constraints in various studies ranging from galaxy formation to the nature of dark matter, but it also poses a significant challenge for traditional modelling pipelines. To this end, our automated model includes several new, state-of-the-art features and approaches leveraging the framework of simulation-based inference (SBI). We infer a total of 20 parameters describing the mass and light profiles of both lens and source galaxies, using simulated raw multi-band data modelled under noise and observing conditions expected by the Legacy Survey of Space and Time (LSST), with its summary statistics generated by a residual network. We examine the efficacy of multi-band data in extracting nearly 20 model parameters simultaneous from strong lensing images including lens light. Finally, We perform a comprehensive set of diagnostics for SBI models, evaluating the model's prediction accuracy, stability, and uncertainty quantification.

Zhao, Roy J. [Chicago U., KICP]↗
NASA NTRS1990

Estimation of minority carrier diffusion lengths in InP/GaAs solar cells

Minority carrier diffusion length is one of the most important parameters affecting the solar cell performance. An attempt is made to estimate the minority carrier diffusion lengths is the emitter and base of InP/GaAs heteroepitaxial solar cells. The PC-1D computer model was used to simulate the experimental cell results measured at NASA Lewis under AMO (air mass zero) spectrum at 25 C. A 16 nm hole diffusion length in the emitter and a 0.42 micron electron diffusion length in the base gave very good agreement with the I-V curve. The effect of varying minority carrier diffusion lengths on cell short current, open circuit voltage, and efficiency was studied. It is also observed that the front surface recombination velocity has very little influence on the cell performance. The poor output of heteroepitaxial cells is caused primarily by the large number of dislocations generated at the interfaces that propagate through the bulk indium phosphide layers. Cell efficiency as a function of dislocation density was calculated and the effect of improved emitter bulk properties on cell efficiency is presented. It is found that cells with over 16 percent efficiencies should be possible, provided the dislocation density is below 10(exp 6)/sq cm.

Jain, R. K.↗
NASA NTRS2005

EUV Imaging of SWCX-Produced He(+) 30.4-nm Emission/Scattering at the Magnetosheath

Theoretically, charge exchange between solar wind alpha-particles and geocoronal hydrogen at the magnetosheath results in the production of helium ions in an excited state, i.e, He(2+) + H (right arrow) He(+*) + H(+) resulting in the emission of 30.4-nm radiation upon relaxation of the helium ions. It has been estimated that the magnetosphere was compressed to inside the orbit of IMAGE during the Halloween storm of 2003. This configuration should have placed the subsolar point of the magnetosheath well beyond the limb of the solar disk and allow EUV the potential of imaging this solar wind charge exchange interaction Analysis of EUV full-frame data acquired during 31 October 2003 (Day 304) indicates the detection of 30.4-nm photons in the likely vicinity of the magnetosheath either as a direct consequence of the emission proposed above or, provided the magnetosheath He(+) density was sufficient to exceed the EUV sensitivity threshold, via resonant scattering of solar UV. We present initial analysis of EUV imaging during the Halloween 2003 storm from the context of solar wind parameters, including composition, and from the perspective of the generation of simulated EUV imaging of the event both as an emitting and as a scattering process.

Adrian, M. L.↗
DOE OSTI2018

Influence of Local Inhomogeneity of Thermomechanical Treatment Conditions on Microstructure Evolution in Aluminum Alloys

The influence of local inhomogeneity of the stress–strain condition on structure and texture evolution during thermomechanical treatment of aluminum alloys is studied in this work. For this purpose, laboratory rolling and plane strain tests that simulated roughing mill thermomechanical modes were performed. For all processes, the local inhomogeneity of structure evolution was estimated. For this purpose, x-ray texture analysis, EBSD and optical microscopy were used. Additionally, the calculations which allow to evaluate local inhomogeneity of stress–strain conditions for the each process were performed. The experimental results were compared with mathematical simulation output. They indicated structure and texture evolution inhomogeneities, especially during the plane strain and industrial rolling processes. In the plane strain test, typical local deformation zones occurred with different resulting grain size and texture effects than those observed in both rolling processes. This difference was mainly associated with different stress states, strain intensity and strain rate distribution throughout the deformation zone. This study demonstrated that the inhomogeneity of these parameters has a strong impact on structure and texture evolution in the first stage of thermomechanical treatment. In the center layer, laboratory rolling could adequately generate the structure and texture effects observed during rolling of ingots in a commercial mill. Plane strain tests can generate useful results only in the case of adequate choice of sample geometry.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Foreground bias from parametric models of far-IR dust emission

We use simple toy models of far-IR dust emission to estimate the accuracy to which the polarization of the cosmic microwave background can be recovered using multi-frequency fits, if the parametric form chosen for the fitted dust model differs from the actual dust emission. Commonly used approximations to the far-IR dust spectrum yield CMB residuals comparable to or larger than the sensitivities expected for the next generation of CMB missions, despite fitting the combined CMB + foreground emission to precision 0.1% or better. The Rayleigh–Jeans approximation to the dust spectrum biases the fitted dust spectral index by Δβ{sub d}=0.2 and the inflationary B-mode amplitude by Δr=0.03. Fitting the dust to a modified blackbody at a single temperature biases the best-fit CMB by Δr>0.003 if the true dust spectrum contains multiple temperature components. A 13-parameter model fitting two temperature components reduces this bias by an order of magnitude if the true dust spectrum is in fact a simple superposition of emission at different temperatures, but fails at the level Δr=0.006 for dust whose spectral index varies with frequency. Restricting the observing frequencies to a narrow region near the foreground minimum reduces these biases for some dust spectra but can increase the bias for others. Data at THz frequencies surrounding the peak of the dust emission can mitigate these biases while providing a direct determination of the dust temperature profile.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A Scalable Gaussian Process Approach to Shear Mapping with MuyGPs

Analysis of cosmic shear is an integral part of understanding structure growth across cosmic time, which in turn provides us with information about the nature of dark energy. Conventional methods generate shear maps from which we can infer the matter distribution in the universe. Current methods (e.g., Kaiser–Squires inversion) for generating these maps, however, are tricky to implement and can introduce bias. Recent alternatives construct a spatial process prior for the lensing potential, which allows for inference of the convergence and shear parameters given lensing shear measurements. Realizing these spatial processes, however, scales cubically in the number of observations—an unacceptable expense as near-term surveys expect billions of correlated measurements. Therefore, we present a linearly scaling shear map construction alternative using a scalable Gaussian process prior called MuyGPs. MuyGPs avoids cubic scaling by conditioning interpolation on only nearest neighbors and fits hyperparameters using batched leave-one-out cross-validation. This work is the first step toward a full, scalable mass mapping method. We work in a simplified regime where we validate our method by interpolating and analyzing maps given noisy point-estimate data from all three shear fields, taken from a suite of N -body ray-tracing simulations. We also show that we can perform these operations at the scale of billions of galaxies on high-performance computing platforms.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Restrepo, Carolina↗
DOE OSTI2023

Failure Modes and Effects Analysis of Biorefinery Pathways

This talk provides an overview of failure modes and effects analysis (FMEA) development and implementation as a systematic criticality and risk assessment tool for biorefinery pathways within the FCIC. This supports a quality by design (QbD) approach, and this talk provides a high-level overview of the results for the FMEA evaluation focused on the generation of pine residue materials for high-temperature pyrolysis conversion. the FMEA interviews included two approaches. The first approach was based around the entire system of unit operations giving a wholistic system level view. The second approach used detailed interviews from individual unit operation within the system allowing for specific failures for individual system components. These two approaches provide different resolutions of information about the reliability and risk. The FMEA results focused on failures associated with meeting critical quality attributes (CQAs) identified for the high temperature conversion of loblolly pine residues and were supplemented with experimental data supporting process upsets and reliability also collected within the consortium. Estimations of risk scores for meeting each given CQA specification, identification of the impacts for not meeting a CQA specification, capturing causes associated with material attributes and process parameters for each failure, identification of current detection methods, and speculation of potential mitigation strategies for decreasing a failure’s risk score were gathered through the FMEA interviews, and were combined to understand the overall process risk metrics and where technology, process, and knowledge improvements are needed in order to de-risk emerging biorefineries.

09 BIOMASS FUELS↗
NASA NTRS1994

Dynamo generation of magnetic field in the white dwarf GD 358

On the basis of Whole Earth Telescope observations of the g-mode oscillation spectrum of the white dwarf GD 358, Winget et al. find evidence for significant differential rotation and for a time-varying magnetic field concentrated in the surface layers of this star. Here we argue on theoretical grounds that this magnetic field is produced by an alpha omega dynamo operating in the lower part of a surface convection zone in GD 358. Our argument is based on numerical solutions of the nonlinear, local dynamo equations of Robinson & Durney, with specific parameters based on our detailed models of white-dwarf convective envelopes, and universal constants determined by a calibration with the the Sun's dynamo. The calculations suggest a dynamo cycle period of about 6 years for the fundamental mode, and periods as short as 1 year for the higher-order modes that are expected to dominate in view of the large dynamo number we estimate for GD 358. These dynamo periods are consistent with the changes in the magnetic field of GD 358 over the span of 1 month inferred by Winget et. al. from their observations. Our calculations also suggest a peak dynamo magnetic field strength at the base of the surface convection zone of about 1800 G, which is consistent with the field strength inferred from the observations.

Markiel, J. Andrew↗
DOE OSTI2023

Integrative teaching of metabolic modeling and flux analysis with interactive python modules

Abstract The modeling of rates of biochemical reactions—fluxes—in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint‐based (Metabolic Flux Analysis and flux balance analysis) approaches. Although different resources exist for teaching these methods individually, to‐date no resources have been developed to teach these approaches in an integrative way that equips learners with an understanding of each modeling paradigm, how they relate to one another, and the information that can be gleaned from each. We have developed a series of modeling simulations in Python to teach kinetic modeling, metabolic control analysis, 13C‐metabolic flux analysis, and flux balance analysis. These simulations are presented in a series of interactive notebooks with guided lesson plans and associated lecture notes. Learners assimilate key principles using models of simple metabolic networks by running simulations, generating and using data, and making and validating predictions about the effects of modifying model parameters. We used these simulations as the hands‐on computer laboratory component of a four‐day metabolic modeling workshop and participant survey results showed improvements in learners' self‐assessed competence and confidence in understanding and applying metabolic modeling techniques after having attended the workshop. The resources provided can be incorporated in their entirety or individually into courses and workshops on bioengineering and metabolic modeling at the undergraduate, graduate, or postgraduate level.

Kaste, Joshua A. M.↗
DOE OSTI2017

Modelling bivariate extreme precipitation distribution for data-scarce regions using Gumbel-Hougaard copula with maximum entropy estimation

A new method of parameter estimation in data scarce regions is valuable for bivariate hydrological extreme frequency analysis. Here, this paper proposes a new method of parameter estimation (maximum entropy estimation, MEE) for both Gumbel and Gumbel–Hougaard copula in situations when insufficient data are available. MEE requires only the lower and upper bounds of two hydrological variables. To test our new method, two experiments to model the joint distribution of the maximum daily precipitation at two pairs of stations on the tributaries of Heihe and Jinghe River, respectively, were performed and compared with the method of moments, correlation index estimation, and maximum likelihood estimation, which require a large amount of data. Both experiments show that for the Ye Niugou and Qilian stations, the performance of MEE is nearly identical to those of the conventional methods. For the Xifeng and Huanxian stations, MEE can capture information indicating that the maximum daily precipitation at the Xifeng and Huanxian stations has an upper tail dependence, whereas the results generated by correlation index estimation and maximum likelihood estimation are unreasonable. Moreover, MEE is proved tobe generally reliable and robust by many simulations under three different situations. TheGumbel–Hougaard copula with MEE can also be applied to the bivariate frequency analysis ofother extreme events in data-scarce regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Study of SXR/EUV radiation of exploded foils and wires with spectral, spatial and temporal resolution simultaneously on KING electric discharge facility.

The results of studies of the soft X-ray and extreme ultraviolet (SXR/EUV) radiation of thin flat aluminum foils and wires under the explosion in an electric discharge on the compact high-current KING generator are presented. These studies were based on the SXR/EUV spectroscopy with a spectral resolution of 6 Å, a temporal resolution of 5 ns and a spatial resolution of 200 μm. To study the plasma radiation of exploded foils and wires in the SXR/EUV range, we used a transmission diffraction grating spectrograph which in combination with two additional slits provided spectral and spatial resolution. The spectrograph was coupled with a 4-frame recorder based on a microchannel plate for providing temporal resolution. The analysis and comparison of the spectral, spatial, temporal, and energy characteristics of the SXR/EUV radiation of plasma formed under the explosion of foils and wires of a similar mass made of aluminum was carried out. Here, the spectra were calculated as well and the plasma parameters and their changes in time and space were estimated on the basis of these calculations and comparison with relevant experimental results. Experiments have shown that when foils explode, a single intense source of SXR/EUV radiation is formed with radiated energy in the range of 10-20 J and a power of up to 100 MW in the quantum energy range from 30 to 250 eV. At the same time, the radiation power under the explosion of foils turned out to be about twice above the power under the explosion of wires of comparable mass.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2001

A TRMM-Calibrated Infrared Rainfall Algorithm Applied Over Brazil

A satellite infrared (IR) technique for estimating rainfall over northern South America is presented. The objectives are to examine the diurnal variability of rainfall and to investigate the relative contributions from the convective and stratiform components. In this study, we apply the Convective-Stratiform Technique (CST) of Adler and Negri (1988). The parameters of the original technique were re-calibrated using coincident rainfall estimates (Olson et W., 2000) derived from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI) and GOES IR (11 micrometer) observations. Local circulations were found to play a major role in modulating the rainfall and its diurnal cycle. These included land/sea circulations (notably along the northeast Brazilian coast and in the Gulf of Panama), mountain/valley circulations (along the Andes Mountains), and circulations associated with the presence of rivers. This last category was examined in detail along the Amazon R. east of Manaus. There we found an early morning rainfall maximum along the river (5 LT at 58W, 3 LT at 56W). Rainfall avoids the river in the afternoon (12 LT and later), notably at 56 W. The width of the river seems to be generating a land/river circulation which enhances early morning rainfall but inhibits afternoon rainfall. Results are compared to ground-based radar data collected during the Large-Scale Biosphere-Atmosphere (LBA) experiment in southwest Brazil, to monthly raingages in northeastern Brazil, and to data from the TRMM Precipitation Radar.

Negri, Andrew J.↗
NASA NTRS2017

Biomechanical Modeling Analysis of Loads Configuration for Squat Exercise

INTRODUCTION: Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to assist loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft for travel to the Moon or to Mars is limited and therefore compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Biomechanical data collection and computational modeling aid the device design process by quantifying the joint torques and the musculoskeletal forces that occur during exercises performed on the prototype devices. METHODS The computational models currently under development utilize the OpenSim [1] software platform, consisting of open source code for musculoskeletal modeling, using biomechanical input data from test subjects for estimation of muscle and joint loads. The OpenSim Full Body Model [2] is used for all analyses. The model incorporates simplified wrap surfaces, a new knee model and updated lower body muscle parameters derived from cadaver measurements and magnetic resonance imaging of young adults. The upper body uses torque actuators at the lumbar and extremity joints. The test subjects who volunteer for this study are instrumented with reflective markers for motion capture data collection while performing squat exercising on the Hybrid Ultimate Lifting Kit (HULK) prototype device (ZIN Technologies, Middleburg Heights, OH). Ground reaction force data is collected with force plates under the feet, and device loading is recorded through load cells internal to the HULK. Test variables include the applied device load and the dual cable long bar or single cable T-bar interface between the test subject and the device. Data is also obtained using free weights with the identical loading for a comparison to the resistively loaded exercise device trials. The data drives the OpenSim biomechanical model, which has been scaled to match the anthropometrics of the test subject, to calculate the body loads. RESULTS Lower body kinematics, joint moments, joint forces and muscle forces are obtained from the OpenSim biomechanical analysis of the squat exercises under different loading conditions. Preliminary results from the model for the loading conditions will be presented as will hypotheses developed for follow on work.

Human Factors Engineering↗