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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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These codes estimate effective diffusivity for species transport in materials and simultaneously fit multiple temperatures of measured isotherm and effective diffusivities for sorption transport of species through materials. Assumes triple-mode type sorption thermodynamics with mobile and immobile species in quasi-equilibrium.
R code that performs the analysis of a data set presented in the paper ‘Leveraging Multiple Statistical Methods for Inverse Prediction in Nuclear Forensics Applications’ by Lewis, J., Zhang, A., Anderson-Cook, C. It provides functions for doing inverse predictions in this setting using several different statistical methods. The data set is a publicly available data set from a historical Plutonium production experiment.
Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We train a random forest machine learning model to predict snow depth from variability in ground surface temperature. To our knowledge, this is the first time that small ground surface temperature sensors have been used to estimate snow depth. The model performs well at sites where the model was trained and at pan-arctic evaluation sites (RMSE <= 0.15 m). Small temperature sensors are cheap and easy-to-deploy, so this technique enables spatially distributed and temporally continuous snowpack monitoring to an extent previously infeasible. The model is flexible and can be applied to datasets retroactively to retrieve snow depth estimates at additional sites. This code package includes a *.joblib file of the trained random forest model and a *.ipynb file showing how to clean input data, train the random forest model, and apply the model.
As part of a submitted paper, which is collection of previously published analytical solutions to coupled thermo-hydro-mechanical problems in subsurface flow and transport, we have prepared a collection of python scripts to compute and plot those analytic solutions. All code to be released implements existing methods; there are no novel algorithms nor any major innovations to existing software.
This release includes code developed by Benjamin Gerard and Joel Hurtado in summer 2025 to model the performance of different modes of the reflective three-sided pyramid wavefront sensor instrument within the REDWOODS module of the Shane Adaptive Optics system at Lick observatory.
CoSMo is a comprehensive shell model code suite designed for nuclear shell model and configuration interaction calculations. Its highly structured and templated nature allows for flexibility and ease in applications, including those to open quantum systems with non-Hermitian Hamiltonians, clustering, and time-dependent dynamics.
Abstract We present a data assimilation package for use with ocean circulation models in analysis, forecasting, and system evaluation applications. The basic functionality of the package is centered on a multivariate linear statistical estimation for a given predicted/background ocean state, observations, and error statistics. Novel features of the package include support for multiple covariance models, and the solution of the least squares normal equations either using the covariance matrix or its inverse—the information matrix. The main focus of this paper, however, is on the solution of the analysis equations using the information matrix, which offers several advantages for solving large problems efficiently. Details of the parameterization of the inverse covariance using Markov random fields are provided and its relationship to finite-difference discretizations of diffusion equations are pointed out. The package can assimilate a variety of observation types from both remote sensing and in situ platforms. The performance of the data assimilation methodology implemented in the package is demonstrated with a yearlong global ocean hindcast with a 1/4° ocean model. The code is implemented in modern Fortran, supports distributed memory, shared memory, multicore architectures, and uses climate and forecasts compliant Network Common Data Form for input/output. The package is freely available with an open source license from www.tendral.com/tsis/ .
Dynamic and adaptive mesh refinement is pivotal in high-resolution, multi-physics, multi-model simulations, necessitating precise physics resolution in localized areas across expansive domains. Today’s supercomputers’ extreme heterogeneity presents a significant challenge for dynamically adaptive codes, highlighting the importance of achieving performance portability at scale. Our research focuses on astrophysical simulations, particularly stellar mergers, to elucidate early universe dynamics. Here, we present Octo-Tiger, leveraging Kokkos, HPX, and SIMD for portable performance at scale in complex, massively parallel adaptive multi-physics simulations. Octo-Tiger supports diverse processors, accelerators, and network backends. Experiments demonstrate exceptional scalability across several heterogeneous supercomputers including Perlmutter, Frontier, and Fugaku, encompassing major GPU architectures and x86, ARM, and RISC-V CPUs. Parallel efficiency of 47.59% (110,080 cores and 6880 hybrid A100 GPUs) on a full-system run on Perlmutter (26% HPCG peak performance) and 51.37% (using 32,768 cores and 2048 MI250X) on Frontier are achieved.
Valine-glutamine (VQ) motif containing proteins play important roles in abiotic and biotic stress responses in plants. However, little is known about the origin and evolution as well as comprehensive expression regulation of the VQ gene family. In this study, we systematically surveyed this gene family in 50 plant genomes from algae, moss, gymnosperm and angiosperm and explored their presence in other species from animals, bacteria, fungi and viruses. No VQs were detected in all tested algae genomes and all genomes from moss, gymnosperm and angiosperm encode varying numbers of VQs. Interestingly, some of fungi, lower animals and bacteria also encode single to a few VQs. Thus, they are not plant-specific and should be regarded as an ancient family. Their family expansion was mainly due to segmental duplication followed by tandem duplication and mobile elements. Limited contribution of gene conversion was detected to the family evolution. Generally, VQs were very much conserved in their motif coding region and were under purifying selection. However, positive selection was also observed during species divergence. Many VQs were up- or down-regulated by various abiotic / biotic stresses and phytohormones in rice and Arabidopsis. They were also co-expressed with some of other stress-related genes. All of the expression data suggest a comprehensive expression regulation of the VQ gene family. We provide new insights into gene expansion, divergence, evolution and their expression regulation of this VQ family. VQs were detectable not only in plants but also in some of fungi, lower animals and bacteria, suggesting the evolutionary conservation and the ancient origin. Overall, VQs are non-plant-specific and play roles in abiotic / biotic responses or other biological processes through comprehensive expression regulation.
mRNA capping enzymes are directed to nascent RNA polymerase II (Pol2) transcripts via interactions with the carboxy-terminal domains (CTDs) of Pol2 and transcription elongation factor Spt5. Fission yeast RNA triphosphatase binds to the Spt5 CTD, comprising a tandem repeat of nonapeptide motif TPAWNSGSK. Here we report the crystal structure of a Pct1·Spt5-CTD complex, which revealed two CTD docking sites on the Pct1 homodimer that engage TPAWN segments of the motif. Each Spt5 CTD interface, composed of elements from both subunits of the homodimer, is dominated by van der Waals contacts from Pct1 to the tryptophan of the CTD. The bound CTD adopts a distinctive conformation in which the peptide backbone makes a tight U-turn so that the proline stacks over the tryptophan. We show that Pct1 binding to Spt5 CTD is antagonized by threonine phosphorylation. Our results fortify an emerging concept of an “Spt5 CTD code” in which (i) the Spt5 CTD is structurally plastic and can adopt different conformations that are templated by particular cellular Spt5 CTD receptor proteins; and (ii) threonine phosphorylation of the Spt5 CTD repeat inscribes a binary on–off switch that is read by diverse CTD receptors, each in its own distinctive manner.
Use of cellulosic biofuels from non-feedstocks are modeled using the BEPAM (Biofuel and Environmental Policy Analysis Model) model to quantifying the uncertainties about induced land use change effects, net greenhouse gas saving potential, and economic costs. The code is in GAMS, general algebraic modeling language. NOTE: Column 3 is titled "BAU" in "merged_BAU.gdx", "merged_RFS.gdx", and "merged_CEM.gdx", but contains "RFS" data in "merged_RFS.gdx" and "CEM" data in "merged_CEM.gdx".
The dataset consists of: (1) The replication codes and data for the BEPAM model are contained in the "BEPAM_Supplementary Environment Policy Analysis.zip" (2) Simulation results from the BEPAM model are contained in "ModelOutputs.zip" under the "BEPAM_Supplementary Environment Policy Analysis.zip"
This dataset provides raw millikelvin scanning tunneling microscopy/spectroscopy (STM/S) grid spectroscopy data and Python analysis scripts supporting the manuscript “Deciphering Majorana Zero Modes in Topological Superconductor FeTe0.55Se0.45 with Machine-Learning-Assisted Spectral Deconvolution.” The dataset includes a raw grid spectroscopy file acquired on FeTe0.55Se0.45 at 40 mK under magnetic field, together with Python/Jupytext analysis scripts used for STM/S data processing, visualization, spectral deconvolution, Lorentzian peak fitting, feature extraction, machine-learning-assisted clustering, and figure generation. These files support the analysis of vortex-core local density of states and the identification of zero-bias-peak-related spectral components from complex in-gap states. The dataset is intended to provide a citable archival record of the data and analysis code associated with the published manuscript and to support transparency and reproducibility of the reported STM/S and machine-learning workflow.
This paper discusses two cross section interpolation methods commonly found in popular nodal codes; the partial derivatives and multiple tables models. The motivation for choosing a model, and thus a case matrix structure, is a trade off between accuracy and computational cost. Due to decades of experience, there are default structures that are sufficient for current light water reactor analysis. However, this is not necessarily the case for advanced reactor designs. Therefore, it is advantageous to understand the sources of error in cross section interpolation models so that the quality of a case matrix may be improved. A mathematical framework for these models is presented in this work that provides a more rigorous connection between the nuclear engineering field's cross section interpolation methods and the broader mathematical field of function approximation. The two cross section models examined in this paper were found to utilize Lagrange interpolation and are a subset of Lagrange tensor products. Classical results of Lagrange polynomial error analysis were then applied to the partial derivative and multiple tables models to derive expressions for the total point-wise error. The analytical results classify the total error into two parts: the model form error and interpolation error. Finally, based on our observations, a better foundation for improving the quality of a case matrix is proposed. (authors)
Frequency-modulation spectroscopy (FMS) is generally suited to code-division multiplexing, and we demonstrate that capacity in a form of continuous-wave LIDAR, utilizing a sharp CO 2 absorption transition at 1.6 µm in simple ranging setups. The approach retains the advantages of FMS, including coherent detection and good rejection of broad absorption backgrounds. Extensions of this multiplexed approach to the continuous, simultaneous detection of several transitions would come by transmitting an encoded combination of frequency-modulated carriers, each tuned to detect a unique absorption transition. Signal analysis at the receiver involves a simple process of de-multiplexing that, in a general application, reveals targets at various distances and the absorption-related FMS signals in between.
High-resolution phase-contrast 3D imaging using nano-holotomography typically requires collecting multiple tomograms at varying sample-to-detector distances, usually 3 to 4. This multi-distance approach limits temporal resolution, making it impractical for operando studies. Moreover, shifting the sample complicates reconstruction, requiring precise alignment, registration, and interpolation to correct for shift-dependent magnification on the detector. In response, we propose and validate through simulations a novel, to the best of our knowledge, single-distance approach that leverages coded apertures to structure beam illumination while the sample rotates. Finally, this approach relies on a joint reconstruction scheme, which integrates phase retrieval with 3D tomography, ensuring data consistency and achieving artifact-free reconstructions from a single distance, unlocking dynamic experiments.
Data, code, and figures from our meta-analysis of the effect of precipitation change on soil respiration, with an emphasis on ecosystem variability and the effect of study duration. We combined the results of 81 separate studies to determine the effect of altered rainfall on the amount of carbon that leaves soil in the form of carbon dioxide, a major component of global carbon cycling. In addition we looked at how long the changes lasted, and how different soil properties and the intensity of precipitation changes affected the study results. We found that more precipitation resulted in greater amounts of carbon dioxide leaving the soil, and less precipitation resulted in less. However, the changes weakened over time in ecosystems that typically receive plenty of rainfall (e.g., forests), in contrast to ecosystems that typically receive little rainfall (e.g., deserts) where changes strengthened over time. Changes in the amount of carbon dioxide that left the soil were also affected by the amount of carbon in the soil, which impacts how much water soil can hold.
This dataset serves as supplementary information for the paper by Ciulla F. and Varadharajan C. A Network Approach for Multiscale Catchment Classification using Traits (see reference 1). It contains environmental and physical catchment traits, such as temperatures, precipitation, land use and human interference, from 9067 sites across the contiguous United States (CONUS). The purpose of this dataset is to provide information for a better trait-based categorization of river catchments in the CONUS using networks as an analytical tool. The traits variables match the ones present in the GAGES-II dataset and the preprocessing steps are described in the Methods section (processed_dataset.csv). Additionally we include the topologies (nodes, edges and clusters, also referred as classes) of the catchment network and traits network generated by said dataset (csv and json files). A series of tables support the information carried by the network providing more detailed descriptions of cluster components (SI1.pdf). A summary of all the plots of clusters of catchments with at least 50 nodes is provided (SI2.pdf). The characteristic traits for each cluster of catchments is presented as z-score (traits_categories_zscores_per_catchment_class.csv). The link to the hydrological behavior of clusters of catchments is displayed by boxplots, each describing a particular river discharge index (SI3.pdf). Both csv and json files can be read by common text editors but the data contained into them can be better handled using programming languages like python and database oriented libraries like pandas. Pdf files can be read by any pdf reader software.[02-23-2024] Update: The code and datasets necessary to reproduce the results of the study are available as a zipped repository (code_datasets_catchments_similarity.zip).