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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

SPRUCE Whole Ecosystem Warming (WEW) Environmental Data and Water Table Summaries, Marcell Experimental Forest, Minnesota, 2015-2024

This data set contains observations of photosynthetically active radiation (PAR), precipitation, soil temperature, soil volumetric water content, air temperature, relative humidity, and normalized water table depth that are summarized on a daily, weekly, monthly, and annual basis for each of the SPRUCE plots. Observations span 2015-2024. This dataset draws on several datasets (Hanson et al. 2016; Hanson et al. 2020; and Warren, unpublished data) and compiles these environmental observations into useful formats for data analysis. These environmental metrics can be used to understand the environmental conditions inside SPRUCE environmental chambers throughout the durations of the experiment and can be paired with other data for modeling and analysis. R code used to generate these files is provided as part of the data package. This dataset contains four data files in comma separate (.csv) format and a compressed folder (*.zip) containing three R (*.r) scripts. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. User note: Users must cite the original dataset/s along with this dataset when publishing any analyses using this dataset. Details on the dataset used to compile each variable are available in the header row of the files and in the user guide.

air temperature↗
DOE OSTI2022

Soil Incubation, Methane Pool Dilution, Edgewater, MD, USA, July 2022 v1.0.1

Isotopic pool dilution is a powerful approach to quantify gross biogeochemical transformation rates, but remains seldom used despite its potential. To facilitate broader implementation of pool dilution methods, we developed a user-friendly R package that optimizes gross production and consumption rates (and optionally fractionation constants as well) based on standard pool dilution time series data. This data package is the soil methane pool dilution data and code for building and using this software, including source code (R) and raw data (.csv). This package features extensive documentation and example analyses, and is easily integrated into analytical pipelines as R software is free and open source. Operation of this package requires R version 2.10 or newer, and we recommend its use in conjunction with packages testthat (3.0.0), knitr, rmarkdown, ggploto2, tibble, and tidyr.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Analysis of overlapping count data

Counts of a specific characteristic were obtained within regions defined on an object that was manufactured in a proprietary setting. The count regions were altered during production and resulted in misaligned or overlapping count data. A closed-formula maximum likelihood estimator (MLE) of the new region means is derived using all of the available count data and an independent Poisson model. The MLE is shown to be preferable to estimators constructed using generalized linear models for the overlapping data setting. This closed-form estimator extends to over-dispersed overlapping count data as the quasi-MLE and also performs well with correlated overlapping count data. Standard errors for the estimator are approximated and are validated with a simulation study. Additionally, the methods are extended to overlapping multinomial data. Illustrative examples of the methods are provided throughout the paper and are reproducible with the supplemental R code. Additionally, proofs of the paper’s results are also included in the supplemental material.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Data for “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”

This data package contains data and code used in the paper “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”. This paper details results from two studies: 1) a laboratory leaf litter incubation experiment (lab experiment) and 2) a multi-site observational field study (field study). Both studies were designed to test the relationships among litter quality, microbial physiological traits, and mineral-associated soil carbon (C). In the lab experiment, we incubated 16 temperate tree litters of differing chemical quality with isotopically distinct soil, measuring microbial physiological traits and the flow of litter-derived C into the mineral-associated soil C pool. In the field study, we sampled soils (0-5 cm) across six eastern US temperate forests, measuring microbial physiological traits, soil abiotic properties, and leaf litter chemistry. The analysis data are provided in two .csv files corresponding to either the lab experiment or field study. Both files contain data on litter chemistry, microbial physiological traits (growth and turnover rates, and carbon use efficiency [CUE]), and the mineral-associated soil C pool. The lab experiment dataset additionally contains litter-derived versus soil-derived soil C, respiration, and litter decomposition parameters. The field study dataset additionally contains site-level climatic information, ectomycorrhizal dominance of plots, and plot-level soil properties. Also provided is the R code and output reproducing the results in the related publication. Analyses were originally performed using R version 3.6.1 using the package "lavaan" and the packages listed on lines 5-7 in the file "data.R".

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dataset for 'Ombadi et al. (2023). A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature'

This package contains the main codes, sample input data and main result files to reproduce the analysis and results presented in the article: “Ombadi et al. (2023), A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature”. The folder consists of the following: (1) “Raw data”: a folder that contains sample input data which is used in some of the codes for demonstration purposes. It also contains data that was not pre-processed such as Elevation data; (2) “Results”: this folder contains files of the main results presented in the paper including: “Annual-Max-Series”, “Change-rainfall-extremes”, “Change-snow-fraction”, “Warming levels_By scenario_model_year” and “Masks”. Description of these folders is detailed in the "Readme.rtf" file; (3) Python jupyter notebooks (Extract_Annual Max Series (AMS).ipynb, Elevation-dependent amplification of rainfall extremes.ipynb, Sensitivity_to_global_warming.ipynb) demonstrate the main steps of analysis. Further description of those notebooks is provided in the "Readme.rtf" file; (4) R code for extreme value analysis (Extreme_Value_Analysis.R). The sample and pre-processed dataset in "Raw data" is obtained from publicly available repositories of CMIP6 and ERA5 datasets; see Methods for more detail. This research was supported by Office of Science, Office of Biological and Environmental Research of the US Department of Energy under contract no. DE-AC02-05CH11231 for the CASCADE Scientific Focus (funded by the Regional and Global Model Analysis Program area within the Earth and Environmental Systems Modeling Program) and the iNAIADS Early Career Research Project (funded by the Environmental Systems Science program).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data for Photosynthetic responses to temperature across the tropics: a meta-analytic approach

This data package contains raw data, data output, and code of photosynthetic temperature response curves from tropical forests. Data are used in "Photosynthetic responses to temperature across the tropics: a meta-analytic approach". The research investigates how photosynthetic optimum temperatures and shapes of photosynthetic temperature response curves varies across tropical forest climates and growth conditions. Growth climate variables include mean annual temperature, max and max temperature, diurnal temperature range, and aridity index. Meta-analysis combines 18 datasets with representation from Africa, Oceana, North American, and South America. Growth conditions analyzed considers deciduousness, successional status, light conditions, and whether plants are grown in situ or ex situ. All files, except for the raw datafile (Tropical_MetaAnalysis_Master_3.8.22_Edit.csv), have been processed using R code, which is provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

GENESPACE R Package (GENESPACE) v1.0

In short, the GENESPACE pipeline conducts analysis of orthology networks, constrained within syntenic regions. Since analyses are limited to local tests conducted within syntenic blocks, GENESPACE is agnostic to ploidy, duplicated regions, inversions or other whole-genome chromosomal complexities that are common across many evolutionary lineages. This advantage allows for evolutionary tests in polyploids (e.g. switchgrass, manuscript in review), species with ancient, but retained whole-genome duplications (e.g. pecan, manuscript in prep), high levels of tandem array proliferation (e.g. eukalypts, manuscript in review) and many other factors that can confound comparative genomic analyses. The major advances of GENESPACE are three-fold: First, this is the first R package to integrate visualization and analysis of large-scale comparative genomics. R, which offers a high-level environment for graphical and statistical exploration of data, is often speed- and memory-limited and not used for computationally intensive tasks such as comparative genomics. The highly efficient C++ scripts used in GENESPACE (via data.table) permit a much faster and computationally lightweight implementation of comparative genomics than is currently available. Second, the pipeline itself is novel. To the best of our knowledge, no other program accomplishes synteny-constrained and ploidy-agnostic comparative genomics. Since nearly all plants and many animals have a history of whole-genome duplications, this is a major and necessary advance to the field. Third, GENESPACE offers high-level and intuitive multi-genome graphical outputs. The dotplots and 'riparian' plots produced herein, which are produced entirely through original R code, are publication-ready and easily customizable.

Schmutz, Jeremy↗
DOE OSTI2022

BPP R package

The BPP package contains R code to perform Bayesian projection pursuit regression under various regression settings. Bayesian projection pursuit regression learns the functional relationship between inputs and outputs by considering a sum of functions of one dimensional projections of the inputs. This is useful as a general machine learning software.

Francom, Devin↗
DOE OSTI2025

Impala

SAND2025-07450O Impala is a software tool that performs Bayesian model calibration for emulator-based models. The program uses R code to perform the calculations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Tucker, James [Sandia National Lab. (SNL-CA), Live↗
DOE OSTI2022

Reactivity initiated accident uncertainty quantification for fuel assembly with subchannel code

UNIST CORE lab has developed a multiphysics coupling framework (MPCORE) consisting of Neutronics, Thermal Hydraulics and Fuel Performance modules. It can accommodate one-dimensional as well as sub-channel code Thermal Hydraulics (TH) module. Generally, running a transient requires more computational power due to the convergence of modules with each other. The difference between one-dimensional and sub-channel TH modules is studied in this research for a Reactivity Initiated Accident (RIA). Both TH modules are compared for a RIA uncertainty propagation in a single VERA fuel assembly with 2.11% enrichment. MPCORE is capable of analyzing the transient at any burnup point but for current work, only fresh fuel has been considered. The results have been obtained using dynamic gap heat conductance in FRAPTRAN. Peak centerline temperature, fuel enthalpy and DNBR are compared for both the approaches. The results indicate that the use of sub-channel code lead to greater safety margin for critical parameters. Computation time comparison is also presented for both the cases. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Building Interfaces with Echo Using R

The following report details the functionality that was developed to directly query the MongoDB and read in echo records from within R, and the ability to create a cinema database directly from echo records. Both of these efforts used the data collected under the MINOS project for development. The nuclear facility under consideration is the High-Flux Isotope Reactor (HFIR) and co-located Radiochemical Engineering Development Center (REDC) at Oak Ridge National Laboratory in Oak Ridge, TN. HFIR is an 85 MW research reactor and is used primarily for production of a medical radioisotopes, material irradiation experiments, neutron activation, and neutron scattering. Targets for the reactor are fabricated and processed and dissolved at REDC, in addition to other glove-box and hot-cell type activities. An overhead view of the facility is provided. The rest of the report is organized as follows: Section 2 describes how to query the MongoDB and load in echo records from within R, with background information on the database type, MongoDB, and the file format of echo records, hdf5, as well as lessons learned during the development phase. Section 3 details the functionality and usage of creating a cinema database directly from echo records within R. A series of appendixes display all the R code (Section 5), some example scripts where the code is used (Section 6), and useful links for further exploration (Section 7).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Fission Matrix Processing Using the MCNP6.3 HDF5 Restart File

This paper describes an approach to interrogating the fission matrix available in the HDF5-formatted restart file (also known as the “runtape” file), which is produced by the upcoming public release of the MCNP R code, version 6.3. The fission matrix, its eigenvalues, and its eigenvectors, are important tools for characterizing fissile systems such as research and power reactors and for accelerating the convergence of the Monte Carlo fission-source site distribution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Advanced Error Modeling for Prompt Yield Estimation [Slides]

Multi-Phenomenology Explosion Monitoring (MultiPEM) Toolbox provides a capability for post-detonation characterization focusing on yield estimation; Synthesize information from multiple sensor types; Leverage historical databases to inform statistical models; Allows for rapid or comprehensive analysis; Implemented in R code.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Computing the Instantaneous Collision Probability between Satellites using Characteristic Function Inversion

The probability that two satellites overlap in space at a specified instant of time is called their instantaneous collision probability. Assuming Gaussian uncertainties and spherical satellites, this probability is the integral of a Gaussian distribution over a sphere. This paper shows how to compute the probability using an established numerical procedure called characteristic function inversion. The collision probability in the short-term encounter scenario is also evaluated with this approach, where the instant at which the probability is computed is the time of closest approach between the objects. Python and R code is provided to evaluate the probability in practice. Overall, the approach has been established for over fifty years, is implemented in existing software, does not rely on analytical approximations, and can be used to evaluate two and three dimensional collision probabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Microbial Biomass in Soils Receiving Varying Levels of Organic Inputs - A Data Compilation

This dataset contains soil microbial biomass data compiled from published laboratory studies and field manipulations of organic inputs to soils. Each study included at least three levels of a given type of organic input applied to a given type of soil. Studies were selected from the literature that had experimentally manipulated organic input rates to soils using unburned, non-synthetic material (e.g. plant litters, manures, and composts). Fifty-five (55) studies, conducted from 1997 to October 2019, were chosen and compiled into a dataset with 358 observations from 96 combinations of a given organic material applied to a given soil in agricultural systems, laboratory incubations, forests, or grasslands. • Studies were selected when biomass measurements used the chloroform fumigation-extraction procedure followed by carbon analysis, or, in two instances, studies estimated microbial biomass using phospholipid fatty acid analysis. • Studies that used fewer than three input rates or characterized microbial biomass via substrate induced respiration were excluded. • The temporal and spatial aspects of the laboratory and field studies were not essential to the analyses (Craig et al., 2021) and were not included with the measurement data. These data were used to assess the relationship between organic input amounts and microbial biomass. Complete reference citations are provided if additional information is needed. The compiled data are provided in two .csv files: (1) soil treatments and microbial biomass data and (2) literature citations. The “Study” field is the cross reference between files. Also provided is the R code for reproducing the results in the related publication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Beaver Creek Soil Incubation Experiment July 2018

The data accompanies the manuscript Antecedent conditions determine the biogeochemical response of coastal soils to seawater exposure" that evaluates impact of periodic seawater inundations of soils from in a first-order coastal watershed in the Olympic Peninsula of Washington state, USA. Samples were collected in July 2018 and subjected to laboratory incubations. The files contain a read me file, data files including soil chemical characteristics, FTICR-MS molecular and data file, FTICR-MS derived processed data from FREDA, reference file for transformation analysis, LC-MS derived molecular feature abundance data, gas flux data for multiple regression and R codes. The files are related to the publication and have been used in the results and analyses section.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Substrate-explicit Modeling Tutorial

This tutorial Narrative demonstrates how to apply thermodynamic theory, also known as lambda theory, to convert molecular formulas of compounds (derived from FTICR-MS peaks using Formulatiry and R codes) into stoichiometric and kinetic forms of biogeochemical reactions and how to use the resulting kinetic equations to simulate dynamic conversion of compounds in batch and continuous stirred tank reactors. It will address under what conditions respiration rates are driven by thermodynamics, and how respiration rates respond to the variations in parameters and input variables and how to interpret the results.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

Automated RTOP Management System

The structure of NASA's Office of Aeronautics and Space Technology electronic information system network from 1983 to 1985 is illustrated. The RTOP automated system takes advantage of existing hardware, software, and expertise, and provides: (1) computerized cover sheet and resources forms; (2) electronic signature and transmission; (3) a data-based information system; (4) graphics; (5) intercenter communications; (6) management information; and (7) text editing. The system is coordinated with Headquarters efforts in codes R,E, and T.

Hayes, P.↗