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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Satellite Image Simulation Toolkit

The Satellite Image Simulation Toolkit (SatIST) is a python software package designed to generate diverse and realistic satellite imaging scenarios. It serves as a toolkit for simulating data that supports the development and testing of algorithms used in satellite detection, calibration, and characterization. SIST provides a suite of simulation tools that allow users to replicate various satellite observation conditions, including sidereal and target tracking. By enabling the creation of scenarios that mimic real-world satellite operations, SIST facilitates advancements in satellite image data processing and the study of satellite behavior under different observational parameters.

Perloff, AlexxS [Lawrence Livermore National Labor↗
DOE OSTI2026

Data‐Driven Engineering of Thermostable Collagen‐Mimetic Peptoid Triple Helices

Collagen-mimetic peptides (CMPs) are engineered molecules designed to replicate the triple-helical structure of natural collagen. A repeating x–y-Gly sequence is the defining motif of CMPs and is critical to their triple-helical structure and stability. Substitutions to the residues occupying the x and y positions present a means to modulate the CMP structure and properties. Peptoid residues—N-substituted glycine derivatives—present an attractive potential substitution due to their thermal stability, proteolytic resistance, biocompatibility, and diverse palette of non-natural side chains, but also tend to introduce a high degree of backbone flexibility that can diminish the stability of the triple helix. In this work, we report a computational active learning cycle comprising molecular dynamics simulation, Gaussian process regression, and Bayesian optimization to computationally identify a number of promising peptoid substitutions predicted to stabilize the desired quaternary structure through side chain interactions and produce stable peptoid-based collagen-like triple helices. To experimentally test the computational predictions, a top candidate identified by the screen was synthesized and imaged using scanning electron microscopy to resolve fibril-like bundles consistent with collagen-like triple helices. This work predicts a number of CMP peptoid substitutions capable of forming stable triple-helical structures, presents a generalizable design strategy for engineering desired peptoid structures, and opens new avenues for the design of peptoid-based biomimetic materials.

active learning↗
DOE OSTI2026

Comparison of structurally diverse simulation models for prediction of epidemic outcomes caused by a long-distance dispersed pathogen

Long-distance dispersal (LDD) pathogens pose substantial challenges for epidemic control due to their ability to generate new infection foci at great distances. While various modeling approaches have been developed to understand and manage such outbreaks, little work has compared how models of different structures behave under shared conditions. Here, in this study, we compare four structurally distinct epidemiological models — EPIMUL, GEMF, PoPS, and Warwick — each adapted to simulate the spread of wheat stripe rust (WSR), a wind-dispersed LDD pathogen, under identical epidemiological parameters and dispersal kernel. Using data from a controlled field experiment, we evaluate the ability of each model to replicate disease prevalence under nine intervention scenarios that vary in timing and culling area. While the models differ substantially in design — ranging from spatial grid-based to network-based and raster-based frameworks — the shared dispersal kernel allowed for close alignment in their predictions. All models accurately captured general epidemic trends, particularly the strong effect of early intervention on disease suppression. We qualitatively compared their behavioral responses across scenarios and also evaluated an ensemble prediction by averaging across model outputs. Our findings highlight how integrating shared epidemiological components into distinct modeling frameworks can improve consistency and accuracy, while reinforcing the importance of early culling in managing LDD pathogen outbreaks.

Dispersal kernel↗
DOE OSTI2024

Evaluation of neutron dosimetry capabilities with the MC-15 portable multiplicity counter

This work proposes a preliminary neutron dose rate estimation method for a neutron multiplicity detector through measurement- and simulation-based analyses. Uncharacterized neutron-emitting sources may be encountered in situations such as nuclear emergency response, safeguards, and treaty verification. These circumstances may present irradiation risk to personnel conducting field assay, search, and characterization measurements. It is therefore of interest to provide a field neutron dosimetry capability with the existing neutron multiplicity counting (NMC) capabilities. To date, no commercially-available neutron detection systems are capable of both accurate NMC and real-time neutron dosimetry. This work will focus on estimating dose rate using input from a single fielded NMC called the MC-15. The energy-dependent neutron detection efficiency response of the MC-15 was quantified in monoenergetic neutron simulations and evaluated in response to two neutron-emitting sources and to a polyethylene-moderated source. The results were compared to existing neutron dosimeters and established the proof of concept for further investigation of the MC-15 for dose estimation. Measurement results were also replicated in simulations; additional simulations were then conducted to expand upon the limited empirical data. The initial empirical results provided a conversion factor appropriate for use when measuring 252 Cf neutrons that is independent of polyethylene shielding presence and thickness. The simulated data sets were then used to evaluate a fit equation allowing estimation of the neutron dose rate for less restricted geometric configurations and dependent only on the distance between the source and the detector. Additionally, the energy dependence of the efficiency response indicates that further empirical evaluations could provide energy-dependent conversion factors for broader neutron dosimetry capabilities with a wider range of neutron-emitting sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Impact of Interfacial Roughness on the Sorption Properties of Nanocast Polymers

Nanocasting is an emerging method to prepare organic polymers with regular, nanometer pores using inorganic templates. This report assesses the impact of imperfect template replication on the sorption properties of such polymer castings. Existing X-ray diffraction data show that substantial diffuse scattering exists in the small-angle region even though TEM images show near perfect lattices of uniform pores. To assess the origin of the diffuse scattering, the morphology of the phenol - formaldehyde foams (PFF) was investigated by small-angle X-ray scattering (SAXS). The observed diffuse scattering is attributed to interfacial roughness due to fractal structures. Such roughness has a profound impact on the sorption properties. Conventional pore- filling models, for example, overestimate protein sorption capacity. A mathematical framework is presented to calculate sorption properties based on observed morphological parameters. The formalism uses the surface fractal dimension determined by SAXS in conjunction with nitrogen adsorption isotherms to predict lysozyme sorption. The results are consistent with measured lysozyme loading.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Incorporating long-range dependence and fractal features in turbulence spectra

We introduce an advanced turbulence spectrum model developed from mathematical foundations from a covariance function class and empirically validated using extensive field data. This model captures the complex dynamics of long-range dependence, and fractal characteristics prevalent in riverine and atmospheric boundary layer (ABL) flows that are ignored by classical spectrum models, such as IEC (International Electrotechnical Commission) von Kármán and Kaimal model. The model delineates scaling behaviors across distinct frequency bands and offers substantial flexibility through five well-defined parameters each characterizing a distinct physical aspect of the velocity time series. A detailed procedure for obtaining each parameter from time series data is outlined. The comprehensive validations with field data from tidal currents and ABL flows substantiate the model’s fidelity in accurately replicating observed phenomena. This validation establishes the reliability of the proposed model and, when incorporated into stochastic full-field simulators such as TurbSim, demonstrates its potential to advance the predictive modeling and analysis of turbulent flows in environmental science and engineering contexts.

Cheng, Shyuan [Univ. of Illinois at Urbana-Champai↗
DOE OSTI2015

Trichodesmium genome maintains abundant, widespread noncoding DNA in situ, despite oligotrophic lifestyle

Understanding the evolution of the free-living, cyanobacterial, diazotroph Trichodesmium is of great importance due to its critical role in oceanic biogeochemistry and primary production. Unlike the other >150 available genomes of free-living cyanobacteria, only 63.8% of the Trichodesmium erythraeum (strain IMS101) genome is predicted to encode protein, which is 20-25% less than the average for other cyanobacteria and non-pathogenic, free-living bacteria. We use distinctive isolates and metagenomic data to show that low coding density observed in IMS101 is a common feature of the Trichodesmium genus both in culture and in situ. Transcriptome analysis indicates that 86% of the non-coding space is expressed, although the function of these transcripts is unclear. The density of noncoding, possible regulatory elements predicted in Trichodesmium , when normalized per intergenic kilobase, was comparable and two fold higher than that found in the gene dense genomes of the sympatric cyanobacterial genera Synechococcus and Prochlorococcus , respectively. Conserved Trichodesmium ncRNA secondary structures were predicted between most culture and metagenomic sequences lending support to the structural conservation. Conservation of these intergenic regions in spatiotemporally separated Trichodesmium populations suggests possible genus-wide selection for their maintenance. These large intergenic spacers may have developed during intervals of strong genetic drift caused by periodic blooms of a subset of genotypes, which may have reduced effective population size. In conclusion, our data suggest that transposition of selfish DNA, low effective population size, and high fidelity replication allowed the unusual ‘inflation’ of noncoding sequence observed in Trichodesmium despite its oligotrophic lifestyle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Modern nuclear and astrophysical constraints of dense matter in a redefined chiral approach

Here, we explore the quantum chromodynamics (QCD) phase diagram’s complexities, including quark deconfinement transitions, liquid-gas phase changes, and critical points by using the chiral mean-field (CMF) model that is able to capture all these features. We introduce a vector meson field redefinition within the CMF framework, enabling precise adjustments of meson masses and coupling strengths related to vector meson interactions. Performing a new fit to the deconfinement potential, we are able to replicate recent lattice QCD results, low-energy nuclear physics properties, neutron star observational data, and key phase diagram features as per modern constraints. This approach enhances our understanding of vector mesons’ roles in mediating nuclear interactions and their impact on the equation of state, contributing to a more comprehensive understanding of the QCD phase diagram and its implications for nuclear and astrophysical phenomena.

QCD phase transitions↗
DOE OSTI2022

High-Fuel Loading Ignition Delay Time Characterization of Hydrogen/Natural Gas/Ammonia at Gas Turbine-Relevant Conditions Inside a High-Pressure Shock Tube

Abstract This study explores the combustion characterization of high-fuel percentage, air-diluted mixtures of H2 mixed with natural gas (NG) as well as mixtures of H2 and NH3 at temperatures and pressures relevant to turbine operating conditions (20–30 bar, 1000–1500 K). Lower temperatures (below 1070 K) exhibit preignition characteristics due to non-homogeneity. An attempt to mitigate these occurrences at high pressures is investigated using the constrained reaction volume (CRV) stage-filling technique. Due to the need to further refine the facility CRV stage-filling uncertainty, only higher temperature data will be interpreted at this time. The test conditions in this study closely replicate the temperatures, pressures, and mixtures that would be seen in hydrogen-powered gas turbines, making it the first to explore such conditions. The experimental IDTs were compared against the current state-of-the-art chemical kinetic models for mechanism validation. The current work will advance H2-powered turbines and aims to determine the optimum molecular ratio of H2 when mixed with natural gas.

Pierro, Michael↗
DOE OSTI2015

An affinity-structure database of helix-turn-helix: DNA complexes with a universal coordinate system

Molecular interactions between proteins and DNA molecules underlie many cellular processes, including transcriptional regulation, chromosome replication, and nucleosome positioning. Computational analyses of protein-DNA interactions rely on experimental data characterizing known protein-DNA interactions structurally and biochemically. While many databases exist that contain either structural or biochemical data, few integrate these two data sources in a unified fashion. Such integration is becoming increasingly critical with the rapid growth of structural and biochemical data, and the emergence of algorithms that rely on the synthesis of multiple data types to derive computational models of molecular interactions. We have developed an integrated affinity-structure database in which the experimental and quantitative DNA binding affinities of helix-turn-helix proteins are mapped onto the crystal structures of the corresponding protein-DNA complexes. This database provides access to: (i) protein-DNA structures, (ii) quantitative summaries of protein-DNA binding affinities using position weight matrices, and (iii) raw experimental data of protein-DNA binding instances. Critically, this database establishes a correspondence between experimental structural data and quantitative binding affinity data at the single basepair level. Furthermore, we present a novel alignment algorithm that structurally aligns the protein-DNA complexes in the database and creates a unified residue-level coordinate system for comparing the physico-chemical environments at the interface between complexes. Using this unified coordinate system, we compute the statistics of atomic interactions at the protein-DNA interface of helix-turn-helix proteins. We provide an interactive website for visualization, querying, and analyzing this database, and a downloadable version to facilitate programmatic analysis. Lastly, this database will facilitate the analysis of protein-DNA interactions and the development of programmatic computational methods that capitalize on integration of structural and biochemical datasets. The database can be accessed at http://ProteinDNA.hms.harvard.edu.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Coefficient of Thermal Expansion of Pressed PETN Pellets

The PETN single crystal coefficient of thermal expansion (CTE) values were measured and reported by Cady in 1972 [1] over the temperature range of -160 to 100°C. Measurements were made in the (001) and (100) crystallographic directions, see Figure 1 (a replicate of Figure 1 from the Cady paper). Cady used his single-crystal data to calculate the linear CTE for a randomly-oriented multi-crystal pressing of PETN, and his values ranged from 76.5 με/°C (at 20°C) to 89.9 5 με/°C (at 90°C).

36 MATERIALS SCIENCE↗
DOE OSTI2016

Final Report DE-SC0006634. Quantifying phenotypic and genetic diversity of Miscanthus sinensis as a resource for knowledge-based improvement of M. ×giganteus (M. sinensis × M. sacchariflorus)

Miscanthus is especially attractive as a bioenergy crop for temperate environments because it produces high yields, needs few inputs, and grows well during the cool weather of early spring and late fall when few warm-season grasses can. However, Miscanthus feedstock production for the emerging U.S. bioenergy industry and for existing demand in Europe is based on a single sterile, vegetatively propagated variety of M. ×giganteus. M. ×giganteus is an interspecific hybrid of the parental species M. sinensis and M. sacchariflorus. Prior to the current study, little information existed about the genetic diversity and breeding potential of either M. ×giganteus parental species. In the current project, we studied more than 600 accessions of M. sinensis from throughout its native range in China, Japan, and Korea, in addition to ornamental cultivars and U.S. naturalized populations. Using thousands of DNA markers, we identified seven geographically distinct genetic groups of M. sinensis. Notably, we found that the ornamental cultivars and U.S. naturalized populations were derived from only a subset of the Southern Japan group, indicating that our study greatly increased the genetic diversity available for breeding new biomass cultivars. Additionally, this new understanding of M. sinensis population structure could be used to predict which crosses may produce progeny with the greatest hybrid vigor. Replicated field trials were also established at multiple locations in North America and Asia. Data on traits of importance for biomass productivity, such as flowering time, yield and height, were taken. Analyses of the phenotypic data from the field trials along with the DNA markers allowed us to identify many marker-trait associations. These results will enable marker-assisted breeding, which will allow selection at the seedling stage rather than waiting two to three years to obtain phenotypic data. Thus, this study is expected to greatly increase the efficiency of breeding Miscanthus for improved adaptation and biomass yield.

09 BIOMASS FUELS↗
NASA NTRS1999

IRIS Mariner 9 Data Revisited: An Instrumental Effect - 1

Small spurious features are present in data from the Mariner 9 Infrared Interferometer Spectrometer (IRIS). These represent a low amplitude replication of the spectrum with a doubled wavenumber scale. This replication arises principally from an internal reflection of the interferogram at the input window. An algorithm is provided to correct for the effect, which is at the 2% level. We believe that the small error in the uncorrected spectra does not materially affect previous results; however, it may be significant for some future studies at short wavelengths. The IRIS spectra are also affected by a coding error in the original calibration that results in only positive radiances. This reduces the effectiveness of averaging spectra to improve the signal to noise ratio at small signal levels.

Formisano, V.↗
NASA NTRS2014

Development and Implementation of a Hardware In-the-Loop Test Bed for Unmanned Aerial Vehicle Control Algorithms

Successful prediction and management of battery life using prognostic algorithms through ground and flight tests is important for performance evaluation of electrical systems. This paper details the design of test beds suitable for replicating loading profiles that would be encountered in deployed electrical systems. The test bed data will be used to develop and validate prognostic algorithms for predicting battery discharge time and battery failure time. Online battery prognostic algorithms will enable health management strategies. The platform used for algorithm demonstration is the EDGE 540T electric unmanned aerial vehicle (UAV). The fully designed test beds developed and detailed in this paper can be used to conduct battery life tests by controlling current and recording voltage and temperature to develop a model that makes a prediction of end-of-charge and end-of-life of the system based on rapid state of health (SOH) assessment.

Battery Testbed↗
NASA NTRS2018

Comparison of Impact Damage from Spin Pit and Flat Panel Gas Gun Testing

Gas gun experiments can generate useful data for the design of jet engine containment shields at much lower costs. To replicate the damage modes similar to that on a containment shield in fan-blade-out (FBO) testing, the gas gun experiment has to be carefully designed. This work focuses on the design of projectiles. Gas gun experiments were performed for flat composite panel targets with three different projectiles. FBO conditions were simulated using spin pit tests. The damage modes on the flat panels used in the gas gun tests were compared with damage modes on cylindrical composite containment shields used in spin pit tests. The results show that to generate similar damage modes, it is critical to ensure the shape of the projectile used in a gas gun test accounts for the deformation of the released blade during initial contact in the spin pit test.

Vanderklok, Andy↗
NASA NTRS2020

Effects of Long-Duration Space Flight on Training Retention and Transfer

The space environment imposes on the astronaut crew significant physiological, psycho-social, and cognitive loads that can not be replicated on the ground. These loads likely impact crew performance. To date, no systematic data collection has taken place to understand the effects of such loads on crew members ability to retain trained knowledge and skills, and to transfer such knowledge and skills to novel situations. The research described here was originally requested by HRP management to be the first such study to systematically collect data on the effects of long duration space flight on training retention and transfer. Because current theories of retention and transfer are based on results obtained in university laboratories using undergraduate students as research participants, and because crew time in space is very expensive, this study was designed to compare the performance of 4 groups of subjects: crew members in space, crew members on the ground, crew-like subjects, and university undergraduate students. Results from the ground-phase of the study reported here demonstrate that crew members performance under cognitive load can not be predicted from the performance of university undergraduate students. It is still an open question the extent to which crew members cognitive performance in space can be predicted from the performance of crew members on the ground.

Barshi, Immanuel↗
NASA NTRS2020

Effects of Long-Duration Space Flight on Training Retention and Transfer

The space environment imposes on the astronaut crew significant physiological, psycho-social, and cognitive loads that can not be replicated on the ground. These loads likely impact crew performance. To date, no systematic data collection has taken place to understand the effects of such loads on crew members’ ability to retain trained knowledge and skills, and to transfer such knowledge and skills to novel situations. The research described here was originally requested by HRP management to be the first such study to systematically collect data on the effects of long duration space flight on training retention and transfer. Because current theories of retention and transfer are based on results obtained in university laboratories using undergraduate students as research participants, and because crew time in space is very expensive, this study was designed to compare the performance of 4 groups of subjects: crew members in space, crew members on the ground, crew-like subjects, and university undergraduate students. Results from the ground-phase of the study reported here demonstrate that crew members’ performance under cognitive load can not be predicted from the performance of university undergraduate students. It is still an open question the extent to which crew members’ cognitive performance in space can be predicted from the performance of crew members on the ground.

training↗
NASA NTRSDate not supplied

Astronauts' Performance: The Retention and Transfer of Training

The space environment imposes on the astronaut crew significant physiological, psycho-social, and cognitive loads that can not be replicated on the ground. These loads likely impact crew performance. To date, no systematic data collection has taken place to understand the effects of such loads on crew members’ ability to retain trained knowledge and skills, and to transfer such knowledge and skills to novel situations. The research described here was originally designed to be the first such study to systematically collect data on the effects of long duration space flight on training retention and transfer. Because current theories of retention and transfer are based on results obtained in university laboratories using undergraduate students as research participants, and because crew time in space is very expensive, this study was designed to compare the performance of 4 groups of subjects: crew members in space, crew members on the ground, crew-like subjects, and university undergraduate students. Results from the ground-phase of the study reported here demonstrate that crew members’ performance under cognitive load can not be predicted from the performance of university undergraduate students. It is still an open question the extent to which crew members’ cognitive performance in space can be predicted from the performance of crew members on the ground.

training↗