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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

Landscaper v1

Understanding the inner workings of machine learning models through their loss landscapes offers crucial insights into model properties, optimization dynamics, and generalizability. However, accessing these insights has traditionally required specialized mathematical expertise, limiting broader adoption. Landscaper is an open-source Python package designed to bridge this gap. Landscaper seamlessly integrates a suite of multi-dimensional loss landscape analyses with cutting-edge topological data analysis (TDA) methods. This powerful combination makes both fundamental loss landscape analysis and advanced TDA techniques accessible to the broader scientific ML community, without requiring deep pre-existing mathematical knowledge. Landscaper offers three key functionalities: * Construction: Builds detailed loss landscape representations through versatile low and high-dimensional sampling techniques. * Quantification: Applies advanced metrics, including a novel topological data analysis (TDA) based smoothness metric, enabling new perspectives on model behavior. * Visualization: Offers intuitive tools to visualize and interpret loss landscapes, providing actionable insights beyond traditional performance metrics.

Weber, Gunther [Lawrence Berkeley National Laborat↗
NASA NTRS2004

An XMM-Newton Study of the Bright Narrow-Line Seyfert 1 Galaxy Arakelian 564

We report on two XMM-Newton observations of the bright Narrow-Line Seyfert 1 galaxy Ark 564 taken one year apart (2000 June and 2001 June). The 0.6-10 keV continuum is well described by a soft blackbody component (kT - 140-150 eV) plus a steep power law (Gamma - 2.50-2.55). No significant spectral changes are observed between the two observations, although the X-ray flux in the second observation is - 40-50 per cent lower. In both observations we detect a significant absorption edge at a rest-frame energy of - 0.73 keV, corresponding to 0 VII. The presence of the absorption feature is confirmed by a simultaneous Chandra grating observation in 2000 June, although the best-fitting edge threshold is at a slightly lower energy in the Chandra data, possibly because of a different parameterization of the underlying X-ray continuum. We find tentative evidence for a broad iron emission line in the 2000 June observation. The results from an analysis of the power spectral density (PSD) function are also presented. The present XMM-Newton data support the idea that the PSD shows two breaks, although the location of the high-frequency break requires further constraints.

Brandt, Niel↗
NASA NTRS2003

Arakelian 564: An XMM-Newton View

We report on two XMM-Newton observations of the bright narrow-line Seyfert 1 galaxy Ark 564 taken one year apart (2000 June and 2001 June). The 0.6-10 keV continuum is well described by a soft blackbody component (kTau approximately equal 140-150 eV) plus a steep power law (Tau approximately equal to 2.50-2.55). No significant spectral changes are observed between the two observations, although the X-ray flux in the second observation is approximately equal to 40-50 per cent lower. In both observations we detect a significant absorption edge at a rest-frame energy of approximately equal to 0.73 keV, corresponding to O VII. The presence of the absorption feature is confirmed by a simultaneous Chandra grating observation in 2000 June, although the best-fitting edge threshold is at a slightly lower energy in the Chandra data, possibly because of a different parameterization of the underlying X-ray continuum. We find tentative evidence for a broad iron emission line in the 2000 June observation. The results from an analysis of the power spectral density (PSD) function are also presented. The present XMM-Newton data support the idea that the PSD shown two breads, although the location of the high-frequency break requires further constraints.

Vignali, Cristian↗
NASA NTRS1980

Pioneer Venus Sounder Probe gas chromatograph

The design logic, construction, function, and data processing of the Pioneer Venus Sounder Probe gas chromatograph instrument are discussed. A gas chromatograph for the analysis of the chemical composition of the lower atmosphere of Venus was included in the Sounder Probe of the Pioneer Venus mission. This paper describes the design logic of the gas chromatograph as constrained by the mission; attention is given to instrument construction, function, and data reduction.

Oyama, V. I.↗
NASA NTRSDate not supplied

Towards Computational Functional Hazard Assessment (CFHA): A Gap Analysis and Concept for Emerging Aviation Systems

Given the current evolution of the National Airspace and future trajectory towards novel and evolving operations with varying levels of autonomy, complexity, and acceptable risk, there is an opportunity to support safety assurance by extending existing methodologies, such as Functional Hazard Assessment (FHA). In response to challenges in performing FHA for novel aviation concepts, we propose a concept for Computational Functional Hazard Assessment (CFHA), which provides processes, methods, and tools for incorporating external data to facilitate further exploration of the hazard space iterativelty throughout the design process. The core components of CFHA involve knowledge capture from historical and operational data, functional architecture specification via a formal modeling language, and simulation for hazardous scenario analysis. Through this concept, we aim to adapt conventional safety assessment to address the increasingly complex hazard space generated from emerging operations.

Seydou Mbaye↗
NASA NTRSDate not supplied

Towards Functional Hazard Assessment (CFHA): A Gap Analysis and Concept for Emerging Aviation Systems

Given the current evolution of the National Airspace and future trajectory towards novel and evolving operations with varying levels of autonomy, complexity, and acceptable risk, there is an opportunity to support safety assurance by extending existing methodologies, such as Functional Hazard Assessment (FHA). In response to challenges in performing FHA for novel aviation concepts, we propose a concept for Computational Functional Hazard Assessment (CFHA), which provides processes, methods, and tools for incorporating external data to facilitate further exploration of the hazard space iterativelty throughout the design process. The core components of CFHA involve knowledge capture from historical and operational data, functional architecture specification via a formal modeling language, and simulation for hazardous scenario analysis. Through this concept, we aim to adapt conventional safety assessment to address the increasingly complex hazard space generated from emerging operations.

Seydou Mbaye↗
DOE OSTI2026

Informing Robust Functional Relationship Benchmarks: An Evaluation of the Temperature Sensitivity of Ecosystem Respiration Across the Arctic-Boreal Region

During land model development, simulated carbon dynamics are often benchmarked against observational data sets to evaluate model performance. Functional relationship benchmarks are the relationship between a driving variable (e.g., temperature) and a response variable (e.g., ecosystem respiration) and are a promising tool for assessing model performance by evaluating modeled sensitivities to changing environmental conditions. However, observed functional relationships can be influenced by choices made during data collection and throughout the benchmarking process, impacting the inferred skill of land models. To avoid misrepresenting a model's true performance, it is necessary to systematically evaluate best practices when constructing functional relationship benchmarks. We developed a set of guidelines for constructing functional relationship benchmarks, considering the choice of data set, number of daily observations, temporal extent, and temporal resolution across Alaska and Canada over a 20-year period from 2001 to 2020. The temperature sensitivity of ecosystem respiration from observations, evaluated through an apparent Q 10 , is highly variable both spatially and as a result of the data processing approach applied in the benchmark formation. When benchmarking 13 models from the Warming Permafrost Model Intercomparison Project (WrPMIP), the range in inferred model skill is substantially impacted by the choices applied in constructing functional relationship benchmarks. The inferred performance of a given model is most sensitive to the number of daily observations and temporal extent, followed by choice of benchmark data set and temporal averaging. Results from this analysis can guide the development of consistent and robust functional relationships for future model evaluation studies.

Poe, Jeralyn [Northern Arizona University, Flagsta↗
DOE OSTI2022

ESS-DIVE Reporting Format for Amplicon Abundance Table

While standardized sequencing data is available in public repositories and efforts such as MIxS for common sample collection and processing metadata are well established, the lack of common bioinformatic processing metadata has hindered the ability to do large-scale metaanalyses and the potential for data re-use by non-experts such as ecosystem, watershed, or earth system modelers. To address this need for Department of Energy researchers, we have developed an amplicon reporting format which captures both sample preparation and bioinformatic processing metadata and stores processed amplicon data as a paired abundance table and sequencing file to maximize the potential for re-use of these data. To aid in the adoption of accessible and reproducible analysis workflows, this reporting format was developed in concert with amplicon functionality within the Department of Energy’s Systems Biology Knowledgebase (KBase) to ensure common data and metadata requirements and facilitate seamless transfer between these platforms.This dataset contains support documentation for the amplicon reporting format (README.md and instructions.md), templates for both bioinformatic and sequencing metadata (amplicon_bioinformatic_metadata_template_2021_10_03.csv and amplicon_sequencing_metadata_template_2021_10_03.csv), a crosswalk indicating how this reporting format relates to the current MIxS format (ESSDIVE-MIxS_crosswalk.csv), a list of available instrument terms (amplicon_seq_instrument_terms_2021_10_03.csv), a map between QIIME2 parameter settings and metadata fields (amplicon_qiime2_plugin_metadata_map.csv), a data dictionary (amplicon_CSV_dd.csv), and file-level metadata (amplicon_FLMD.csv).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Analysis And Control System For Automated Welding

Automated variable-polarity plasma arc (VPPA) welding apparatus operates under electronic supervision by welding analysis and control system. System performs all major monitoring and controlling functions. It acquires, analyzes, and displays weld-quality data in real time and adjusts process parameters accordingly. Also records pertinent data for use in post-weld analysis and documentation of quality. System includes optoelectronic sensors and data processors that provide feedback control of welding process.

Powell, Bradley W.↗
DOE OSTI2024

Self‐Consistent Convolutional Density Functional Approximations: Application to Adsorption at Metal Surfaces

The exchange-correlation (XC) functional in density functional theory is used to approximate multi-electron interactions. A plethora of different functionals are available, but nearly all are based on the hierarchy of inputs commonly referred to as “Jacob's ladder.” This paper introduces an approach to construct XC functionals with inputs from convolutions of arbitrary kernels with the electron density, providing a route to move beyond Jacob's ladder. We derive the variational derivative of these functionals, showing consistency with the generalized gradient approximation (GGA), and provide equations for variational derivatives based on multipole features from convolutional kernels. A proof-of-concept functional, PBEq, which generalizes the PBEα framework with mathematical equation being a spatially-resolved function of the monopole of the electron density, is presented and implemented. It allows a single functional to use different GGAs at different spatial points in a system, while obeying PBE constraints. Analysis of the results underlines the importance of error cancellation and the XC potential in data-driven functional design. After testing on small molecules, bulk metals, and surface catalysts, the results indicate that this approach is a promising route to simultaneously optimize multiple properties of interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit

ABSTRACT We describe and test the fiducial covariance matrix model for the combined two-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) data set. Using a variety of new ansatzes for covariance modelling and testing, we validate the assumptions and approximations of this model. These include the assumption of Gaussian likelihood, the trispectrum contribution to the covariance, the impact of evaluating the model at a wrong set of parameters, the impact of masking and survey geometry, deviations from Poissonian shot noise, galaxy weighting schemes, and other sub-dominant effects. We find that our covariance model is robust and that its approximations have little impact on goodness of fit and parameter estimation. The largest impact on best-fitting figure-of-merit arises from the so-called fsky approximation for dealing with finite survey area, which on average increases the χ2 between maximum posterior model and measurement by $3.7{{\ \rm per\ cent}}$ (Δχ2 ≈ 18.9). Standard methods to go beyond this approximation fail for DES-Y3, but we derive an approximate scheme to deal with these features. For parameter estimation, our ignorance of the exact parameters at which to evaluate our covariance model causes the dominant effect. We find that it increases the scatter of maximum posterior values for Ωm and σ8 by about $3{{\ \rm per\ cent}}$ and for the dark energy equation-of-state parameter by about $5{{\ \rm per\ cent}}$.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Global QCD analysis of spin PDFs in the proton with high-𝑥 and lattice constraints

We perform a comprehensive global QCD analysis of spin-dependent parton distribution functions (PDFs), combining all available data on inclusive and semi-inclusive deep-inelastic scattering (DIS), as well as inclusive weak boson and jet production in polarized 𝑝⁢𝑝 collisions, simultaneously extracting spin-averaged PDFs and fragmentation functions. Including recent Jefferson Lab DIS data at high 𝑥, together with subleading power corrections to the leading-twist framework, allows us to verify the stability of the PDFs for 𝑊 2 ≥ 4 GeV 2 and quantify the uncertainties on the spin structure functions more reliably. We explore the use of new lattice QCD data on gluonic pseudo-Ioffe time distributions, which, together with jet production and high-𝑥 DIS data, improve the constraints on the polarized gluon PDF. The expanded kinematic reach afforded by the data into the high-𝑥 region allows us to refine the bounds on higher-twist contributions to the spin structure functions, and test the validity of the Bjorken sum rule.

Perturbative QCD↗
DOE OSTI2020

Multi-Gas Sensors for Enhanced Reliability of SOFC Operation

GE Research, in partnership with SUNY Polytechnic Institute (SUNY Poly), designed, built, and tested gas sensors for in situ monitoring of H 2 and CO anode tail gases produced with on-site steam reforming in solid oxide fuel cell (SOFC) systems. The knowledge of the H 2 /CO ratio of these anode tail gases should allow accurate determination and control of the efficiency of the reforming process in the SOFC system and should deliver a lower operating cost for SOFC customers. The project objectives were to achieve multi-gas monitoring capability with a single multivariable sensor, and to sustain this performance in the presence of gaseous interferences and a potential poison for the sensor. The duration of the project was 24 months with the project structure that included three technical tasks such as (1) development of design rules of photonic nanostructures for H 2 and CO gas detection, (2) laboratory validation of photonic nanostructures for selective H 2 and CO gas detection, and (3) validation of photonic nanostructures for initial stability and poison-resistance against H 2 S. To build multivariable sensors for selective H 2 and CO gas detection in the presence of interferences, we expanded our earlier knowledge of multi-gas sensors into new fabrication and functionalization methodologies as well as into new methodologies for the spectral data analysis of multi-gas responses. We have advanced our design rules of the three-dimensional (3D) photonic nanostructures that allowed detection of H 2 and CO at high temperatures as individual gases and as their mixtures and rejection of interferences such as CO 2 , H 2 O, CH 4 , and other hydrocarbons for SOFC applications. Our advanced design rules should be attractive for building the new generation of cost-effective industrial sensors. Stability and poison resistance of our 3D photonic nanostructures was tested in the laboratory conditions. While initially we utilized conventional machine learning data analysis tools, we have found that they were unable to correct for the sensor drift. Thus, we have implemented new methods of machine learning for the analysis of our spectral data. These learnings pave the way to move the future studies into advanced testing of effects of interferences, aging and field tests. In future, our work will continue to advance our sensing designs to operate in conditions with known and unknown interferences by implementing nanostructures with enhanced spectral diversity of responses to gaseous species of interest and interferences. Our systematic reduction of technical risks in this completed project and in future studies will ensure transition of this sensing technology to commercialization.

03 NATURAL GAS↗
DOE OSTI2022

The SpacePy space science package at 12 years

For over a decade, the SpacePy project has contributed open-source solutions for the production and analysis of heliophysics data and simulation results. Here we introduce SpacePy’s functionality for the scientific user and present relevant design principles. We examine recent advances and the future of SpacePy in the broader scientific Python ecosystem, concluding with some of the work that has used SpacePy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

High-Throughput Field Plant Phenotyping: A Self-Supervised Sequential CNN Method to Segment Overlapping Plants

High-throughput plant phenotyping—the use of imaging and remote sensing to record plant growth dynamics—is becoming more widely used. The first step in this process is typically plant segmentation, which requires a well-labeled training dataset to enable accurate segmentation of overlapping plants. However, preparing such training data is both time and labor intensive. To solve this problem, we propose a plant image processing pipeline using a self-supervised sequential convolutional neural network method for in-field phenotyping systems. This first step uses plant pixels from greenhouse images to segment nonoverlapping in-field plants in an early growth stage and then applies the segmentation results from those early-stage images as training data for the separation of plants at later growth stages. The proposed pipeline is efficient and self-supervising in the sense that no human-labeled data are needed. We then combine this approach with functional principal components analysis to reveal the relationship between the growth dynamics of plants and genotypes. We show that the proposed pipeline can accurately separate the pixels of foreground plants and estimate their heights when foreground and background plants overlap and can thus be used to efficiently assess the impact of treatments and genotypes on plant growth in a field environment by computer vision techniques. This approach should be useful for answering important scientific questions in the area of high-throughput phenotyping.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1977

Detection of alteration associated with a porphyry copper deposit in southern Arizona

Computer processing of Landsat MSS data was performed using contrast stretching and band-to-band ratioing. A false color ratio composite picture showed color anomalies which coincided with known areas of alteration on and about Red Mountain. A helicopter survey of the study area was undertaken using a portable field reflectance spectrometer. One hundred fifty-six spectra were obtained in the 0.4 to 2.5 micrometer wavelength region. The spectra were digitized, and contour maps for 24 wavelength intervals were produced; no spectral anomalies were evident for the known altered areas. A contour map produced from the 1.6 and 2.2 micrometer ratio generally delineated the alteration areas. The 1.3, 1.6, and 2.2 micrometer wavelength data were canonically transformed using a transformation empirically derived from discriminant function analysis of altered and unaltered materials for the Goldfield, Nevada region, and a contour map was produced for the first canonical variable. The known areas of alteration were clearly defined on the contour map.

Abrams, M. J.↗
NASA NTRS1977

Prediction of in-depth gap heating ratios from wing glove model test data

In-depth gap heating ratios were predicted down RSI tile sidewalls based on temperature measurements obtained from the JSC arc-jet Wing Glove model tests in order to develop gap heating ratios which resulted in the best possible fit of test data and to produce a set of engineering verification heating ratios similar in shape to one another which could be used at various body points on the Orbiter during reentry. The Rockwell TPS Multidimensional heat conduction program was used to perform 3-D thermal analyses using a 3.0 in. thick section of a curved RSI tile with 283 nodal points. Correlation with test data shows that the predicted heating ratios were significantly higher down in the gap than the zero pressure values for T/C stacks 39 and 38 on the Wing Glove model. For stack 37 (in a low pressure region), the baseline heating ratio overpredicted the temperature data. This analysis, which showed that the heating ratios were a strong function of the product of pressure and pressure gradient, will be used to compare with recent Gap/Step and Ames Double Wedge test/analysis results in the effort to identify the Orbiter gap response to high delta P flight environment.

Source record↗