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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Forced Response Aeromechanics Analysis in MATLAB®-Based Environment Code With Application to Distortion-Tolerant Fan R24 Blade Geometry

Researchers at the NASA Glenn Research Center have developed a research-level code for forced response analysis for turbomachinery that provides a streamlined framework for aeromechanics analysis, as well as for generating Goodman diagrams. The Forced Response Aeromechanics Analysis in a MATLAB-Based Environment (FRAAME, Version 1) code is designed to accept blade surface unsteady pressure time histories generated by three-dimensional (3D) Unsteady Reynolds-Averaged Navier-Stokes (URANS) code TURBO and modal displacements, modal stresses, and static stresses generated via expanded ANSYS® (Ansys, Inc.) cyclic symmetry analysis. The code’s looping structure allows for largescale analyses, including many blade surface pressure files, modal displacements, and modal stress files for full annulus forced response analysis, including a modal summation method for multiple engine orders and modes. This code is applied to the R24 fan geometry for the Boundary Layer Ingesting Inlet/Distortion-Tolerant Fan (BLI2DTF) project, a propulsion system being developed to increase the fuel efficiency of future aircraft, to serve as validation of experimental data as well as external simulation results. This tool’s functional, modular form is intended to allow users to make modifications easily. Those modifications can include requests for information for any step in the analysis process, as well as adding various functions to compute additional information of interest. It is also written, given sufficient input information, as a general blade geometry forced response solver that is not necessarily specific to the R24 geometry but is used here for verification of code functionality and accuracy. Although forced response analysis tools are also available in commercially available code packages, the post-processing FRAAME code offers reliable, fast, and scalable forced response analysis and Goodman diagram generation for large cases utilizing, specifically, TURBO and ANSYS® results information in an effort to streamline forced response and high cycle fatigue analyses.

Aeromechanics↗
NASA NTRS2019

VIPER Integrated MDAO Analysis for Conceptual Design of Supersonic X-Plane Vehicles

A streamlined Multi-Disciplinary Analysis and Optimization (MDAO) process is being developed to provide feedback on conceptual designs and early airspace modeling assessments of unconventional aircraft. This MDAO process has been demonstrated using a Low-Boom Flight Demonstrator (LBFD) like configuration by performing a trade study of various flap sizes. The results of this trade showed that shorter takeoff distances are achieved with increased flap chord and flap deflections. This trend is unlike conventional transport type aircraft which typically show increased required takeoff distances due to the increased drag during its take-off flap configurations. The LBFD like configuration results are attributed to its high engine thrust which overcomes the higher drag associated with these takeoff flap configurations.

MDAO↗
DOE OSTI2026

pathSQE : an automated workflow for single-crystal inelastic neutron scattering data processing and analysis

Inelastic neutron scattering (INS) experiments utilizing modern time-of-flight spectrometers enable the comprehensive mapping of the energy (E)- and momentum (Q)-resolved dynamical structure factor of single crystals, probing both the lattice and magnetic excitations. Yet, the large size and complexity of four-dimensional INS data are challenging current analysis workflows, often resulting in an underutilization of the measured information. To help address this issue, this paper introduces new software interfaced with the Mantid framework, pathSQE, designed to streamline the processing, analysis and interpretation of 4D single-crystal INS data. By automating key tasks such as 1D/2D slicing, symmetrization, Brillouin zone folding, data visualization, prioritization and filtering, and comparisons with simulations, pathSQE facilitates and accelerates INS data analysis workflows. Here, this paper outlines the features and implementation and provides several illustrations of the use of pathSQE on data collected on single crystals using direct-geometry time-of-flight spectrometers at the Spallation Neutron Source, including Ge, FeSi, MnO and SnS single-crystal measurements on the ARCS, HYSPEC and CNCS neutron spectrometers. Beyond streamlining post-experiment data processing, pathSQE establishes an automated and modular processing pipeline that could support future real-time experiment steering.

36 MATERIALS SCIENCE↗
NASA NTRS2016

SUPIN: A Computational Tool for Supersonic Inlet Design

A computational tool named SUPIN is being developed to design and analyze the aerodynamic performance of supersonic inlets. The inlet types available include the axisymmetric pitot, three-dimensional pitot, axisymmetric outward-turning, two-dimensional single-duct, two-dimensional bifurcated-duct, and streamline-traced inlets. The aerodynamic performance is characterized by the flow rates, total pressure recovery, and drag. The inlet flow-field is divided into parts to provide a framework for the geometry and aerodynamic modeling. Each part of the inlet is defined in terms of geometric factors. The low-fidelity aerodynamic analysis and design methods are based on analytic, empirical, and numerical methods which provide for quick design and analysis. SUPIN provides inlet geometry in the form of coordinates, surface angles, and cross-sectional areas. SUPIN can generate inlet surface grids and three-dimensional, structured volume grids for use with higher-fidelity computational fluid dynamics (CFD) analysis. Capabilities highlighted in this paper include the design and analysis of streamline-traced external-compression inlets, modeling of porous bleed, and the design and analysis of mixed-compression inlets. CFD analyses are used to verify the SUPIN results.

computational fluid dynamics↗
NASA NTRS2011

Addressing and Presenting Quality of Satellite Data via Web-Based Services

With the recent attention to climate change and proliferation of remote-sensing data utilization, climate model and various environmental monitoring and protection applications have begun to increasingly rely on satellite measurements. Research application users seek good quality satellite data, with uncertainties and biases provided for each data point. However, different communities address remote sensing quality issues rather inconsistently and differently. We describe our attempt to systematically characterize, capture, and provision quality and uncertainty information as it applies to the NASA MODIS Aerosol Optical Depth data product. In particular, we note the semantic differences in quality/bias/uncertainty at the pixel, granule, product, and record levels. We outline various factors contributing to uncertainty or error budget; errors. Web-based science analysis and processing tools allow users to access, analyze, and generate visualizations of data while alleviating users from having directly managing complex data processing operations. These tools provide value by streamlining the data analysis process, but usually shield users from details of the data processing steps, algorithm assumptions, caveats, etc. Correct interpretation of the final analysis requires user understanding of how data has been generated and processed and what potential biases, anomalies, or errors may have been introduced. By providing services that leverage data lineage provenance and domain-expertise, expert systems can be built to aid the user in understanding data sources, processing, and the suitability for use of products generated by the tools. We describe our experiences developing a semantic, provenance-aware, expert-knowledge advisory system applied to NASA Giovanni web-based Earth science data analysis tool as part of the ESTO AIST-funded Multi-sensor Data Synergy Advisor project.

Leptoukh, Gregory↗
DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Analysis of Jupiter's Oval BA: A Streamlined Approach

We present a novel method of constructing streamlines to derive wind speeds within jovian vortices and demonstrate its application to Oval BA for 2001 pre-reddened Cassini flyby data, 2007 post-reddened New Horizons flyby data, and 1998 Galileo data of precursor Oval DE. Our method, while automated, attempts to combine the advantages of both automated and manual cloud tracking methods. The southern maximum wind speed of Oval BA does not show significant changes between these data sets to within our measurement uncertainty. The northern maximum dries appear to have increased in strength during this time interval, tvhich likely correlates with the oval's return to a symmetric shape. We demonstrate how the use of closed streamlines can provide measurements of vorticity averaged over the encircled area with no a priori assumptions concerning oval shape. We find increased averaged interior vorticity between pre- and post-reddened Oval BA, with the precursor Oval DE occupying a middle value of vorticity between these two.

Sussman, Michael G.↗
DOE OSTI2024

Flexible Technoeconomic Analysis Tools for Evaluating Emerging Power Generation Technologies in Hourly Electricity Markets using IDAES and Pyomo

Conference presentation leveraging the recently developed “price-taker class”. We use the tool to develop and showcase workflows that enable rapid technology evaluation for power generation technologies. This work shows a reimplementation of previous results that were conducted outside the price-taker class framework, indicating this workflow is indeed streamlining emerging technology analysis.

Laky, Daniel↗
NASA NTRS2012

Application of the Marsupial Paradigm to Tropical Cyclone Formation from Northwestward-Propagating Disturbances

A wave-tracking algorithm is developed for northwestward-propagating waves that, on occasion, play a role in tropical cyclogenesis over the western oceans. To obtain the Lagrangian flow structure, the frame of reference is translated obliquely at the same propagation speed with the precursor disturbance. Trajectory analysis suggests that streamlines in the obliquely translated frame of reference can be used to approximate flow trajectories. The algorithm was applied to Super Typhoon Nakri (2008), Tropical Cyclone Erika (2009), and a few other examples. Diagnoses of meteorological analyses and satellite-derived moisture and precipitation fields show that the marsupial framework for tropical cyclogenesis in tropical easterly waves is relevant also for northwestward-propagating disturbances as are commonly observed in the tropical western Atlantic, the Gulf of Mexico, and the western North Pacific. Finally, it is suggested that analysis of the global model data and satellite observations in the marsupial framework can provide useful guidance on early tropical cyclone advisories.

Wang, Zhuo↗
DOE OSTI2025

Machine Learning for Well Log Analysis in Uranium Mining

This project explores the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to automate well log analysis for uranium mining. Geophysical log data—spontaneous potential, resistivity, and gamma ray—were used to classify lithology, correlate well logs and identify roll front zonation patterns, which are critical for locating uranium ore bodies. Supervised ML algorithms such as eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Random Forest were trained to classify lithology with high accuracy. Gradient Boosting Machines (GBM), XGBoost, Random Forest, and Neural Networks were also used for role front zone identification. Moreover, a Fast Dynamic Time Warping (FastDTW) algorithm was employed for well log correlation. Additionally, sample lag was addressed using dynamic programming. Results demonstrate the potential of AI and ML to streamline well log analysis and enhance uranium exploration workflows.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Heat load measurements for the PIP-II pHB650 cryomodule

This study presents a brief overview of the 1st and 2nd phases and an in-depth analysis of the 3rd phase heat load testing performed on the pHB650 (prototype High Beta 650 MHz) cryomodule at PIP2IT (PIP-II Injector Test Facility), with a focus on both the results and the methodological advancements that have improved testing efficiency and accuracy. A key challenge identified in the testing campaign is the higher-than-expected heat loads observed in the first PIP-II (Proton Improvement Plan II) prototype cryomodules (pSSR1 and pHB650) tested at PIP2IT. Elevated heat loads are concerning given the fixed capacity of the PIP-II cryoplant that is currently being installed at Fermilab. However, understanding the sources of these elevated heat loads offers a critical opportunity to implement effective heat load mitigations on upcoming PIP-II cryomodules to stay within the available capacity of the PIP-II cryoplant. The study includes a summary of test results, descriptions of measurement procedures, and key observations on parameters directly and indirectly related to heat load measurements. Direct observations include measured heat loads and the effectiveness of JT heat exchanger under varying conditions, while indirect observation analyze factors such as the temperature distribution on the two-phase pipe and relief piping under varying conditions. Thermal acoustic oscillations (TAO) were identified during testing, which was mitigated by replacing the original G10 stem with a stainless steel stem equipped with wipers for the cryomodule cooldown valve. A major innovation during pHB650 Phase 3 testing was the development of an automated Python script to streamline data acquisition, analysis, and reporting of heat load results. This script automatically retrieved data from ACNET (Accelerator Control Network), performed heat load calculations, and generated detailed reports featuring plots and tables. This advancement significantly reduced manual labor and enhanced the thoroughness of data analysis compared to earlier campaigns. The heat load test reports were promptly uploaded to the electronic logbook shortly after each test, enabling rapid feedback and collaboration between the SRF and cryogenic teams. The heat load measurements included various components: HTTS (high-temperature thermal shield), LTTS (low-temperature thermal shield), 2K isothermal and non-isothermal heat loads. Results were recorded both within the cryomodule and between the bayonet can supply and return. Measurements were conducted under different operating conditions such as "standard", "linac", and "simulated dynamic". Additionally, HTTS and LTTS heat loads were calculated in real time, allowing for the tracking of thermal stability and identification of changes during testing, both in steady-state and transient conditions. The results of this testing campaign not only provide valuable insights into the performance of the pHB650 cryomodule but also highlight best practices and lessons learned that will inform future cryomodule testing at PIP2IT. These include adopting automated tools for data analysis, refining real-time measurement capabilities, and emphasizing detailed pre-test planning. The framework established in this campaign aims to set an improved standard for cryomodule testing and heat load reporting in future cryomodule test campaigns.

Porwisiak, D. [Fermilab; Wroclaw Tech. U.]↗
DOE OSTI2018

Developing an Interactive Data Visualization Tool to Assess the Impact of Decision Support on Clinical Operations

Due to mandates from recent legislation, clinical decision support (CDS) software is being adopted by radiology practices across the country. This software provides imaging study decision support for referring providers at the point of order entry. CDS systems produce a large volume of data, providing opportunities for research and quality improvement. In order to better visualize and analyze trends in this data, an interactive data visualization dashboard was created using a commercially available data visualization platform. Following the integration of a commercially available clinical decision support product into the electronic health record, a dashboard was created using a commercially available data visualization platform (Tableau, Seattle, WA). Data generated by the CDS were exported from the data warehouse, where they were stored, into the platform. This allowed for real-time visualization of the data generated by the decision support software. The creation of the dashboard allowed the output from the CDS platform to be more easily analyzed and facilitated hypothesis generation. Integrating data visualization tools into clinical decision support tools allows for easier data analysis and can streamline research and quality improvement efforts.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Explainable artificial intelligence relates perovskite luminescence images to current-voltage metrics

As the demand for low-cost, high-efficiency solar energy technologies grows, metal halide perovskite (MHP) solar cells have emerged as a promising candidate for next-generation photovoltaics due to their high power conversion efficiencies. However, their poor durability and issues with manufacturing consistency remain significant barriers to commercialization. In this work, we develop deep learning models to support materials characterization and provide insight into features and processes influencing performance. The models are trained using transfer learning of a pretrained model to predict relevant current-voltage (IV) metrics based on different combinations of input electroluminescence (EL) and photoluminescence (PL) images of MHP devices. We examine which image types are most informative in accurately predicting different IV metrics. Additionally, we use explainable artificial intelligence (XAI) techniques to provide insights into specific spatial features in the devices that drive differences in performance. We find that stabilized luminescence images (e.g. those collected after biasing the devices for at least 1 min) are better for predicting metrics of open-circuit voltage (by PL) and short-circuit current (by PL with EL), but that predicting fill factor and overall power output may use the time-evolution of EL images. Based on attribution masks generated by integrated gradients for each device performance metric, we further suggest different loss mechanisms associated with categories of large and small spatial defects. Overall, this case study highlights the potential applicability of XAI methodology for streamlining MHP device analysis and accelerating detailed understanding of the relationships between spatial defects and impacts on performance.

14 SOLAR ENERGY↗
DOE OSTI2023

The fast camera (Fastcam) imaging diagnostic systems on the DIII-D tokamak

Two camera systems are installed on the DIII-D tokamak at the toroidal positions of 90° (90° system) and 225° (225° system), respectively. The cameras have two types of relay optics, namely, a coherent optical fiber bundle and a periscope system. The periscope system provides absolute intensity calibration stability while sacrificing resolution (10 lp/mm), while the fiber system provides high resolution (16 lp/mm) while sacrificing calibration stability. The periscope is available only for the 90° system. The optics of the 225° system were designed for view stability, repeatability, and easy maintenance. The cameras are located inside optimized neutron, x ray and magnetic shielding in order to reduce electronics damage, reboots, and magnetic and neutron interference, increasing the overall system reliability. An automated filter wheel, providing remote filter change, allows for remote wavelength selection. A software suite automates camera acquisition and data storage, allowing for remote operation and reduced operator involvement. System metadata is used to streamline the data analysis workflow, particularly for intensity calibration. Here, the spatial calibration uses multiple observable wall features, resulting in a reconstruction accuracy ≤2 cm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1977

Doubly-curved variable-thickness isoparametric heterogeneous finite element

This paper describes an element streamlined for the analysis of doubly-curved, variable-thickness structural components and illustrates its effective application to vibration and static problems. The element is isoparametric, doubly-curved, thin-shell and triangular with variable thickness and accounts for anisotropic, inhomogeneous elastic material behavior. The element has six nodes (three corner and three mid-side) with five degrees-of-freedom (DOF) per node - three translations and two rotations. Quadratic isoparametric interpolation polynomials are used to express the element geometry and displacement variables in terms of corresponding nodal variables.

Minich, M. D.↗
NASA NTRS1993

Two-layer convective heating prediction procedures and sensitivities for blunt body reentry vehicles

This paper provides a description of procedures typically used to predict convective heating rates to hypersonic reentry vehicles using the two-layer method. These procedures were used to compute the pitch-plane heating distributions to the Apollo geometry for a wind tunnel test case and for three flight cases. Both simple engineering methods and coupled inviscid/boundary layer solutions were used to predict the heating rates. The sensitivity of the heating results in the choice of metrics, pressure distributions, boundary layer edge conditions, and wall catalycity used in the heating analysis were evaluated. Streamline metrics, pressure distributions, and boundary layer edge properties were defined from perfect gas (wind tunnel case) and chemical equilibrium and nonequilibrium (flight cases) inviscid flow-field solutions. The results of this study indicated that the use of CFD-derived metrics and pressures provided better predictions of heating when compared to wind tunnel test data. The study also showed that modeling entropy layer swallowing and ionization had little effect on the heating predictions.

Bouslog, Stanley A.↗
NASA NTRS2007

Modeling and Grid Generation of Iced Airfoils

SmaggIce Version 2.0 is a software toolkit for geometric modeling and grid generation for two-dimensional, singleand multi-element, clean and iced airfoils. A previous version of SmaggIce was described in Preparing and Analyzing Iced Airfoils, NASA Tech Briefs, Vol. 28, No. 8 (August 2004), page 32. To recapitulate: Ice shapes make it difficult to generate quality grids around airfoils, yet these grids are essential for predicting ice-induced complex flow. This software efficiently creates high-quality structured grids with tools that are uniquely tailored for various ice shapes. SmaggIce Version 2.0 significantly enhances the previous version primarily by adding the capability to generate grids for multi-element airfoils. This version of the software is an important step in streamlining the aeronautical analysis of ice airfoils using computational fluid dynamics (CFD) tools. The user may prepare the ice shape, define the flow domain, decompose it into blocks, generate grids, modify/divide/merge blocks, and control grid density and smoothness. All these steps may be performed efficiently even for the difficult glaze and rime ice shapes. Providing the means to generate highly controlled grids near rough ice, the software includes the creation of a wrap-around block (called the "viscous sublayer block"), which is a thin, C-type block around the wake line and iced airfoil. For multi-element airfoils, the software makes use of grids that wrap around and fill in the areas between the viscous sub-layer blocks for all elements that make up the airfoil. A scripting feature records the history of interactive steps, which can be edited and replayed later to produce other grids. Using this version of SmaggIce, ice shape handling and grid generation can become a practical engineering process, rather than a laborious research effort.

Vickerman, Mary B.↗