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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

A Presentation on Robust Flutter Margin Analysis and a Flutterometer

This paper documents an invited presentation given to The Boeing Company, Seattle, Washington, on September 9, 1997. The audience consisted of structural dynamic and flight test engineers from the Boeing Commercial Airplane Group who were interested in discussing research which may be applied to future flight flutter test programs. A method to compute robust flutter margins is described which is a significant departure from traditional methods. This method uses the structured singular value, mu, to compute a flutter margin which directly accounts for modeling errors such that a worst-case flutter margin is computed with respect to those errors. This method may be applied in several ways. A post-flight application uses data sets from multiple test points to compute worst-case flutter margins and a worst-case flight envelope. An on-line implementation computes flutter margins at each test point to track the flutter margins during a flight test. This on-line implementation is the basis for a flutterometer flight test tool that displays the distance to flutter at a given test point. Such a tool was not previously possible using traditional flutter flight test analysis methods. The F/A-18 System Research Aircraft was used to demonstrate these applications using flight data recorded from test points throughout the flight envelope.

Lind, Rick C.↗
DOE OSTI2026

Maximizing efficiency of dataset compression for machine learning potentials with information theory

Machine learning interatomic potentials (MLIPs) balance high accuracy and lower costs compared to density functional theory calculations, but their performance often depends on the size and diversity of training datasets. Large datasets improve model accuracy and generalization but are computationally expensive to produce and train on, while smaller datasets risk discarding rare but important atomic environments and compromising MLIP accuracy/reliability. Here, we develop an information-theoretical framework to quantify the efficiency of dataset compression methods and propose an algorithm that maximizes this efficiency. By framing atomistic dataset compression as an instance of the minimum set cover (MSC) problem over atom-centered environments, our method identifies the smallest subset of structures that contains as much information as possible from the original dataset while pruning redundant information. The approach is extensively demonstrated on the GAP-20 and TM23 datasets and validated on 64 varied datasets from the ColabFit repository. Across all cases, MSC consistently retains outliers, preserves dataset diversity, and reproduces the long-tail distributions of forces even at high compression rates, outperforming other subsampling methods. Furthermore, MLIPs trained on MSC-compressed datasets exhibit reduced error for out-of-distribution data even in low-data regimes. We explain these results using an outlier analysis and show that such quantitative conclusions could not be achieved with conventional dimensionality reduction methods. The algorithm is implemented in the open-source QUESTS package and can be used for several tasks in atomistic modeling, from data subsampling, outlier detection, and training improved MLIPs at a lower cost.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Oregon Rivers Characterization Tool

DHS’s Regional Resiliency Assessment Program (RRAP) undertook the Oregon State Transportation Systems RRAP project between 2018-2021 to assess the seismic vulnerabilities of the state’s transportation system to a Cascadia Subduction Zone (CSZ) earthquake (CISA 2021). The project primarily focused on the effects of a CSZ earthquake on the mobility of emergency response efforts into the region. In the event that bridges located at crucial river crossings fail during a CSZ earthquake, rivers will become natural barriers affecting the ability to support response and recovery efforts. The characteristics of rivers (e.g., width, depth, and flow) are critical data to inform planning for the recovery of transportation systems across river barriers and determine reopening times following a CSZ earthquake. As part of the transportation system assessment, an Argonne National Laboratory (Argonne) project team developed a River Characterization Tool (RCT) to quantify the physical characteristics of the river system in Oregon, which can be used to inform a system-level analysis of transportation recovery and reopening times. This report mainly discusses approaches, methods, development, and applications of the RCT. The use of the river data generated from this tool for a system-level analysis of transportation recovery is discussed in the Oregon Transportation Systems RRAP Resiliency Assessment report (CISA 2021). The primary goal of the RCT is to generate statewide dataset of widths, depths, and flows for all rivers across Oregon to assess the effects of river barriers on emergency response and recovery efforts following a CSZ earthquake. The RCT leverages remote sensing data that multispectral sensors collect from satellites, employs a deep learning model to characterize river predictions, and computes river channel geometric dimensions with hydraulic relationships and river predictions. The entire process of river characterization is automated and implemented through the RCT.

58 GEOSCIENCES↗
NASA NTRS2004

Evaluation of Rock Powdering Methods to Obtain Fine-grained Samples for CHEMIN, a Combined XRD/XRF Instrument

A miniature XRD/XRF (X-ray diffraction / X-ray fluorescence) instrument, CHEMIN, is currently being developed for definitive mineralogic analysis of soils and rocks on Mars. One of the technical issues that must be addressed to enable remote XRD analysis is how best to obtain a representative sample powder for analysis. For powder XRD analyses, it is beneficial to have a fine-grained sample to reduce preferred orientation effects and to provide a statistically significant number of crystallites to the X-ray beam. Although a two-dimensional detector as used in the CHEMIN instrument will produce good results even with poorly prepared powder, the quality of the data will improve and the time required for data collection will be reduced if the sample is fine-grained and randomly oriented. A variety of methods have been proposed for XRD sample preparation. Chipera et al. presented grain size distributions and XRD results from powders generated with an Ultrasonic/Sonic Driller/Corer (USDC) currently being developed at JPL. The USDC was shown to be an effective instrument for sampling rock to produce powder suitable for XRD. In this paper, we compare powder prepared using the USDC with powder obtained with a miniaturized rock crusher developed at JPL and with powder obtained with a rotary tungsten carbide bit to powders obtained from a laboratory bench-scale Retsch mill (provides benchmark mineralogical data). These comparisons will allow assessment of the suitability of these methods for analysis by an XRD/XRF instrument such as CHEMIN.

Chipera, S. J.↗
NASA NTRS1978

Acoustic emission strand burning technique for motor burning rate prediction

An acoustic emission (AE) method is being used to measure the burning rate of solid propellant strands. This method has a precision of 0.5% and excellent burning rate correlation with both subscale and large rocket motors. The AE procedure burns the sample under water and measures the burning rate from the acoustic output. The acoustic signal provides a continuous readout during testing, which allows complete data analysis rather than the start-stop clockwires used by the conventional method. The AE method helps eliminate such problems as inhibiting the sample, pressure increase and temperature rise, during testing.

Christensen, W. N.↗
DOE OSTI2024

The MUSIC Critical Benchmark and Nuclear Data

The Measurement of Uranium Subcritical and Critical (MUSIC) experiment was a series of measurements of critical and subcritical configurations of bare highly enriched uranium. The goal was to compare measurement methods, analysis techniques, and simulation methods across regimes of criticality and to provide high-quality validation of 235 U nuclear data. A benchmark evaluation of the two critical configurations of the MUSIC experiments will soon be published in the release of the International Criticality Safety Benchmark Evaluation Project Handbook. The recent execution of the experiment aids in proper quantification of model simplifications and all uncertainties associated with the experiment. Historical benchmark evaluations are heavily relied on for uranium nuclear data validation despite the fact that the same level of documentation and comparable uncertainty analysis may not be present. The MUSIC evaluation is less likely to include “unknown unknowns” that could impede accurately modeling the system. Presented are both highly detailed and very simplified models, which represent the experimental configurations accurately, aiding the users of the benchmark for nuclear data or transport code validation. The sensitivities of k eff to nuclear data and nuclear data–related uncertainties are very similar between this experiment and previous bare uranium sphere experiments. In addition, the nuclear data uncertainties to any nuclides other than 235 U are small. For all these reasons, the recently evaluated MUSIC benchmark critical configurations could prove very useful for 235 U nuclear data validation. Currently, major libraries have good agreement with the experimental results, within 200 pcm for all nuclear data libraries, and within one standard deviation of the experimental result for most. Suggested nuclear data adjustments based on MUSIC and Lady Godiva are also presented, with posterior improvements to both the agreement in k eff and the uncertainty associated with the nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Bayesian inference of nuclear-matter density from proton scattering

Background: Proton elastic scattering at intermediate energy is widely employed as a tool for determining the matter radius of atomic nuclei. Here, the sensitivity of the approach relies on high-resolution measurements at small scattering angles and low-momentum transfer. Under these conditions, the Glauber multiple scattering theory accurately describes the proton-nucleus elastic cross section. Purpose: Investigate the sensitivity of the Glauber multiple scattering theory to uncertainties associated with input parameters such as the nuclear-matter density distribution and nucleon-nucleon data. Method: A joint Bayesian inference was performed using 12 angular distributions of elastic scattering at different energies on 58 Ni, 90 Zr, and 208 Pb targets. A Metropolis-Hastings algorithm was implemented to make an uncertainty quantification analysis for the input parameters used in the Glauber multiple scattering theory. Results: The experimental cross sections were fitted simultaneously using a joint Bayesian inference approach. Posterior probability density distributions of 42 input parameters were obtained from the analysis. A moderate correlation between the nuclear density parameters and the nucleon-nucleon cross sections was found. This correlation impacts the extraction of the nuclear-matter radius. Conclusions: The present analysis provided a consistent method for extracting the nuclear-matter density distribution of 58 Ni, 90 Zr, and 208 Pb from data across different incident energies. Due to the correlation of the nucleon-nucleon cross sections with the other input parameters, a constrained Bayesian inference using free nucleon-nucleon cross section data was performed. The nuclear-matter radii obtained from the analysis are in good agreement with multiple results reported in the literature.

190 ≤ A ≤ 219↗
DOE OSTI2024

Automated Algorithms for Screening Electronic Parts for Aging using Power Spectra Analysis (PSA) Data

Understanding the age of semiconductor parts being built into devices and systems is of interest for manufacturing quality control. Power spectrum analysis (PSA) is a fast, non-destructive, sensitive method for examining semiconductor parts. This talk will cover the use of multivariate analysis on both PSA data and conventional current-voltage data generated prior to PSA analysis to create algorithms that can be automated to screen semiconductor parts for aging.

Multari, Rosalie A↗
NASA NTRS1973

Implementation and extension of the impulse transfer function method for future application to the space shuttle project. Volume 1: Analysis and correlation studies

Computer programming, data processing, and a correlation study that employed data collected in the first phase test were used to demonstrate that standard test procedures and equipment could be used to collect a significant number of transfer functions from tests of the Lunar Module test article LTA-11. The testing consisted of suspending the vehicle from the apex fittings of the outrigger trusses through a set of air springs to simulate the free-free state. Impulsive loadings were delivered, one at a time, at each of the landing gear's attachment points, in three mutually perpendicular directions; thus a total of 36 impulses were applied to the vehicle. Time histories of each pulse were recorded on magnetic tape along with 40 channels of strain gage response and 28 channels of accelerometer response. Since an automated data processing system was not available, oscillograph playbacks were made of all 2400 time histories as a check on the validity of the data taken. In addition, one channel of instrumentation was processed to determine its response to a set of forcing functions from a prior LTA-11 drop test. This prediction was compared with drop test results as a first measure of accuracy.

Mantus, M.↗
NASA NTRS1976

Flooding of Monroe County, Michigan - A comparison of three remote sensor data sets

During the spring of 1973, three techniques were used to obtain remotely sensed data pertaining to the flooded shoreline of Monroe County, Michigan. Although digitized data from the Earth Resources Technology Satellite were available on magnetic tapes, analysis was based on interpretation methods normally used for aerial photography, since the black and white IR photography and side-looking airborne radar (SLAR) data were available only as images. Using IR photography as the standard, it was found that ERTS-1 Band 7 imagery had a 93% accuracy in detecting areas in the combined category of open water and flooded fields. X(HH) data from SLAR detected that built-up and wet areas were built-up (89 to 100% accuracy), but not that they were wet. It is suggested that these two sensors used in concert from orbital heights could provide information useful to relief organizations in flooded areas. It is considered likely that SLAR data will improve as higher resolution becomes available.

Bryan, M. L.↗
NASA NTRS1996

A New Method of Deriving Time-Averaged Tropospheric Column Ozone over the Tropics Using Total Ozone Mapping Spectrometer (TOMS) Radiances: Intercomparison and Analysis Using TRACE A Data

Error analysis of archived total 03 from total ozone mapping spectrometer (TOMS) (version 6) presented. Daily total 03 maps for the tropics, from the period October 6-21, 1992, are derived from TOMS radiances following correction for these errors. These daily maps, averaged together, show a wavelike feature, which is observed in all latitude bands, underlying sharp peaks which occur at different longitudes depending on the latitude. The wave pattern is used to derive both time-averaged stratospheric and tropospheric 03 fields. The nature of the wave pattern (stratospheric or tropospheric) cannot be determined with certainty due to missing data (no Pacific sondes, no lower stratospheric Stratospheric Aerosol and Gas Experiment (SAGE) ozone for 18 months after the Mt. Pinatubo eruption) and significant uncertainties in the corroborative satellite record in the lower stratosphere (solar backscattered ultraviolet (SBUV), microwave limb sounder (MLS)). However, the time- averaged tropospheric ozone field, based on the assumption that the wave feature is stratospheric, agrees within 10% with ultraviolet differential absorption laser Transport and Atmospheric Chemistry near the Equator-Atlantic) (TRACE A) 03 measurements from the DC-8 and with ozonesonde measurements over Brazzaville, Congo, Ascension Island, and Natal, Brazil, for the period October 6-21, 1992. The derived background (nonpolluted) Indian Ocean tropospheric ozone amount, 26 Dobson units (DU), agrees with the cleanest African ozonesonde profiles for September-October 1992. The assumption of a totally tropospheric wave (flat stratosphere) gives 38 DU above the western Indian Ocean and 15-40% disagreements with the sondes. Tropospheric column 03 is high from South America to Africa, owing to interaction of dynamics with biomass burning emissions. Comparison with fire distributions from advanced very high resolution radiometer (AVHHR) during October 1992 suggests that tropospheric 03 produced from biomass burning in South America and Africa dominates the 03 budget in the tropical southern hemisphere during the study period.

Kim, J. H.↗
NASA NTRS2000

Geoid Recovery using Geophysical Inverse Theory Applied to Satellite to Satellite Tracking Data

This report describes a new method for determination of the geopotential. The analysis is aimed at the GRACE mission. This Satellite-to-Satellite Tracking (SST) mission is viewed as a mapping mission The result will be maps of the geoid. The elements of potential theory, celestial mechanics, and Geophysical Inverse Theory are integrated into a computation architecture, and the results of several simulations presented Centimeter accuracy geoids with 50 to 100 km resolution can be recovered with a 30 to 60 day mission.

Gaposchkin, E. M.↗
NASA NTRS1997

Using Non-Linear Statistical Methods with Laboratory Kinetic Data

This paper will demonstrate the usefulness of standard non-linear statistical analysis on ICR and SIFT kinetic data. The specific systems used in the demonstration are the isotopic and change transfer reactions in the system of H2O+/D2O, H30+/D2O, and other permutations.

non-linear analysis kinetic isotopic permutations ↗
DOE OSTI2023

Dynamic Network Analysis of Nuclear Science Literature for Research Influence Assessment

Analyzing nuclear science literature via data-driven methods is a critical step for assessing research influence and technology advancements. Indicators of scholarly activities may be buried in large volumes of nuclear research publications and collaboration networks over time. Mining for relevant scholarly influence trends in large volumes of text can be computationally challenging; however, open-source information on research collaborations over time can offer opportunities to extract meaningful insights. While network centrality analysis of scholarly research provides topology-based insights, additional emphasis on dynamics associated with the diffusion of information through these networks is important. Here this paper represents a step in that direction through the development of a novel dynamic network analysis framework and computational engine to identify key entities and capabilities over time within global scholarly nuclear science collaboration networks. Network theoretic, stochastic simulation, and optimization methods are leveraged to address variability in scholarly interactions, influence propagation, and collaboration patterns via network connections. A topic-aware influence maximization algorithm is developed to address the goal of identifying key influential authors in diverse research topics over time. Efficient parallelized implementation of the algorithm is applied to reduce computational costs. A proof-of-concept case study using open-source Scopus data with 33,517 published nuclear research papers from 2000-2019 is presented and representative analytic insights are generated. Broad implications of these insights are discussed and future research directions are also identified.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Increasing the Scale of the Mass Spectrometry Query Language Compendium with Explainable AI

A significant bottleneck in metabolomics data interpretation is the effective use of domain knowledge to assign structural information based on fragmentation patterns. The mass spectrometry query language (MassQL) aims to make this process accessible and applicable across multiple analysis platforms. While advanced computational methods are capable of predicting compound structures from fragmentation data, AI/ML approaches often rely on complex, opaque criteria that are difficult to interpret or modify. As a result, their predictive patterns cannot be readily translated into human-readable rules, such as those used in MassQL. Here, in this study, we introduce ChemEcho, a machine learning embedding method that converts tandem mass spectrometry data into sparse feature vectors containing peak and neutral mass subformulae to enhance explainable AI/ML-based methods. An advantage of this approach is that decision trees trained using these feature vectors can be directly translated to MassQL. Using a battery of decision trees trained using ChemEcho embeddings to predict molecular attributes, we generated over 1500 MassQL queries for 765 molecular features and evaluated their precision and recall. From these queries, the 50 highest-performing queries were integrated into the MassQL compendium. This set of generated MassQL queries included environmentally and biologically relevant classes such as PFAS and molecules containing phosphate or sulfate substructures. To illustrate the impact these queries would have on a typical metabolomics experiment, these MassQL queries were applied to a public metabolomics data set─resulting in a marked increase in the structural information derived from tandem mass spectra. Access and reuse of these queries is expected to enhance structural annotation in untargeted experiments, leading to more specific claims and advancing many applications in metabolomics.

Harwood, Thomas V. [USDOE Joint Genome Institute (↗
NASA NTRS1984

Component specific modeling

Modern jet engine design imposes extremely high loadings and temperatures on hot section components. A series of interdisciplinary modeling and analysis techniques which were specialized to address three specific components (combustor burner linings, hollow air-cooled turbine blades, and air-cooled turbine vanes) were developed and verified. These techniques will incorporate data as well as theoretical methods from many diverse areas, including cycle and performance analysis, heat transfer analysis, linear and nonlinear stress analysis, and mission analysis. Building on the proven techniques already available in these fields, the new methods developed will be integrated to predict temperature, deformation, stress, and strain histories throughout a complete flight mission.

Roberts, M. L.↗