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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Ballistic Impact Response of Kevlar 49 and Zylon under Conditions Representing Jet Engine Fan Containment

A ballistic impact test program was conducted to provide validation data for the development of numerical models of blade out events in fabric containment systems. The impact response of two different fiber materials - Kevlar 49 (E.I. DuPont Nemours and Company) and Zylon AS (Toyobo Co., Ltd.) was studied by firing metal projectiles into dry woven fabric specimens using a gas gun. The shape, mass, orientation and velocity of the projectile were varied and recorded. In most cases the tests were designed such that the projectile would perforate the specimen, allowing measurement of the energy absorbed by the fabric. The results for both Zylon and Kevlar presented here represent a useful set of data for the purposes of establishing and validating numerical models for predicting the response of fabrics under conditions simulating those of a jet engine blade release situation. In addition some useful empirical observations were made regarding the effects of projectile orientation and the relative performance of the different materials.

Pereira, J. Michael↗
NASA NTRS2008

FAA Development of Reliable Modeling Methodologies for Fan Blade Out Containment Analysis: Ballistic Impact Testing - Part 2

This report summarizes the ballistic impact testing that was conducted to provide validation data for the development of numerical models of blade out events in fabric containment systems. The ballistic impact response of two different fiber materials - Kevlar 49 (E.I. DuPont Nemours and Company) and Zylon AS (Toyobo Co., Ltd.) was studied by firing metal projectiles into dry woven fabric specimens using a gas gun. The shape, mass, orientation and velocity of the projectile were varied and recorded. In most cases the tests were designed such that the projectile would perforate the specimen, allowing measurement of the energy absorbed by the fabric. The results for both Zylon and Kevlar presented here represent a useful set of data for the purposes of establishing and validating numerical models for predicting the response of fabrics under conditions simulating those of a jet engine blade release situations. In addition some useful empirical observations were made regarding the effects of projectile orientation and the relative performance of the different materials.

Revilock, Duane M.↗
NASA NTRS2004

Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response Due to Foreign Object Damage (FOD) Events

The development of a wavelet-based feature extraction technique specifically targeting FOD-event induced vibration signal changes in gas turbine engines is described. The technique performs wavelet analysis of accelerometer signals from specified locations on the engine and is shown to be robust in the presence of significant process and sensor noise. It is envisioned that the technique will be combined with Kalman filter thermal/health parameter estimation for FOD-event detection via information fusion from these (and perhaps other) sources. Due to the lack of high-frequency FOD-event test data in the open literature, a reduced-order turbofan structural model (ROM) was synthesized from a finite element model modal analysis to support the investigation. In addition to providing test data for algorithm development, the ROM is used to determine the optimal sensor location for FOD-event detection. In the presence of significant noise, precise location of the FOD event in time was obtained using the developed wavelet-based feature.

Turso, James↗
NASA NTRS2007

Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response Due to Foreign Object Damage "FOD" Events

The development of a wavelet-based feature extraction technique specifically targeting FOD-event induced vibration signal changes in gas turbine engines is described. The technique performs wavelet analysis of accelerometer signals from specified locations on the engine and is shown to be robust in the presence of significant process and sensor noise. It is envisioned that the technique will be combined with Kalman filter thermal/ health parameter estimation for FOD-event detection via information fusion from these (and perhaps other) sources. Due to the lack of high-frequency FOD-event test data in the open literature, a reduced-order turbofan structural model (ROM) was synthesized from a finite-element model modal analysis to support the investigation. In addition to providing test data for algorithm development, the ROM is used to determine the optimal sensor location for FOD-event detection. In the presence of significant noise, precise location of the FOD event in time was obtained using the developed wavelet-based feature.

Turso, James A.↗
NASA NTRS1974

Spaceflight tracking and data network operational reliability assessment for Skylab

Data on the spaceflight communications equipment status during the Skylab mission were subjected to an operational reliability assessment. Reliability models were revised to reflect pertinent equipment changes accomplished prior to the beginning of the Skylab missions. Appropriate adjustments were made to fit the data to the models. The availabilities are based on the failure events resulting in the stations inability to support a function of functions and the MTBF's are based on all events including 'can support' and 'cannot support'. Data were received from eleven land-based stations and one ship.

Seneca, V. I.↗
NASA NTRS2017

Relationship Between Carbon Dioxide Levels and Reported Congestion and Headaches on the International Space Station

Congestion is commonly reported during spaceflight, and most crewmembers have reported using medications for congestion during International Space Station (ISS) missions. Although congestion has been attributed to fluid shifts during spaceflight, fluid status reaches equilibrium during the first week after launch while congestion continues to be reported throughout long duration missions. Congestion complaints have anecdotally been reported in relation to ISS CO2 levels; this evaluation was undertaken to determine whether or not an association exists. METHODS: Reported headaches, congestion symptoms, and CO2 levels were obtained for ISS expeditions 2-31, and time-weighted means and single-point maxima were determined for 24-hour (24hr) and 7-day (7d) periods prior to each weekly private medical conference. Multiple imputation addressed missing data, and logistic regression modeled the relationship between probability of reported event of congestion or headache and CO2 levels, adjusted for possible confounding covariates. The first seven days of spaceflight were not included to control for fluid shifts. Data were evaluated to determine the concentration of CO2 required to maintain the risk of congestion below 1% to allow for direct comparison with a previously published evaluation of CO2 concentrations and headache. RESULTS: This study confirmed a previously identified significant association between CO2 and headache and also found a significant association between CO2 and congestion. For each 1-mm Hg increase in CO2, the odds of a crew member reporting congestion doubled. The average 7-day CO2 would need to be maintained below 1.5 mmHg to keep the risk of congestion below 1%. The predicted probability curves of ISS headache and congestion curves appear parallel when plotted against ppCO2 levels with congestion occurring at approximately 1mmHg lower than a headache would be reported. DISCUSSION: While the cause of congestion is multifactorial, this study showed congestion is associated with CO2 levels on ISS. Data from additional expeditions could be incorporated to further assess this finding. CO2 levels are also associated with reports of headaches on ISS. While it may be expected for astronauts with congestion to also complain of headaches, these two symptoms are commonly mutually exclusive. Furthermore, it is unknown if a temporal CO2 relationship exists between congestion and headache on ISS. CO2 levels were time-weighted for 24hr and 7d, and thus the time course of congestion leading to headache was not assessed; however, congestion could be an early CO2-related symptom when compared to headache. Future studies evaluating the association of CO2-related congestion leading to headache would be difficult due to the relatively stable daily CO2 levels on ISS currently, but a systematic study could be implemented on-orbit if desired.

Cole, Robert↗
DOE OSTI2025

Data-driven model validation for neutrino-nucleus cross section measurements

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mismodeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Data-driven model validation for neutrino-nucleus cross section measurements

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mismodeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2020

Application of Sparse Identification of Nonlinear Dynamics for Physics-Informed Learning

Advances in machine learning and deep neural networks has enabled complex engineering tasks like image recognition, anomaly detection, regression, and multi-objective optimization, to name but a few. The complexity of the algorithm architecture, e.g., the number of hidden layers in a deep neural network, typically grows with the complexity of the problems they are required to solve, leaving little room for interpreting (or explaining) the path that results in a specific solution. This drawback is particularly relevant for autonomous aerospace and aviation systems, where certifications require a complete understanding of the algorithm behavior in all possible scenarios. Including physics knowledge in such data-driven tools may improve the interpretability of the algorithms, thus enhancing model validation against events with low probability but relevant for system certification. Such events include, for example, spacecraft or aircraft sub-system failures, for which data may not be available in the training phase. This paper investigates a recent physics-informed learning algorithm for identification of system dynamics, and shows how the governing equations of a system can be extracted from data using sparse regression. The learned relationships can be utilized as a surrogate model which, unlike typical data-driven surrogate models, relies on the learned underlying dynamics of the system rather than large number of fitting parameters. The work shows that the algorithm can reconstruct the differential equations underlying the observed dynamics using a single trajectory when no uncertainty is involved. However, the training set size must increase when dealing with stochastic systems, e.g., nonlinear dynamics with random initial conditions.

Corbetta, Matteo↗
DOE OSTI2021

Search for phenomena beyond the Standard Model in events with large $b$-jet multiplicity using the ATLAS detector at the LHC

A search is presented for new phenomena in events characterised by high jet multiplicity, no leptons (electrons or muons), and four or more jets originating from the fragmentation of b -quarks ( b -jets). The search uses 139 fb -1 of $\sqrt{s}$ = 13 TeV proton–proton collision data collected by the ATLAS experiment at the Large Hadron Collider during Run 2. The dominant Standard Model background originates from multijet production and is estimated using a data-driven technique based on an extrapolation from events with low b -jet multiplicity to the high b -jet multiplicities used in the search. No significant excess over the Standard Model expectation is observed and 95% confidence-level limits that constrain simplified models of R-parity-violating supersymmetry are determined. The exclusion limits reach 950 GeV in top-squark mass in the models considered.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Evaluation of a preliminary regional Earth model through comparison of synthetic and observed waveform data

In this report, we document the process related to developing a regional geologic model of a 605 x 1334 km area centered around Utah and encompassing surrounding states. This model is developed to test the effect that composition of a model has on the generation of synthetic data with the intent of using this information to improve upon full waveform moment tensor inversions. We compare observed data from three seismic events and five stations to the synthetic data generated by a preliminary model derived from a geologic framework model (GFM) developed by the USGS. The synthetic data and observed data comparisons indicate that our preliminary model performs well at smaller offset distances in the northern and central sections of the model. However, the southern stations consistently display synthetic data P- and S-wave arrival times that do not match the observed data arrival times, indicating that the velocity structure of the southern part of the model especially is inaccurate.

58 GEOSCIENCES↗
NASA NTRS1999

A Probabilistic Approach of Incorporating Safety and Reliability in System Designs for a Manned Mission to Mars

Conceptual stages in mission design often lack the input of quantitative safety and reliability assessments, simply because failure rates or other data are not yet available for systems that have not yet been designed. Absence of such data should not, however, prevent the development of a quantitative risk models with placeholders for missing data. Functions (that is, actions the systems must perform) in mission design will eventually require system probabilities of success, and there could be much learned from surrogate data, adequately bounded in uncertainty, used in a large event tree model of a complex mission.

Railsback, Jan W.↗
DOE OSTI2025

The Dynamic Networks Experiments: Virtual Experiments to Quantify Gains in Nuclear Explosion Monitoring

We describe an ongoing series of virtual experiments conducted collaboratively by four United States National Laboratories: Sandia National Laboratories, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory. These Dynamic Network Experiments (DNEs) provide an experimental framework to evaluate the potential impact of new research tools on nuclear explosion monitoring. The second DNE (DNE2), completed in 2024, exploited waveform data (seismic, infrasound, and electromagnetic) that was recorded by multi-modal sensors within and near the Nevada National Security Site and synthetic radionuclide signatures over multiple time periods. During the execution of DNE2, we processed and analyzed data through a multi-stage event processing pipeline that ingested raw data, performed quality control, detected signals, built events from these signals, located these events, and characterized the events’ source types and sizes. For each stage and over the entire event processing pipeline, we evaluated performance changes by comparing the performance of new data processing methods, models, and algorithms against a baseline. We also performed an additional execution phase to assess event processing pipeline function, speed, and efficiency against that of an expert analyst, including computational and manual efforts. Finally, we assessed the impact and effort of modern computing infrastructure on the monitoring pipeline. This paper describes key elements of the DNEs, from formulation through execution, as demonstrated in DNE2. The DNEs introduce several novel concepts to quantitatively measure the potential impact of new methods on explosion monitoring, including the collaborative design of multi-modal datasets, performance and logistical metrics, and integrated analyses.

42 ENGINEERING↗
DOE OSTI2024

Adjoint Waveform Tomography for Crustal and Upper Mantle Structure of the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data

Here we present a new model of radially anisotropic seismic wavespeeds for the crust and upper mantle of a broad region of the Middle East and Southwest Asia (MESWA) derived from adjoint waveform tomography. The new model enables fully 3D simulations of complete three-component waveforms and provides improved fits that were not possible with previous models. We inverted over 32,000 waveforms from 192 earthquakes recorded by over 1000 openly available broadband seismic stations from permanent and temporary networks in the region with highly uneven coverage. Inversion iterations proceeded from the period band 50–100 s in six stages and 54 total iterations reducing the minimum period to 30 s. Our final model, MESWA, improves waveform fits compared to the starting and other models for both the data used in the inversion and an independent validation set of 66 events. Restitution tests indicate that the model resolves features in the central part of the model to depths of about 150 km. The new model reveals tectonic features imaged by other studies and methods but in a new holistic model of anisotropic shear and compressional wavespeeds (V S and V P , respectively) covering a larger domain with smaller scale length and amplified features. Examples include low crustal V S in the Tethyan belt and low mantle VS following divergent (Gulf of Aden, Red Sea) and transform (Dead Sea fault) margins of the Arabian plate. Low V S is imaged below Cenozoic volcanic centers of the Mecca–Madina–Nafud Line, Arabian Peninsula, and the Türkiye–Iran border region. Elevated V S tracks Makran subduction under southeast Iran with near vertical dip. MESWA could be used as a starting model for further improvements, say, using waveforms from in-country seismic networks that are not currently openly available and/or smaller-scale studies targeting a shorter period. The model could be used to improve earthquake hazard studies and nuclear explosion monitoring.

58 GEOSCIENCES↗
DOE OSTI2025

Search for top squarks in final states with many light-flavor jets and 0, 1, or 2 charged leptons in proton-proton collisions at $\sqrt{s}=13$ TeV

Several new physics models including versions of supersymmetry (SUSY) characterized by R-parity violation (RPV) or with additional hidden sectors predict the production of events with top quarks, low missing transverse momentum, and many additional quarks or gluons. The results of a search for top squarks decaying to two top quarks and six additional light-flavor quarks or gluons are reported. The search employs a novel machine learning method for background estimation from control samples in data using decorrelated discriminators. The search is performed using events with 0, 1, or 2 electrons or muons in conjunction with at least six jets. No requirement is placed on the magnitude of the missing transverse momentum. The result is based on a sample of proton-proton collisions at $\sqrt{s}=13$ TeV corresponding to 138 fb −1 of integrated luminosity collected with the CMS detector at the LHC in 2016–2018. With no statistically significant excess of events observed beyond the expected contributions from the standard model, the data are used to determine upper limits on the top squark pair production cross section in the frameworks of RPV and stealth SUSY. Models with top squark masses less than 700 (930) GeV are excluded at 95% confidence level for RPV (stealth) SUSY scenarios.

Hadron-Hadron Scattering↗
DOE OSTI2023

Learning-based demand-supply-coupled charging station location problem for electric vehicle demand management

We present a learning-based, demand-supply-coupled optimization model for the charging station location problem (CSLP), aiming to integrate the concept of electric vehicle (EV) charging demand management into the planning of charging infrastructures. In stage one, a gradient boosting-based learning model is developed to predict the charging demand of a charging station based on 15 defined features. Next, in stage two, a demand–supply-coupled CSLP model is developed to optimize the total charging usage rates of both existing and newly selected charging stations. We design a gradient-based stochastic spatial search algorithm to solve the proposed model. A case study with 6-year charging event data from Kansas City Missouri is performed. Results show that the proposed method can generate satisfactory charging demand predictions, and can increase charging usage rates by 14%, outperforming two benchmark approaches. Furthermore, the results of this research are poised to guide agencies in identifying optimal locations for new charging stations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Generic Pressurized Water Reactor Model for SAPHIRE

Generic Pressurized Water Reactor Model for SAPHIRE This report contains a data dump from a SAPHIRE Generic Pressurized Water Reactor (PWR) model. The intent is to have this information reviewed for export control and classification so that the generic model can be used external to INL. The facility model is not applicable to any existing nuclear reactors. The Generic PWR model does not represent any existing power plant and was created to support research and training purposes. Three distinct types of data are used to create a SAPHIRE risk model: - Event trees representing typical PWR sequences - Fault trees representing generic system performance - Basic events (e.g., component failure information) Where possible, we have taken information from publicly available documents and referenced that information tagged to a specific item.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1978

The occultation of Epsilon Geminorum by Mars as observed at Princeton

Results are reported for two-color (red and blue) high-speed photometric observations of the April 8, 1976, occultation of Epsilon Gem by Mars. The observing system is briefly described, fits to an isothermal atmospheric model of the event are presented, and the blue data are used to derive temperature profiles of the Martian atmosphere in the manner of Wasserman and Veverka (1973). The results are compared with those of Elliot et al. (1977), which were obtained from the NASA Kuiper Airborne Observatory.

Groth, E. J.↗