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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Neural Network Modeling of UH-60A Pilot Vibration

Full-scale flight-test pilot floor vibration is modeled using neural networks and full-scale wind tunnel test data for low speed level flight conditions. Neural network connections between the wind tunnel test data and the tlxee flight test pilot vibration components (vertical, lateral, and longitudinal) are studied. Two full-scale UH-60A Black Hawk databases are used. The first database is the NASMArmy UH-60A Airloads Program flight test database. The second database is the UH-60A rotor-only wind tunnel database that was acquired in the NASA Ames SO- by 120- Foot Wind Tunnel with the Large Rotor Test Apparatus (LRTA). Using neural networks, the flight-test pilot vibration is modeled using the wind tunnel rotating system hub accelerations, and separately, using the hub loads. The results show that the wind tunnel rotating system hub accelerations and the operating parameters can represent the flight test pilot vibration. The six components of the wind tunnel N/rev balance-system hub loads and the operating parameters can also represent the flight test pilot vibration. The present neural network connections can significandy increase the value of wind tunnel testing.

Kottapalli, Sesi↗
NASA NTRS1988

Parameter identification of material constants in a composite shell structure

One of the basic requirements in engineering analysis is the development of a mathematical model describing the system. Frequently comparisons with test data are used as a measurement of the adequacy of the model. An attempt is typically made to update or improve the model to provide a test verified analysis tool. System identification provides a systematic procedure for accomplishing this task. The terms system identification, parameter estimation, and model correlation all refer to techniques that use test information to update or verify mathematical models. The goal of system identification is to improve the correlation of model predictions with measured test data, and produce accurate, predictive models. For nonmetallic structures the modeling task is often difficult due to uncertainties in the elastic constants. A finite element model of the shell was created, which included uncertain orthotropic elastic constants. A modal survey test was then performed on the shell. The resulting modal data, along with the finite element model of the shell, were used in a Bayes estimation algorithm. This permitted the use of covariance matrices to weight the confidence in the initial parameter values as well as confidence in the measured test data. The estimation procedure also employed the concept of successive linearization to obtain an approximate solution to the original nonlinear estimation problem.

Martinez, David R.↗
DOE OSTI2025

BatteryPro: A Python Toolkit for Battery Data Analysis and Machine Learning Predictions

Analyzing battery test data for research & development can be time-consuming since battery tests often run on the order of months to years, generating large volumes of data. BatteryPro is a comprehensive Python package and software designed to facilitate advanced analysis and performance predictions for battery test data. Developed for battery researchers, it supports data types from widely used battery testing instruments, including MACCOR and Biologic cycling systems. The software provides a variety of tools for extracting and plotting key battery parameters such as time, voltage, capacity, current, and pressure. In addition to its extensive data analysis capabilities, BatteryPro features a dedicated machine learning module that employs a Bayesian Gaussian Mixture Model (GMM) to predict battery performance and degradation. Users can generate synthetic capacity fade data, calculate fade metrics, and leverage predictive models to forecast long-term battery behavior. The software's graphical user interface (GUI) enhances usability, allowing researchers to upload, merge, and analyze multiple data files with full customizability. The GUI also supports machine learning predictions, enabling users to fit models and make predictions based on selected data and parameters. BatteryPro is built using QtDesigner, scikit-learn, matplotlib, and pandas, ensuring a high level of customization, flexibility, and accuracy in battery data analysis. This tool aims to empower researchers with the ability to perform detailed battery analysis and make informed predictions, ultimately advancing the field of battery research.

25 - ENERGY STORAGE↗
NASA NTRS2020

SEE Test and Data Analysis for Complex FPGA Systems

Critical space applications require knowledge of single event upset (SEU) susceptibility (mission survivability). Generic SEU test and analysis techniques do not provide adequate data for survivability analysis. This presentation provides information on how to: (1) Investigate (test for) SEU susceptibilities of tactical (mission specific) designs that are implemented in a SRAM-based FPGA; and (2) Analyze SEU cross-sections for use in survivability prediction.

Berg, Melanie↗
NASA NTRS2014

A Super-Resolution Algorithm for Enhancement of FLASH LIDAR Data: Flight Test Results

This paper describes the results of a 3D super-resolution algorithm applied to the range data obtained from a recent Flash Lidar helicopter flight test. The flight test was conducted by the NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) project over a simulated lunar terrain facility at NASA Kennedy Space Center. ALHAT is developing the technology for safe autonomous landing on the surface of celestial bodies: Moon, Mars, asteroids. One of the test objectives was to verify the ability of 3D super-resolution technique to generate high resolution digital elevation models (DEMs) and to determine time resolved relative positions and orientations of the vehicle. 3D super-resolution algorithm was developed earlier and tested in computational modeling, and laboratory experiments, and in a few dynamic experiments using a moving truck. Prior to the helicopter flight test campaign, a 100mX100m hazard field was constructed having most of the relevant extraterrestrial hazard: slopes, rocks, and craters with different sizes. Data were collected during the flight and then processed by the super-resolution code. The detailed DEM of the hazard field was constructed using independent measurement to be used for comparison. ALHAT navigation system data were used to verify abilities of super-resolution method to provide accurate relative navigation information. Namely, the 6 degree of freedom state vector of the instrument as a function of time was restored from super-resolution data. The results of comparisons show that the super-resolution method can construct high quality DEMs and allows for identifying hazards like rocks and craters within the accordance of ALHAT requirements.

Bulyshev, Alexander↗
NASA NTRS1984

Data from tests of a R4 airfoil in the Langley 0.3-meter transonic cryogenic tunnel

Aerodynamic data for the DFVLR R4 airfoil are presented in both graphic and tabular form. The R4 was tested in the Langley 0.3-Meter Transonic Cryogenic Tunnel (TCT) at Mach number from 0.60 to 0.78 at angles of attack from -2.0 to 8.0 degrees. The airfoil was tested at Reynolds numbers of 4, 6, 10, 15, 30, and 40 million based on the 152.32 mm chord.

Jenkins, R. V.↗
NASA NTRS2011

Approaches for Tensile Testing of Braided Composites

For angleply composites, lamina tension and compression strengths are commonly determined by applying classical lamination theory to test data obtained from testing of angleply composite specimens. For textile composites such as 2D triaxial braids, analysis is more complex and standard test methods do not always yield reliable strength measurements. This paper describes recent research focused on development of more reliable tensile test methods for braided composites and presents preliminary data for various approaches. The materials investigated in this work have 0deg+/-60 2D triaxial braid architecture with nearly equal fiber volume fraction in each of the three fiber directions. Flat composite panels are fabricated by resin transfer molding (RTM) using six layers of the braided preform aligned along the 0deg fiber direction. Various epoxy resins are used as matrix materials. Single layer panels are also fabricated in order to examine local variations in deformation related to the braid architecture. Specimens are cut from these panels in the shape of standard straight-sided coupons, an alternative bowtie geometry, and an alternative notched geometry. Axial tensile properties are measured using specimens loaded along the 0deg fiber direction. Transverse tensile properties are measured using specimens loaded perpendicular to the 0deg fibers. Composite tubes are also fabricated by RTM. These tubes are tested by internal pressurization using a soft rubbery material sealed between the inside diameter of the tube and the load fixtures. The ends of the tube are unconstrained, so the primary load is in the hoop direction. Tubes are fabricated with the 0deg fibers aligned along the tube axis by overbraiding the preform on a mandrel. Since the loading is in the hoop direction, testing of the overbraided tube provides a measure of transverse tensile strength. Previous work has indicated that straight-sided coupons yield a transverse tensile strength that is much lower than the expected material strength because of premature edge-initiated failure. Full-field strain measured during transverse tensile tests clearly showed accumulation of edge damage prior to failure. In the current work, high speed video and testing of single layer specimens are used to investigate potential failure mechanisms in more detail. High speed video clearly shows the edge initiation in six layer transverse tensile test coupons. Specimens with the bowtie geometry and the notched geometry minimize this edge effect and yield significantly higher transverse tensile strength values compared to the straight-sided coupons. However, bowtie and notched specimens geometries are not ideal because of the non-uniform stress and strain fields in the region of failure. Testing of tubes using internal pressurization eliminates edge-initiated failure and provides a more uniform state of stress and strain. Preliminary results indicate that bowtie, notched, and tube specimens yield comparable values for transverse tensile strength and that these values are much higher than the strength measured using a straight-sided coupon.

Roberts, Gary D.↗
NASA NTRS2005

Model for Vortex Ring State Influence on Rotorcraft Flight Dynamics

The influence of vortex ring state (VRS) on rotorcraft flight dynamics is investigated, specifically the vertical velocity drop of helicopters and the roll-off of tiltrotors encountering VRS. The available wind tunnel and flight test data for rotors in vortex ring state are reviewed. Test data for axial flow, non-axial flow, two rotors, unsteadiness, and vortex ring state boundaries are described and discussed. Based on the available measured data, a VRS model is developed. The VRS model is a parametric extension of momentum theory for calculation of the mean inflow of a rotor, hence suitable for simple calculations and real-time simulations. This inflow model is primarily defined in terms of the stability boundary of the aircraft motion. Calculations of helicopter response during VRS encounter were performed, and good correlation is shown with the vertical velocity drop measured in flight tests. Calculations of tiltrotor response during VRS encounter were performed, showing the roll-off behavior characteristic of tiltrotors. Hence it is possible, using a model of the mean inflow of an isolated rotor, to explain the basic behavior of both helicopters and tiltrotors in vortex ring state.

Johnson, Wayne↗
NASA NTRS2004

Model for Vortex Ring State Influence on Rotorcraft Flight Dynamics

The influence of vortex ring state (VRS) on rotorcraft flight dynamics is investigated, specifically the vertical velocity drop of helicopters and the roll-off of tiltrotors encountering VRS. The available wind tunnel and flight test data for rotors in vortex ring state are reviewed. Test data for axial flow, nonaxial flow, two rotors, unsteadiness, and vortex ring state boundaries are described and discussed. Based on the available measured data, a VRS model is developed. The VRS model is a parametric extension of momentum theory for calculation of the mean inflow of a rotor, hence suitable for simple calculations and real-time simulations. This inflow model is primarily defined in terms of the stability boundary of the aircraft motion. Calculations of helicopter response during VRS encounter were performed, and good correlation is shown with the vertical velocity drop measured in flight tests. Calculations of tiltrotor response during VRS encounter were performed, showing the roll-off behavior characteristic of tiltrotors. Hence it is possible, using a model of the mean inflow of an isolated rotor, to explain the basic behavior of both helicopters and tiltrotors in vortex ring state.

VORTEX RING STATE↗
NASA NTRS2006

Structural Analysis and Test Comparison of a 20-Meter Inflation-Deployed Solar Sail

Under the direction of the NASA In-Space Propulsion Technology Office, the team of L Garde, NASA Jet Propulsion Laboratory, Ball Aerospace, and NASA Langley Research Center has been developing a scalable solar sail configuration to address NASA s future space propulsion needs. Prior to a flight experiment of a full-scale solar sail, a comprehensive test program was implemented to advance the technology readiness level of the solar sail design. These tests consisted of solar sail component, subsystem, and sub-scale system ground tests that simulated the aspects of the space environment such as vacuum and thermal conditions. In July 2005, a 20-m four-quadrant solar sail system test article was tested in the NASA Glenn Research Center s Space Power Facility to measure its static and dynamic structural responses. Key to the maturation of solar sail technology is the development of validated finite element analysis (FEA) models that can be used for design and analysis of solar sails. A major objective of the program was to utilize the test data to validate the FEA models simulating the solar sail ground tests. The FEA software, ABAQUS, was used to perform the structural analyses to simulate the ground tests performed on the 20-m solar sail test article. This paper presents the details of the FEA modeling, the structural analyses simulating the ground tests, and a comparison of the pretest and post-test analysis predictions with the ground test results for the 20-m solar sail system test article. The structural responses that are compared in the paper include load-deflection curves and natural frequencies for the beam structural assembly and static shape, natural frequencies, and mode shapes for the solar sail membrane. The analysis predictions were in reasonable agreement with the test data. Factors that precluded better correlation of the analyses and the tests were unmeasured initial conditions in the test set-up.

Sleight, David W.↗
NASA NTRS2005

Rr2004 Test1 and 4 Data Analysis

Test 1 data analysis for Kydex, Royal Blue Cotton, and Silicon along with test 4 data analysis for Raychem Electrical Wire is presented.

Beeson, Harold D.↗
DOE OSTI2024

Initial Alloy 709 constitutive models for use with the ASME design by inelastic analysis and EPP+SMT design methods

This report details a preliminary inelastic constitutive model describing the behavior of Alloy 709. This model will serve two purposes: (1) integration into Nonmandatory Appendix HBB-Z of the ASME Boiler & Pressure Vessel Code Section III, Division 5 and (2) extrapolating cyclic test data to difficult to measure conditions for formulating improved creep-fatigue design methods. For both applications, the model must accurately capture the material behavior across a wide range of temperatures and a variety of test conditions, both monotonic and cyclic. For this purpose we adopt a universal model form under consideration to standardize the description of high temperature constitutive models in the ASME Code. This report briefly restates that model form and how we calibrate the model against the test data, summarizes the test database, and validates the final, trained model by comparison to the experimental tests.

36 MATERIALS SCIENCE↗
DOE OSTI2022

AN ESTIMATE OF SPENT NUCLEAR FUEL MECHANICAL LOADS IN THE GENERAL 30 CM PACKAGE DROP SCENARIO

The US Department of Energy Spent Fuel and Waste Science and Technology (SFWST) program is performing research to determine the mechanical loading conditions applied to spent nuclear fuel (SNF) during normal conditions of transport to inform mechanical tests of SNF and close an important knowledge gap related to the practical disposition of SNF in the US. Researchers at Pacific Northwest National Laboratory (PNNL) have completed an extensive finite element study to characterize and estimate the potential mechanical loads on SNF during a hypothetical 30 cm drop of an SNF transportation package. This modeling study is validated with test data collected by the SFWST program during a physical test campaign that included one-third scale package drop tests and full-scale single fuel assembly drop tests. The test campaign was led by Sandia National Laboratories (SNL) and included international collaboration with Equipos Nucleares S.A, S.M.E (ENSA) and Bundesanstalt für Materialforschung und -prüfung (BAM). The key contribution of the modeling study is to go beyond the limitations of the limited number of physical tests to estimate the impact response to variations in impact angle, initial gap conditions, fuel assembly design, burnup and other parameters that affect the mechanical loads. The methodology of this study included a classic parametric study to calculate the impact response of highly detailed fuel assemblies over many combinations of parameters. Models of a 17x17 pressurized water reactor fuel assembly and a generic 10x10 boiling water reactor fuel assembly were both used in this study to cover the major fuel assembly types in the US inventory. Over 2,000 impact responses were calculated. The results of the parametric study were evaluated using traditional methods and basic statistics. The results were also used to construct a damage model using multiple nonlinear regression techniques to predict the mechanical loads over the full range of all input parameters. The damage model was found to work very well for all impact angle cases where the cask came to rest on its side. It was concluded that end drop cases where the cask remained vertical (instead of tipping over onto its side) were not sufficiently characterized by the current set of parametric study cases to include in the damage model, but it was not a priority to fully investigate that range because the highest mechanical loads were observed in the broader range of side impact cases. This modeling work provides sufficient insight into the mechanical loads on SNF during a hypothetical 30 cm package drop that, when considered along with the physical test data collected by the SNL-led team, the SFSWT program can consider the knowledge gap closed.

Klymyshyn, Nicholas A.↗
NASA NTRS1975

Detailed requirements document for the Interactive Financial Management System (IFMS), volume 1

The detailed requirements for phase 1 (online fund control, subauthorization accounting, and accounts receivable functional capabilities) of the Interactive Financial Management System (IFMS) are described. This includes information on the following: systems requirements, performance requirements, test requirements, and production implementation. Most of the work is centered on systems requirements, and includes discussions on the following processes: resources authority, allotment, primary work authorization, reimbursable order acceptance, purchase request, obligation, cost accrual, cost distribution, disbursement, subauthorization performance, travel, accounts receivable, payroll, property, edit table maintenance, end-of-year, backup input. Other subjects covered include: external systems interfaces, general inquiries, general report requirements, communication requirements, and miscellaneous. Subjects covered under performance requirements include: response time, processing volumes, system reliability, and accuracy. Under test requirements come test data sources, general test approach, and acceptance criteria. Under production implementation come data base establishment, operational stages, and operational requirements.

Dodson, D. B.↗
NASA NTRS2010

Northrop Grumman TR202 LOX/LH2 Deep Throttling Engine Technology Project Status

NASA's Propulsion and Cryogenic Advanced Development (PCAD) project is currently developing enabling propulsion technologies in support of future lander missions. To meet lander requirements, several technical challenges need to be overcome, one of which is the ability for the descent engine(s) to operate over a deep throttle range with cryogenic propellants. To address this need, PCAD has enlisted Northrop Grumman Aerospace Systems (NGAS) in a technology development effort associated with the TR202 engine. The TR202 is a LOX/LH2 expander cycle engine driven by independent turbopump assemblies and featuring a variable area pintle injector similar to the injector used on the TR200 Apollo Lunar Module Descent Engine (LMDE). Since the Apollo missions, NGAS has continued to mature deep throttling pintle injector technology. The TR202 program has completed two series of pintle injector testing. The first series of testing used ablative thrust chambers and demonstrated igniter operation as well as stable performance at discrete points throughout the designed 10:1 throttle range. The second series was conducted with calorimeter chambers and demonstrated injector performance at discrete points throughout the throttle range as well as chamber heat flow adequate to power an expander cycle design across the throttle range. This paper provides an overview of the TR202 program, describing the different phases and key milestones. It describes how test data was correlated to the engine conceptual design. The test data obtained has created a valuable database for deep throttling cryogenic pintle technology, a technology that is readily scalable in thrust level.

Gromski, Jason↗
NASA NTRS2015

Nonlinear Analysis and Preliminary Testing Results of a Hybrid Wing Body Center Section Test Article

A large test article was recently designed, analyzed, fabricated, and successfully tested up to the representative design ultimate loads to demonstrate that stiffened composite panels with through-the-thickness reinforcement are a viable option for the next generation large transport category aircraft, including non-conventional configurations such as the hybrid wing body. This paper focuses on finite element analysis and test data correlation of the hybrid wing body center section test article under mechanical, pressure and combined load conditions. Good agreement between predictive nonlinear finite element analysis and test data is found. Results indicate that a geometrically nonlinear analysis is needed to accurately capture the behavior of the non-circular pressurized and highly-stressed structure when the design approach permits local buckling.

Przekop, Adam↗
NASA NTRSDate not supplied

QuantifyML: How good is my machine learning model?

This paper presents an approach, QuantifyML, which employs model counting to assess the learnability and robustness of machine learning models. Typically the efficacy of machine learning models is determined by computing their accuracy statistically on test data sets. However, this may be misleading, if the test data is not representative of the problem that is being studied. Further, two different models may have the same accuracy on a given data set, measured statistically, but may be very different in their behavior on unseen data. Also, models with high accuracy could have poor adversarial robustness. In QuantifyML, our goal is to precisely quantify the extent to which machine learning models have learned and generalized from the given data. In QuantifyML, a trained model is translated into a C program, which is fed to the CBMC model checking tool to produce a formula in Conjunctive Normal Form (CNF), which in turn is analyzed with state-of-the-art model counters to efficiently obtain precise counts w.r.t different outputs. QuantifyML enables i) evaluating the learnability of models by comparing the counts for the outputs to ground truth, expressed as logical predicates (if available), ii) comparing the performance of different models that may be built with different machine learning algorithms (e.g., decision-trees vs. neural networks), and iii) quantifying the robustness of trained models around given inputs. Our evaluation demonstrates these applications of QuantifyML on decision trees and neural networks trained to learn relational properties of graphs, for which we know the ground truth, and to perform image classification, for which we do not have the ground truth, but we can quantify local robustness.

Deep Neural Networks↗