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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Correlation of full-scale drag predictions with flight measurements on the C-141A aircraft : Phase 2: Wind tunnel tests, analysis, and prediction techniques. Volume 2: Wind tunnel test and basic data

A research program has been conducted to determine the degree of cruise drag correlation on the C-141A aircraft between predictions based on wind tunnel test data, and flight test results. Information is presented on the wind tunnel test program and basic aerodynamic data on the C-141A wind-tunnel model used in the correlation studies.

Macwilkinson, D. G.↗
DOE OSTI2015

Automated contouring error detection based on supervised geometric attribute distribution models for radiation therapy: A general strategy

Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy based on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets were separately employed to test the effectiveness of the proposed contouring error detection strategy. Results: An evaluation tool was implemented to illustrate how the proposed strategy automatically detects the radiation therapy contouring errors for a given patient and provides 3D graphical visualization of error detection results as well. The contouring error detection results were achieved with an average sensitivity of 0.954/0.906 and an average specificity of 0.901/0.909 on the centroid/volume related contouring errors of all the tested samples. As for the detection results on structural shape related contouring errors, an average sensitivity of 0.816 and an average specificity of 0.94 on all the tested samples were obtained. The promising results indicated the feasibility of the proposed strategy for the detection of contouring errors with low false detection rate. Conclusions: The proposed strategy can reliably identify contouring errors based upon inter- and intrastructural constraints derived from clinically approved contours. It holds great potential for improving the radiation therapy workflow. ROC and box plot analyses allow for analytically tuning of the system parameters to satisfy clinical requirements. Future work will focus on the improvement of strategy reliability by utilizing more training sets and additional geometric attribute constraints.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Unsupervised discovery of temporal sequences in high-dimensional datasets, with applications to neuroscience

Identifying low-dimensional features that describe large-scale neural recordings is a major challenge in neuroscience. Repeated temporal patterns (sequences) are thought to be a salient feature of neural dynamics, but are not succinctly captured by traditional dimensionality reduction techniques. Here, we describe a software toolbox—called seqNMF—with new methods for extracting informative, non-redundant, sequences from high-dimensional neural data, testing the significance of these extracted patterns, and assessing the prevalence of sequential structure in data. We test these methods on simulated data under multiple noise conditions, and on several real neural and behavioral data sets. In hippocampal data, seqNMF identifies neural sequences that match those calculated manually by reference to behavioral events. In songbird data, seqNMF discovers neural sequences in untutored birds that lack stereotyped songs. Thus, by identifying temporal structure directly from neural data, seqNMF enables dissection of complex neural circuits without relying on temporal references from stimuli or behavioral outputs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Resistive AC-Coupled Silicon Detectors: principles of operation and first results from a combined analysis of beam test and laser data

This paper presents the principles of operation of Resistive AC-Coupled Silicon Detectors (RSDs) and measurements of the temporal and spatial resolutions using a combined analysis of laser and beam test data. RSDs are a new type of n-in-p silicon sensor based on the Low-Gain Avalanche Diode (LGAD) technology, where the n+ implant has been designed to be resistive, and the read-out is obtained via AC-coupling. The truly innovative feature of RSD is that the signal generated by an impinging particle is shared isotropically among multiple read-out pads without the need for floating electrodes or an external magnetic field. Careful tuning of the coupling oxide thickness and the n+ doping profile is at the basis of the successful functioning of this device. Several RSD matrices with different pad width-pitch geometries have been extensively tested with a laser setup in the Laboratory for Innovative Silicon Sensors in Torino, while a smaller set of devices have been tested at the Fermilab Test Beam Facility with a 120 GeV/c proton beam. The measured spatial resolution ranges between 2.5μm for 70–100 pad-pitch geometry and 17μm with 200–500 matrices, a factor of 10 better than what is achievable in binary read-out (bin size/12). Beam test data show a temporal resolution of ~40ps for 200 μm pitch devices, in line with the best performances of LGAD sensors at the same gain.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1979

Aerodynamic heating to representative SRB and ET protuberances

Heating data and data scaling methods which can be used on representative solid rocket booster and external tank (ET) protuberances are described. Topics covered include (1) ET geometry and heating points; (2) interference heating test data (51A); (3) heat transfer data from tests FH-15 and FH-16; (4) individual protuberance data; and (5) interference heating of paint data from test IH-42. A set of drawings of the ET moldline and protuberances is included.

Engel, C. D.↗
NASA NTRS1976

Physiologic and anti-G suit performance data from YF-16 flight tests

Biomedical data were collected during high-G portions of 11 YF-16 test flights. Test pilots monitored revealed increased respiratory rate and volume, decreased tidal volume, and increased heart rate at higher G levels, with one pilot exhibiting various cardiac arrhythmias. Anti-G suit inflation and pressurization lags varied inversely with G-onset rate, and suit pressurization slope was near the design value.

Gillingham, K. K.↗
NASA NTRS1982

Rotorcraft Blade Mode Damping Identification from Random Responses Using a Recursive Maximum Likelihood Algorithm

An on line technique is presented for the identification of rotor blade modal damping and frequency from rotorcraft random response test data. The identification technique is based upon a recursive maximum likelihood (RML) algorithm, which is demonstrated to have excellent convergence characteristics in the presence of random measurement noise and random excitation. The RML technique requires virtually no user interaction, provides accurate confidence bands on the parameter estimates, and can be used for continuous monitoring of modal damping during wind tunnel or flight testing. Results are presented from simulation random response data which quantify the identified parameter convergence behavior for various levels of random excitation. The data length required for acceptable parameter accuracy is shown to depend upon the amplitude of random response and the modal damping level. Random response amplitudes of 1.25 degrees to .05 degrees are investigated. The RML technique is applied to hingeless rotor test data. The inplane lag regressing mode is identified at different rotor speeds. The identification from the test data is compared with the simulation results and with other available estimates of frequency and damping.

Molusis, J. A.↗
NASA NTRS1995

A review of propeller noise prediction methodology: 1919-1994

This report summarizes a review of the literature regarding propeller noise prediction methods. The review is divided into six sections: (1) early methods; (2) more recent methods based on earlier theory; (3) more recent methods based on the Acoustic Analogy; (4) more recent methods based on Computational Acoustics; (5) empirical methods; and (6) broadband methods. The report concludes that there are a large number of noise prediction procedures available which vary markedly in complexity. Deficiencies in accuracy of methods in many cases may be related, not to the methods themselves, but the accuracy and detail of the aerodynamic inputs used to calculate noise. The steps recommended in the report to provide accurate and easy to use prediction methods are: (1) identify reliable test data; (2) define and conduct test programs to fill gaps in the existing data base; (3) identify the most promising prediction methods; (4) evaluate promising prediction methods relative to the data base; (5) identify and correct the weaknesses in the prediction methods, including lack of user friendliness, and include features now available only in research codes; (6) confirm the accuracy of improved prediction methods to the data base; and (7) make the methods widely available and provide training in their use.

Metzger, F. Bruce↗
NASA NTRS2006

Cryogenic Tank Modeling for the Saturn AS-203 Experiment

A computational fluid dynamics (CFD) model is developed for the Saturn S-IVB liquid hydrogen (LH2) tank to simulate the 1966 AS-203 flight experiment. This significant experiment is the only known, adequately-instrumented, low-gravity, cryogenic self pressurization test that is well suited for CFD model validation. A 4000-cell, axisymmetric model predicts motion of the LH2 surface including boil-off and thermal stratification in the liquid and gas phases. The model is based on a modified version of the commercially available FLOW3D software. During the experiment, heat enters the LH2 tank through the tank forward dome, side wall, aft dome, and common bulkhead. In both model and test the liquid and gases thermally stratify in the low-gravity natural convection environment. LH2 boils at the free surface which in turn increases the pressure within the tank during the 5360 second experiment. The Saturn S-IVB tank model is shown to accurately simulate the self pressurization and thermal stratification in the 1966 AS-203 test. The average predicted pressurization rate is within 4% of the pressure rise rate suggested by test data. Ullage temperature results are also in good agreement with the test where the model predicts an ullage temperature rise rate within 6% of the measured data. The model is based on first principles only and includes no adjustments to bring the predictions closer to the test data. Although quantitative model validation is achieved or one specific case, a significant step is taken towards demonstrating general use of CFD for low-gravity cryogenic fluid modeling.

Grayson, Gary D.↗
DOE OSTI2019

Multi-Formalism Modeling for Disaster Resilience, Forecasting, and Response

Disaster response preparedness, risk mitigation, and effective post-event response are critical for national security, public health, and economic integrity. For areas impacted by extreme events, timely and accurate impact assessments of lifeline infrastructures are critical. Traditional disaster management and situational awareness platforms are not capable of handling the massive influx of available information from traditional and non-traditional sources. Next-generation analytic assessment approaches, where use of dynamically sourced, heterogeneous data with near real-time availability are integrated into a continually-updated analytics framework. The objective of this research was to develop a foundational multi-formalism modeling platform to integrate novel data sources for use in improving situational awareness after a disaster event. Specifically, to 1) provide an architecture for machine-learning based data fusion various multi-sensor datasets; 2) classify, geolocate, and temporally bin novel data sources for use in spatially-enabled machine-learning based data fusion; and 3) derive confidence-based observation data with machine-learning based prediction to fill spatial and temporal observation gaps. This project developed a reusable cloud-based pipeline architecture for ingesting, storing, and analyzing relevant data, executing a range of deep-learning models, and visualize the information geographically. The pipeline development was informed by previous PNNL investments (StreamKit) and built upon leading-edge technologies consisting of: 1) a raw datastore; 2) a data enrichment pipeline with custom and third-party analytics; 3) enriched data storage; and 4) a custom UI to display the enriched data. Machine learning/deep learning models were selected and tested to classify social media images for relevancy and presence of flood waters. Our custom trained relevance models were run on a validation dataset and the overall accuracy of the relevance classifiers ranged from 65% to 90%. We found that convolutional neural network (CNN) models were both faster and more accurate than more traditional machine learning models. We applied the relevance classifier to remove non-relevant images and then undertook a limited training of CNN models to detect flood on ~1,800 labeled images. The testing accuracy of the flood detection models were ~88%. To improve the geographic location of both social media and oblique aerial images we tested a multi-step workflow built on a pre-trained deep-learning model. To identify similarity features from test and reference scenes, we applied the Xception and Faiss models to a set of test images with inaccurate spatial locations, as well and precisely-located reference scenes from the general area. Matching reference scenes to the test scenes with the closest similarity index had limited success in improving the precision of test scene location and additional methods have been identified for testing. Data fusion between authoritative geographic data (satellite imaging) and non-authoritative crowdsourced data is an underlying theme throughout this research and methods are tested bring these data to a common geographic form through feature matching and transformations. The automated extraction of supporting information for disaster response from oblique aerial images or ground-level social media images is accomplished through semantic image segmentation and transformation. The non-authoritative data are used to validate the authoritative data collections and processing and optionally, t+0 flood models. In addition, the common form geographic data are combined with other static landscape features to develop spatially-explicit training vectors used in deep generative statistical inference models to develop complex non-linear relationships in static and dynamic data and ultimately derive a spatially continuous and probabilistic assessment of flood damage with the event domain.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

Impact properties of irradiated HT9 from the fuel duct of FFTF

This paper reports Charpy impact test data for the ACO-3 duct material (HT9) from the Fast Flux Test Facility (FFTF) and its archive material. Irradiation doses for the specimens were in the range of 3– 148 dpa and irradiation temperatures in the range of 378–504 *C. The impact tests were performed for the small V-notched Charpy specimens with dimensions of 3 * 4 * 27 mm at an impact speed of 3.2 m/s in a 25 J capacity machine. Irradiation lowered the upper-shelf energy (USE) and increased the transition temperatures significantly. The shift of ductile–brittle transition temperatures (DDBTT) was greater after relatively low temperature irradiation. The USE values were in the range of 5.5–6.7 J before irradiation and decreased to the range of 2–5 J after irradiation. Lower USEs were measured for lower irradiation temperatures and specimens with T-L orientation. The dose dependences of transition temperature and USE were not significant because of the radiation effect on impact behavior nearly saturated at the lowest dose of about 3 dpa. A comparison showed that the lateral expansion of specimens showed a linear correlation with absorbed impact energy, but with large scatter in the results. Size effect was also discussed to clarify the differences in the impact property data from subsize and standard specimens as well as to provide a basis for comparison of data from different specimens. The USE and DDBTT data from different studies were compared.

Byun, Thak Sang↗
DOE OSTI2021

D2U: Data Driven User Emulation for the Enhancement of Cyber Testing, Training, and Data Set Generation

Whether testing intrusion detection systems, conducting training exercises, or creating data sets to be used by the broader cybersecurity community, realistic user behavior is a critical component of a cyber range. Existing methods either rely on network level data or replay recorded user actions to approximate real users in a network. Our work is the first to produce generative models trained on actual user data (sequences of application usage) collected on endpoints. Once trained to the user's behavioral data, these models can generate novel sequences of actions %that appear to come from the same distribution as the training data. These sequences of actions are then fed to our custom software via configuration files, which replicate those behaviors on end devices. Notably, our models are platform agnostic and could generate behavior data for any emulation software package. In this paper we present our model generation process, software architecture, and an initial evaluation of the fidelity of our models. Our software is currently deployed in a cyber range to help evaluate the efficacy of defensive cyber technologies. We suggest additional ways that the cyber community as a whole can benefit from more realistic user behavior emulation. The data used to train our model, as well as sample configuration files produced by the model, are available at [redacted].

Oesch, T↗
NASA NTRS2005

Integrated Structural Analysis and Test Program

An integrated structural-analysis and structure-testing computer program is being developed in order to: Automate repetitive processes in testing and analysis; Accelerate pre-test analysis; Accelerate reporting of tests; Facilitate planning of tests; Improve execution of tests; Create a vibration, acoustics, and shock test database; and Integrate analysis and test data. The software package includes modules pertaining to sinusoidal and random vibration, shock and time replication, acoustics, base-driven modal survey, and mass properties and static/dynamic balance. The program is commanded by use of ActiveX controls. There is minimal need to generate command lines. Analysis or test files are selected by opening a Windows Explorer display. After selecting the desired input file, the program goes to a so-called analysis data process or test data process, depending on the type of input data. The status of the process is given by a Windows status bar, and when processing is complete, the data are reported in graphical, tubular, and matrix form.

Kaufman, Daniel↗
DOE OSTI2015

Tensile and Fatigue Testing and Material Hardening Model Development for 508 LAS Base Metal and 316 SS Similar Metal Weld under In-air and PWR Primary Loop Water Conditions

This report provides an update on an assessment of environmentally assisted fatigue for light water reactor components under extended service conditions. This report is a deliverable in September 2015 under the work package for environmentally assisted fatigue under DOE’s Light Water Reactor Sustainability program. In an April 2015 report we presented a baseline mechanistic finite element model of a two-loop pressurized water reactor (PWR) for systemlevel heat transfer analysis and subsequent thermal-mechanical stress analysis and fatigue life estimation under reactor thermal-mechanical cycles. In the present report, we provide tensile and fatigue test data for 508 low-alloy steel (LAS) base metal, 508 LAS heat-affected zone metal in 508 LAS–316 stainless steel (SS) dissimilar metal welds, and 316 SS-316 SS similar metal welds. The test was conducted under different conditions such as in air at room temperature, in air at 300 oC, and under PWR primary loop water conditions. Data are provided on materials properties related to time-independent tensile tests and time-dependent cyclic tests, such as elastic modulus, elastic and offset strain yield limit stress, and linear and nonlinear kinematic hardening model parameters. The overall objective of this report is to provide guidance to estimate tensile/fatigue hardening parameters from test data. Also, the material models and parameters reported here can directly be used in commercially available finite element codes for fatigue and ratcheting evaluation of reactor components under in-air and PWR water conditions.

316 Stainless Steel↗
NASA NTRS1994

Spacecraft Data Simulator for the test of level zero processing systems

The Microelectronic Systems Branch (MSB) at Goddard Space Flight Center (GSFC) has developed a Spacecraft Data Simulator (SDS) to support the development, test, and verification of prototype and production Level Zero Processing (LZP) systems. Based on a disk array system, the SDS is capable of generating large test data sets up to 5 Gigabytes and outputting serial test data at rates up to 80 Mbps. The SDS supports data formats including NASA Communication (Nascom) blocks, Consultative Committee for Space Data System (CCSDS) Version 1 & 2 frames and packets, and all the Advanced Orbiting Systems (AOS) services. The capability to simulate both sequential and non-sequential time-ordered downlink data streams with errors and gaps is crucial to test LZP systems. This paper describes the system architecture, hardware and software designs, and test data designs. Examples of test data designs are included to illustrate the application of the SDS.

Shi, Jeff↗
NASA NTRS2023

First Principles Modeling of the Thermal Amine Scrubber Flight Experiment’s Chemical Performance

The removal of atmospheric CO2 from a spacecraft is of particular importance to NASA’s mission, and is an area of continual study and technological advancement. One of the more recent advancements has been with reusable sorbents being regenerated with a combination of heat and vacuum. One such technology is the Thermal Amine Scrubber (TAS) flight experiment on the ISS, though several others are currently flying or preparing to fly. A model was created of the TAS to predict chemical performance, using fundamental chemistry and physics based on principles rather than empirical relations. Since the physical laws are true across all conditions, such a model enables greater model accuracy outside the bounds of test data, and allows for virtual testing of the hardware at conditions that are prohibitively difficult or expensive to actually test. This paper details the model’s development, operation, and correlation to data from the flight unit. The model is then compared to a data set taken from the flight unit under different flow, CO2 partial pressure, and bed configuration conditions, resulting in only a 2% error. The equations and principles laid forth in this paper are applicable to a wide range of thermally regenerated sorbents, and additional models of a similar nature would allow for potentially the most straightforward and direct method of comparison of technologies available to date.

CO2 removal↗