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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Land Product Validation

The "Land Product Validation" (LPV) subgroup of the Committee on Earth Observing Satellites Working on Group on Calibration and Validation was formed in 2000. Goals of the LPV subgroup are: (1)to increase the quality and economy of global satellite product validation via developing and promoting international standards and protocols for field sampling, scaling, error budgeting, data exchange and product evaluation, and (2) to advocate mission-long validation programs for current and future earth observing satellites. First-round LPV activities will compliment the research themes of the Global Observation of Forest Cover (GOFC) program, which are: biophysical products, fire/burn scar detection, and land cover mapping. Meetings in June and July of 2001 focused on the first two themes. The GOFC "Forest Cover Characteristics and Changes" meeting provides a forum to initiate LPV activities related to Land Cover. The presentation will start with a summary of the LPV subgroup and its current activities. This will be followed by an overview of areas for potential coordination between the LPV and the GOFC Land Cover Theme.

Morisette, Jeffrey↗
NASA NTRS2010

Phased Array Noise Source Localization Measurements Made on a Williams International FJ44 Engine

A 48-microphone planar phased array system was used to acquire noise source localization data on a full-scale Williams International FJ44 turbofan engine. Data were acquired with the array at three different locations relative to the engine, two on the side and one in front of the engine. At the two side locations the planar microphone array was parallel to the engine centerline; at the front location the array was perpendicular to the engine centerline. At each of the three locations, data were acquired at eleven different engine operating conditions ranging from engine idle to maximum (take off) speed. Data obtained with the array off to the side of the engine were spatially filtered to separate the inlet and nozzle noise. Tones occurring in the inlet and nozzle spectra were traced to the low and high speed spools within the engine. The phased array data indicate that the Inflow Control Device (ICD) used during this test was not acoustically transparent; instead, some of the noise emanating from the inlet reflected off of the inlet lip of the ICD. This reflection is a source of error for far field noise measurements made during the test. The data also indicate that a total temperature rake in the inlet of the engine is a source of fan noise.

Podboy, Gary G.↗
NASA NTRS2019

Alignment and Test of the Wide Field Infrared Survey Telescope (WFIRST) Engineering Design Unit (EDU) Grism

The WFIRST wide field instrument (WFI) includes a slitless spectrometer, which plays an important role in the WFIRST mission for the survey of emission-line galaxies. WFI is building engineering design and environmental test (EDU and ETU) units to reduce risk for the flight grism unit. We report here on successful build and test of the EDU grism. The four-element EDU grism consists of two prism elements and two diffractive elements that provide R700 dispersion. The elements were fabricated with alignment fiducials and integral flats to allow opto-mechanical alignment in six-degrees of freedom. Each element in turn, was installed onto a hexapod and positioned to its nominal orientation relative to the grism deck, then bonded into individual cells. Alignment measurements were performed in situ using theodolites to set tip/tilt and a Micro-vu non-contact Multisensor Measurement System was used to set despace, decenter and clocking of each element using the hexapod. After opto-mechanical alignment, the grism wavefront was measured using an Infrared ZYGO interferometer at various field points extending over a 20 by 14- degree (local) field of view. Using modeled alignment sensitivities, we determined the alignment correction required on our Element 2 prism compensator and successfully minimized the field dependent wavefront error and confocality. This paper details the alignment and testing of the EDU grism at ambient and cold operating temperatures.

Hagopian, John↗
NASA NTRSDate not supplied

Enhanced Simulation Techniques in Predicting Sonic Boom Loudness Using CFD

This paper outlines advancements in predicting sonic boom loudness within the Launch, Ascent, and Vehicle Aerodynamics (LAVA) computational framework. Traditionally, a two step process consisting of a steady state computational fluid dynamics problem for near-field analysis and a far-field propagation solver for calculation of loudness metrics has been used. Improvements to this process made in this work include utilizing a high-order space marching method for mid-field computations, developing a novel output-based mesh adaptation method targeting error in near-field pressure sig-natures, and developing a robust scripting system using curvilinear grids to increase robustness and simplify the process of running large databases of simulation cases. These advancements are detailed and applied to the simulation of the X-59, presenting comparative cost and timing analyses between the prior two step workflow and the current three step procedure. We achieve increased accuracy and robustness for loudness predictions with at least a50%computational cost reduction.

CST↗
DOE OSTI2014

MATCHED-INDEX-OF-REFRACTION FLOW FACILITY FOR FUNDAMENTAL AND APPLIED RESEARCH

Significant challenges face reactor designers with regard to thermal hydraulic design and associated modeling for advanced reactor concepts. Computational thermal hydraulic codes solve only a piece of the core. There is a need for a whole core dynamics system code with local resolution to investigate and understand flow behavior with all the relevant physics and thermo-mechanics. The matched index of refraction (MIR) flow facility at Idaho National Laboratory (INL) has a unique capability to contribute to the development of validated computational fluid dynamics (CFD) codes through the use of state-of-the-art optical measurement techniques, such as Laser Doppler Velocimetry (LDV) and Particle Image Velocimetry (PIV). PIV is a non-intrusive velocity measurement technique that tracks flow by imaging the movement of small tracer particles within a fluid. At the heart of a PIV calculation is the cross correlation algorithm, which is used to estimate the displacement of particles in some small part of the image over the time span between two images. Generally, the displacement is indicated by the location of the largest peak. To quantify these measurements accurately, sophisticated processing algorithms correlate the locations of particles within the image to estimate the velocity (Ref. 1). Prior to use with reactor deign, the CFD codes have to be experimentally validated, which requires rigorous experimental measurements to produce high quality, multi-dimensional flow field data with error quantification methodologies. Computational thermal hydraulic codes solve only a piece of the core. There is a need for a whole core dynamics system code with local resolution to investigate and understand flow behavior with all the relevant physics and thermo-mechanics. Computational techniques with supporting test data may be needed to address the heat transfer from the fuel to the coolant during the transition from turbulent to laminar flow, including the possibility of an early laminarization of the flow (Refs. 2 and 3) (laminarization is caused when the coolant velocity is theoretically in the turbulent regime, but the heat transfer properties are indicative of the coolant velocity being in the laminar regime). Such studies are complicated enough that computational fluid dynamics (CFD) models may not converge to the same conclusion. Thus, experimentally scaled thermal hydraulic data with uncertainties should be developed to support modeling and simulation for verification and validation activities. The fluid/solid index of refraction matching technique allows optical access in and around geometries that would otherwise be impossible while the large test section of the INL system provides better spatial and temporal resolution than comparable facilities. Benchmark data for assessing computational fluid dynamics can be acquired for external flows, internal flows, and coupled internal/external flows for better understanding of physical phenomena of interest. The core objective of this study is to describe MIR and its capabilities, and mention current development areas for uncertainty quantification, mainly the uncertainty surface method and cross-correlation method. Using these methods, it is anticipated to establish a suitable approach to quantify PIV uncertainty for experiments performed in the MIR.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1984

A generalization of the near-optimum binary coherent state receiver concept

The structure of a maximum a posteriori decoder is derived for binary optical fields processed according to Kennedy's near-optimum scheme, but operating in the presence of random optical phase-error and interfering background fields. An exact expression is found for the error probability, and examples to illustrate decoder performance under various operating conditions of interest are provided.

Vilnrotter, V. A.↗
NASA NTRS1976

Demonstration of the frequency offset errors introduced by an incorrect setting of the Zeeman/magnetic field adjustment on the cesium beam frequency standard

The fine frequency setting of a cesium beam frequency standard is accomplished by adjusting the C field control with the appropriate Zeeman frequency applied to the harmonic generator. A novice operator in the field, even when using the correct Zeeman frequency input, may mistakenly set the C field to any one of seven major Beam I peaks (fingers) represented by the Ramsey curve. This can result in frequency offset errors of as much as 2.5 parts in ten to the tenth. The effects of maladjustment are demonstrated and suggestions are discussed on how to avoid the subtle traps associated with C field adjustments.

Kaufmann, D. C.↗
DOE OSTI2020

Towards Feature-Preserving 2D and 3D Vector Field Compression

The objective of this work is to develop error-bounded lossy compression methods to preserve topological features in 2D and 3D vector fields. Specifically, we explore the preservation of critical points in piecewise linear vector fields. We define the preservation of critical points as, without any false positive, false negative, or false type change in the decompressed data, (1) keeping each critical point in its original cell and (2) retaining the type of each critical point (e.g., saddle and attracting node). The key to our method is to adapt a vertex-wise error bound for each grid point and to compress input data together with the error bound field using a modified lossy compressor. Our compression algorithm can be also embarrassingly parallelized for large data handling and in situ processing. We benchmark our method by comparing it with existing lossy compressors in terms of false positive/negative/type rates, compression ratio, and various vector field visualizations with several scientific applications.

critical points↗
NASA NTRS2003

A Wavelet based Suboptimal Kalman Filter for Assimilation of Stratospheric Chemical Tracer Observations

A suboptimal Kalman filter system which evolves error covariances in terms of a truncated set of wavelet coefficients has been developed for the assimilation of chemical tracer observations of CH4. This scheme projects the discretized covariance propagation equations and covariance matrix onto an orthogonal set of compactly supported wavelets. Wavelet representation is localized in both location and scale, which allows for efficient representation of the inherently anisotropic structure of the error covariances. The truncation is carried out in such a way that the resolution of the error covariance is reduced only in the zonal direction, where gradients are smaller. Assimilation experiments which last 24 days, and used different degrees of truncation were carried out. These reduced the covariance size by 90, 97 and 99 % and the computational cost of covariance propagation by 80, 93 and 96 % respectively. The difference in both error covariance and the tracer field between the truncated and full systems over this period were found to be not growing in the first case, and growing relatively slowly in the later two cases. The largest errors in the tracer fields were found to occur in regions of largest zonal gradients in the constituent field. This results indicate that propagation of error covariances for a global two-dimensional data assimilation system are currently feasible. Recommendations for further reduction in computational cost are made with the goal of extending this technique to three-dimensional global assimilation systems.

Tangborn, Andrew↗
NASA NTRS1999

Main Geomagnetic Field Models from Oersted and Magsat Data Via a Rigorous General Inverse Theory with Error Bounds

The purpose of the grant was to study how prior information about the geomagnetic field can be used to interpret surface and satellite magnetic measurements, to generate quantitative descriptions of prior information that might be so used, and to use this prior information to obtain from satellite data a model of the core field with statistically justifiable error estimates. The need for prior information in geophysical inversion has long been recognized. Data sets are finite, and faithful descriptions of aspects of the earth almost always require infinite-dimensional model spaces. By themselves, the data can confine the correct earth model only to an infinite-dimensional subset of the model space. Earth properties other than direct functions of the observed data cannot be estimated from those data without prior information about the earth. Prior information is based on what the observer already knows before the data become available. Such information can be "hard" or "soft". Hard information is a belief that the real earth must lie in some known region of model space. For example, the total ohmic dissipation in the core is probably less that the total observed geothermal heat flow out of the earth's surface. (In principle, ohmic heat in the core can be recaptured to help drive the dynamo, but this effect is probably small.) "Soft" information is a probability distribution on the model space, a distribution that the observer accepts as a quantitative description of her/his beliefs about the earth. The probability distribution can be a subjective prior in the sense of Bayes or the objective result of a statistical study of previous data or relevant theories.

Backus, George E.↗
NASA NTRS1994

Active control of fan noise from a turbofan engine

A three-channel active control system is applied to an operational turbofan engine to reduce tonal noise produced by both the fan and the high-pressure compressor. The control approach is the feedforward filtered-x least-mean-square algorithm implemented on a digital signal processing board. Reference transducers mounted on the engine case provide blade passing and harmonics frequency information to the controller. Error information is provided by large area microphones placed in the acoustic far field. To minimize the error signal, the controller actuates loudspeakers mounted on the inlet to produce destructive interference. The sound pressure level of the fundamental tone of the fan was reduced using the three-channel controller by up to 16 dB over a +/- 30-deg angle about the engine axis. A single-channel controller could produce reduction over a +/- 15-deg angle. The experimental results show the control to be robust. Outside of the areas contolled, the levels of the tone actually increased due to the generation of radial modes by the control sources. Simultaneous control of two tones is achieved with parallel controllers. The fundamental and the first harmonic tones of the fan were controlled simultaneously with reductions of 12 and 5 dBA, respectively, measured on the engine axis. Simultaneous control was also demonstrated for the fan fundamental and the high-pressure compressor fundamental tones.

Thomas, Russell H.↗
NASA NTRS2019

Sketch-To-Solution: An Exploration of Viscous CFD with Automatic Grids

Numerical simulation of the Reynolds-averaged Navier–Stokes (RANS) equations has become a critical tool for the design of aerospace vehicles. However, the issues that affect the grid convergence of three dimensional RANS solutions are not completely understood, as documented in the AIAA Drag Prediction Workshop series. Grid adaption methods have the potential for increasing the automation and discretization error control of RANS solutions to impact the aerospace design and certification process. The realization of the CFD Vision 2030 Study includes automated management of errors and uncertainties of physics-based, predictive modeling that can set the stage for ensuring a vehicle is in compliance with a regulation or specification by using analysis without demonstration in flight test (i.e., certification or qualification by analysis). For example, the Cart3D inviscid analysis package has automated Cartesian cut-cell gridding with output-based error control. Fueled by recent advances in the fields of anisotropic grid adaptation, error estimation, and geometry modeling, a similar work flow is explored for viscous CFD simulations; where a CFD application engineer provides geometry, boundary conditions, and flow parameters, and the sketch-to-solution process yields a CFD simulation through automatic, error-based, grid adaptation.

Kleb, William L.↗
DOE OSTI2024

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.

3D reconstruction model↗
NASA NTRS2000

Gravity and Nonconservative Force Model Tuning for the GEOSAT Follow-On Spacecraft

The US Navy's GEOSAT Follow-On spacecraft was launched on February 10, 1998 and the primary objective of the mission was to map the oceans using a radar altimeter. Three radar altimeter calibration campaigns have been conducted in 1999 and 2000. The spacecraft is tracked by satellite laser ranging (SLR) and Doppler beacons and a limited amount of data have been obtained from the Global Positioning Receiver (GPS) on board the satellite. Even with EGM96, the predicted radial orbit error due to gravity field mismodelling (to 70x70) remains high at 2.61 cm (compared to 0.88 cm for TOPEX). We report on the preliminary gravity model tuning for GFO using SLR, and altimeter crossover data. Preliminary solutions using SLR and GFO/GFO crossover data from CalVal campaigns I and II in June-August 1999, and January-February 2000 have reduced the predicted radial orbit error to 1.9 cm and further reduction will be possible when additional data are added to the solutions. The gravity model tuning has improved principally the low order m-daily terms and has reduced significantly the geographically correlated error present in this satellite orbit. In addition to gravity field mismodelling, the largest contributor to the orbit error is the non-conservative force mismodelling. We report on further nonconservative force model tuning results using available data from over one cycle in beta prime.

Lemoine, Frank G.↗
NASA NTRS2001

The impact of Doppler lidar wind observations on a single-level meteorological analysis

Through the use of observation operators, modern data assimilation systems have the capability to ingest observations of quantities that are not themselves model variables, but are mathematically related to those variables. An example of this are the so-called LOS (line of sight) winds that a Doppler wind Lidar can provide. The model - or data assimilation system - needs information about both components of the horizontal wind vectors, whereas the observations in this case only provide the projection of the wind vector onto a given direction. The analyzed value is then calculated essentially based on a comparison between the observation itself and the model-simulated value of the observed quantity. However, in order to assess the expected impact of such an observing system, it is important to examine the extent to which a meteorological analysis can be constrained by the LOS winds. The answer to this question depends on the fundamental character of the atmospheric flow fields that are analyzed, but more importantly it also depends on the real and assumed error covariance characteristics of these fields. A single-level wind analysis system designed to explore these issues has been built at the NASA Data Assimilation Office. In this system, simulated wind observations can be evaluated in terms of their impact on the analysis quality under various assumptions about their spatial distribution and error characteristics and about the error covariance of the background fields. The basic design of the system will be presented along with experimental results obtained with it. In particular, the value of simultaneously measuring LOS winds along two different directions for a given location will be discussed.

Riishojgaard, L. P.↗
NASA NTRS2019

Uncertainty of Observation Impact Estimation in an Adjoint Model Investigated with an Observing System Simulation Experiment

Adjoint models are often used to estimate the impact of different observations on short-term forecast skill. A common difficulty with the evaluation of short term forecast quality is the choice of verification fields. The use of self-analysis fields for verification is typical but incestuous, and introduces uncertainty due to biases and errors in the analysis field. In this study, an observing system simulation experiment (OSSE) is used to explore the uncertainty in adjoint model estimations of observation impact. The availability of the true state for verification in the OSSE framework in the form of the Nature Run allows calculation of the observation impact without the uncertainties present in self-analysis verification. These impact estimates are compared to estimates calculated using self-analysis verification. The Global Earth Observing System version 5 (GEOS-5) forecast model with Gridpoint Statistical Interpolation (GSI) is used with the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) OSSE capability. The adjoint model includes moist processes, with total wet energy selected as the norm for evaluation of observation impacts. The results show that there are measurable but small discrepancies in the adjoint model estimation of observation impact. In general, observations of temperature and winds tend to have overestimated impacts with self-analysis verification, while observations of humidity and moisture-affected observations tend to have underestimated impacts. The small magnitude of the differences in impact estimates supports the robustness of the adjoint method of estimating observation impacts.

N C Prive↗
DOE OSTI2017

Checking Questionable Entry of Personally Identifiable Information Encrypted by One-Way Hash Transformation

Background: As one of the several effective solutions for personal privacy protection, a global unique identifier (GUID) is linked with hash codes that are generated from combinations of personally identifiable information (PII) by a one-way hash algorithm. On the GUID server, no PII is permitted to be stored, and only GUID and hash codes are allowed. The quality of PII entry is critical to the GUID system. Objective: The goal of our study was to explore a method of checking questionable entry of PII in this context without using or sending any portion of PII while registering a subject. Methods: According to the principle of GUID system, all possible combination patterns of PII fields were analyzed and used to generate hash codes, which were stored on the GUID server. Based on the matching rules of the GUID system, an error-checking algorithm was developed using set theory to check PII entry errors. We selected 200,000 simulated individuals with randomly-planted errors to evaluate the proposed algorithm. These errors were placed in the required PII fields or optional PII fields. The performance of the proposed algorithm was also tested in the registering system of study subjects. Results: There are 127,700 error-planted subjects, of which 114,464 (89.64%) can still be identified as the previous one and remaining 13,236 (10.36%, 13,236/127,700) are discriminated as new subjects. As expected, 100% of nonidentified subjects had errors within the required PII fields. The possibility that a subject is identified is related to the count and the type of incorrect PII field. For all identified subjects, their errors can be found by the proposed algorithm. The scope of questionable PII fields is also associated with the count and the type of the incorrect PII field. The best situation is to precisely find the exact incorrect PII fields, and the worst situation is to shrink the questionable scope only to a set of 13 PII fields. In the application, the proposed algorithm can give a hint of questionable PII entry and perform as an effective tool. Conclusions: The GUID system has high error tolerance and may correctly identify and associate a subject even with few PII field errors. Correct data entry, especially required PII fields, is critical to avoiding false splits. In the context of one-way hash transformation, the questionable input of PII may be identified by applying set theory operators based on the hash codes. The count and the type of incorrect PII fields play an important role in identifying a subject and locating questionable PII fields.

59 BASIC BIOLOGICAL SCIENCES↗