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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Progress in navigation filter estimate fusion and its application to spacecraft rendezvous

A new derivation of an algorithm which fuses the outputs of two Kalman filters is presented within the context of previous research in this field. Unlike other works, this derivation clearly shows the combination of estimates to be optimal, minimizing the trace of the fused covariance matrix. The algorithm assumes that the filters use identical models, and are stable and operating optimally with respect to their own local measurements. Evidence is presented which indicates that the error ellipsoid derived from the covariance of the optimally fused estimate is contained within the intersections of the error ellipsoids of the two filters being fused. Modifications which reduce the algorithm's data transmission requirements are also presented, including a scalar gain approximation, a cross-covariance update formula which employs only the two contributing filters' autocovariances, and a form of the algorithm which can be used to reinitialize the two Kalman filters. A sufficient condition for using the optimally fused estimates to periodically reinitialize the Kalman filters in this fashion is presented and proved as a theorem. When these results are applied to an optimal spacecraft rendezvous problem, simulated performance results indicate that the use of optimally fused data leads to significantly improved robustness to initial target vehicle state errors. The following applications of estimate fusion methods to spacecraft rendezvous are also described: state vector differencing, and redundancy management.

Carpenter, J. Russell↗
DOE OSTI2023

Large Ensemble Particle Filter for Spatial Climate Reconstructions Using a Linear Inverse Model

Proxy records that document the last 2000 years of climate provide evidence for the wide range of the natural climate variability from inter-annual to secular timescales not captured by the short window of recent direct observations. Assessing climate models ability to reproduce such natural variations is crucial to understand climate sensitivity and impacts of future climate change. Paleoclimate data assimilation (PDA) offers a powerful way to extend the short instrumental period by optimally combining the physics described by General Circulation Climate Models (GCMs) with information from available proxy records while taking into account their uncertainties. Here we present a new PDA approach based on a sequential importance resampling (SIR) Particle filter (PF) that uses Linear Inverse Modeling (LIM) as an emulator of several CMIP-class GCMs. We examine in a perfect-model framework the skill of the various LIMs to forecast the dynamics of the surface temperatures and provide spatial field reconstructions over the last millennium in a SIR PF. Our results show that the LIMs allow for skillful ensemble forecasts at 1-year lead-time based on GCMs dynamical knowledge with best prediction in the tropics and the North Atlantic. The PDA further provides a set of physically consistent spatial fields allowing robust uncertainty quantification related to climate models biases and proxy spatial sampling. Our results indicate that the LIM yields dynamical memory improving climate variability reconstructions and support the use of the LIM as a GCM-emulator in real reconstruction to propagate large ensembles of particles at low cost in SIR PF.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Model based estimation of image depth and displacement

Passive depth and displacement map determinations have become an important part of computer vision processing. Applications that make use of this type of information include autonomous navigation, robotic assembly, image sequence compression, structure identification, and 3-D motion estimation. With the reliance of such systems on visual image characteristics, a need to overcome image degradations, such as random image-capture noise, motion, and quantization effects, is clearly necessary. Many depth and displacement estimation algorithms also introduce additional distortions due to the gradient operations performed on the noisy intensity images. These degradations can limit the accuracy and reliability of the displacement or depth information extracted from such sequences. Recognizing the previously stated conditions, a new method to model and estimate a restored depth or displacement field is presented. Once a model has been established, the field can be filtered using currently established multidimensional algorithms. In particular, the reduced order model Kalman filter (ROMKF), which has been shown to be an effective tool in the reduction of image intensity distortions, was applied to the computed displacement fields. Results of the application of this model show significant improvements on the restored field. Previous attempts at restoring the depth or displacement fields assumed homogeneous characteristics which resulted in the smoothing of discontinuities. In these situations, edges were lost. An adaptive model parameter selection method is provided that maintains sharp edge boundaries in the restored field. This has been successfully applied to images representative of robotic scenarios. In order to accommodate image sequences, the standard 2-D ROMKF model is extended into 3-D by the incorporation of a deterministic component based on previously restored fields. The inclusion of past depth and displacement fields allows a means of incorporating the temporal information into the restoration process. A summary on the conditions that indicate which type of filtering should be applied to a field is provided.

Damour, Kevin T.↗
NASA NTRS1978

ORACLS: A system for linear-quadratic-Gaussian control law design

A modern control theory design package (ORACLS) for constructing controllers and optimal filters for systems modeled by linear time-invariant differential or difference equations is described. Numerical linear-algebra procedures are used to implement the linear-quadratic-Gaussian (LQG) methodology of modern control theory. Algorithms are included for computing eigensystems of real matrices, the relative stability of a matrix, factored forms for nonnegative definite matrices, the solutions and least squares approximations to the solutions of certain linear matrix algebraic equations, the controllability properties of a linear time-invariant system, and the steady state covariance matrix of an open-loop stable system forced by white noise. Subroutines are provided for solving both the continuous and discrete optimal linear regulator problems with noise free measurements and the sampled-data optimal linear regulator problem. For measurement noise, duality theory and the optimal regulator algorithms are used to solve the continuous and discrete Kalman-Bucy filter problems. Subroutines are also included which give control laws causing the output of a system to track the output of a prescribed model.

Armstrong, E. S.↗
NASA NTRS2007

A Catalog of Galaxy Clusters Observed by XMM-Newton

Images and the radial profiles of the temperature, abundance, and brightness for 70 clusters of galaxies observed by XMM-Newton are presented along with a detailed discussion of the data reduction and analysis methods, including background modeling, which were used in the processing. Proper consideration of the various background components is vital to extend the reliable determination of cluster parameters to the largest possible cluster radii. The various components of the background including the quiescent particle background, cosmic diffuse emission, soft proton contamination, and solar wind charge exchange emission are discussed along with suggested means of their identification, filtering, and/or their modeling and subtraction. Every component is spectrally variable, sometimes significantly so, and all components except the cosmic background are temporally variable as well. The distributions of the events over the FOV vary between the components, and some distributions vary with energy. The scientific results from observations of low surface brightness objects and the diffuse background itself can be strongly affected by these background components and therefore great care should be taken in their consideration.

Snowden, S. L.↗
NASA NTRS1999

Improved Earth Sensor Performance Using a Sequentially Correlated Noise Model

Spacecraft attitude estimation by means of an extended Kalman filter requires a reasonably true model of the inherent noise of each sensor. For some sensors, the largest uncorrected noise comes not from the sensor itself, but from errors in the model for the predicted observations. This is certainly the case for Earth horizon sensors. The Earth horizon as seen from low Earth orbit is nearly a circle whose radius depends primarily on altitude. A straightforward latitude-dependent correction is added to this to account for the oblateness of the Earth. There also are both seasonal and stochastic variations in the horizon height. The seasonal variations can be predicted to some limited degree based on models derived from historical data. The stochastic component characteristically shows variations that are correlated both in time and space but which are unpredictable over long time spans. This work investigates whether Earth horizon sensor performance can be improved by solving for its systematic error as an augmentation of an attitude Kalman filter. It is found that using only Earth and Sun sensors, the augmented state is not fully observable. Even when magnetometer data is included, only the pitch axis component of the error can be improved; the roll component is unobservable.

Sedlak, J.↗
NASA NTRS1999

Improved Earth Sensor Performance Using a Sequentially Correlated Noise Model

Spacecraft attitude estimation by means of an extended Kalman filter requires a reasonably true model of the inherent noise of each sensor. For some sensors, the largest uncorrected noise comes not from the sensor itself, but from errors in the model for the predicted observations. This is certainly the case for Earth horizon sensors. The Earth horizon as seen from low Earth orbit is nearly a circle whose radius depends primarily on altitude. A straightforward latitude-dependent correction is added to this to account for the oblateness of the Earth. There also are both seasonal and stochastic variations in the horizon height. The seasonal variations can be predicted to some limited degree based on models de(ived from historical data. The stochastic component characteristically shows variations that are correlated both in time and space but which are unpredictable over long time spans. This work investigates whether Earth horizon sensor performance can be improved by solving for its systematic error as an augmentation of an attitude Kalman filter. It is found that using only Earth and Sun sensors, the augmented state is not fully observable. Even when magnetometer data is included, only the pitch axis component of the error can be improved; the roll component is unobservable.

Sedlak, Joseph↗
NASA NTRS1976

Stochastic simulation of vertically nonhomogeneous gusts

The small-scale horizontal gust structure of detailed wind profiles along the vertical in the first 20 km of the atmosphere is a vertically nonhomogeneous process. A linear stochastic model is developed for the process based on the process covariance function. This model is formulated through the use of a scaling hypothesis that transforms the nonhomogeneous gust process into a nondimensional gust process which is homogeneous in a nondimensional height coordinate. The velocity scaling parameter for the gust process is the gust standard deviation, and the length scale used to nondimensionalize the altitude is the vertical space lag associated with the first zero of the gust covariance function. State space theory is used to derive a digital filter from the model, which can be readily used to simulate gusts for space vehicle design applications.

Fichtl, G. H.↗
NASA NTRS1975

Stochastic simulation of vertically nonhomogeneous gusts

The small-scale horizontal gust structure of detailed wind profiles along the vertical in the first 20 km of the atmosphere is a vertically nonhomogeneous process. A linear stochastic model was developed based on the process covariance function. This model was formulated through the use of a scaling hypothesis which transforms the nonhomogeneous gust process into a nondimensional gust process which is homogeneous in a nondimensional gust height coordinate. The velocity scaling parameter for the gust process is the gust standard deviation, and the length scale used to nondimensionalize the altitude is the vertical space lag associated with the first zero of the gust covariance function. State space theory was used to derive a digital filter from the model, which can be readily used to simulate gusts for space vehicle design applications.

Fichtl, G. H.↗
DOE OSTI2025

ICAT: The Interactive Corpus Analysis Tool

The Interactive Corpus Analysis Tool (ICAT) is a Python library for creating dashboards to explore textual datasets and build simple binary classification models to help filter through them and focus on entries of interest. This tool uses a form of interactive machine learning (IML), a paradigm of “machine teaching” (Simard et al., 2017) that sits at the intersection of the fields of human computer interaction (HCI), visual analytics, and machine learning. The intent of ICAT is to allow subject matter experts (SME) with limited to no experience in machine learning to benefit from an iterative human-in-the-loop (HITL) approach to building their own model without needing to understand the details of the underlying algorithm. This interactivity is achieved by allowing the user to create features, label data points, and visually manipulate a representation of the features to manually cluster and investigate data, while a model is trained on the fly based on these actions. ICAT is built on top of the Panel (Holoviz, 2018) library, using a combination of Vega, a custom IPyWidget using D3, and ipyvuetify, and is intended to be used inside of a Jupyter environment.

Martindale, Nathan [Oak Ridge National Laboratory ↗
NASA NTRS1999

Scale-Similar Models for Large-Eddy Simulations

Scale-similar models employ multiple filtering operations to identify the smallest resolved scales, which have been shown to be the most active in the interaction with the unresolved subgrid scales. They do not assume that the principal axes of the strain-rate tensor are aligned with those of the subgrid-scale stress (SGS) tensor, and allow the explicit calculation of the SGS energy. They can provide backscatter in a numerically stable and physically realistic manner, and predict SGS stresses in regions that are well correlated with the locations where large Reynolds stress occurs. In this paper, eddy viscosity and mixed models, which include an eddy-viscosity part as well as a scale-similar contribution, are applied to the simulation of two flows, a high Reynolds number plane channel flow, and a three-dimensional, nonequilibrium flow. The results show that simulations without models or with the Smagorinsky model are unable to predict nonequilibrium effects. Dynamic models provide an improvement of the results: the adjustment of the coefficient results in more accurate prediction of the perturbation from equilibrium. The Lagrangian-ensemble approach [Meneveau et al., J. Fluid Mech. 319, 353 (1996)] is found to be very beneficial. Models that included a scale-similar term and a dissipative one, as well as the Lagrangian ensemble averaging, gave results in the best agreement with the direct simulation and experimental data.

Sarghini, F.↗
NASA NTRS1997

Root-Raised Cosine Filter Implementation That Uses Canonical Signed Digits for High-Speed Digital Filter Applications

NASA Lewis Research Center's Space Communications Division has been investigating high-speed digital filters that can operate at a higher speed than those in current use for a digital modulator and demodulator (modem). Using the Canonical Signed Digits (CSD) number representation for filter coefficients is a very effective way to increase the filter's speed while reducing complexity in the digital filter hardware design. This approach is a good alternative to using an expensive parallel-processing design technique or custom, application-specific integrated circuits. Such integrated circuits may not be suitable for applications that require filter speeds faster than what application-specific integrated circuits digital signal processors can offer for a dedicated channel. When a communication channel is a dedicated, multiplication process--a costly, time-consuming process--it can be greatly simplified by a replacement of the filter coefficients with CSD numbers. A computer code written with the MATLAB software package runs the program and generates CSD-represented filter coefficients that are based on minimizing minimum mean square errors. Also, the Alta Group of Cadence's Signal Processing Workstation is used to simulate and analyze the CSD filter responses. The impulse response of the root-raised cosine filter that is used as a base model is defined. From this filter, a set of coefficients is sampled and stored in a file. For the all coefficients, the optimal CSD number for each coefficient is searched on the basis of the minimum-mean-square-errors criterion. Because the distribution of CSD numbers is not uniform, quantization errors tend to be bigger for coefficients greater than 1/2. To offset errors that occur in a region of coefficients between 1/2 to 1 and to better represent fractions with CSD numbers, an extra nonzero digit is allowed for any coefficients exceeding 1/2. This will greatly improve frequency response as well as intersymbol interference at the receiver. The frequency response of a set of collected CSD-represented filter coefficients was compared with the same filter that was conventionally implemented. Analyses show CSD-implemented filters perform as well as conventional filters. Comparison of eye diagrams and bit-error-rate curves between CSD filters and traditionally implemented filters are almost indistinguishable. However, filter complexity was reduced from almost 3.5 to 1 for CSD filters. Complete computer simulation results are available. In the near future, work will focus on building actual working digital filter hardware in a field programmable gate array (FPGA).

Kim, Heechul↗
NASA NTRS1984

Input filter compensation for switching regulators

Problems caused by input filter interaction and conventional input filter design techniques are discussed. The concept of feedforward control is modeled with an input filter and a buck regulator. Experimental measurement and comparison to the analytical predictions is carried out. Transient response and the use of a feedforward loop to stabilize the regulator system is described. Other possible applications for feedforward control are included.

Lee, F. C.↗
NASA NTRS2021

Estimation of Snow Mass Information via Assimilation of C-Band Synthetic Aperture Radar Backscatter Observations Into an Advanced and Surface Model

This study assimilated Sentinel-1 C-band backscatter observations over snow-covered terrain into the Noah-Multiparameterization land surface model using support vector machine (SVM) regression and an ensemble Kalman filter to improve the modeled terrestrial snow mass estimates. The data assimilation (DA) experiment was conducted across Western Colorado from September 2016 to August 2017. As part of the DA experiments, the impact of a rule-based update was evaluated by comparing snow water equivalent (SWE) estimates via DA (with [ DAv1 ] and without [ DAv2 ] the rule-based update) against SNOTEL SWE measurements. Results confirmed that rule-based update helped minimize SVM controllability issues, and in turn, improved the accuracy of SWE estimates relative to both open loop (OL) and DAv2 . Comparison of SWE estimates from Sentinel-1 DAv1 against SNOTEL SWE revealed that 75% of stations showed improvements in bias and correlation coefficient relative to the OL. Assimilated SWE estimates also showed statistical improvements during both the snow accumulation and snow ablation periods. However, unbiased root mean square error showed a slight increase during the snow ablation period due to the large variability in the electromagnetic response of C-band backscatter over deep and/or wet snow. Improvement of the SWE estimates also resulted in improving river discharge estimates compared to in situ measurements. River discharge using Sentinel-1 DAv1 improved the Nash–Sutcliffe efficiency at all available stations. These results suggest that physically constrained SVM can serve as an efficient observation operator for snow mass DA through explicit consideration of the first-order C-band scattering mechanisms over different terrestrial snow conditions.

Jongmin Park↗
DOE OSTI2022

Adaptive Internal Model Based Current Control with Embedded Active Damping of a Three-Phase Grid-Connected Inverter with LCL Filter for PV Application

This paper presents an internal model based controller with embedded active damping for a three-phase grid-connected inverter with LCL filter. A strategy to control the grid current based on the internal model principle is presented in this paper. It is known that a third-order LCL filter apart from providing better attenuation also poses the problem of initiating unwanted resonance oscillations especially during transients. To address this problem, an active damping strategy based on virtual resistance emulation on the grid side filter is implemented. Also, to ensure effective active damping, an online parameter update strategy is implemented for the filter parameters. The proposed method provides better attenuation to oscillation damping and achieves good tracking performance without adversely affecting the bandwidth. The architecture is verified based on computer simulations via MATLAB/Simulink and PLECS domain and various important case study results are presented.

grid-connected inverter↗
DOE OSTI2023

Benchtop assessment of sealing efficacy and breathability of additively manufactured (AM) face masks

The onset of the 2019 novel coronavirus disease (COVID-19) led to a shortage of personal protective equipment (PPE), medical devices, and other medical supplies causing many stakeholders and the general public alike to turn to additive manufacturing (AM) as a stopgap when normally accessible devices were not available. However, without a method to test these AM constructs, there continued to be a disconnect between AM suppliers and the community’s needs. The objective of this study was to characterize the pressure drop and leakage of four different publicly available AM face mask models with two filter material combinations, as well as to investigate the impact of frame modification techniques including the use of foam strips and hot-water face forming to improve fit when the masks are donned on manikin head forms. AM face mask frame designs were downloaded from public repositories during the early stages of the COVID-19 pandemic. AM face masks were fabricated and tested on manikin head forms within a custom chamber containing dry aerosolized NaCl. Pressure drops, particle penetration, and leakage were evaluated for various flow rates and NaCl concentrations. Results indicated that filter material combination and frame modification played a major role in the overall performance of the AM face masks studied. Filter material combinations showed improved performance when high filtration fabric was used, and the cross-sectional area of the fabric was increased. AM frame modifications appeared to improve AM face mask leakage performance by as much as 69.6%.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Spatial and temporal prediction of radiation dose rates near Fukushima Daiichi Nuclear Power Plant

In this paper, we have developed a methodology to estimate the spatiotemporal distribution of radiation air dose rates around the Fukushima Daiichi Nuclear Power Plant (FDNPP). In our exploratory data analysis, we found that (1) the temporal evolution of dose rates is composed of a log-linear decay trend and fluctuations of air dose rates that are spatially correlated among adjacent monitoring posts; and (2) the slope of the log-linear environmental decay trend can be represented as a function of the apparent initial dose rates, coordinate position, land-use type, and soil type. From these observations, we first estimated the log-linear decay trend at each location based on these predictors, using the random forest method. We then developed a modified Kalman filter coupled with a Gaussian process model to estimate the dose-rate time series at a given location and time. We applied this method to the Fukushima evacuation zone (as of March 2017), which included 17 monitoring post locations (with monitoring datasets collected between 2014 and 2018) and generated a time series of dose-rate maps. Our results show that this approach allows us to produce accurate spatial and temporal predictions of radiation dose-rate maps using limited spatiotemporal measurements.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Damped Ly α absorbers and atomic hydrogen in galaxies: the view of the GAEA model

ABSTRACT Using the GAEA semi-analytic model, we analyse the connection between Damped Ly α systems (DLAs) and H i in galaxies. Our state-of-the-art semi-analytic model is tuned to reproduce the local galaxy H i mass function, and that also reproduces other important galaxy properties, including the galaxy mass–gas metallicity relation. To produce catalogues of simulated DLAs we throw 105 random lines of sight in a composite simulated volume: dark matter haloes with log$(\frac{M_{200}}{ {\rm M}_{\odot }}) \ge 11.5$ are extracted from the Millennium Simulation, while for $9.2 \le \log (\frac{M_{200}}{ \mathrm{M}_{\odot }})\lt 11.5$ we use the Millennium II, and for $8 \le \log (\frac{M_{200}}{\mathrm{M}_{\odot }}) \lt 9.2$ a halo occupation distribution model. At 2 < z < 3, where observational data are more accurate, our fiducial model predicts the correct shape of the column density distribution function, but its normalization falls short of the observations, with the discrepancy increasing at higher redshift. The agreement with observations is significantly improved increasing both the H i masses and the disc radii of model galaxies by a factor of 2, as implemented ‘a posteriori’ in our 2M−2R model. In the redshift range of interest, haloes with $M_{200} \ge {10}^{11} \, \mathrm{M}_{\odot }$ give the major contribution to ΩDLA, and the typical DLA host halo mass is $\sim \!{10}^{11} \, \mathrm{M}_{\odot }$. The simulated DLA metallicity distribution is in relatively good agreement with observations, but our model predicts an excess of DLAs at low metallicities. Our results suggest possible improvements for the adopted modelling of the filtering mass and metal ejection in low-mass haloes.

Di Gioia, Serafina↗