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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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Utilizing spatial filtering for analyzing structural configuration of Michigan Basin for application to remote sensing
The application of the failure detection filter to the detection and identification of aircraft control element failures was evaluated in a linear digital simulation of the longitudinal dynamics of a B-737 Aircraft. Simulation results show that with a simple correlator and threshold detector used to process the filter residuals, the failure detection performance is seriously degraded by the effects of turbulence.
Kalman filter alternate form extended to include multiple simultaneous correlated measurements, testing with ballistic model and using square root formulation for trajectory determination
Battery performance is strongly correlated with electrode microstructural properties. To account for its impact, lithium-ion battery (LIB) models either abstract the microstructural heterogeneity of composite electrodes using effective macroscopic properties (macro- or meso- scale models) or directly solve the system of equations on the microstructure geometry or mesh (microstructure-scale models). Therefore, to be adequate, both families of models require information from the microstructure geometry, which can be provided by the numerical tool presented in this work. MATBOX is a MATLAB open-source application [1] developed by NREL for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization and correlation, visualization, and microstructure meshing. MATBOX was originally developed for the analysis of LIB electrode microstructures; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphical-User Interface, requires no coding by the user, and is well documented. This presentation will illustrate various MATBOX features for the characterization of a LIB electrode, including a fully automated Representative Volume Element (RVE) analysis, the numerical generation of complex 'virtual' microstructure, including dual-layer electrodes and carbon-binder additive phase, and the meshing of a complex NMC/graphite full cell microstructure suitable for 3D finite-element modeling. Other modules (segmentation, visualization, and correlation) will be briefly presented. Thanks to its modular, open-source approach, MATBOX can easily incorporate third-party algorithms to eventually build a standard in the field that will benefit the whole scientific community. Effective diffusion coefficient [2], additive phase numerical generation [3], and meshing [4] third-party algorithms have been already integrated in the toolbox with more to come.
Kalman filter alternate form extended to include multiple simultaneous correlated measurements, testing with ballistic model and using square root formulation for trajectory determination
As lithium-ion battery energy densities continue to rise, managing the heat and pressure generated during failure events has become increasingly critical. Safety systems must effectively relieve pressure without releasing sparks, flames, or particulate matter, requiring robust filtration solutions. The challenge is compounded by the reduced free volume available for gas expansion in high-density designs, which increases the demands on these filters. While significant progress has been made through experimental studies and modeling efforts to understand the behavior of ejecta during battery failures, there remains a pressing need for practical, rule-of-thumb sizing parameters. These parameters would help correlate high-energy waste streams with appropriate filter design, ensuring reliable containment and safety. This talk will explore recent experimental findings in this area and discuss the potential pathways for developing these essential sizing guidelines.
The operation of a deformable mirror device (DMD) as a Fourier plane phase modulating filter is described. An analysis of the optical characteristics of the DMD elements as phase modulators is summarized. Analytical and experimental results indicating the existence of a quasi-phase-only operational mode are presented. These results are used to specify the mirror deflection required to implement a binary phase-only image correlation operation. An optical correlator system is implemented using the DMD Fourier plane filter and experimental results from this system are compared with computer simulations of the correlator operation.
Optical pattern recognition allows objects to be recognized from their images and permits their positional parameters to be estimated accurately in real time. The guiding principle behind optical pattern recognition is that a lens focusing a beam of coherent light modulated with an image produces the two-dimensinal Fourier transform of that image. When the resulting output is further transformed by the matched filter corresponding to the original image, one obtains the autocorrelation function of the original image, which has a peak at the origin. Such a device is called an optical correlator and may be used to recognize the locate the image for which it is designed. (From a practical perspective, an approximation to the matched filter must be used since the spatial light modulator (SLM) on which the filter is implemented usually does not allow one to independently control both the magnitude and phase of the filter.) Generally, one is not just concerned with recognizing a single image but is interested in recognizing a variety of rotated and scaled views of a particular image. In order to recognize these different views using an optical correlator, one may select a subset of these views (whose elements are called training images) and then use a composite filter that is designed to produce a correlation peak for each training image. Presumably, these peaks should be sharp and easily distinguishable from the surrounding correlation plane values. In this report we consider two areas of research regarding composite optical correlators. First, we consider the question of how best to choose the training images that are used to design the composite filter. With regard to quantity, the number of training images should be large enough to adequately represent all possible views of the targeted object yet small enough to ensure that the resolution of the filter is not exhausted. As for the images themselves, they should be distinct enough to avoid numerical difficulties yet similar enough to avoid gaps in which certain views of the target will be unrecognized. One method that we introduce to study this problem is called probing and involves the creation of the artificial imagery. The second problem we consider involves the clasification of the composite filter's correlation plane data. In particular, we would like to determine not only whether or not we are viewing a training image, but, in the former case, we would like to determine which training image is being viewed. This second problem is investigated using traditional M-ary hypothesis testing techniques.
This paper presents an algorithm for azimuth correlation of synthetic aperture radar (SAR) data with extraordinarily large-range migration which cannot be accommodated by the existing frequency domain interpolation approach used in current Seasat SAR processing. A mathematical model is provided for the SAR range-correlated point-target response both in the spatial and frequency domains. A simple and efficient processing algorithm derived from the exact two-dimensional correlation algorithm is given. This algorithm enables azimuth correlation by two cascaded one-dimensional correlation steps. The first step is to transform the range-correlated SAR data into the frequency domain in azimuth, followed by a newly developed range convolution filter to correct the range-dispersed spectrum of the range-correlated point-target response (RCPTR). The second step is the frequency-domain range migration correction approach for the azimuth compression. Simulation results provided here indicate that this processing algorithm yields a satisfactory compressed impulse response for SAR data with large-range migration whereas previous methods were subject to a broadening of the impulse response along range.
The Artemis Program is NASA’s campaign to explore the Moon and beyond. Artemis-1, the uncrewed exoLEO test flight of the Orion spacecraft, was completed in 2022. There were four navigation Extended Kalman Filters (EKFs) that are part of the Orion navigation system. The Atmospheric Extended Kalman Filter (ATMEKF) estimates the vehicle position, velocity, and attitude (referred to as the vehicle state) during the ascent and entry phases of flight. Once Orion is outside of Earths atmosphere, the Earth Orbit Extended Kalman Filter (EOEKF) and CisLunar Extended Kalman Filter (CLEKF) estimate the translational states, depending on the phase of flight, while the Attitude Extended Kalman Filter (ATTEKF) estimates the rotational state of the vehicle. The Kalman filters propagate the vehicle state forward in time using a combination of dynamics models and the output data from the Inertial Measurement Unit (IMU). The filters update the vehicle states and associated uncertainties, in the form of the covariance matrix, using pseudorange measurements from GPS (in ATMEKF/EOEKF), optical navigation measurements of the Earth or Moon (in CLEKF), and star tracker measurements (in ATTEKF). Simultaneously, the Kalman filters estimate error sources in the sensors, which are included in the state vectors as Exponentially Correlated Random Variables (ECRVs). This paper will summarize the performance of these filters during the Artemis-1 mission.
The effectivity of multichannel Wiener filters to improve images obtained with passive microwave systems was investigated by applying Wiener filters to passive microwave images of first-year sea ice. Four major parameters which define the filter were varied: the lag or pixel offset between the original and the desired scenes, filter length, the number of lines in the filter, and the weight applied to the empirical correlation functions. The effect of each variable on the image quality was assessed by visually comparing the results. It was found that the application of multichannel Wiener theory to passive microwave images of first-year sea ice resulted in visually sharper images with enhanced textural features and less high-frequency noise. However, Wiener filters induced a slight blocky grain to the image and could produce a type of ringing along scan lines traversing sharp intensity contrasts.
Abstract A large fraction of Type Ia supernova (SN Ia) observations over the next decade will be in the near-infrared (NIR), at wavelengths beyond the reach of the current standard light-curve model for SN Ia cosmology, SALT3 (∼2800–8700 Å central filter wavelength). To harness this new SN Ia sample and reduce future light-curve standardization systematic uncertainties, we train SALT3 at NIR wavelengths (SALT3-NIR) up to 2 μ m with the open-source model-training software SALTshaker , which can easily accommodate future observations. Using simulated data, we show that the training process constrains the NIR model to ∼2%–3% across the phase range (−20 to 50 days). We find that Hubble residual (HR) scatter is smaller using the NIR alone or optical+NIR compared to optical alone, by up to ∼30% depending on filter choice (95% confidence). There is significant correlation between NIR light-curve stretch measurements and luminosity, with stretch and color corrections often improving HR scatter by up to ∼20%. For SN Ia observations expected from the Roman Space Telescope, SALT3-NIR increases the amount of usable data in the SALT framework by ∼20% at redshift z ≲ 0.4 and by ∼50% at z ≲ 0.15. The SALT3-NIR model is part of the open-source SNCosmo and SNANA SN Ia cosmology packages.
Global ozone variations are evaluated by analyzing satellite measurements, using the technique of integrating out dynamical effects causing large variations in total ozone at individual locations. Analysis of Nimbus 4 reprocessed BUV data was extended to cover the period from April 1970 through December 1975. Temporal and latitudinal variation of biases and yearly change in global biases between the satellite and ground based ozone measurements are indicated. The bias-corrected 6-month-running filtered global means are shown, and the correlation coefficient between ozone and the solar activity index remains high at 0.94. It is concluded that the results give a strong indication of an ozone-solar activity relationship that is caused by solar UV variability.
Atmospheric Explorer C (AE-C) data are analyzed to study wavelike perturbations in the thermosphere at an altitude of about 260 km. Four geophysical parameters are analyzed. These are nitrogen and oxygen densities, electron density and ion temperature as measured by three different instruments on board AE-C. The data are processed by normalizing them to their average values and their fluctuations are obtained by passing the normalized data through a high pass filter. These fluctuations exhibit strong periodicities that persist throughout the records, regardless of the filter cutoff frequency. The fluctuations are cross correlated by direct comparison, by comparison of their spectral content as obtained by the MEM and FFT, and by computing cross correlation functions.
Preliminary MAGSAT scalar magnetic anomaly data of Africa, Europe, and adjacent marine areas were reduced to the pole assuming a constant inducing Earth's magnetic field of 60,000 nT. This process leads to a consistent anomaly data set free from marked variations in directional and intensity effects of the Earth's magnetic field over this extensive region. The resulting data are correlated with long wave length-pass filtered free-air gravity anomalies; regional heat flow, and tectonic data to investigate magatectonic elements and the region's geologic history. Magnetic anomalies are related to both ancient as well as more recent Cenozoic structural features.
Scalar aeromagnetic data obtained by the U.S. Naval Oceanographic Office (NOO) Vector Magnetic Survey of the conterminous U.S. were screened for periods of intense diurnal magnetic activity and reduced to anomaly form, filtered, and continued upward. A number of correlations between the NOO, POGO and preliminary MAGSAT data are evident at satellite elevations, including a prominent transcontinental magnetic high which extends from the Anadarko Basin to the Cincinnati Arch. The transcontinental magnetic high is breached by negative anomalies located over the Rio Grande Rift and Mississippi River Aulacogen. Differentially reduced-to-pole NOO and POGO magnetic anomaly data show that the transcontinental magnetic high corresponds to a well-defined regional trend of negative free-air gravity and enhanced crustal thickness anomalies.
Distributions of temperature dust, vapors, and condensates measured. Report describes design and intended uses of developmental pressure-modulator infrared readimeter, PMIRR, carried aboard Mars Observer spacecraft. Applies remote-sensing techniques used to study atmosphere of Earth. Takes similar measurements from polar orbit around Mars. Nine-channel atmospheric sounder that employs filter and pressure-modulation gas-correlation infrared radiometry.
The SMAP microwave radiometer will measure land surface brightness temperature at L-band (1413 MHz) in the presence of radio frequency interference (RFI) for soil moisture remote sensing. The radiometer design was driven by the requirements to incorporate internal calibration, to operate synchronously with the SMAP radar, and to mitigate the deleterious effects of RFI. The system design includes a highly linear super-heterodyne microwave receiver with internal reference loads and noise sources for calibration and an innovative digital signal processor and detection system. The front-end comprises a coaxial cable-based feed network, with a pair of diplexers and a coupled noise source, and radiometer front-end (RFE) box. Internal calibration is provided by reference switches and a common noise source inside the RFE. The RF back-end (RBE) downconverts the 1413 MHz channel to an intermediate frequency (IF) of 120 MHz. The IF signals are then sampled and quantized by high-speed analog-to-digital converters in the radiometer digital electronics (RDE) box. The RBE local oscillator and RDE sampling clocks are phase-locked to a common reference to ensure coherency between the signals. The RDE performs additional filtering, sub-band channelization, cross-correlation for measuring third and fourth Stokes parameters, and detection and integration of the first four raw moments of the signals. These data are packetized and sent to the ground for calibration and further processing. Here we discuss the novel features of the radiometer hardware particularly those influenced by the need to mitigate RFI.