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At least 487 records · Page 27

Compact Planar Microwave Blocking Filter

This paper proposes a technique to design a compact planar broadband microwave blocking filter. The filter is constructed from multiple sections of bandstop filters with means to control radiation loss. As a result, the filter has small physical size and provides multi-decade of suppression frequency bandwidth. The total length is less than half-wavelength long at the 3-dB corner frequency of 1.45 GHz. The experimental results show that the microstrip microwave blocking filter can provide an attenuation of more than 70 dB from 7 GHz to 39.5GHz with the total DC capacitance of les than 23 pF.

U-yen, Kongpop↗

High-Order Finite-Difference Nonlinear Filter Methods for Subsonic Turbulence Simulation with Stochastic Forcing

Numerical stability of high-order filter schemes developed by Yee & Sjogreen is tested on three-dimensional turbulence simulations with stochastic forcing and their performance is compared with that of TVD and WENO schemes. The best­ performing filter method employs an eighth-order central base scheme with the Kennedy & Gruber skew-symmetric splitting of the inviscid flux derivative, a wavelet-based local flow sensor, a nonlinear filter utilizing the dissipative portion of seventh-order \VENO scheme, and an explicit third - or fourth-order Runge­-Kutta time integration. We show that the filter scheme is more computational]y efficient and provides a wider spectral bandwidth compared to the seventh-order WENO scheme. The method also demonstrates robust long-time integration for moderately compressible turbulence. In contrast, the fifth- and seventh­ order WENO schemes show non-trivial evolution of the velocity and density power spectra. over a. few dozen dynamical times, where both TVD and filter schemes recover a so lid statistically stationary turbulent state

Kritsuk, Alexei G.↗

Effect of Spatial Filtering in Implicit Large-Eddy Simulations of Separated Flows

The relatively high Reynolds number of turbulent flows encountered in various applications puts these problems well beyond the reach of direct numerical simulation (DNS) at present. Meanwhile, lower-fidelity Reynolds-averaged Navier-Stokes (RANS) calculations are known to be not accurate enough in complex problems, such as smooth-body flow separation and other flows involving highly-unsteady phenomena. Hence, given the current infeasibility of DNS and the unsatisfactory performance of RANS, intermediate techniques such as large-eddy simulation (LES) and hybrid RANS-LES, whose fidelity lie between RANS and DNS, have received much attention for application to various problems of practical importance. Modeling of the effect of missing scales on resolved scales, also known as subgrid-scale (SGS) modeling, is an important subject for LES. SGS models can be broadly categorized as explicit or implicit approaches. The explicit approach is based on an SGS model that explicitly appears in the governing equations expressed in the form of so-called “filtered Navier-Stokes equations”, which describe the evolution of the turbulence scales resolved by the LES grid. The effect of the scales unresolved by the grid is represented by the SGS model. The implicit modeling approach, on the other hand, does not employ an explicit model but instead treats the intrinsic dissipation of the numerical discretization scheme as an implicit SGS model. An LES without an explicit SGS model is commonly termed as an implicit LES (ILES). The relative merits of one SGS modeling approach over another is a subject of ongoing debate. We have opted to employ an ILES methodology, based on high-order compact finite-difference and spatial filtering schemes, in our recent investigations of separated flow problems [1, 2]. Further discussion of our preference of ILES over explicit LES is provided in Uzun and Malik [2]. The spatial filtering operation, described in the next section, is treated as an implicit SGS model for the ILES. Some observations made during the course of our recent investigations, which pointed out to excessive numerical dissipation in certain parts of the flowfield, prompted us to take a closer look at the potential effect of the spatial filter on ILES predictions. This technical note is therefore devoted to spatial filter effects in the context of a high Reynolds number, transonic shock-induced separated flow.

Ali Uzun↗

Using Computational Flow Imaging to Optimize Filtered Rayleigh Scattering Measurements of an Isolator Shock Train

Filtered Rayleigh scattering (FRS) is a laser diagnostic where the intensity of elastically scattered light is measured after it passes through a molecular absorption filter. The filter removes background interference that overwhelms the relatively weak scattering from the gas molecules. However, with a filter, the measured light intensity depends on many of the scattering gas properties, including pressure, density, temperature, and velocity. In this work, CFD simulations of an isolator shock train flow field are input into a physics-based model to predict the values of FRS intensity measurements in a proposed experiment. The goal is to evaluate if a simplistic FRS setup (that utilizes one camera, laser, and absorption filter) can be used to accurately quantify number density despite the fact that the scattered light intensity also depends on other gas properties. It is found that the experimental setup can be optimized such that a linear relationship describes the number density with an average prediction error of 2%. The vast majority of the flow exhibits prediction errors of less than 3%, but small regions of the flow reach up to 11% error. A sensitivity analysis shows that the prediction error increases with the central wavelength of the incident laser light and decreases with the angle between the camera and laser propagation directions. The optimal experimental parameters are chosen based on a compromise between the prediction error, spatial resolution, and the amount of unfiltered light. In the future, the proposed FRS setup will be implemented to acquire new and valuable information on an isolator shock train, a flow field that has been traditionally studied using wall static pressure measurements and path-integrated visualization techniques, such as schlieren and shadowgraphy.

Hunt, Robin L.↗

Development Requirements for the Exploration PLSS (xPLSS) Thermal Loop Filter

The fluid thermal control loop and auxiliary thermal control loop contain multiple filters including the Thermal Filters (F-448/F-548), which are used to scrub precipitates and biofilms from the cooling loops in order to protect components that may be sensitive to such contamination. The F-448/F-548 filters are comprised of multiple machined piece parts to create the filter housing as well as the removable pressure cap assembly to allow for the thermal filter cartridge replacement.

Kristina Noelle Todd↗

Design of high-transmission plasmonic wavelength and polarization filters for infrared photodetectors

We have designed plasmonic filters that simultaneously perform wavelength and polarization filtering in the wavelength range 3-5 micrometers. In this work we outline the design and present the simulated results of our filters. The filters consist of sub wavelength slits in a thin metal sheet which is deposited on top of a gallium antimonide (GaSb) substrate and a spacer layer of SiO2. This configuration makes our filters suitable for integration with GaSb based infrared photodetectors and photodetector arrays that are used in space applications. Our work opens up the possibility of using these detector arrays for highly compact Earth-observing infrared polarimeters and multispectral imaging applications.

Wenger, Tobias↗

Non-Gaussian Ensemble Filtering and Adaptive Inflation for Soil Moisture Data Assimilation

The rank histogram filter (RHF) and the ensemble Kalman filter (EnKF) are assessed for soil moisture estimation using perfect model (identical twin) synthetic data assimilation experiments. The primary motivation is to gauge the impact on analysis quality attributable to the consideration of non-Gaussian forecast error distributions. Using the NASA Catchment land surface model, the two filters are compared at 18 globally-distributed single-catchment locations for a 10-year experiment period. It is shown that both filters yield adequate estimates of soil moisture, with the RHF having a small but significant performance advantage. Most notably, the RHF systematically increases the normalized information contribution (NIC) score of the mean absolute bias by 0.05 over that of the EnKF for surface, root-zone and profile soil moisture. The RHF also increases the NIC score for the anomaly correlation of surface soil moisture by 0.02 over that of the EnKF (at a 5% significance level). Results also demonstrate that the performance of both filters is somewhat improved when the ensemble priors are adaptively inflated to offset the negative effects of systematic errors.

Soil moisture↗

Development of Challenge Aerosols for Testing Filters in Spacecraft Air Revitalization Systems

The common means for reducing particle concentrations in air in enclosed spaces, including in space habitats, are source prevention and particle removal by air filters. While air filtration and testing is a well-established discipline and industry, testing and classifying filters according to commonly used standards rely on a test aerosol that is often arbitrary and chosen for the convenience of the test method. In space habitats, the particle size distributions are expected to be quite different than the particle size distributions prescribed in test standards, due to the partial or low gravity environment affecting sedimentation of large particulates like hair or cloth fibers, or the introduction of planetary dust to the pressurized volume. This means that the efficacy of the filter will be quite different in the space habitat than specified according to a prevailing standard. This paper will present a means to specify and generate a “composite” test aerosol that is similar to the measured and reported particle sizes utilizing the International Space Station (ISS) as an example. Application of this test aerosol is expected to yield filter efficiencies and loading effects closer to what one can expect on the ISS and to be useful in determining filter lifetime and replacement cycles. The method can be tuned, within reason, to match other particle size distributions one may encounter, such as the intrusion of Lunar dust for a Lunar lander or habitat.

Filtration↗

Hybrid Flush and Synthetic Air Data Filter for Entry Vehicle Atmospheric State Estimation

A hybrid flush/synthetic air data sensing filter utilizing Kalman-Schmidt and Rach-Tung-Striebel smoothers is developed to obtain entry vehicle atmosphere estimates. The filter/smoother blends information from pressure sensors distributed on the heatshield with measurements of the vehicle aerodynamic forces and moments computed from mass properties and inertial measurement unit data, and prior estimates of the atmosphere. The filter produces estimates of the atmospheric conditions along the entry trajectory, and systematic error estimates to reconcile differences between the pressure and aerodynamic data sources. The filter is applied to data acquired during the Mars Science Laboratory and Mars 2020 entry, descent, and landing at Gale crater and at Jezero crater, respectively. The results show that the hybrid filter produces estimates of the freestream flight condition with lower uncertainty than either the flush or synthetic air data algorithms. The filter accomplishes this result by incorporating additional data and computing estimates of systematic error parameters in the pressure data and the aerodynamic model to further reduce the uncertainties.

Christopher D. Karlgaard↗

An Efficient Filter for Measurements Corrupted with Cauchy Noise

This paper present a new sequential filter for state estimation using measurements corrupted with Cauchy noise. The new filter retains the familiar structure of the Kalman filter and is computationally efficient. In addition, it does not exhibit computational complexity which grows or varies in time like existing methods. These results are based upon a nearly 50 year old result by Masreliez in which the conditional mean estimator is approximated via linearization of the measurement predictive density. This work derives the new filter, provides discussion regarding practical implementation, and present Monte Carlo analyses to validate and assess the new filter's performance.

James S McCabe↗

Evaluation of Finite Impulse Response Filters for Turbulence Effects on Sonic Booms

Turbulence effects on sonic booms lead to random variability of sonic boom waveforms measured on the ground, complicating the prediction of such waveforms using sonic boom propagation codes that do not account for turbulence effects. The NASA PCBoom software is one such code shown to accurately predict sonic booms above the atmospheric boundary layer but not those on the ground. Analyses of measured sonic booms show that, on average, the turbulence effects result in sonic boom loudness reduction, on average, that increases with propagation distance and turbulence strength. To efficiently account for such effects, a signal processing-based approach has been developed at NASA using finite impulse response filters derived from predicted waveforms by solving a nonlinear parabolic equation. Analyses indicate that the mean loudness reduction obtained using the filters does not increase with propagation distance or with increasing turbulence strength, in disagreement with flight test data. An alternative approach to the filters is currently under development employing the multiple scattering theory (MST) of wave propagation. Available results from the physics-based MST approach are used to evaluate the predictive capability of the filters, suggesting that the filters can severely underestimate the prediction of the MST approach.

sonic booms↗

Evaluation of Finite Impulse Response Filters for Turbulence Effects on Sonic Booms

Turbulence effects on sonic booms lead to random variability of sonic boom waveforms measured on the ground, complicating the prediction of such waveforms using sonic boom propagation codes that do not account for turbulence effects. The NASA PCBoom software is one such code shown to accurately predict sonic booms above the atmospheric boundary layer but not those on the ground. Analyses of measured sonic booms show that, on average, the turbulence effects result in sonic boom loudness reduction, on average, that increases with propagation distance and turbulence strength. To efficiently account for such effects, a signal processing-based approach has been developed at NASA using finite impulse response filters derived from predicted waveforms by solving a nonlinear parabolic equation. Analyses indicate that the mean loudness reduction obtained using the filters does not increase with propagation distance or with increasing turbulence strength, in disagreement with flight test data. An alternative approach to the filters is currently under development employing the multiple scattering theory (MST) of wave propagation. Available results from the physics-based MST approach are used to evaluate the predictive capability of the filters, suggesting that the filters can severely underestimate the prediction of the MST approach.

sonic booms↗

Non-Gaussian Ensemble Filtering and Adaptive Inflation for Soil Moisture Data Assimilation

The rank histogram filter (RHF) and the ensemble Kalman filter (EnKF) are assessed for soil moisture estimation using perfect model (identical twin) synthetic data assimilation experiments. The primary motivation is to gauge the impact on analysis quality attributable to the consideration of non-Gaussian forecast error distributions. Using the NASA Catchment land surface model, the two filters are compared at 18 globally distributed single-catchment locations for a 10-yr experiment period. It is shown that both filters yield adequate estimates of soil moisture, with the RHF having a small but significant performance advantage. Most notably, the RHF consistently increases the normalized information contribution (NIC) score of the mean absolute bias by 0.05 over that of the EnKF for surface, root-zone, and profile soil moisture. The RHF also increases the NIC score for the anomaly correlation of surface soil moisture by 0.02 over that of the EnKF (at a 5% significance level). Results additionally demonstrate that the performance of both filters is somewhat improved when the ensemble priors are adaptively inflated to offset the negative effects of systematic errors.

Rolf Reichle↗

AC and DC Fault Management for Megawatt Electrified Aircraft Electrical Powertrains - Task 2: Power Quality Filtering Using Nanocrystalline Soft Magnetic Inductor

The NASA RTAPS program on AC and DC Fault Management for Megawatt Electrified Power Train is a multi-year joint project with Pratt & Whitney (P&W), Collins Aerospace (CA), and RTX Technology Research Center (RTRC). This research program focuses on the high-voltage distribution issues that present a significant technological obstacle in the adoption of Electrified Aviation Propulsion (EAP) systems. One challenge to the adoption of high-voltage distribution systems with power electronic converters is the need for filter elements to limit the generation and propagation of noise, protect the cable systems from premature aging and prevent against excessive heating within subcomponents due to high-frequency induced currents. While increased distribution voltages aide in reducing the cable mass for a fixed power system, the associated mass with the filtering elements for power electronic converter can grow with increasing distribution voltages – thereby mitigating any benefit associated with increasing the distribution system voltage. To enable high-voltage distribution systems with high system specific power densities, new magnetic materials must be developed. Therefore, the second task of the NASA RTAPS program is associated with the design and application of advanced soft magnetic components for Megawatt class electric propulsion systems, specifically the motor drive system. This report covers the collaborative work between NASA Glenn Research Center (GRC), RTRC, P&W and CA in the development of three types of magnetic components over the span of the three-year program. These critical magnetic components are the DC side EMI filter, which limits the propagation of harmful electromagnetic noise to the rise of the distribution system, and the AC side damping with the dv/dt filter, which limits the fast rise time of the power electronic converter output voltage to limit the degradation on the cable/motor insulation systems. Each of these components are investigated from component level design and are optimized at the system level with a combined modelling and testing effort. In the final experimental evaluation of the NASA developed soft magnetic material with a dv/dt filter, a commercial-off-the-shelf (COTS) magnetic core and the GRC magnetic core are optimized and loaded at 320Arms to evaluate their difference in performance. After a run time of 30 minutes in a MW-class motor driver at RTRC, the NASA GRC cores were found to not only offer a lower temperature rise of nearly 25°𝐶, but also a reduction in measured core loss of 25% (12.75W to 9.5W).

Elecrified Aircraft Propulsion↗

Communication device, spread-spectrum receiver, and related method using normalized matched filter for improving signal-to-noise ratio in harsh environments

A communication device, a method of operating a communication device, and a spread-spectrum receiver are disclosed. The method includes receiving an incoming RF signal, demodulating the incoming RF signal to generate a baseband signal, filtering the baseband signal with a normalized matched filter having filter characteristics matched to a pulse-shaping filter of the transmitter that generated the incoming RF signal, and extracting a received signal from a normalized output generated by the normalized matched filter. As a result, interferences and noise from harsh environments may be suppressed.

42 ENGINEERING↗

Complementary reverse order filters

In example implementations, an apparatus is provided. The apparatus includes an optical transmission component and an optical reception component. The optical transmission component includes a plurality of lasers and a transmit filter. The plurality of lasers each emit a different wavelength of light. The transmit filter includes a plurality of different regions that correspond to one of the different wavelengths of light emitted by the plurality of lasers. The optical reception component includes a plurality of photodiodes and a complementary reverse order (CRO) filter. The CRO filter includes a same plurality of different regions as the transmit filter in a reverse order.

42 ENGINEERING↗

Filtering micro-operations for a micro-operation cache in a processor

A processor includes a micro-operation cache having a plurality of micro-operation cache entries for storing micro-operations decoded from instruction groups and a micro-operation filter having a plurality of micro-operation filter table entries for storing identifiers of instruction groups for which the micro-operations are predicted dead on fill if stored in the micro-operation cache. The micro-operation filter receives an identifier for an instruction group. The micro-operation filter then prevents a copy of the micro-operations from the first instruction group from being stored in the micro-operation cache when a micro-operation filter table entry includes an identifier that matches the first identifier.

Scrbak, Marko↗

In-Band Scattering and Absorption of Infrared Blocking Foam Filters for Millimeter-wave Cameras

Expanded closed-cell polymer foams are widely used as thermal infrared (IR) blocking filters in millimeter-wave cameras, particularly for Cosmic Microwave Background observations. Precise knowledge of their millimeter-wave properties is essential for optimizing sensitivity. We present broadband (150 GHz - 2 THz) transmittance spectroscopy of Styroace-II and several Zotefoam filters, fitting their spectra with a radiative transfer model incorporating dielectric absorption and Rayleigh, Mie, and higher-order scattering. For a typical 5~cm thick filter stack at 280~GHz, Styroace-II exhibits ${\sim}10\%$ scattering with absorption estimated as ${\lesssim}5\%$ by effective-medium theory, while Zotefoam HD30 offers superior performance at ${\sim}3\%$ scattering and absorption likewise bounded to ${{\lesssim}0.3\%}$. Each model component is constrained at the ${\sim}0.1\%$ transmittance level for millimeter wavelengths. We observe batch-to-batch scattering variability of up to 2 percentage points in foams with multiple tested batches. Less commonly used Zotefoam formulations (LD15 and LD24) can further reduce in-band scattering to ${<}1\%$ while maintaining negligible in-band absorption and likely comparable IR blocking due to shared polyethylene absorption features and similar cell sizes. Based on this work, a filter constructed from the best measured LD24 batch has replaced the Styroace-II filter in a Simons Observatory 220/280 GHz Small Aperture Telescope.

Thomas, Alex [Chicago U., Astron. Astrophys. Ctr.;↗