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NASA NTRS2008

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↗

NASA NTRS2019

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.↗

NASA NTRS2019

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↗

NASA NTRS2019

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.↗

NASA NTRS2020

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↗

NASA NTRS2020

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↗

NASA NTRS2023

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↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

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

sonic booms↗

NASA NTRSDate not supplied

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↗

NASA NTRS2024

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↗

DOE OSTI2015

High exhaust temperature, zoned, electrically-heated particulate matter filter

A system includes a particulate matter (PM) filter, an electric heater, and a control circuit. The electric heater includes multiple zones, which each correspond to longitudinal zones along a length of the PM filter. A first zone includes multiple discontinuous sub-zones. The control circuit determines whether regeneration is needed based on an estimated level of loading of the PM filter and an exhaust flow rate. In response to a determination that regeneration is needed, the control circuit: controls an operating parameter of an engine to increase an exhaust temperature to a first temperature during a first period; after the first period, activates the first zone; deactivates the first zone in response to a minimum filter face temperature being reached; subsequent to deactivating the first zone, activates a second zone; and deactivates the second zone in response to the minimum filter face temperature being reached.

42 ENGINEERING↗

DOE OSTI2017

Tunable electro-optic filter stack

A holographic polymer dispersed liquid crystal (HPDLC) tunable filter exhibits switching times of no more than 20 microseconds. The HPDLC tunable filter can be utilized in a variety of applications. An HPDLC tunable filter stack can be utilized in a hyperspectral imaging system capable of spectrally multiplexing hyperspectral imaging data acquired while the hyperspectral imaging system is airborne. HPDLC tunable filter stacks can be utilized in high speed switchable optical shielding systems, for example as a coating for a visor or an aircraft canopy. These HPDLC tunable filter stacks can be fabricated using a spin coating apparatus and associated fabrication methods.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Tunable electro-optic filter stack

Fontecchio, Adam K.↗

DOE OSTI2018

Optimization study of B4C filter thickness for shifting to fast spectrum at experimental position in NRAD core

The Japan Atomic Energy Agency (JAEA) has investigated an accelerator-driven system (ADS) to transmute minor actinides (MAs) partitioned from the high level waste. In the nuclear transmutation system such as the ADS, the nuclear data validation of MA is required to reduce the uncertainty caused by the nuclear data of MA. In order to validate the nuclear data, many independent experimental data need to be mutually compared. The Idaho National Laboratory (INL) considers the measurement of fission rate ratio and sample worth with a wide spectral indices by inserting several types of thermal neutron shielding filters in the experimental position in Neutron RADiography (NRAD) which is the thermal neutron reactor. The JAEA has a plan to perform integral experiments with fission chambers in the NRAD because of the expansion of the experimental data contributing to nuclear data validation of MA. In this study, the optimization of the NRAD core configuration, the B4C filter thickness, and the experimental position design was conducted to acquire the high-accuracy and the beneficial experimental data by using MCNP 6.1 and ENDF/B-VII.1. First, by locating the experimental position as close to the center of the core as possible and concentrating the fuel around that position, the neutron flux of the optimized model could be constructed 2.5 times as much as that of the previous model. Second, the optimized B4C filter thickness was determined to be 3mm based on the comprehensive evaluation from the viewpoints of the shielding ability of low energy neutrons, the level of the total neutron flux, and the influence of fabrication accuracy of the B4C filter. Third, we constructed the experimental position model that could further reduce the influence of the low energy neutrons by adopting the aluminum dry box and the bottom filter. Moreover, the neutron energy spectrum of the tentative optimized model constructed by following the above results was compared with that of the fast neutron reactors such as the ADS and the Fast Critical Assembly (FCA). As a result, the tentative optimized model would be able to be obtained the beneficial experimental data for the verification of FCA-IX series data and the validation of MA nuclear data for accuracy improvement of ADS design. Furthermore, the adoption of the tentative optimized model would be acquired the experimental data such as fission reaction rate and sample worth with the wider spectral indices than the previous one because the tentative optimized model would be able to increase the ratio of the fast neutrons by almost completely eliminating the effect of the thermal neutrons.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗