SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
In November 2018, the Aerosol Engineering Facility measured the pressure drop of Speclon TM 5 air filter material at filter face velocities 0.067, 0.677, and 2.165 m/s. This is referred to as “New Speclon 5” (received in November 2018) for this document. For comparison, the pressure drop of “Speclon 5”filter (received in July 2018) was also measured at five different filter velocities between 0.067 m/s and2.165 m/s.
Continuing last year’s (fiscal year 2020) work, a Proof-of-Concept (POC) instrument was developed to assess the functionality of filters on transuranic waste containers (commonly called 55 Gallon ring-top drums) without requiring removal of the drum lid. The purpose of this work is to determine the air flow and pressure characteristics associated with filter clogging, filter pressure drop, headspace volume, leakage around the lid seal and influence of the additional filter on a bag-out bag.
This project explored “bio-mining” of critical materials from electronic waste (E-waste) streams by developing living filters arrays capable of recovering these materials, focusing on the platinum group metals (PGMs) and rare earth elements (REEs). While highly toxic, E-waste is considered a valuable “urban mine” as it contains critical materials such as PGMs and REEs with orders of magnitude higher purity than the richest ores. The aim of the project was to: (1) develop mechanically robust, silk-based biomaterial filtration membranes that can capture REEs from dilute aqueous waste; (2) design and build 3D bioprinted living filters containing encapsulated electrochemically active bacteria (EAB) capable of bio-reducing PGMs and recovering them from waste streams; and (3) constructing combined living filter arrays using both components to efficiently capture REE and PGM from the same waste stream. The developed silk-based filtration membranes were self-assembled using silk-nanofibrils (SNFs) derived from silkworm (Bombyx mori) cocoons in conjunction with recombinant silk-elastin-like proteins (SELPs), which contained lanthanide-binding peptide tags (LBTs) with a high affinity and specificity towards REEs. These 100% biodegradable protein-based membranes were capable of recovering up to 85% of model REE ions (Tb 3+ ) filtered through the membrane, with ~50% recovery achieved in the presence of high concentrations (100X) of common interfering metals (Ca 2+ , Cu 2+ , Fe 3+ , Zn 2+ ). REE captured by the membranes were easily recovered by applying a low pH desorption buffer. The membranes also demonstrated substantial reusability, with only a 30% loss in binding capacity after 4 cycles of REE binding and recovery. To recover the PGMs, we created a bottom-up assembling strategy to construct a living hydrogel composed of a seamlessly integrated living catalyst, Shewanella loihica PV-4 (PV-4), for metal reduction, and their structural and functional linkers, bio-reduced graphene oxide (B-rGO). This hydrogel demonstrated a close to 90% recovery of model metal ions, Pd, from a simulated e-waste leaching stream with minimum-to-no biomass production. It’s also worth noting that the Pd recovery is initiated immediately after the introduction of living hydrogel, compared to conventional biocarriers that required start-up times within hours to days. Overall, these living hydrogels demonstrated superior bioactivity, structural integrity, and agility over existing biocarriers, which offers extensive opportunities to advance the biological metal recovery with unparallel efficiency, reduced energy/material consumption, and minimal environmental impact.
Fireball observations from camera networks provide position and time information along the trajectory of a meteoroid that is transiting our atmosphere. The complete dynamical state of the meteoroid at each measured time can be estimated using Bayesian filtering techniques. A particle filter is a novel approach to modeling the uncertainty in meteoroid trajectories and incorporates errors in initial parameters, the dynamical model used, and observed position measurements. Unlike other stochastic approaches, a particle filter does not require predefined values for initial conditions or unobservable trajectory parameters. The Bunburra Rockhole fireball, observed by the Australian Desert Fireball Network (DFN) in 2007, is used to determine the effectiveness of a particle filter for use in fireball trajectory modeling. The final mass is determined to be 2.16±1.33 kg with a final velocity of 6030±216 m s{sup −1}, similar to previously calculated values. The full automatability of this approach will allow an unbiased evaluation of all events observed by the DFN and lead to a better understanding of the dynamical state and size frequency distribution of asteroid and cometary debris in the inner solar system.
The goal of the Event Horizon Telescope (EHT) is to provide spatially resolved images of Sgr A*, the source associated with the Galactic Center black hole. Because Sgr A* varies on timescales that are short compared to an EHT observing campaign, it is interesting to ask whether variability contains information about the structure and dynamics of the accretion flow. In this paper, we introduce “time-domain filtering,” a technique to filter time fluctuating images with specific temporal frequency ranges and to demonstrate the power and usage of the technique by applying it to mock millimeter wavelength images of Sgr A*. The mock image data is generated from the General Relativistic Magnetohydrodynamic (GRMHD) simulation and the general relativistic ray-tracing method. We show that the variability on each line of sight is tightly correlated with a typical radius of emission. This is because disk emissivity fluctuates on a timescale of the order of the local orbital period. Time-domain filtered images therefore reflect the model dependent emission radius distribution, which is not accessible in time-averaged images. We show that, in principle, filtered data have the power to distinguish between models with different black-hole spins, different disk viewing angles, and different disk orientations in the sky.
In this work, we analyze the global convergence properties of the filtered spherical harmonic (FPN) equations for radiation transport. The well-known spherical harmonic (PN) equations are a spectral method (in angle) for the radiation transport equation and are known to suffer from Gibbs phenomena around discontinuities. The filtered equations include additional terms to address this issue that are derived via a spectral filtering procedure. We show explicitly how the global $L^2$ convergence rate (in space and angle) of the spectral method to the solution of the transport equation depends on the smoothness of the solution (in angle only) and on the order of the filter. The results are confirmed by numerical experiments. Numerical tests have been implemented in MATLAB and are available online.
This paper discusses the Spitzer Instrument Pointing Frame (IPF) Kalman Filter algorithm. The IPF Kalman filter is a high-order square-root iterated linearized Kalman filter, which is parametrized for calibrating the Spitzer Space Telescope focal plane and aligning the science instrument arrays with respect to the telescope boresight. The most stringent calibration requirement specifies knowledge of certain instrument pointing frames to an accuracy of 0.1 arcseconds, per-axis, 1-sigma relative to the Telescope Pointing Frame. In order to achieve this level of accuracy, the filter carries 37 states to estimate desired parameters while also correcting for expected systematic errors due to: (1) optical distortions, (2) scanning mirror scale-factor and misalignment, (3) frame alignment variations due to thermomechanical distortion, and (4) gyro bias and bias-drift in all axes. The resulting estimated pointing frames and calibration parameters are essential for supporting on-board precision pointing capability, in addition to end-to-end 'pixels on the sky' ground pointing reconstruction efforts.
The Global Modeling and Assimilation Office is preparing to upgrade its three-dimensional variational system to a hybrid approach in which the ensemble is generated using a square-root ensemble Kalman filter (EnKF) and the variational problem is solved using the Grid-point Statistical Interpolation system. As in most EnKF applications, we found it necessary to employ a combination of multiplicative and additive inflations, to compensate for sampling and modeling errors, respectively and, to maintain the small-member ensemble solution close to the variational solution; we also found it necessary to re-center the members of the ensemble about the variational analysis. During tuning of the filter we have found re-centering and additive inflation to play a considerably larger role than expected, particularly in a dual-resolution context when the variational analysis is ran at larger resolution than the ensemble. This led us to consider a hybrid strategy in which the members of the ensemble are generated by simply converting the variational analysis to the resolution of the ensemble and applying additive inflation, thus bypassing the EnKF. Comparisons of this, so-called, filter-free hybrid procedure with an EnKF-based hybrid procedure and a control non-hybrid, traditional, scheme show both hybrid strategies to provide equally significant improvement over the control; more interestingly, the filter-free procedure was found to give qualitatively similar results to the EnKF-based procedure.
In this paper, we present a two-stage hybrid Kalman filter to estimate both observation and forecast bias in hydrologic models, in addition to state variables. The biases are estimated using the discrete Kalman filter, and the state variables using the ensemble Kalman filter. A key issue in this multi-component assimilation scheme is the exact partitioning of the difference between observation and forecasts into state, forecast bias and observation bias updates. Here, the error covariances of the forecast bias and the unbiased states are calculated as constant fractions of the biased state error covariance, and the observation bias error covariance is a function of the observation prediction error covariance. In a series of synthetic experiments, focusing on the assimilation of discharge into a rainfall-runoff model, it is shown that both static and dynamic observation and forecast biases can be successfully estimated. The results indicate a strong improvement in the estimation of the state variables and resulting discharge as opposed to the use of a bias-unaware ensemble Kalman filter. Furthermore, minimal code modification in existing data assimilation software is needed to implement the method. The results suggest that a better performance of data assimilation methods should be possible if both forecast and observation biases are taken into account.
Tunable mid-wave infrared (MWIR) filters are highly desirable in a wide variety of imaging and sensing, as the MWIR contains numerous spectral signatures. We fabricated spectrally-tunable Fabry-Perot bandpass filters operating across the MWIR by utilizing the phase-change material GeSbTe (GST) as a tunable cavity medium between distributed Bragg reflectors. The induced refractive index modulation of the GST increases the cavity’s optical path length, tuning the passband. Our filters have 300-nm spectral tunability, 60-75% transmission efficiencies, and 50-65 nm narrowband FWHMs (Q-factor 70-90). We demonstrate multispectral thermal imaging and dynamic gas sensing by matching the filter’s passband (~ 4.25μm) to a CO2 vibrational-absorption mode.
In this presentation, we introduce phase-change tunable filters (PCTFs), which are capable of actively tunable spectral filtering as well as continuous tuning (hyperspectral) across multiple IR wavebands (1–10 μm); several orders-of-magnitude faster switching speeds (GHz–MHz) than the state-of-the-art, and narrowband filtering (~50 nm passband). This technology subsystem is based on the unique electro-optics of non-volatile, phase-change materials (PCMs) such as GeSbTe and SbS. PCMs exhibit a large, reversible refractive index shift through applied energetic pulses. By integrating PCMs with established optical filter designs—whose optical properties are strongly dependent on the constituent materials’ refractive indices—we can rapidly and reversibly tune the PCTFs center wavelength (passband).
We have developed a suite of novel infrared-blocking filters made by embedding scattering particles in a polymer aerogel substrate. Our developments allow us to tune the spectral performance of the filters based on both the composition of the base aerogel material and the properties of the scattering particles. Our filters are targeted for use in a variety of applications, from ground-based CMB experiments to planetary science probes. We summarize the formulations we have fabricated and tested to date, including several polyimide base aerogel formulations incorporating a range of size distributions of diamond scattering particles. We also describe the spectral characterization techniques used to measure the filters’ optical properties, including the development o fa mm-wave Fourier transform spectrometer testbed.
Pilot Plant (WIPP) underground repository resulted in the release of americium and plutonium (mostly {sup 241}Am) into the environment and contaminated portions of the repository, primarily along the ventilation path from the location of the incident. The WIPP uses a ventilation system to ensure that underground air is circulated through the repository and to ensure that air quality conditions are safe for the workers. Since the air in the repository exits to the surface through an exhaust shaft, this shaft is the sole potential pathway for airborne radioactivity release from the repository. During normal operations before the 2014 incident, exhaust air was released to the environment unfiltered, with an automatic switch to filtration when airborne radioactivity was detected immediately down-stream from the active waste disposal operation. However, since the radiation release event, the WIPP ventilation system has been, and will likely remain in what is called 'filtration mode,' (i.e., exhaust air is routed through a HEPA filter system). Redirection of the ventilation system through the HEPA (High Efficiency Particulate Air) filter system was necessary at the peak of the radiation release event to protect aboveground workers at the site and the public in the surrounding areas; however, it has hampered recovery efforts and has exacerbated the inherent safety issues of working underground. As a component of the Carlsbad Environmental Monitoring and Research Center's (CEMRC) WIPP environmental monitoring program, airborne radioactivity samples are collected daily in the exhaust shaft ventilation air as it reaches the surface, and before entering the HEPA filters. Since June 2014, airborne radiation levels entering the HEPA filters have averaged about 1% of a derived air concentration (DAC) for {sup 241}Am. An airborne radioactivity level of one DAC is equivalent to a potential worker internal dose exposure of 50 mSv per work year, if a worker were continuously exposed for a full work year (2000 hours). During Project Reach and throughout decontamination campaigns conducted in Panel 7 for several months in 2015, these unfiltered levels rose to 3-5% of a DAC, with a one week spike reaching almost one DAC in June 2015, during decontamination of the most heavily contaminated exhaust drift in Panel 7. Since that period, the unfiltered levels have never exceeded 2% of a DAC. Going forward, the question is, should WIPP resume unfiltered discharge of its underground ventilation air? Evaluation of more than two years of underground ventilation sampling data indicates that residual radioactivity levels in the underground no longer warrant HEPA filtration in order to meet either worker or environmental protection criteria. In terms of radiological risk at or in the vicinity of the WIPP site, the increased risk from resuming unfiltered ventilation is exceedingly small and would not result in a hypothetical dose to a member of the public in excess of the 100 micro Sv per year limit for periodic confirmatory sampling as required for operating repositories by the Environmental Protection Agency (40 CFR 191). In addition, the requirement for respiratory protection for workers underground exposed to 1-2% of a DAC is questionable, given the added industrial safety risk of heavy equipment operation while wearing respirators. (authors)
In this paper, real-time fault detection and transient identification are studied with adaptive estimation methods, in particular parallel processing methods by implementing a bank of extended Kalman filters. Adaptive estimation is combined with probabilistic risk assessment to allow for real-time continuous monitoring of initiating events. The approach provides a probability of an initiating event happening. Real-time monitoring of initiating events can reduce labor demand. Each extended Kalman filter is configured to operate at a single configuration, either at normal operation or a faulted state. Fault detection is based on calculating a likelihood function for each extended Kalman filter to determine the posteriori conditional probability that the system configuration is the true configuration. The transient identification is determined by performing a multivariate statistical analysis on each extended Kalman filter to provide a posterior probability assessment that the reactor states and its dynamics are within the allowable limits. The probability distribution being outside the allowable limits indicate a transient has occurred. The combination of parallel processing methods with the multivariate statistical analysis for transient identification allows for the operator to perform transient identification with having a high level of certainty of the current system configuration. We demonstrate the real-time fault detection and transient identification on a simple reactor example to determine the reactor power, reactor temperature, and coolant temperature in the presence of various faults. (authors)
This study deals with the design of low-power, high performance, continuous-time filters. The proposed OTA architecture employs current-reuse differential difference amplifiers in order to produce more power efficient Gm-C filter solutions. To demonstrate this, a 6th order low-pass Butterworth filter was designed in 0.18 m CMOS achieving a 65-MHz -3-dB frequency, an in-band input-referred third-order intercept point of 12.0 dBm, and an input referred noise density of 40 nV/Hz1=2, while only consuming 8.07 mW from a 1.8 V supply and occupying a total chip area of 0.21 mm2 with a power consumption of only 1.19 mW per pole.
We demonstrate experimentally a tunable third-order optical filter fabricated from the three voltage-controlled lithium niobate whispering gallery-mode resonators. The filter operates at 1550 nm with 30-MHz bandwidth and can be electrooptically tuned by 12 GHz in the linear regime with approximately 80-MHz/V tuning rate. With this filter, we have demonstrated 6-dB fiber-to-fiber insertion loss and 30-ns tuning speed, limited by the resonator buildup time.
The terahertz magnetize-field tunable filtering properties in a multichannel filter based on a one-dimensional photonic crystal doped by magnetized plasma are theoretically investigated. The considered structure of (AB){sub 4}(ACB){sub N}(AB){sub 4} is designed, where A and B are two dielectric layers, C is the plasma layer, and N is the defect number. First, the structure can be worked as a multichannel filter whose channel number equals N. Second, the defect mode frequencies are all red-shifted as the ratio of dielectric refractive index or the sum of the A and B layer length increases. Third, we find that the channel frequencies can be shifted as a function of the applied magnetic field and the defect mode frequencies are all red-shifted as the plasma density increases. And the thickness of a plasma layer also affects the intensity, position and number of the defect modes. Therefore, these unusual properties may provide a novel design idea of a tunable terahertz multichannel transmission filter in future.
The second derivative image (SDI) method is uniformly applied to sharpen dispersive data features in multi-dimensional spectroscopies such as angle resolved photoemission spectroscopy (ARPES). In this work, the SDI function is represented in Fourier space, where it has the form of a multi-band pass filter. The interplay of the SDI procedure with undesirable noise and background features in ARPES data sets is reviewed, and it is shown that final image quality can be improved by eliminating higher Fourier harmonics of the SDI filter. Furthermore, we discuss extensions of SDI-like band pass filters to higher dimensional data sets, and how one can create even more effective filters with some a priori knowledge of the spectral features.