Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “filtering”

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.

At least 1,459 records · Page 81

Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems

Complex engineering systems pose fundamental challenges in real-time operations and control because they are highly dynamic systems consisting of a large number of elements with severe nonlinearities and discontinuities. Today’s tools for real-time complex system operations are mostly based on steady state models, unable to capture the dynamic nature and too slow to prevent system failures. We developed advanced Kalman filtering techniques and the formulation of dynamic state estimation using Kalman filtering techniques to capture complex system dynamics in aiding real-time operations and control. In this work, we looked at complex system issues including severe nonlinearity of system equations, discontinuities caused by system controls and network switches, sparse measurements in space and time, and real-time requirements of power grid operations. We sought to bridge the disciplinary boundaries between Computer Science and Power Systems Engineering, by introducing methods that leverage both existing and new techniques. While our methods were developed in the context of electrical power systems, they should generalize to other large-scale scientific and engineering applications.

97 MATHEMATICS AND COMPUTING↗

HEPA Filter Disposal Write-Up 10/19/16

Process knowledge (PK) collection on HEPA filters is handled via the same process as other waste streams at LLNL. The Field technician or Characterization point of contact creates an information gathering document (IGD) in the IGD database, with input provided from the generator, and submits it for electronic approval. This document is essentially a waste generation profile, detailing the physical, chemical as well as radiological characteristics, and hazards, of a waste stream. It will typically contain a general, but sometimes detailed, description of the work processes which generated the waste. It will contain PK as well as radiological and industrial hygiene analytical swipe results, and any other analytical or other supporting knowledge related to characterization. The IGD goes through an electronic approval process to formalize the characterization and to ensure the waste has an appropriate disposal path. The waste generator is responsible for providing initial process knowledge information, and approves the IGD before it routed to chemical and radiological waste characterization professionals. This is the standard characterization process for LLNL-generated HEPA Filters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

CFD Analysis of RLUOB Zone 1 HEPA Filter Plenum and Testing Manifolds

The purpose of this computational fluid dynamics (CFD) analysis is to ensure that Camfil Farr’s upstream and downstream injection and sampling manifolds can meet or exceed the requirements outlined in the ASME AG-1 1997 a(2000) Code on Nuclear Air and Gas Treatment for the testing of HEPA and adsorbent filters. This paper will present a numerical simulation of airflow in the Radiological Laboratory Utility Office Building (RLUOB) zone 1 HEPA filter plenum and testing manifolds using the commercial CFD software ANSYS FLUENT 2020R1. The CFD analysis focuses on the investigation of the air flow distribution and air-aerosol mixing uniformity. The evaluation was done for all steps of the modeling process: grid generation, physics setup, simulation, and post-processing. The mass flow rate in each section of the zone 1 injection and sampling manifolds is also reported.

42 ENGINEERING↗

Earth Filter Mathematica Toolbox V4 User’s Guide: Simplifying, Visualizing and Quick Modeling of All Fission Products from 60 Nuclear Sources

The Earth Filter Mathematica toolbox is a set of user-friendly routines that accurately calculate the ingrowth and decay of any of the 908 fission products for an infinite combination of sources over a large dynamic range and large time scales. This toolbox was developed by Dr. W. P. Brug at Los Alamos National Laboratory and eliminates the need for the user to define and solve differential equations by automatically scanning the ENDF-349 dataset and creating a complete set of differential equations (including delayed neutron branches to both the ground and metastable states) for every fission product. Additionally, this code allows the user to choose the data source for half-lives from several key references (i.e., TORI, IAEA, ENDF or NUDAT.) The complete set of ENDF-349 independent and cumulative fission yields for all 60 isotopic targets and 4 different neutron spectrums are included. This allows nearly any nuclear fission source to be accurately modeled as a linear combination of endpoint sources. The Earth Filter Toolbox has no limit as to the length of split list, and split lists of 5 or more endpoint sources can be quite common.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Theory-Guided Autoencoders

Data assimilation is a Bayesian inference process that obtains an enhanced understanding of a physical system of interest by fusing information from an inexact physics-based model, and from noisy sparse observations of reality. The multifidelity ensemble Kalman filter (MFEnKF) recently developed by the authors combines a full-order physical model and a hierarchy of reduced order surrogate models in order to increase the computational efficiency of data assimilation. The standard MFEnKF uses linear couplings between models, and is statistically optimal in case of Gaussian probability densities. This work extends the MFEnKF into to make use of a broader class of surrogate model such as those based on machine learning methods such as autoencoders non-linear couplings in between the model hierarchies. We identify the right-invertibility property for autoencoders as being a key predictor of success in the forecasting power of autoencoder-based reduced order models. We propose a methodology that allows us to construct reduced order surrogate models that are more accurate than the ones obtained via conventional linear methods. Numerical experiments with the canonical Lorenz'96 model illustrate that nonlinear surrogates perform better than linear projection-based ones in the context of multifidelity ensemble Kalman filtering. We additionality show a large-scale proof-of-concept result with the quasi-geostrophic equations, showing the competitiveness of the method with a traditional reduced order model-based MFEnKF.

97 MATHEMATICS AND COMPUTING↗

Detecting Proxima b’s Atmosphere with JWST Targeting CO{sub 2} at 15 μ m Using a High-pass Spectral Filtering Technique

Exoplanet Proxima b will be an important laboratory for the search for extraterrestrial life for the decades ahead. Here, we discuss the prospects of detecting carbon dioxide at 15 μ m using a spectral filtering technique with the Medium Resolution Spectrograph (MRS) mode of the Mid-Infrared Instrument (MIRI) on the James Webb Space Telescope ( JWST ). At superior conjunction, the planet is expected to show a contrast of up to 100 ppm with respect to the star. At a spectral resolving power of R = 1790–2640, about 100 spectral CO{sub 2} features are visible within the 13.2–15.8 μ m (3B) band, which can be combined to boost the planet atmospheric signal by a factor of 3–4, depending on the atmospheric temperature structure and CO{sub 2} abundance. If atmospheric conditions are favorable (assuming an Earth-like atmosphere), with this new application to the cross-correlation technique, carbon dioxide can be detected within a few days of JWST observations. However, this can only be achieved if both the instrumental spectral response and the stellar spectrum can be determined to a relative precision of ≤1 × 10{sup −4} between adjacent spectral channels. Absolute flux calibration is not required, and the method is insensitive to the strong broadband variability of the host star. Precise calibration of the spectral features of the host star may only be attainable by obtaining deep observations of the system during inferior conjunction that serve as a reference. The high-pass filter spectroscopic technique with the MIRI MRS can be tested on warm Jupiters, Neptunes, and super-Earths with significantly higher planet/star contrast ratios than the Proxima system.

79 ASTRONOMY AND ASTROPHYSICS↗

Investigation of Lubricant Additive Interactions on Gasoline Particulate Filters

To understand how the composition of novel lubricant additives and their ash interact with gasoline particulate filters (GPFs), an accelerated aging protocol was conducted using three lubricant additive formulations and two GPF types. The additive packages (adpaks) consisted of Ca+Mg detergent in a 3:1 or 0:1 ratio and an anti-wear component—either zinc dialkyl dithiophosphate (ZDDP) or a novel phosphonium-phosphinate ionic liquid (IL) substitute. The particulate sampling captured amount/compositions of particulate matter (PM) generated, total particulate number, and size distribution. Five ash loadings were completed. GPF position and adpak composition affected the backpressure, ash composition, ash morphology, and captured mass. The particulate sampling indicated that the ash component consisted primarily of particles less than 50 nm in size and that the Mg-only adpak resulted in more particulate of 50–400 nm in size. Postmortem materials characterization indicated GPFs in the underfloor position had deeper penetration of ash into the walls compared to the close-coupled position. Additionally, the Mg-only adpak had a higher filter collection efficiency (>90%) and the ash particles consisted of a higher concentration of dense ash material. In contrast, four of the 3:1 Ca:Mg lubricant adpaks resulted in a collection efficiency of only 40–50%. Although the collection efficiency was higher with the Mg-only adpak, the ash layer in the GPF was not thicker, nor was the penetration into the wall more significant, and surprisingly the full useful life (FUL) backpressure was lower than with Ca:Mg adpaks. The higher density of the Mg-derived ash was the only detectable difference. A possible explanation of this observation is that Mg ash has a lower melting point and is more susceptible to densification during combustion or GPF regeneration. The substitution of IL in place of the ZDDP did not lead to any notable changes in collection efficiency or location of the ash.

42 ENGINEERING↗

Miniature low-pass filter in low-loss 9k7 LTCC

DuPont 9k7 low-temperature cofired ceramic (LTCC) is a low-loss, or high-quality-factor Q, tape system targeting at radio frequency (RF) applications. This paper reports on the effect of a critical process parameter, the heating rate, on the densification and dielectric properties of the 9k7 LTCC. The role of competing densification and crystallization during the sintering of 9k7 is discussed. The high Q of DuPont 9K7 can be used to improve RF system performance, for example a better receiver noise figure, by designing embedded passive RF components such as inductors, capacitors and filters. Furthermore, miniaturized multilayer low-pass filters (LPF) with a wide stopband were fabricated to showcase the technology.

36 MATERIALS SCIENCE↗

A stochastic covariance shrinkage approach to particle rejuvenation in the ensemble transform particle filter

Rejuvenation in particle filters is necessary to prevent the collapse of the weights when the number of particles is insufficient to properly sample the high-probability regions of the state space. Rejuvenation is often implemented in a heuristic manner by the addition of random noise that widens the support of the ensemble. This work aims at improving canonical rejuvenation methodology by the introduction of additional prior information obtained from climatological samples; the dynamical particles used for importance sampling are augmented with samples obtained from stochastic covariance shrinkage. A localized variant of the proposed method is developed. Numerical experiments with the Lorenz '63 model show that modified filters significantly improve the analyses for low dynamical ensemble sizes. Furthermore, localization experiments with the Lorenz '96 model show that the proposed methodology is extendable to larger systems.

54 ENVIRONMENTAL SCIENCES↗

The design of digital filters

Digital filter design program capable of generating discrete representations for continuous filters - digital computer

ELECTRONIC FILTER↗

An optimal modification of a Kalman filter for time scales

The Kalman filter in question, which was implemented in the time scale algorithm TA(NIST), produces time scales with poor short-term stability. A simple modification of the error covariance matrix allows the filter to produce time scales with good stability at all averaging times, as verified by simulations of clock ensembles.

time scale Kalman filter↗

Digital Filter ASIC for NASA Deep Space Radio Science

This paper is about the implementation of an 80 MHz, 16-bit, multi-stage digital filter to decimate by 1600, providing a 50 kHz output with bandpass ripple of less than +/-0.1 dB. The chip uses two decimation by five units and six decimations by two executed by a single decimation by two units. The six decimations by two consist of six halfband filters, five having 30-taps and one having 51-taps. Use of a 16x16 register file for the digital delay lines enables implementation in the Vitesse 350K gate array.

Digital Filter↗

A Stabilized Sparse-Matrix U-D Square-Root Implementation of a Large-State Extended Kalman Filter

The full nonlinear Kalman filter sequential algorithm is, in theory, well-suited to the four-dimensional data assimilation problem in large-scale atmospheric and oceanic problems. However, it was later discovered that this algorithm can be very sensitive to computer roundoff, and that results may cease to be meaningful as time advances. Implementations of a modified Kalman filter are given.

data assimilation modified Kalman filter sequentia↗

Spatiotemporal Filtering Using Principal Component Analysis and Karhunen-Loeve Expansion Approaches for Regional GPS Network Analysis

Spatial filtering is an effective way to improve the precision of coordinate time series for regional GPS networks by reducing so-called common mode errors, thereby providing better resolution for detecting weak or transient deformation signals. The commonly used approach to regional filtering assumes that the common mode error is spatially uniform, which is a good approximation for networks of hundreds of kilometers extent, but breaks down as the spatial extent increases. A more rigorous approach should remove the assumption of spatially uniform distribution and let the data themselves reveal the spatial distribution of the common mode error. The principal component analysis (PCA) and the Karhunen-Loeve expansion (KLE) both decompose network time series into a set of temporally varying modes and their spatial responses. Therefore they provide a mathematical framework to perform spatiotemporal filtering.We apply the combination of PCA and KLE to daily station coordinate time series of the Southern California Integrated GPS Network (SCIGN) for the period 2000 to 2004. We demonstrate that spatially and temporally correlated common mode errors are the dominant error source in daily GPS solutions. The spatial characteristics of the common mode errors are close to uniform for all east, north, and vertical components, which implies a very long wavelength source for the common mode errors, compared to the spatial extent of the GPS network in southern California. Furthermore, the common mode errors exhibit temporally nonrandom patterns.

displacement↗

Spectral Cloud-Filtering of AIRS Data: Non-Polar Ocean

The Atmospheric Infrared Sounder (AIRS) is a grating array spectrometer which covers the thermal infrared spectral range between 640 and 1700/cm. In order to retain the maximum radiometric accuracy of the AIRS data, the effects of cloud contamination have to be minimized. We discuss cloud filtering which uses the high spectral resolution of AIRS to identify about 100,000 of 500,000 non-polar ocean spectra per day as relatively "cloud-free". Based on the comparison of surface channels with the NCEP provided global real time sst (rtg.sst), AIRS surface sensitive channels have a cold bias ranging from O.5K during the day to 0.8K during the night. Day and night spatial coherence tests show that the cold bias is due to cloud contamination. During the day the cloud contamination is due to a 2-3% broken cloud cover at the 1-2 km altitude, characteristic of low stratus clouds. The cloud-contamination effects surface sensitive channels only. Cloud contamination can be reduced to 0.2K by combining the spectral filter with a spatial coherence threshold, but the yield drops to 16,000 spectra per day. AIRS was launched in May 2002 on the Earth Observing System (EOS) Aqua satellite. Since September 2002 it has returned 4 million spectra of the globe each day.

infrared↗