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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

International Space Station (ISS) Bacterial Filter Elements (BFEs): Filter Efficiency and Pressure Drop Testing of Returned Units

The air quality control equipment aboard the International Space Station (ISS) and future deep space exploration vehicles provide the vital function of maintaining a clean cabin environment for the crew and the hardware. This becomes a serious challenge in pressurized space compartments since no outside air ventilation is possible, and a larger particulate load is imposed on the filtration system due to lack of sedimentation. The ISS Environmental Control and Life Support (ECLS) system architecture in the U.S. Segment uses a distributed particulate filtration approach consisting of traditional High-Efficiency Particulate Air (HEPA) filters deployed at multiple locations in each U.S. Seg-ment module; these filters are referred to as Bacterial Filter Elements, or BFEs. In our previous work, we presented results of efficiency and pressure drop measurements for a sample set of two returned BFEs with a service life of 2.5 years. In this follow-on work, we present similar efficiency, pressure drop, and leak tests results for a larger sample set of six returned BFEs. The results of this work can aid the ISS Program in managing BFE logistics inventory through the stations planned lifetime as well as provide insight for managing filter element logistics for future exploration missions. These results also can provide meaningful guidance for particulate filter designs under consideration for future deep space exploration missions.

ISS Air Quality↗
DOE OSTI2020

Filtered Backprojection in Compton Imaging using a Spherical Harmonic Wiener Filter with Pixelated CdZnTe

Filtered backprojection is an image reconstruction technique for Compton imaging that provides reasonably high resolution at much lower computational costs when compared to iterative methods. Here, this work applies a Wiener filter that has been derived for spherical harmonics on Compton imaging using the OrionUM pixelated CdZnTe imaging-spectrometer. To regularize the filter, an investigation is made into the power spectral density of the signal and noise to develop an appropriate spectral signal-to-noise ratio model for the restoration process. Experimental measurements were conducted with two 228Th sources placed 30° apart. The resulting filtered image of the two sources have an average full-width-at-half-maximum (FWHM) of 9.8° or 7.5° when using a mean squared error and structural similarity optimization approach respectively; an improvement from the 29.0° FWHM image when using simple backprojection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Implicit filtered P{sub N} for high-energy density thermal radiation transport using discontinuous Galerkin finite elements

In this work, we provide a fully-implicit implementation of the time-dependent, filtered spherical harmonics (FP{sub N}) equations for non-linear, thermal radiative transfer. We investigate local filtering strategies and analyze the effect of the filter on the conditioning of the system, showing in particular that the filter improves the convergence properties of the iterative solver. We also investigate numerically the rigorous error estimates derived in the linear setting, to determine whether they hold also for the non-linear case. Finally, we simulate a standard test problem on an unstructured mesh and make comparisons with implicit Monte Carlo (IMC) calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Wide bandwidth and high resolution planar filter array based on DBR-metasurface-DBR structures

Here, we propose and experimentally demonstrate a planar array of optical bandpass filters composed of low loss dielectric metasurface layers sandwiched between two distributed Bragg reflectors (DBRs). The two DBRs form a Fabry-Perot resonator whose center wavelength is controlled by the design of the transmissive metasurface layer which functions as a phase shifting element. We demonstrate an array of bandpass filters with spatially varying center wavelengths covering a wide range of operation wavelengths of 250nm around λ = 1550nm (Δλ/λ = 16%). The center wavelengths of each filter are independently controlled only by changing the in-plane geometry of the sandwiched metasurfaces, and the experimentally measured quality factors are larger than 700. The demonstrated filter array can be directly integrated on top of photodetector arrays to realize on-chip high-resolution spectrometers with free-space coupling.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Extraction of Tumor Site from Cancer Pathology Reports using Deep Filters

Purpose: Pathology reports are the primary source of information concerning the millions of cancer cases across the United States. Cancer registries manually process the pathology reports to extract the pertinent information including primary tumor site, behavior, histology, laterality, and grade. Processing a large volume of the pathology reports in a timely manner is a continuing challenge for cancer registries. The purpose of this study is to develop an information extraction pipeline to reliably and efficiently extract reportable information. Method: We have developed a novel inverse-regression (IR) based information extraction pipeline. The inverse-regression based supervised filter has been successfully applied to many application domains. However, its application to the information extraction from unstructured text is hindered primarily by the extreme high-dimensionality of n-gram representations of text. In this study, we attempt to overcome the obstacles by a novel bootstrapping strategy. First, we use an information-theoretic mutual information based filter to discard the excessive and redundant n-gram features. This step reduces the size and improves the condition number of the sample covariance matrix, thus reducing the computational cost and improving the numerical stability of the subsequent inverse-regression step. Then we use localized sliced inverse-regression (LSIR) to learn a low-dimensional discriminatory subspace for information inference. In particular, we use the k-nearest neighbors of an unlabeled pathology report in the learned representation to infer the desired information from the labeled data in a supervised manner. Results: The experiments were conducted on a set of de-identified pathology reports with human expert labels as the ground truth. Our pipeline consistently performed better than or comparable to the best performing state-of-the-art methods while reducing the training and inference times substantially. Conclusion: Our results demonstrate the potential of inverse-regression based information extraction pipeline for reliable and efficient information extraction from unstructured text. The information extracted from the pathology reports can be used along with clinical information, medical imaging, and genomic information to instigate discoveries in cancer research.

Dubey, Abhishek↗
DOE OSTI2023

On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments

This work describes the investigation of neuromorphic computing-based spiking neural network (SNN) models used to filter data from sensor electronics in high energy physics experiments conducted at the High Luminosity Large Hadron Collider. We present our approach for developing a compact neuromorphic model that filters out the sensor data based on the particle's transverse momentum with the goal of reducing the amount of data being sent to the downstream electronics. The incoming charge waveforms are converted to streams of binary-valued events, which are then processed by the SNN. We present our insights on the various system design choices - from data encoding to optimal hyperparameters of the training algorithm - for an accurate and compact SNN optimized for hardware deployment. Our results show that an SNN trained with an evolutionary algorithm and an optimized set of hyperparameters obtains a signal efficiency of about 91% with nearly half as many parameters as a deep neural network.

R. Kulkarni, Shruti↗
NASA NTRS1975

Worst-error analysis of batch filter and sequential filter in navigation problems

This paper proposes a worst-error analysis for dealing with problems of estimation of spacecraft trajectories in deep space missions. Navigation filters in use assume either constant or stochastic (Markov) models for their estimated parameters. When the actual behavior of these parameters does not follow the pattern of the assumed model, the filters sometimes result in very poor performance. To prepare for such pathological cases, the worst errors of both batch and sequential filters are investigated based on the incremental sensitivity studies of these filters. By finding critical switching instances of non-gravitational accelerations, intensive tracking can be carried out around those instances. Also the worst errors in the target plane provide a measure in assignment of the propellant budget for trajectory corrections. Thus the worst-error study presents useful information as well as practical criteria in establishing the maneuver and tracking strategy of spacecraft's missions.

Nishimura, T.↗
NASA NTRS1990

Rocket noise filtering system using digital filters

A set of digital filters is designed to filter rocket noise to various bandwidths. The filters are designed to have constant group delay and are implemented in software on a general purpose computer. The Parks-McClellan algorithm is used. Preliminary tests are performed to verify the design and implementation. An analog filter which was previously employed is also simulated.

Mauritzen, David↗
NASA NTRS1991

Mass property identification - A comparison study between extended Kalman filter and neuro-filter approaches

Two algorithms, extended Kalman filter and neuro-filter, are formulated to perform mass property identification for the Space Station Freedom. Control moment gyros that are part of the Station's basic momentum management system are chosen to provide input excitation in the form of applied torques. These torques together with the measured angular body rate responses are supplied to the filters. From these data, both algorithms are shown to accurately identify the station mass properties when excitation levels are high and balanced between axes. The neuro-filter, however, is shown to be more robust and to perform well even with weakly persistent, unbalanced signals contaminated with noise.

Lam, Quang↗
NASA NTRS2017

Summary of Martian Dust Filtering Challenges and Current Filter Development

Traditional air particulate filtering in manned spaceflight (Apollo, Shuttle, ISS, etc.) has used cleanable or replaceable catch filters such as screens and High-Efficiency Particulate Arrestance (HEPA) filters. However, the human mission to Mars architecture will require a new approach. It is Martian dust that is the particulate of concern but the need also applies to particulates generated by crew. The Mars Exploration Program Analysis Group (MEPAG) high-lighted this concern in its Mars Science, Goals, Objectives, Investigations and Priorities document [7], by saying specifically that one high priority investigation will be to "Test ISRU atmospheric processing systems to measure resilience with respect to dust and other environmental challenge performance parameters that are critical to the design of a full-scale system." By stating this as high priority the MEPAG is acknowledging that developing and adequately verifying this capability is critical to success of a human mission to Mars. This architecture will require filtering capabilities that are highly reliable, will not restrict the flow path with clogging, and require little to no maintenance. This paper will summarize why this is the case, the general requirements for developing the technology, and the status of the progress made in this area.

O'Hara, William J., IV↗
DOE OSTI2014

Prediction of L70 Life and Assessment of Color Shift for Solid-State Lighting Using Kalman Filter and Extended Kalman Filter-Based Models

Solid-state lighting (SSL) luminaires containing light-emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in nonclimate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at the end of life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn“. The LEDs continually degrade, and the light output decreases eventually below useful levels causing failure. Currently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time, causing lumen depreciation. The underlying TM-21 model may not capture the failure physics in presence of multiple failure mechanisms. The correlation of lumen maintenance with underlying physics of degradation at system level is needed. In this paper, Kalman filter (KF) and extended Kalman Filters (EKF) have been used to develop a 70% Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand-hour LM-80 test data for various LEDs are used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise, and measurement noise. The future state of the lumen depreciation are estimated based on a second-order Kalman Filter model and a Bayesian Framework. The measured state variable are related to the underlying damage using physics-b- sed models. Life prediction of L70 life for the LEDs used in SSL luminaires from KF- and EKF-based models are also compared with the TM-21 model predictions and experimental data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Filter Test System for Nuclear Container Filters

The purpose of this procedure is to measure the collection efficiency of the filters that are integrated into the lids of containers for nuclear material at Los Alamos National Laboratory (LANL). As an application of this procedure, a filter test report certificate can be created to document the measurement process. This procedure is intended to describe the TA-55, PF-4 (room 6A) operation of a Filter Test System (FTS) for Hagan and SAVY storage containers.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integrate them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Spin polarized state filter based on semiconductor–dielectric–iron–semiconductor multi-nanolayer device

Highlights: • Development of a new spintronics device. • Development of quantum spin polarized filters. • Development of theory of quantum spin polarized filter. - Abstract: Presently we report spin-polarized state transport in semiconductor–dielectric–iron–semiconductor (SDIS) four-nanolayer sandwich devices. The exchange-resonance spectra in such devices are quite specific, differing also from spectra observed earlier in other three-nanolayer devices. The theoretical model developed earlier is extended and used to interpret the available experimental results. A detailed ab initio analysis of the magnetic-field dependence of the output magnetic moment is also performed. The model predicts an exchange spectrum comprising a series of peaks, with the spectral structure determined by several factors, discussed in the paper.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Rhenium-phthalocyanine molecular nanojunction with high magnetic anisotropy and high spin filtering efficiency

Using the density functional and non-equilibrium Green's function approaches, we studied the magnetic anisotropy and spin-filtering properties of various transition metal-Phthalocyanine molecular junctions across two Au electrodes. Our important finding is that the Au-RePc-Au junction has both large spin filtering efficiency (>80%) and large magnetic anisotropy energy, which makes it suitable for device applications. To provide insights for the further experimental work, we discussed the correlation between the transport property, magnetic anisotropy, and wave function features of the RePc molecule, and we also illustrated the possibility of controlling its magnetic state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗