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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

WIPP Safety Significant Confinement Ventilation System (SSCVS) HEPA Filtration System - 20165

Construction and major equipment fabrication are underway for a new ventilation exhaust system at the Waste Isolation Pilot Plant (WIPP). The new system will provide continuous High Efficiency Particulate Air (HEPA) filtration of the exhaust from the WIPP underground while meeting the ventilation demands for expanded waste emplacement and mining operations over the next 40 years. The integrated system design provides for reducing the salt, clay and diesel particulates from the exhaust airflow from the mine, prior to full filtration using Nuclear Safety Significant HEPA filters. The SSCVS design and equipment provides for continuous HEPA filtration over a wide range of operating and environmental conditions. The new exhaust system connects to the existing underground exhaust shaft, and the exhaust air flows from the underground through Salt Reduction Units (SRUs) to protect the final filter banks from excessive moisture and rapid salt/dust buildup. Each of the six (6) SRUs consists of a demister to remove entrained moisture, a dry salt remover unit to filter approximately 90% of the entrained salt/dust, and an automated water treatment system to periodically clean the demisters and to remove salt from the SRU filters. At the maximum expected exhaust flowrate of 540,000 Cubic Feet per Minute (CFM) / 255 Cubic Meters per Second (m{sup 3}/s), five (5) salt removal units will be in operation with one unit in standby or maintenance. An in-line variable frequency drive booster fan will offset pressure losses through each SRU and reduce the relative humidity of the air exiting the SRUs. In the event of a high radiation alarm from the underground Continuous Air Monitors (CAMs), the SRUs will be automatically bypassed, which places the SRS and building outside of the Safety Significant confinement boundary. From the SRUs, the exhaust is directed to the HEPA filter banks located in the New Filter Building. The exhaust system is designed to provide continuous HEPA filtration prior to release to the exhaust stack. There are 22 HEPA filter banks rated at 27,000 CFM / 12.75 m{sup 3}/s each. Each filter bank has two stages of pre-filters and two stages of HEPA filters. The filtered air from each of the 22 filter banks discharges into a common concrete plenum, which is maintained under a negative pressure by the main exhaust fans. Six 1,000 HP variable frequency drive exhaust fans are provided on the south side of the plenum. At the maximum expected exhaust flow of 540,000 CFM, four exhaust fans and twenty filter banks will be in operation. The fans discharge vertically to a separate concrete exhaust plenum. The filtered exhaust is routed from the exhaust plenum to a 125-foot-tall exhaust stack via a 13-foot diameter duct. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Internal Model-Based Active Damping Strategy for a Back-to-Back Modular Multilevel Converter System for Advanced Grid Support: Preprint

The proposed work focuses on the possibility of achieving the reduction in the size of the interfacing filter for the grid connection for a back-to-back modular multilevel converter system with the use of third order LCL filters. To achieve the same attenuation, it is possible to reduce the size of the interfacing filters by the usage of third order filters. However, this kind of filtering comes with the limitation of having sustained oscillations due to lack of damping especially during transient changes. Therefore, in this work, a methodology has been proposed based on the principle of internal model to cater for this unwanted oscillations. The third order system is modeled inside the microcontroller with the damping enabled. The error between the output from the model and the actual are compared and the error is utilized to accomplish the active damping strategy. The proposed architecture is verified via computer simulations based on MATLAB/Simulink domain and various case study results along with their discussion is presented in this paper.

dq control↗
DOE OSTI2024

Filtration of Hanford Tank 241-AN-107 Supernatant at 16 °C

Approximately 9 liters of supernatant from Hanford waste tank 241-AN-107 was delivered by Washington River Protection Solutions to the Radiochemical Processing Laboratory (RPL) at Pacific Northwest National Laboratory. The thirty-six AN-107 sample bottles consisted of six sets of six samples, with each set pulled from a unique tank sampling level. Prior to testing, samples from each level were composited to provide nominally level-independent feed for dead end filtration and ion exchange testing. The composited 241-AN-107 supernatant was chilled to 16 °C for 1 week prior to testing. Filtration testing was then conducted using a backpulse dead-end filter (BDEF) system equipped with a feed vessel and a Mott inline filter Model 6610 (Media Grade 5) in the hot cells of the RPL. The purpose of this testing is to a) demonstrate dead-end filtration (DEF) of AN-107 feed at reduced temperature to obtain prototypic tank side cesium removal (TSCR) flux rates and identify issues that may impact filtration after dilution to 5.5M Na, and b) provide feed for a follow on ion exchange unit operation. The feed was filtered through the BDEF system at a targeted flux of 0.065 gpm/ft 2 . During filtration the differential pressure required to effect filtration at 0.065 gpm/ft 2 was slow to increase for most of the filtration campaign. After all the feed bottles had been pumped into the slurry reservoir, the bottoms of the bottles were added to the reservoir and transmembrane pressure (TMP) reached 2.0 psid (the TSCR action limit). The prototypic filter cleaning process was unable to effectively restore filter performance, and cleaning with oxalic acid was required before flow through the filter could be restored. This indicates that the Media Grade 5 filter may require an alternative cleaning protocol when processing AN-107 supernatant. After completing filtration of the AN-107 feed, the filter was cleaned. Solids concentrated from the backpulse solutions were composed of natrophosphate, Mn-Fe phases, and fluoro-natrophosphate that occurred as particle agglomerates. The individual particles were in some cases 100s of micrometers across which is consistent with prior observations from AN-107 supernate waste characterizations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Code Standard Evaluation for ASME AG-1-2019, Section FL

ASME AG-1 Section FL Deep Bed Sand Filters includes a requirement to use Special Test Sections to provide a representative assessment of the filter efficiency. The SRPPF project design basis is to test the entire filter bed (versus a representative sample) following the same basis methodology to test the existing filters at the Savannah River Site. Using a combination of: 1) the filter testing experience at SRS since the early 1970’s, 2) the methodology found in ASME AG-1 for testing high capacity HEPA filter housings and 3) requirements for stack or duct sampling systems published by the Environmental Protection Agency (EPA), the Special Test Sections methodology for Deep Bed Sand (DBS) filters in ASME AG-1 Section FL has been replaced with a methodology to test the entire DBS filter system.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Singleton Sieving: Overcoming the Memory/Speed Trade-Off in Exascale k-mer Analysis

Traditional filter data structures, such as Bloom filters, do not offer necessary features that modern high-performance data analytics applications need in order to efficiently perform complex data analysis tasks. For example, MetaHipMer, a de novo metagenome assembler, can use filters to weed out singleton k-mers and reduce memory usage by 30%-70%. However, the filter needs the ability to associate values with k-mers in order to perform the analysis in a single communication pass. Bloom filters do not support value associations and cause the application to perform an extra communication pass, thereby increasing the run time. Therefore, MetaHipMer faces a trade off between memory and speed due to the limited capabilities of traditional filters. In this paper, we overcome the memory and speed trade off in MetaHipMer by integrating a GPU-based feature-rich filter, the Two-Choice filter (TCF), in the MetaHipMer pipeline. The TCF uses key-value association to approximately store k-mers with extensions. This allows MetaHipMer to perform k-mer analysis on the GPUs in a single communication pass. Our empirical analysis shows a 50% reduction in memory usage in k-mer analysis on each node in MetaHipMer without any effect on the overall run time or assembly quality. The memory reduction in turn results in a 43% reduction in the number of nodes required to assemble datasets and enables MetaHipMer to scale to much larger datasets.

McCoy, Hunter↗
DOE OSTI2021

CACTI ARM Aerial Facility Measurements of Ice Nucleating Particles

The dataset comprises measures, using Colorado State University's Ice Spectrometer (IS, an immersion freezing device with a range from 0°C down to -26 to -29°C) of atmospheric ice nucleating particle (INP) concentrations taken on the Atmospheric Radiation Measurement (ARM) program Aerial Facilty (AAF) G-1 aircraft. INP measurements on the G-1 were collected from varied altitudes on different flights over the region of the Sierras de Córdoba mountain range of north-central Argentina, centred over ARM's Mobile Facility (AMF-1) near Villa Yacanto, where ground-based INP measures were being taken concurrently. Both studies took place as part of the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Experiment. A filter sampling system was deployed on the G-1 to collect aerosol particles for post-processing of INPs collected on filters (measuring their immersion freezing ability) once returned to Colorado State University (CSU). Filter holders used were pre-cleaned aluminum in-line units loaded with pre-cleaned and pre-sterilized 47 mm dia. Nuclepore polycarbonate filters (0.2 mm pore size). Filters were drawn for varied times, resulting in varied volumes collected (51 to 1667 SL). Mass flow rate was recorded in real-time so that total sampled volume (at standard temperature and pressure) could be determined. A total of 34 sample filters were collected over the IOP, including 5 blanks. Filters were stored at -20°C freezer prior to frozen return to Colorado State University (CSU). . Processing to obtain spectra of INP number concentration active via the immersion freezing mechanism versus temperature was conducted using CSU's IS instrument (McCluskey et al., 2018). For measurment of INPs, collected aerosol particles were re-suspended in 7 mL of 0.02 µm-filtered deionized water. Aliquots of each suspension, and serial dilutions, were dispensed into trays which were fit into aluminum blocks in the IS. Samples are cooled at 0.33°C min-1 and the freezing temperatures of wells recorded automatically. Cumulative INP concentrations were determined by first calculating the INPs per mL of suspension based on Vali (1971) and then converting to concentration per standard liter of air using the proportion of the total liquid sample dispensed and the air sample volumes. Aliquots of suspensions from selected samples were also heat treated (95°C for 20 min) to denature and deactivate biological INPs, and digested in 10% H2O2 at 95°C under UV-B to remove all organic carbon INPs. McCluskey, C. S., J. Ovadnevaite, M. Rinaldi, J. Atkinson, F. Belosi, D. Ceburnis, S. Marullo, T. C. J. Hill, U. Lohmann, Z. A. Kanji, C. O’Dowd, S. M. Kreidenweis, P. J. DeMott, 2018: Marine and Terrestrial Organic Ice Nucleating Particles in Pristine Marine to Continentally-Influenced Northeast Atlantic Air Masses, Journal of Geophysical Research: Atmospheres, 123, 6196–6212, https://doi.org/10.1029/2017JD028033. Vali, G., 1971: Quantitative evaluation of experimental results on the heterogeneous freezing nucleation of supercooled liquids. J. Atmos. Sci., 28, 402–409.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

AEROICESTUDY-Colorado State University Ice Spectrometer

The dataset comprises measures, using Colorado State University's Ice Spectrometer (IS, an immersion freezing device with a range from 0 °C down to -26 to -29 °C) of atmospheric ice nucleating particle (INP) concentrations taken at ARM's Southern Great Plains (SGP) Site Guest Instrument Facility (GIF), in Lamont, Oklahoma, during the Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY). A filter sampler was mounted approximately 6 m above ground level atop the GIF rooftop platform. Single-use filter units open to the atmosphere fitted with pre-cleaned and pre-sterilized, 47-mm diameter Nuclepore polycarbonate filters were used. Filters were typically drawn for either a full day period (9AM-5PM CDT) or broken up into morning (9AM-12PM CDT) and afternoon (1PM-5PM CDT) periods. Additionally, 4 overnight filters were taken (6PM-8AM CDT). The volume of air filtered was typically between 3000 and 8000 standard liters for daily samples. After collection, filters were stored at -20 °C until processed. Initial processing to obtain spectra of INP number concentration active via the immersion freezing mechanism versus temperature was conducted using CSU's IS instrument (McCluskey et al., 2018). For measurement of INPs, collected aerosol particles were re-suspended in 8 mL of 0.1 µm-filtered deionized (DI) water. Aliquots of each suspension, and serial dilutions, were dispensed into trays which were fit into aluminum blocks in the IS. Samples were cooled at 0.33 °C per min and the freezing temperatures of wells recorded automatically. Cumulative INP concentrations were determined by first calculating the INPs per mL of suspension based on Vali (1971) and then converting to concentration per standard liter of air using the proportion of the total liquid sample dispensed and the air sample volumes. Two-tailed, 95% confidence intervals for binomial sampling were based on Equation 2 from Agresti and Coull (1998). Aliquots of suspensions from selected samples were also heat treated (95 °C for 20 min) to denature and deactiv

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

MOSAiC-Colorado State University Ice Spectrometer

This data set contains atmospheric ice nucleating particle (INP) measurements, using Colorado State University&rsquo;s (CSU) Ice Spectrometer (IS), of filter collections taken at the U.S. DOE ARM AMF2 site onboard the R/V Polarstern P-deck during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign. Samples were collected from October 27, 2019 to September 24, 2020. A filter sampler was mounted approximately 15 m above ground level on a railing in proximity to (and approximately 3 m below) the Aerosol Observation System (AOS) inlet. Single-use filter units open to the atmosphere were pre-cleaned and pre-loaded with 47-mm diameter Nuclepore polycarbonate (0.2 &micro;m pore-diameter) filters. Filters were typically drawn for a three-day period, with an average volume of air filtered of 87,000 standard liters. Total volumes were calculated through recorded daily flow rates using a mass flow meter (TSI). After collection, filters were stored and transported frozen until analysis using CSU&rsquo;s IS instrument (McCluskey et al., 2018). Aerosol particles were first re-suspended in 8 mL of 0.1 &micro;m-filtered deionized (DI) water. Aliquots of each suspension, and corresponding 11-fold dilutions, were dispensed into polymerase chain reaction (PCR) trays and placed into the aluminum blocks of the IS. Samples were cooled at approximately 0.33 &deg;C min -1 and freezing detected optically with corresponding temperatures recorded. Cumulative INP concentrations were determined through calculating the number of INPs per mL of suspension (Vali, 1971) and converting to concentration per standard L of air by accounting for the proportion of liquid used and volume of air collected. All samples were corrected for the number of INPs on the average of four field blanks (cleaned, handled, transported, and analyzed in the same way without air flow). Two-tailed, 95% confidence intervals for binomial sampling are provided (Agresti and Coull, 1998). Select samples were also heat treated (95 &deg;C for 20 min) to denature and deactivate biological INPs present and digested in 10% H 2 O 2 at 95 &deg;C under UV-B for 20 min to remove any organic carbon INPs. Agresti, A, and BA Coull. 1998. "Approximate is better than &ldquo;exact&rdquo; for interval estimation of binomial proportions." American Statistics 52: 119&ndash;126. https://doi.org/10.2307/2685469 McCluskey, CS, J Ovadnevaite, M Rinaldi, J Atkinson, F Belosi, D Ceburnis, &hellip; and PJ DeMott. 2018. "Marine and Terrestrial Organic Ice-Nucleating Particles in Pristine Marine to Continentally Influenced Northeast Atlantic Air Masses." Journal of Geophysical Research: Atmospheres 123 (11): 6196&ndash;6212, https://doi.org/10.1029/2017JD028033 Vali, G. 1971. "Quantitative Evaluation of Experimental Results and the Heterogeneous Freezing Nucleation of Supercooled Liquids." Journal of the Atmospheric Sciences 28: 402-209. https://doi.org/10.1175/1520-0469(1971)028<0402:QEOERA>2.0.CO;2

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

tbsinp (00)

The ice nucleation spectrometer (INS) is an offline analytical measurement system used to process filter samples for freezing temperature spectra of immersion-mode ice-nucleating particle (INP) number concentrations. It is almost identical to the Colorado State University (CSU) ice spectrometer design. The INS-AIR is specific to filter samples collected on aerial platforms, such as the DOE ARM tethered balloon system (TBS) operated by Sandia National Laboratories, using miniaturized aerosol filter samplers. Users are referred to the INS instrument handbook for INS-AIR sampler details. INS-AIR filter samples are collected during intensive operational periods at various ARM sites and then processed on the INS at CSU. This filter log contains the detailed metadata at all ARM sites where INP filter sample collection has occurred or is currently ongoing, including both ground-based routine INP sampling (INS) and TBS INP sampling (INS-AIR). Metadata include start and end times, vacuum line pressures and temperatures, and flow rates; total accumulated flow through each filter; and notes on collection issues or weather conditions. Users can also keep up to date with the status of filter and data processing, even before data are available on ARM’s Data Discovery. Users can contact INP mentors Jessie Creamean or Thomas Hill with any questions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Memory row recording for mitigating crosstalk in dynamic random access memory

A method includes adding a set of one or more victim rows to a first probabilistic filter and to a second probabilistic filter, in response to a memory access request, identifying a candidate victim row adjacent to a memory address specified by a memory access request, identifying the candidate victim row as a victim row in the set of victim rows based on performing a lookup of the candidate victim row in a selected filter, where the selected filter includes one of the first probabilistic filter and the second probabilistic filter, in response to identifying the candidate row as the victim row, enabling a row hammering countermeasure, clearing the first probabilistic filter in each of a first set of time periods, and clearing the second probabilistic filter in each of a second set of time periods interleaved with the first set of time periods.

SeyedzadehDelcheh, SeyedMohammad↗