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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Overview of 2016 through 2018 Testing of Air-Purifying Respirator (APR) Cartridge Performance on Multiple Hanford Tank Headspaces and Exhausters

Between 2016 and 2018, 28 air purifying respirator (APR) cartridge tests were performed on headspace vapors from seven Hanford waste storage tanks (SY-102, A-101, BY-108, AX-101, BY-110, SX-101, and SX-104) and seven waste tank exhausters (AP in 2016, AP in 2018, 702-AZ, AN and AW in 2016, and AX and 702-AZ in 2017). All but two tests were conducted under static conditions absent waste-disturbing activities in the subject tanks or tank farms. The two exceptions were cartridges tested with vapors from 702-AZ in 2017 when samples were taken during waste-disturbing activities. Multipurpose APR cartridges, SCOTT 7422-SD1 and 7422-SC1, were tested on samples from each of the 14 tanks or exhausters. Out of 612 Chemicals of Potential Concern (COPCs), only ammonia, mercury, N-nitrosodimethylamine (NDMA), 2,5-dimethylfuran, 2,5-dihydrofuran, furan, and 1,3-butadiene exhibited breakthroughs with outlet concentrations that were >10% of their Occupational Exposure Limits (OEL).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Analysis of Respirator Cartridge Performance Testing on Hanford Tank AX-101

Washington River Protection Solutions (WRPS) conducted tests using two types of chemical cartridges for use in air purifying respirators to determine the period of time that the cartridges would provide adequate protection to worker when exposed to a mixture of Chemicals of Potential Concern (COPCs) from vapors emanating from the headspace of tank AX-101 on the Hanford Site. Pacific Northwest National Laboratory (PNNL) was tasked with conducting an independent analysis of the analytical results and making recommendations based on the results for respiratory cartridge performance and change schedules.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Analysis of Respirator Cartridge Performance Testing on Hanford Tank BY-108 (Rev.1)

Washington River Protection Solutions (WRPS) conducted tests using two types of chemical cartridges for use in air purifying respirators to determine the period of time that the cartridges would provide adequate protection to worker when exposed to a mixture of Chemicals of Potential Concern (COPCs) from vapors emanating from the headspace of tank BY-108 on the Hanford Site. Pacific Northwest National Laboratory (PNNL) was tasked with conducting an independent analysis of the analytical results and making recommendations based on the results for respiratory cartridge performance and change schedules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Overview of 2017 Through 2018 Testing of Powered Air-Purifying Respirator (PAPR) Cartridge Performance on Multiple Hanford Tank Headspaces and Exhausters

Between 2017 and 2018, 10 powered air-purifying respirator (PAPR) cartridge tests were performed on headspace vapors from three Hanford tanks (BY-108, SX-101, and SX-104) and two Hanford Tank Farm exhausters (AP in 2018 and AX in 2017). All tests were conducted under static conditions absent waste-disturbing activities in the subject tanks or tank farms. Multipurpose high-efficiency PAPR cartridges, MSA-TL (TL1) (MSA Safety Inc., Pittsburgh, Pennsylvania) and 3M FR-57 (TL2) (3M Company, Maplewood, Minnesota), were tested on each of the five tanks or exhausters. Out of 61 1 Chemicals of Potential Concern (COPCs), only ammonia and 2,5-dimethylfuran exhibited breakthroughs with outlet concentrations that were greater than 10% of their Occupational Exposure Limits (OEL). For 2,5-dimethylfuran, elevated concentrations found in blank tube samples made the elevated outlet measurements for this COPC questionable.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Data From: Influence of Hydrological Perturbations and Riverbed Sediment Characteristics on Hyporheic Zone Respiration of CO2 and N-2, Journal of Geophysical Research-Biogeosciences

This data package contains pumping data (.txt), parameter matrices, and R code (.R, .RData) to perform bootstrapping for parameter selection for the bioclogging model development. The pumping data were collected from the Russian River Riverbank Filtration site located in Sonoma County, California from 2010-2017 from three riverbank collection wells located alongside the study site. The pumping data is directly correlated with water table oscillations, so the code performs these correlations and simulates stochastic versions of water table oscillations. See Metadata Description.pdf for full details on dataset production. This dataset must be used with the R programming language. This dataset and R code is associated with the publication "Influence of Hydrological Perturbations and Riverbed Sediment Characteristics on Hyporheic Zone Respiration of CO2 and N-2"This research was supported by the Jane Lewis Fellowship from the University of California, Berkeley, the Sonoma County Water Agency (SCWA), the Roy G. Post Foundation Scholarship, the U.S. Department of Energy, Office of Science Graduate Student Research (SCGSR) Program, U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under award DE-AC02-05CH11231, and the UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition

Purpose: Myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera. Methods: A clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K1) and wash-out (k2) rates at each gate were also estimated. Results: The MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K1 and k2 were also consistent with the ground truth. Conclusion: The continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

On the role of soil water retention characteristic on aerobic microbial respiration

Soil water status is one of the most important environmental factors that control microbial activity and rate of soil organic matter (SOM) decomposition. Its effect can be partitioned into effect of water energy status (water potential) on cellular activity, effect of water volume on cellular motility, and aqueous diffusion of substrate and nutrients, as well as the effect of air content and gas-diffusion pathways on concentration of dissolved oxygen. Nonetheless,moisture functions widely used in SOM decomposition models are often based on empirical functions rather than robust physical foundations that account for these disparate impacts of soil water. The contributions of soil water content and water potential varyfrom soil to soil according to the soil water characteristic (SWC), which in turn is strongly dependent on soil texture and structure. The overall goal of this study is to introduce a physically based modeling framework of aerobic microbial respiration that incorporates the role of SWC under arbitrary soil moisture status. The model was tested by contrasting it with published data sets of SOM decomposition under laboratory conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

SUPECA kinetics for scaling redox reactions in networks of mixed substrates and consumers and an example application to aerobic soil respiration

Abstract. Several land biogeochemical models used for studying carbon–climate feedbacks have begun explicitly representing microbial dynamics. However, to our knowledge, there has been no theoretical work on how to achieve a consistent scaling of the complex biogeochemical reactions from microbial individuals to populations, communities, and interactions with plants and mineral soils. We focus here on developing a mathematical formulation of the substrate–consumer relationships for consumer-mediated redox reactions of the form A + BE→ products, where products could be, e.g., microbial biomass or bioproducts. Under the quasi-steady-state approximation, these substrate–consumer relationships can be formulated as the computationally difficult full equilibrium chemistry problem or approximated analytically with the dual Monod (DM) or synthesizing unit (SU) kinetics. We find that DM kinetics is scaling inconsistently for reaction networks because (1) substrate limitations are not considered, (2) contradictory assumptions are made regarding the substrate processing rate when transitioning from single- to multi-substrate redox reactions, and (3) the product generation rate cannot be scaled from one to multiple substrates. In contrast, SU kinetics consistently scales the product generation rate from one to multiple substrates but predicts unrealistic results as consumer abundances reach large values with respect to their substrates. We attribute this deficit to SU's failure to incorporate substrate limitation in its derivation. To address these issues, we propose SUPECA (SU plus the equilibrium chemistry approximation – ECA) kinetics, which consistently imposes substrate and consumer mass balance constraints. We show that SUPECA kinetics satisfies the partition principle, i.e., scaling invariance across a network of an arbitrary number of reactions (e.g., as in Newton's law of motion and Dalton's law of partial pressures). We tested SUPECA kinetics with the equilibrium chemistry solution for some simple problems and found SUPECA outperformed SU kinetics. As an example application, we show that a steady-state SUPECA-based approach predicted an aerobic soil respiration moisture response function that agreed well with laboratory observations. We conclude that, as an extension to SU and ECA kinetics, SUPECA provides a robust mathematical representation of complex soil substrate–consumer interactions and can be applied to improve Earth system model (ESM) land models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration

Climate change is reshaping vulnerable ecosystems, leading to uncertain effects on ecosystem dynamics, including evapotranspiration (ET) and ecosystem respiration (R eco ). However, accurate estimation of ET and R eco still remains challenging at sparsely monitored watersheds, where data and field instrumentation are limited. In this study, we developed a hybrid predictive modeling approach (HPM) that integrates eddy covariance measurements, physically based model simulation results, meteorological forcings, and remote-sensing datasets to estimate ET and R eco in high space–time resolution. HPM relies on a deep learning algorithm and long short-term memory (LSTM) and requires only air temperature, precipitation, radiation, normalized difference vegetation index (NDVI), and soil temperature (when available) as input variables. We tested and validated HPM estimation results in different climate regions and developed four use cases to demonstrate the applicability and variability of HPM at various FLUXNET sites and Rocky Mountain SNOTEL sites in Western North America. To test the limitations and performance of the HPM approach in mountainous watersheds, an expanded use case focused on the East River Watershed, Colorado, USA. The results indicate HPM is capable of identifying complicated interactions among meteorological forcings, ET, and R eco variables, as well as providing reliable estimation of ET and R eco across relevant spatiotemporal scales, even in challenging mountainous systems. The study documents that HPM increases our capability to estimate ET and R eco and enhances process understanding at sparsely monitored watersheds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Leaf Photosynthetic Parameters: Quantum Yield, Convexity, Respiration, Gross CO2 Assimilation Rate and Raw Gas Exchange Data, Utqiagvik (Barrow), Alaska, 2016

Leaf photosynthetic parameters including quantum yield, convexity, respiration and gross CO2 assimilation rate determined from the response of photosynthesis to irradiance and supporting raw gas exchange data. Measured in Barrow, Alaska in 2016 on six plant species: Arctophila fulva, Arctagrostis latifolia, Carex aquatilis, Eriophorum angustifolium, Petasites frigidus, and Salix pulchra. Version 2 (V2) note (01 Feb 2021): An earlier version of this data contained an incorrectly labeled data column in NGA175_AQfittedParams_Barrow_2016.csv. Mean_Ci was incorrectly labeled as Mean_Ci_LowLight. "_v2" contains the correct data for both of these variables. In December 2020, these data were updated to comply with the leaf-level gas exchange data and metadata reporting format (Ely et al 2020, doi:10.15485/1659484). These updates involved editing of some variable names, change of file formats to csv, addition of AQ curves data (subset of complete instrument output included in the original data package) and inclusion of additional methods and instrument details metadata files. No changes were made to the data. The package includes six *.csv files and one *.pdf. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Environmental Trade-Offs for a Process Utilizing Aerobic Respiration for Biological Conversion of Cellulosic Biomass-Derived Sugars to Hydrocarbons (Renewable Diesel Blendstock): Cooperative Research and Development Final Report, CRADA Number CRD-18-00765, Project 1

Phase II work is meant to develop an advanced understanding of how production of a renewable diesel blendstock from lignocellulosic biomass feedstocks via aerobic respiration at different production scales affects emissions of criteria pollutants and greenhouse gases (GHGs), local and regional air quality. The results could inform decisions by stakeholders (e.g., industry, community, air quality planners, investors) regarding relationships and tradeoffs between multiple environmental impacts and the challenges and opportunities for the design and deployment of a sustainable biofuel supply chain.

09 BIOMASS FUELS↗