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27 results for “Soa”
SoA of existing barriers against the measuring of H2NG mixtures or pure H2
<p>Deliverable D1.2 of THOTH2 project aims to investigate technical barriers and limitations of hydrogen injection in existing gas grids with a focus on measuring devices. Injecting hydrogen into existing gas networks requires several actions to assess the content of hydrogen in the H2NG mixture that can be transported through gas pipelines. One of the areas that needs to be evaluated is the field of gas quality and quantity measurements.</p> <p>The Task 1.2 "Technical and performance barriers and limitations" aimed to identify barriers and gaps related to measurement devices such as gas meters, volume converters, pressure and temperature transducers, process gas chromatographs, dew point transducers, and leak detectors. By defining this measurement area, it allows identifying gaps and barriers concerning custody transfer measurements (gas volume and heating value).</p> <p>Due to the different physicochemical properties of hydrogen and methane, the identification of barriers and considerations includes not only the measurement capabilities of devices for H2NG mixtures but also the resistance of design solutions to the effects of hydrogen. The assessment of the state-of-the-art technology was conducted based on a literature review, including the outcomes of projects such as "HyDeploy 2 Project" and "HyWay 27: hydrogen transmission using the existing natural gas grid?". The literature review was complemented by feedback gathered from surveys sent to manufacturers of measurement devices, selected based on the results of Task 1.1. The analyses conducted allowed identifying the following gaps and barriers:</p> <ul> <li>In the area of gas composition analyzers: there are solutions available that allow measuring the composition of H2NG mixtures with up to 100% hydrogen content. However, these solutions are not currently utilized by Transmission System Operators (TSOs) and Distribution System Operators (DSOs), since they entered in the market recently.</li> <li>In the area of dew point transducers: there are solutions resistant to hydrogen up to 20% content, and they are partially used by TSOs and DSOs.</li> <li>In the area of leak detectors: there are solutions that can be used by operational services on gas networks transporting H2NG mixtures. These detectors allow measuring hydrogen content in the air from 0 to 100% of the lower explosive limit. This range is sufficient to ensure safe network operation. However, such leak detectors are not currently employed by TSOs and DSOs.</li> </ul>
SoA of measuring devices installed in NG transmission and distribution networks
<p>Deliverable D1.1 aims to design the state of the art of measuring devices in natural gas transmission and distribution networks. </p> <p>Transporting green hydrogen into existing gas assets requires carefully assessing its effect on the existing components. Since several projects have already been completed or have planned research activities to answer still-existing technical questions, the THOTH2 project focuses on the existing measuring devices. Specifically, the focus of the project regards the identification of the existing gaps in normative standards and the suggestions for solutions to cover them (if any). To contribute the hydrogen readiness of the existing gas transport and distribution infrastructures, new methodologies and protocols have to be developed to perform validated tests for metering devices. Suggestions on the need to change the standards or develop new ones will be based on the results of these experimental tests. Despite the simplicity of the methodological approach, it would be very critical when applying it to measuring devices. Several technologies are available in the market to measure gas properties. Furthermore, the operators can select more than one configuration based on the expected field conditions.</p> <p>Since limited resources are available, testing all the possible configurations would be impossible. Prioritization is required. Task 1.1 aims to collect all the information to provide a clear overview of the measuring devices installed in the existing gas assets. Specifically, this document includes the state of the art of measuring devices installed in gas assets. Different technologies are available to measure gas parameters. For example, turbine, rotary piston, ultrasonic, diaphragm, thermal mass, orifice, and Coriolis meters are available to measure flow rate. These technologies differ not only for the operating principle but also for the material used, the size available on the market, and the effect that different conditions could have on the metrological performances like, for example, overload conditions, flow rate pulsations, leakages through the clearance and pressure drops. Furthermore, different maintenance activities are usually expected, resulting in different operative costs throughout the lifetime. To date, turbine, rotary piston gas, and ultrasonic meters are used for fiscal gas metering in transmission networks. Specifically, based on the data collected, turbine gas meters are the most installed technologies for medium to high flow rate, followed by rotary piston and ultrasonic (for high flow rate). Few cases of use of Coriolis meters have been found. Regarding distribution, a different situation results. Despite the fact that few answers have been received to date, and only from Italy, it appears that diaphragm gas meters are the prevailing technology installed, even if a greater penetration is expected for thermal mass meters. THOTH2 also includes other measurements like gas quality by chromatographs, pressure and temperature, and trace water dew point. Regarding temperature, it was assumed that since the sensor is not in contact with the fluid but is protected by the thermowell, it can be assumed that no problem would arise. However, further investigation should be performed to investigate if any effect of hydrogen on response time exists. Regarding pressure measurement, many models are commercially available, but attention should be given to the effect of hydrogen on the material with which the fluid is in contact. Specifically, identifying critical materials that can be affected by hydrogen among those available in commercial products should be the next step to identifying the products to be tested. Gas chromatographs are also present in different models and configurations in the existing networks. Usually, different columns are used based on the specific analysis to be performed. Even if the range of the concentration allowed for each molecule is usually known for each model, more details about the configuration of each gas chromatograph are needed to complete the analysis and check the capability to handle hydrogen. Only some models of trace water sensors have been identified in the investigated networks. Specifically, impedance sensors result in the most implemented devices. Other devices are also typically used in the networks. Electronic Volume Converters and Flow Computers convert measurements into standardized gas volumes for fiscal purposes. The main issues to be investigated are the implemented algorithms and their capability to consider hydrogen. The main algorithms are AGA8, SGERG, and AGA-NX19, and the Operators can check the hydrogen limits. The main issue is that many different models are installed in gas transmission and distribution networks. Furthermore, based on the conclusion about pressure and temperature sensors, the potential effects of hydrogen on the metrological performances of those devices that have these sensors integrated have to be carefully assessed not to overcome the limits on errors provided by the standards. Last, leak detection is essential to detect fugitive emissions to the atmosphere and to minimize the risk of failures or accidents . To date, many devices are supplied to the technicians on the field to verify the presence of hazardous substances. Since different sensors can be implemented in the same devices to measure different quantities, attention should be given in Task 2.1 to selecting those sensors that, on the current knowledge, appear to be most critical when being in contact with hydrogen.</p>
Using GECKO-A to derive mechanistic understanding of SOA formation from the ubiquitous but understudied camphene
<p>This data repository contains the simulation outputs of GECKO-A model used in the manuscript: <br> "Using GECKO-A to derive mechanistic understanding of secondary organic aerosol formation from the ubiquitous but understudied camphene"<br> by Afreh et al., 2021 in ACP</p> <p>The original ACP article should be properly cited when these data are used in a publication.</p>
GEOS-Chem v9-02 with simple SOA scheme for ATAL simulations & model output
<p>This code/data repository includes (1) GEOS-Chem (v9-02, <a href="http://www.geos-chem.org/">http://www.geos-chem.org/</a>) code modified to use the simple SOA scheme in the simulation of Asian Tropopause Aerosol Layer (ATAL), and (2) model ATAL simulation output. Please see README.txt and this paper for details:</p> <p>Citation: Fairlie, T.D., H. Liu, J.-P. Vernier, P. Campuzano-Jost, J. L. Jimenez, D.S. Jo, B. Zhang, M. Natarajan, M.A. Avery, and G. Huey, Estimates of regional source contributions to the Asian Tropopause Aerosol Layer using a chemical transport model, Journal of Geophysical Research-Atmospheres, in press, Jan. 2020.</p>
ParticleSizeDistribution_SG+Li2CO3+SoA
<p>This file contains statistical analysis and the relative plots of the particle size distribution of the powders G018-402, Li2CO3, and SoA. This powders were used to develop inks for robocasting deposition of glass sealant applied in Na-Zn batteries. This dataset is linked with this one (10.5281/zenodo.13254112) that contains the micrographs from which the particle size data were taken</p> <p> </p>
FIGURES 7–11 in New species of Soa Enderlein, 1904 (Psocodea: 'Psocoptera': Lepidopsocidae) from the Western Ghats of India
FIGURES 7–11. Soa papanasam sp. nov. Female. 7–8. Left and right meso-coxae; 9. Lacinia; 10. Forewing scales; 11. Claw.
IEPOX-SOA and related chemical/meteorological fields simulated by CESM2/CAM-chem under present and future conditions
This dataset contains IEPOX-SOA (Isoprene epoxydiol derived secondary organic aerosol) concentrations and other related variables under present and future conditions. CESM2.1/CAM6-chem (Community Earth System Model version 2.1 / Community Atmosphere Model version 6 with comprehensive tropospheric and stratospheric chemistry representation) was used with a horizontal resolution of 0.95° in latitude by 1.25° in longitude, and 32 vertical layers up to 1 hPa (40 km). Four shared socioeconomic pathways (SSPs) were used for the simulation of the mid and end of the 21st century - SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The detailed information is available in Table 1 in the following manuscript: Jo et al., Future changes in isoprene-epoxydiol-derived secondary organic aerosol (IEPOX-SOA) under the shared socioeconomic pathways: the importance of physico-chemical dependency., ACP, 2021 (https://doi.org/10.5194/acp-2020-543). Please contact Duseong Jo (cdswk@ucar.edu) or Louisa Emmons (emmons@ucar.edu) if you have questions about this dataset.
Graph Machine Learning Dataset SOA-SW
<p><strong>SOA-SW</strong> is a heterogeneous graph machine learning dataset based on the RDF knowledge graph <a href="doi.org/10.5281/zenodo.10299132">SemOpenAlex-SemanticWeb</a>.</p><p>SOA-SW contains six node types - works (95,575 nodes), authors (19,970 nodes), concepts (38,050 nodes), sources (10,739 nodes), institutions (5,846 nodes), and publishers (786 nodes), and seven edge types. </p><p>Each node has rich semantic node features as node representation (content-based and topology-based node features are available).</p><p>More information can be found in the README.txt and on <a href="https://github.com/davidlamprecht/AutoRDF2GML">https://github.com/davidlamprecht/AutoRDF2GML.</a></p><p> </p><p><strong>soa-sw-homogeneous-author</strong> only models the co-author network of SOA-SW.</p><p>It is a homogeneous graph containing the author node type (19,970 nodes) and the edge type author- author.</p><p>The authors' content-based features (nodes-nld) are based on the titles and abstracts of the authors' works (128-dimensional SciBERT embeddings).</p>
Impact of atmospheric water-soluble iron on α-pinene-derived SOA formation and transformation in the presence of aqueous droplets
<p>The following data sets belong to the article "Impact of atmospheric water-soluble iron on α-pinene-derived SOA formation and transformation in the presence of aqueous droplets" The impact of water-soluble atmospheric iron on formation, growth and aging of secondary organic aerosol (SOA) is a controversial subject in the literature. Iron chemistry drives Fenton-like reactions in the aqueous phase which is dependent on pH. Flow reactor experiments in the dark and under humid conditions were conducted to investigate systematically the influence of ferrous iron in the aqueous phase on α-pinene SOA by online physical analysis and offline high-resolution mass spectrometry. In total 31 flow reactor experiments were conducted in four sets of experiments. All SMPS data and mass spectra in negative mode are uploaded sorted by set of experiments and figures in the paper. You can find the workflow of SMPS data analysis as well as the retention times of the target analysis in the paper and SI.</p>
dataset for MT-SOA CCN activity
<p>This dump provides access to the metadata from the main text related to publication of MT-SOA CCN activity.</p>
Data for "• Can we achieve atmospheric chemical environments in the laboratory? An integrated model-measurement approach to chamber SOA studies"
Open the record for dataset details and reuse information.
The sex-specific factor SOA establishes X chromosome dosage compensation in Anopheles mosquitos [SOAR-RNA-seq]
GEO Series GSE233473. Anopheles gambiae. 7 samples. Type: Expression profiling by high throughput sequencing.
SOA confers X chromosome dosage compensation in Anopheles gambiae mosquitoes (RNA-Seq I)
GEO Series GSE210625. Anopheles gambiae. 9 samples. Type: Expression profiling by high throughput sequencing.
SOA confers X chromosome dosage compensation in Anopheles gambiae mosquitoes (RNA-Seq II)
GEO Series GSE210629. Anopheles gambiae. 8 samples. Type: Expression profiling by high throughput sequencing.
Modeling the influence of carbon branching structure on SOA formation via multiphase reactions of alkanes
<p>This data set includes smog chamber data obtained from experiments performed with branched alkanes as well as gas and aerosol model simulations. Please read the "Read Me.Txt" file for more detailed information.</p>
Contract design thinking: a service oriented architecture SOA for contract models, maintenance and testing
Open the record for dataset details and reuse information.
SOA confers X chromosome dosage compensation in Anopheles gambiae mosquitoes (CUT&Tag I)
GEO Series GSE210627. Anopheles gambiae. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
The sex-specific factor SOA establishes X chromosome dosage compensation in Anopheles mosquitos [SOAR-CUTnTag]
GEO Series GSE233472. Anopheles gambiae. 7 samples. Type: Other.
The sex-specific factor SOA establishes X chromosome dosage compensation in Anopheles mosquitos [Mybless-CUTnTag]
GEO Series GSE233471. Anopheles gambiae. 8 samples. Type: Other.
SOA confers X chromosome dosage compensation in Anopheles gambiae mosquitoes (CUT&Tag II)
GEO Series GSE210628. Anopheles gambiae. 20 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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