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1015 research outputs found
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An empirical analysis on webservice antipattern prediction in different variants of machine learning perspective
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Examining pathways for a climate neutral Europe by 2050; A model comparison analysis including integrated assessment models and energy system models
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Fracture Characterization for New Landfill Sites in Crystalline Bedrock: A Case Study from Rogaland, Southwestern Norway
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The Langmuir Probe Instrument on Board the Rashid-1 Rover of the Emirates Lunar Mission
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Critical properties and testing methods for sealants in CCS applications
Full text linkLong-term wellbore seal integrity is an important challenge for secure geological storage of CO2. Based on experimental research performed by the CEMENTEGRITY project, as well as literature study, we have identified three key abilities that any CCS wellbore sealant must have. These are: the ability to form and maintain a seal; the ability to resist exposure to CO2-containing fluids; and the ability to withstand thermal shocks or cycling. We have assessed these abilities for five different sealant compositions, using different methodologies for each ability. Based on that research, this report identifies the basic properties that are critical for ensuring a high-quality seal, as well as its long-term durability and integrity during CO2-injection and - storage. When assessing a sealant design for a specific application, these properties and the impact of CO2, thermal changes, and other potentially deleterious effects on them should be tested. Furthermore, as all research groups collaborating in CEMENTEGRITY performed their research on centrally prepared samples, we were able to compare results obtained by different research groups that used different methods to assess the key abilities. Such a comparison is presented in this report, and is used as a basis for suggesting preferred testing methods for CCS sealants.Critical properties and testing methods for sealants in CCS applicationspublishedVersio
Web-based phishing URL detection model using deep learning optimization techniques
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