An Active Learning Method for the Comparison of Agent-based Models.
Abstract not provided.
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Abstract not provided.
This disclosure provides microbes engineered to detect virulent and spore states of pathogens and release an appropriate therapeutic response accordingly and compositions and methods of use of the same.
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Presented by NETL at 2019 Carbon Capture, Utilization, Storage, and Oil and Gas Technologies Integrated Review Meeting, 08/19
Presented by NETL at 2019 International Pittsburgh Coal Conference, 09/19
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Abstract not provided.
The purpose of this grant was to conduct scientific research and prototype applications to support NPP outage staff in their adaptive decision-making in efficient scheduling and resource allocation while preventing violation of safety technical specifications. The project contributed to scientific knowledge and engineering methods in (1) user interface design, (2) scheduling optimization and risk estimation, and (2) natural language processing that would benefit the nuclear power plants in minimizing schedule overruns and even unexpected shutdowns. The research team conducted site visits at a test reactor facility and an operating nuclear power plant to gather necessary information and inputs for research and development of a software application to support NPP staff in executing their outages. The final software application consisted of three modules. First, the natural language processing module supports interactive processing of technical documentation to build a database for outage staff to query non-permissible actions on system components. This module can alleviate outage staff from reviewing extensive documentation and minimize violation of technical specifications, especially in time-sensitive situations. Second, the schedule optimization module schedules outage activities and compute risk indices that outperform existing software and current practice. This module can reduce completion time of an outage that typically have too many activities for human to optimize based on current practice that does not apply the latest operations research. Finally, the visualization module presents progress and risk information of the overall outage and individual activities, as well as enabling access to the natural language processing and schedule optimization modules. This module can provide outage staff with situation awareness that are necessary to make risk-informed decisions in response to unexpected events during the execution of an outage.
38th Annual International Pittsburgh Coal Conference, Virtual, September 20-23, 2021
Abstract not provided.
Conference Research Paper Presentation
Abstract not provided.
A nuclear magnetic resonance (NMR) system is configured to detect chemical threat material. The system comprises a magnet configured to generate a magnetic field of about 300 millitesla or less; and a probe configured to detect nuclear relaxation of at least two nuclei selected from the group consisting of 1H, 19F, 31P and 14N, and detect the spin density of nuclei selected from the group consisting of 1H, 19F, 31P and 14N, following excitation.
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Circular Economy (CE) aims at decoupling human activities from economic growth and resource use. While CE economic and environmental benefits are often touted by its proponents, increased circularity and improved sustainability do not necessarily go hand-in-hand. The Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework simulates the transition of renewable energy technology supply chains towards circularity and quantifies spatially explicit environmental impacts and supply chain costs. Using wind blade end-of-life (EOL) management as a case study, this presentation will highlight CELAVI's features. Furthermore, envisioned extension to the framework could improve the stakeholder decision model by accounting for logistical and other factors. The CELAVI framework could be leveraged to answer crucial questions regarding renewables EOL management.
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