Energy
This dataset supports the manuscript titled “Strategies for Mitigating Degradation of Medium Voltage Electrical Equipment in Harsh Saline Environments.” The study focuses on identifying and addressing the challenges faced by medium voltage equipment in coastal environments characterized by high salinity, humidity, and extreme weather conditions. The dataset includes:
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The given data contains the results from laboratory trials related to the paper "Optimizing Congestion Management andEnhancing Resilience in Low-Voltage Grids Using OPF and MPC Control Algorithms Through Edge Computing and IEC 61850 Standards" currently in publication in IEEE Access.
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Autonomous underwater vehicles (AUVs) are extensively utilized for underwater resource exploration, requiring inductive power transfer (IPT) systems with large output power to achieve quick charging. However, underwater positioning errors result in significant variations in the coupling coefficient of the IPT system. Moreover, AUVs employ diverse battery types and voltages, exacerbating the issue of decreased transferred power when the coupling coefficient and battery voltage are low, thereby prolonging the AUVs' charging time.
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Numerical simulations are used to assess the efficiency of floor heating, ceiling heating, and plane radiator heating in a selected family house room under winter conditions in the Central European climate zone. COMSOL Multiphysics software was used for computer simulations. The output data were subsequently processed and analyzed using MATLAB software. Results indicate that floor and ceiling heating systems achieve higher and more rapid temperature increases compared to plane radiators.
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This dataset comprises Bloomberg Terminal data from 2017 to 2021, detailing environmental footprints, disclosure practices, risk profiles, and ESG fund commitments of Fortune 500 companies. The data captures various dimensions of environmental, social, and governance (ESG) performance, providing a comprehensive view of corporate sustainability trends. It includes quantitative indicators and qualitative scores for companies' ESG strategies, enabling researchers to analyze ESG practices and trends over time.
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Well logs are interpreted/processed to estimate the in-situ reservoir properties (petrophysical, geomechanical, and geochemical), which is essential for reservoir modeling, reserve estimation, and production forecasting. The modeling is often based on multi-mineral physics or empirical formulae. When sufficient amount of training data is available, machine learning solution provides an alternative approach to estimate those reservoir properties based on well log data and is usually with less turn-around time and human involvements.
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This paper presents a method for modeling and simulating three-phase grid-connected solid-oxide fuel cell systems in the Matlab/Simulink environment. The approach is utilized to analyze the interaction between solid-oxide fuel cells and the electrical power system, focusing on understanding the dynamics of the electrochemical reaction and its impact on the performance of grid-connected fuel cell systems. The results highlight the effectiveness of the proposed method in accurately modeling and operating three-phase grid-connected solid-oxide fuel cell systems.
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This dataset is in support of my research claim and presentation. Make sure you have read Caution. Make sure you have read LegalDisclosureStatement, as some later accuse of hiding.
I. Research/ Presentation Title *:
(For Free download, pls. click on title)
* The submitted work will be used in my future presentations or future research paper, with same or different titles.
Videos uploaded on YouTube are
II. Model
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This dataset is in support of my research claim and presentation. Make sure you have read Caution. Make sure you have read LegalDisclosureStatement, as some later accuse of hiding.
I. Research/ Presentation Title *:
(For Free download, pls. click on title)
* The submitted work will be used in my future presentations or future research paper, with same or different titles.
Videos uploaded on YouTube are
II. Model
- Categories:
This dataset is in support of my research claim and presentation. Make sure you have read Caution. Make sure you have read LegalDisclosureStatement, as some later accuse of hiding.
I. Research/ Presentation Title *:
(For Free download, pls. click on title)
* The submitted work will be used in my future presentations or future research paper, with same or different titles.
Videos uploaded on YouTube are
II. Model
- Categories: