1,720,983 research outputs found
Graph neural network for multi-physics geothermal simulation with discrete fracture network
No full textWith the increasing global energy demand, geothermal energy provides a clean and sustainable alternative to traditional fossil fuel energy. Numerical simulation of geothermal energy recovery requires high computational cost, since it considers the coupled physics of fluid flow in porous media, heat transport, and geomechanics. Even though many recent studies focus on developing deep-learning models to accelerate geothermal reservoir simulation, they are relatively limited to geothermal reservoirs with no fractures or relatively simple planar fractures, which typically use Cartesian grids for discretization.Manojkumar Gudala, and Bicheng Yan thanks for Research Support from King Abdullah University of Science and Technology (KAUST), Saudi Arabia through grants BAS/1/1423-01-01 and FCC/1/4491-22-01
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Optimization of Solar-Geothermal Hybrid Power Plant System Through Deep Learning
No full textIn 2017, the Kingdom of Saudi Arabia (KSA) began to construct NEOM, a city powered entirely on renewable energy. Geothermal and solar are two of the most abundant renewable resources in NEOM, with great potential for electricity generation. What's more, the hybridization of two resources can significantly enhance the performances of the binary geothermal power plant. However, most of the existing simulation models fail to integrate the geothermal reservoir, the solar field and the power plant, leading to inaccurate evaluations of the electricity capacity of both energy resources. Therefore, in this work, we present a novel optimization framework in which the geothermal reservoir model, the solar field model as well as the hybrid power plant model are fully coupled. The geothermal production temperature from the reservoir is predicted through decline curve analysis (DCA) and deep neural network (DNN), which is then coupled with the in-house solar field model and power plant model. Finally, the three parts in the integrated model are optimized simultaneously by a multi-objective optimizer for the best thermodynamic and economic performances. Results show that the DNN model can accurately and efficiently predict the parameters of the decline model with R2 scores of 0.973, 0.961, 0.953, 0.998 and 0.996, with an error of 0.56 ± 0.42% for the bottom hole temperature and 0.55 ± 0.42% for the surface production temperature. The average CPU time is 0.0026 s per case. Both the solar field model and the power plant models are validated with data from the literature with tolerable deviations. Optimization results indicate that the supercritical configuration is the optimal configuration for both the geothermal stand-alone and hybrid power plants. The hybridization of the solar and geothermal can generate more electricity and reduce the levelized cost of electricity. Our optimization work can provide guidance to the implementation and operations of the geothermal reservoir, the solar field and the power plant under optimal conditions.The authors thanks the King Abdullah University of Science and Technology (KAUST) for the research funding through grant BAS/1/1423-01-01
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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