1,720,958 research outputs found
Transient Modeling and Simulation of Variable Geometry Industrial Gas Turbines
No full textGas Turbines are widely used in the power industry and petrochemical industries. The present thesis deals with transient modeling and simulation of industrial gas turbines featured by a schedule for variable inlet guide vanes (VIGV). Both the modelling (steady-state and transient) and simulation are carried out by using a commercial software called GasTurb 12 that was originally developed by Dr Kurzke. The whole process is demonstrated by considering a three-shaft industrial gas turbine (GE LM1600) because it deals with a lot of complexities during transient operation. First, the design point and off-design steady state results were compared with data from already published literature. Secondly, the combined effect of performance deterioration phenomena (VIGV, compressor fouling, and high inlet air temperatures) on the overall health and performance of gas turbine was investigated through a steady state off-design simulation. Thirdly, the transient simulation is performed to study load change phenomena through acceleration and deceleration; two kinds of fuel flow schedules were incorporated
Performance-Based Intelligent Diagnostics, Prognostics, and Health Monitoring of Hydrogen Fueled Gas Turbines
Get PDFGlobal energy transition efforts towards decarbonization requires significant advances within the energy sector. In this regard, hydrogen is envisioned as a long-term alternative fuel for gas turbines. Accordingly, the gas turbine industry has expedited their efforts in developing 100% hydrogen compliant burners and associated auxiliary components for retrofitting the existing gas turbines. The utilization of hydrogen in gas turbines has some underlying challenges such as corrosion mainly originating from increased steam content in the hot gas path. In addition to corrosion, the gas turbine compressor is vulnerable to fouling, which is the most commonly occurring fault in gas turbine operating over certain time window. Both faults are susceptible to performance and health degradation. Owing to these problems, an in-depth thermodynamic performance assessment along with combustor’s flue gas thermophysical properties analysis becomes crucial. In addition to the thermodynamic performance model, performance-based intelligent fault diagnostics and prognostics/ remaining useful life (RUL) estimation of hydrogen fueled gas turbine is point of concern for the gas turbines original equipment manufacturers (OEMs) and operators.
The present thesis therefore addresses the above-mentioned technical challenges by providing a detailed comparative thermodynamic performance assessment of both hydrogen and natural gas (NG) fueled gas turbine scenarios. Besides, a comparative analysis of various artificial intelligence (AI) based approaches have been conducted for performance degradation estimation and fault diagnostics. Furthermore, to avoid expensive asset loss caused by unexpected downtimes and shutdowns, data-statistical prognostics have been employed for both NG and hydrogen fueled scenarios.
The first part of the thesis consists of thermodynamic performance and combustion flue gas analysis. The combustion reactions and detailed analysis of fluid flow properties manifested that H2 fuel utilization results
in an increased steam content (by ~106%) as compared to NG combustion. The combined effect of turbine corrosion severity level and high ambient temperature on the overall performance of the MGT showsthat the increased corrosion severity level at high ambient temperature can lead to deterioration in power and thermal efficiency. The second part deals with fault diagnostics using different machine learning based techniques. To identify an accurate algorithm, various algorithms such as support vector machine, decision tree, random forest algorithm, k-nearest neighbors, and artificial neural network were tested. The findings from fault diagnostics process (classification) revealed that ANN outperformed its counterpart algorithm by giving accuracy of 94.55%. Similarly, ANN also showed higher accuracy in performance degradation estimation process (regression) by showing the MSE of training loss as low as ~0.14. The comparative analysis of all the chosen algorithms in the present study revealed ANN as the most accurate algorithm for fault diagnostics of hydrogen fueled gas turbines. The last part dealt with prognostics/RUL estimation. In this regard, the study incorporated linear and polynomial regression approaches and compared the end of life of gas turbines running on natural gas and hydrogen fuels. It became evident from the study that RUL of a gas turbine running on hydrogen fuel is 6.47% lower than that of natural gas fueled gas turbines. These findings underline the necessity of using strong prediction models, as well as targeted maintenance actions, to limit the consequences of turbine corrosion in hydrogen powered MGTs. The findings of the present study further provide new horizons for design modification and effective health monitoring of hydrogen fueled gas turbines
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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