Exergy-based method for analyzing the composition of the electricity cost generated in gas-fired combined cycle plants

The proposed method to analyze the composition of the cost of electricity is based on the energy conversion processes and the destruction of the exergy through the several thermodynamic processes that comprise a combined cycle power plant. The method uses thermoeconomics to evaluate and allocate the cost of exergy throughout the processes, considering costs related to inputs and investment in equipment. Although the concept may be applied to any combined cycle or cogeneration plant, this work develops only the mathematical modeling for three-pressure heat recovery steam generator (HRSG) configurations and total condensation of the produced steam. It is possible to study any n x 1 plant configuration (n sets of gas turbine and HRSGs associated to one steam turbine generator and condenser) with the developed model, assuming that every train operates identically and in steady state. The presented model was conceived from a complex configuration of a real power plant, over which variations may be applied in order to adapt it to a defined configuration under study [Borelli SJS. Method for the analysis of the composition of electricity costs in combined cycle thermoelectric power plants. Master in Energy Dissertation, Interdisciplinary Program of Energy, Institute of Eletro-technical and Energy, University of Sao Paulo, Sao Paulo, Brazil, 2005 (in Portuguese)]. The variations and adaptations include, for instance, use of reheat, supplementary firing and partial load operation. It is also possible to undertake sensitivity analysis on geometrical equipment parameters. (C) 2007 Elsevier Ltd. All rights reserved.

An everyday nostalgia: Memory and the fictions of belonging

In 1984, George Orwell presented the future as a dystopian vision, where everyday existence was governed and redefined by an oppressive regime. Winston Smith's daily duties at the Ministry of Truth involved the invention, rewriting and erasing of fragments of history as a means of perpetuating contentment, uniformity and control. History, as Orwell described it in the novel 'was a palimpsest, scraped clean and reinscribed exactly as often as was necessary.' More that a quarter of a century after the publication of 1984, Michel Foucault discussed the cinematic representation and misrepresentation of French history and identity in terms of what he called the manipulation of 'popular memory'. In what was tantamount to a diluted version of Orwell's palimpsestic histories, Foucault stated that 'people are not shown what they were, but what they must remember having been.' This paper will investigate notions of memory, identity and the everyday through a discussion of the community of Celebration in Florida. Conceived in the 1990s, Celebration was designed around a fictionalised representation of pre 1940s small town America, using nostalgia for a mythologised past to create a sense of comfort, community and conformity among its residents. Adapting issues raised by Orwell, Foucault and Baudrillard, this paper will discuss the way in which architecture, like film and literature, can participate in what Foucault discussed as the manipulation of popular memory, inducing and exploiting a nostalgia for an everyday past that that never really existed.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

New ideologies of everyday life in South Korean language textbooks

This chapter analyses with critical discourse analysis, contemporary Korean language textbooks which are being used in early primary school.

Analyzing the researcher's work in generating data: The case of complaints

This article investigates the researcher's work in the coproduction (or not) of complaint sequences in research interviews. Using a conversation analytic approach, we show how the interviewer's management of complaint sequences in a research setting is consequential for subsequent talk and thus directly affects the data generated. In the examples shown here, researchers sharing cocategorial incumbency with respondents may well provide spaces for research participants to formulate complaints. This article examines sequences of talk surrounding complaints to show how researchers generate complaints (or not) and handle unsafe complaints. Researchers are able to provoke specific types of accounts from respondents, whereas their respondents may actively resist the researchers' direction. For researchers using the interview as a method of data generation, examination of complaint sequences and how these appear in interview data provides insight into how interview talk is coproduced and managed within a socially situated setting.