1,721,678 research outputs found
Modeling and optimization of a binary geothermal power plant
Full text linkA model is developed for an existing organic Rankine cycle (ORC) utilizing a low temperature geothermal source. The model is implemented in Aspen Plus® and used to simulate the performance of the existing ORC equipped with an air-cooled condensation system. The model includes all the actual characteristics of the components. The model is validated by approximately 5000 measured data in a wide range of ambient temperatures. The net power output of the system is maximized. The results suggest different optimal operation strategies based on the ambient temperature. Existing literature claims that no superheat is optimal for maximum performance of the system; this is confirmed only for low ambient temperatures. For moderate ambient temperatures (Tamb ≥ 1.7 °C) superheat maximizes net power output of the system. The value of the optimal superheat increases with increasing ambient temperature. The optimal operation boosts the total power produced in a year by 9%. In addition, a simpler and semi-analytic model is developed that enables very quick optimization of the operation of the cycle. Based on the pinch condition at the condenser, a simple explicit formula is derived that predicts the outlet pressure of the turbine as a function of mass flow rate of working fluid.Ente nazionale per l'energia elettricaNatural Sciences and Engineering Research Council of Canada (NSERC Postdoctoral Fellowship
Optimization of multi-pressure himidification-dehumidification desalination using thermal vapor compression and hybridization
Full text linkConference site: http://www.ishmt2011.iitm.ac.in/Humidification-dehumidification (HD or HDH) desalination, and specifically HD driven by a thermal vapor compressor (TVC), is a thermal desalination method that has the potential to produce potable water efficiently in order to address the growing demand for water. This article presents a numerical study and optimization of two HD-TVC cycle configurations in order to determine the best achievable thermal performance. Through the use of nonlinear programming, it is found that the simplest configuration of HD-TVC has performance comparable to a traditional single-stage,
single-pressure HD cycle (GOR 0.8–2.0), while the hybridized HD-TVC cycle with reverse osmosis (RO)
has thermal performance that is competitive with existing large scale desalination systems (GOR 11.8–28.3).Center for Clean Water and Clean Energy at MIT and KFUPMNumerica TechnologyKing Fahd University of Petroleum and Mineral
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Advanced System Simulation, Parameter Estimation and Process Design in Preparative Chromatography
No full textPreparative chromatography is one of the prevailing processes in academia and industry to extract or purify one or several target components from a mixture solution. Mathematical modeling can support rational design and analysis of experiments that are usually time-consuming and expensive. In this thesis, model based contributions are made to advanced simulation and efficient optimization of preparative chromatography. Bayesian inference is applied to parameter estimation of chromatographic models in batch mode. To this end, a Markov Chain Monte Carlo (MCMC) algorithm is enhanced for improved convergence and efficiency. Experimental data for a case study, using lysozyme as model protein, was provided by a collaboration partner. Parameter estimation is performed in several stages, each resulting in probability distributions for the sought parameters and using previous results as prior information. Uncertainty of the estimated parameters is quantified using credible intervals. Throughput of chromatographic processes can be increased by using continuous instead of batch operation, e.g., simulated moving bed (SMB), which is a network of single columns operated in counter-current mode. A modeling strategy for SMB processes based on weak coupling of individual column models is developed, which has flexibilities in not only supporting different network configurations but also choosing between various modeling options for the columns and dead volumes. The one-column analog has been published, while operating-splitting appears to be novel at least in the field of chromatography modeling. Four numerical methods are developed in one software such that a fair comparison between them is presented. The introduced methods for solving inverse problems and efficiently simulating SMB chromatography are applied to optimally design ion-exchange SMB (IEX-SMB) units for protein separations. The major difficulty in determining operating conditions of IEX-SMB processes is the nonlinearity that results from its binding kinetics. Consequently, the commonly used triangle theory is not applicable, and inverse methods are applied in this study. A binary and a ternary mixture are used as case studies; the process design of ternary separation using closed-loop IEX-SMB is novel. Suitable network configurations have been successfully determined to separate the proteins. Lastly, the author has implemented the MCMC algorithm (CADET-MCMC) and different solution approaches for SMB models (CADET-SMB) in software packages based on the CADET project. They are published as open-source software and freely distributed under the GPL license
Variations on the Author
Full text link“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
Full text linkWe 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
Simultaneous real-time scheduling of multi-energy systems and dynamic production processes
No full textVolatile renewable electricity production causes a temporal mismatch of supply and demand, which can be reduced by consumers using optimal production scheduling to shift their demand in time. However, if production processes with nonlinear dynamics must be scheduled simultaneously with multi-energy systems (MESs) introducing discrete on/off decisions, the resulting optimization problems are typically not solvable in real-time today. This thesis reformulates simultaneous dynamic scheduling (SDS) problems of MESs and nonlinear production processes to mixed-integer linear programs (MILPs), which can be solved in real-time. These MILP reformulations rely on tailored scheduling models consisting of three piece-wise affine (PWA) parts: (1) process output models, (2) data-driven process energy demand models, and (3) MILP energy system models. For part 1, we present two alternatives: First, we use a scale-bridging model (SBM), which is easy-to-apply but requires heuristic tuning. We use two cooled continuous stirred tank reactor (CSTR) case studies to show that our approach can capture the major part of the nonlinear potential in real time, and a heated distillation column case study to show that our approach can reduce the number of states substantially. Second, as a rigorous alternative to the heuristically tuned SBM, we derive dynamic ramping constraints (DRCs), which are first restricted to flat processes with only one scheduling relevant variable. These DRCs consider linear dynamics of high order with PWA constraints. We use that, for flat processes, a nonlinear model can be transferred to a linear model by coordinate transformation. Again, we use a CSTR case study to show that our approach can capture the major part of the nonlinear potential. For non-flat processes, we develop heuristic DRCs, based on simulation experiments. For the heated distillation column, these heuristic DRCs perform similarly to SBMs regarding both optimization runtime and operational costs. Lastly, we show that DRCs can also consider multiple scheduling-relevant variables by applying DRCs to an electrolyzer with slow temperature dynamics. We outperform a quasi-steady-state scheduling through optimized temperature dynamics. This thesis thus offers reformulations that strike reasonable compromises between optimization runtime and solution quality for SDS of production processes and MESs. While SBMs can be applied with less effort and knowledge, DRCs offer more dynamic flexibility for flat processes
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
- …
