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Correlation Equation (correlation + equation)

Distribution by Scientific Domains

Chemistry	57%
Engineering	28%

Selected Abstracts

Correlation equation for predicting filter coefficient under unfavorable deposition conditions

AICHE JOURNAL, Issue 5 2008
You-Im Chang
Abstract A new correlation equation for predicting the filter coefficient under unfavorable deposition conditions is presented. By adopting the triangular network model of using the Brownian dynamic simulation method, as the sum of four individual deposition mechanisms, e.g., the Brownian diffusion, the DLVO interactions, the gravitational force, and the interception, the correlation equation is obtained by regressing against a broad range of parameter values governing particle deposition in deep bed filtration. The new correlation equation is able to describe previous experimental results well, especially for those submicro particles with significant Brownian motion behavior. © 2008 American Institute of Chemical Engineers AIChE J, 2008 [source]

Iterative correlation-based controller tuning

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2004
A. Karimi
Abstract This paper gives an overview on the theoretical results of recently developed algorithms for iterative controller tuning based on the correlation approach. The basic idea is to decorrelate the output error between the achieved and designed closed-loop systems by iteratively tuning the controller parameters. Two different approaches are investigated. In the first one, a correlation equation involving a vector of instrumental variables is solved using the stochastic approximation method. It is shown that, with an appropriate choice of instrumental variables and a finite number of data at each iteration, the algorithm converges to the solution of the correlation equation. The convergence conditions are derived and the accuracy of the estimates are studied. The second approach is based on the minimization of a correlation criterion. The frequency analysis of the criterion shows that the two norm of the error between the desired and achieved closed-loop transfer functions is minimized independent of the noise characteristics. This analysis leads to the definition of a generalized correlation criterion which allows the mixed sensitivity problem to be handled in two norm. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Modelling and experimental studies on heat transfer in the convection section of a biomass boiler

INTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 12 2006
Jukka Yrjölä
Abstract This paper describes a model of heat transfer for the convection section of a biomass boiler. The predictions obtained with the model are compared to the measurement results from two boilers, a 50 kWth pellet boiler and a 4000 kWth wood chips boiler. An adequate accuracy was achieved on the wood chips boiler. As for the pellet boiler, the calculated and measured heat transfer rates differed more than expected on the basis of the inaccuracies in correlation reported in the literature. The most uncertain aspect of the model was assumed to be the correlation equation of the entrance region. Hence, the model was adjusted to improve the correlation. As a result of this, a high degree of accuracy was also obtained with the pellet boiler. The next step was to analyse the effect of design and the operating parameters on the pellet boiler. Firstly, the portion of radiation was established at 3,13 per cent, and the portion of entrance region at 39,52 per cent of the entire heat transfer rate under typical operating conditions. The effect of natural convection was small. Secondly, the heat transfer rate seemed to increase when dividing the convection section into more passes, even when the heat transfer surface area remained constant. This is because the effect of the entrance region is recurrent. Thirdly, when using smaller tube diameters the heat transfer area is more energy-efficient, even when the bulk velocity of the flow remains constant. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Correlation equation for predicting filter coefficient under unfavorable deposition conditions

Combination of Fragmental and Topological Descriptors for QSPR Estimations of Boiling Temperature

MOLECULAR INFORMATICS, Issue 8 2004
Irina
Abstract The novel QSPR equation for estimation of physicochemical properties of organic substances is proposed. This equation includes contributions depending on the counts of bonds and nonadditive contribution. The nonadditive term is represented as an explicit function of topological distances on the line graph of molecules. The original mathematical form for description of nonadditive contribution is suggested. The application of the derived equation to estimation of normal boiling temperatures for the saturated hydrocarbons (total number of compounds n=198; correlation coefficient r=0.9966; mean square deviation ,=3.4,K) has proved the effectiveness of the proposed approach. The modification of correlation equation is made for estimations of normal boiling temperatures for substances with OH and NH2 groups (n =139; r=0.9971; ,=3.9,K). [source]

Estimation and hedging effectiveness of time-varying hedge ratio: Flexible bivariate garch approaches

THE JOURNAL OF FUTURES MARKETS, Issue 1 2010
Sung Yong Park
Bollerslev's (1990, Review of Economics and Statistics, 52, 5,59) constant conditional correlation and Engle's (2002, Journal of Business & Economic Statistics, 20, 339,350) dynamic conditional correlation (DCC) bivariate generalized autoregressive conditional heteroskedasticity (BGARCH) models are usually used to estimate time-varying hedge ratios. In this study, we extend the above model to more flexible ones to analyze the behavior of the optimal conditional hedge ratio based on two (BGARCH) models: (i) adopting more flexible bivariate density functions such as a bivariate skewed- t density function; (ii) considering asymmetric individual conditional variance equations; and (iii) incorporating asymmetry in the conditional correlation equation for the DCC-based model. Hedging performance in terms of variance reduction and also value at risk and expected shortfall of the hedged portfolio are also conducted. Using daily data of the spot and futures returns of corn and soybeans we find asymmetric and flexible density specifications help increase the goodness-of-fit of the estimated models, but do not guarantee higher hedging performance. We also find that there is an inverse relationship between the variance of hedge ratios and hedging effectiveness. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:71,99, 2010 [source]