A systemic approach for optimal cooling tower operation

The thermal performance of a cooling tower and its cooling water system is critical for industrial plants, and small deviations from the design conditions may cause severe instability in the operation and economics of the process. External disturbances such as variation in the thermal demand of the process or oscillations in atmospheric conditions may be suppressed in multiple ways. Nevertheless, such alternatives are hardly ever implemented in the industrial operation due to the poor coordination between the utility and process sectors. The complexity of the operation increases because of the strong interaction among the process variables. In the present work, an integrated model for the minimization of the operating costs of a cooling water system is developed. The system is composed of a cooling tower as well as a network of heat exchangers. After the model is verified, several cases are studied with the objective of determining the optimal operation. It is observed that the most important operational resources to mitigate disturbances in the thermal demand of the process are, in this order: the increase in recycle water flow rate, the increase in air flow rate and finally the forced removal of a portion of the water flow rate that enters the cooling tower with the corresponding make-up flow rate. (C) 2009 Elsevier Ltd. All rights reserved.

Minimizing total tardiness in a stochastic single machine scheduling problem using approximate dynamic programming

This paper addresses the non-preemptive single machine scheduling problem to minimize total tardiness. We are interested in the online version of this problem, where orders arrive at the system at random times. Jobs have to be scheduled without knowledge of what jobs will come afterwards. The processing times and the due dates become known when the order is placed. The order release date occurs only at the beginning of periodic intervals. A customized approximate dynamic programming method is introduced for this problem. The authors also present numerical experiments that assess the reliability of the new approach and show that it performs better than a myopic policy.

Stochastic stability analysis for the constant-modulus algorithm

We derive an easy-to-compute approximate bound for the range of step-sizes for which the constant-modulus algorithm (CMA) will remain stable if initialized close to a minimum of the CM cost function. Our model highlights the influence, of the signal constellation used in the transmission system: for smaller variation in the modulus of the transmitted symbols, the algorithm will be more robust, and the steady-state misadjustment will be smaller. The theoretical results are validated through several simulations, for long and short filters and channels.

SELF-SIMILARITY AND LAMPERTI CONVERGENCE FOR FAMILIES OF STOCHASTIC PROCESSES

We define a new type of self-similarity for one-parameter families of stochastic processes, which applies to certain important families of processes that are not self-similar in the conventional sense. This includes Hougaard Levy processes such as the Poisson processes, Brownian motions with drift and the inverse Gaussian processes, and some new fractional Hougaard motions defined as moving averages of Hougaard Levy process. Such families have many properties in common with ordinary self-similar processes, including the form of their covariance functions, and the fact that they appear as limits in a Lamperti-type limit theorem for families of stochastic processes.

Influence of storage temperature on cooling intensity of topical emulsions containing encapsulated menthol

The cooling intensity of topical emulsions added with encapsulated or free menthol was evaluated by a screened and trained panel recruited based on the American Society for Testing and Materials method. A sensory panel composed of 10 trained judges performed the evaluation of samples stored at 22 +/- 2C for 24 h and, after 28 days of storage, at 37.0 +/- 0.5C. The obtained data were analyzed by analysis of variance and Tukey`s test. The results showed an increase of cooling intensity as a function of encapsulated menthol concentration. The opposite was observed in samples added with free menthol, which may have caused sensory fatigue. Storage at 37 +/- 0.5C for 28 days had no impact on the cooling intensity of emulsions containing encapsulated menthol, demonstrating high stability and suggesting its application in cooling skin care products. In contrast, emulsions added with free menthol showed a drastic decrease of cooling intensity at 37 +/- 0.5C..

Influence of the irradiation distance and the use of cooling to increase enamel-acid resistance with Er:YAG laser

Objectives: The aim of this study was to assess the influence of irradiation distance and the use of cooling in the Er:YAG laser efficacy in preventing enamel demineralization. Methods: 84 enamel blocks were randomly assigned to seven groups (n = 12): G1: control group - no treatment, G2-G7: experimental groups treated with Er:YAG laser (80 mJ/2 Hz) at different irradiation distances with or without cooling: G2: 4 mm/2 mL; G3: 4 mm/no cooling; G4: 8 mm/2 mL; G5: 8 mm/no cooling; G6: 16 mm/2 mL; G7: 16 mm/no cooling. The samples were submitted to an in vitro pH cycles for 14 days. Next, the specimens were sectioned in sections of 80-100 mu m in thickness and the demineralization patterns of prepared slices were assessed using a polarized light microscope. Three samples from each group were analyzed with scanning electronic microscopy. Analysis of variance and the Fisher test were performed for the statistical analysis of the data obtained from the caries-lesion-depth measurements (CLDM) (alpha = 5%). Results: The control group (CLDM = 0.67 mm) was statistically different from group 2 (CLDM = 0.42 mm), which presented a smaller lesion depth, and group 6 (0.91 mm), which presented a greater lesion depth. The results of groups 3 (CLDM = 0.74 mm), 4 (CLDM = 0.70 mm), 5 (CLDM = 0.67 mm) and 7 (CLDM = 0.89 mm) presented statistical similarity. The scanning electronic microscopy analysis showed ablation areas in the samples from groups 4, 5, 6 and 7, and a slightly demineralized area in group 2. Conclusions: It was possible to conclude that Er:YAG laser was efficient in preventing enamel demineralization at a 4-mm irradiation distance using cooling. (C) 2010 Elsevier Ltd. All rights reserved.

An alternative method to study the cooling of glasses from melt to solid phase

The aim of this preliminary work was to present a novel method, suitable to investigate the glass cooling, from melt to solid state, based on a fast, non-usual and easy microwave method. The following glass system xBaO . (100-x)B(2)O(3) (x = 0% and 40%) was selected as an example for this study. The melt was poured inside a piece of waveguide and then, its cooling was monitored by the microwave signal as a function of time. The variations in the signal can provide valuable informations about some structural changes that take place during the cooling stages, such as relaxation processes. This method can be useful to investigate the cooling and heating of other materials, opening new possibilities for investigation of dielectric behavior of materials under high temperatures. (C) 2008 Elsevier Inc. All rights reserved.

Stochastic simulations of the Madden-Julian oscillation activity

The Madden-Julian oscillation (MJO) is the most prominent form of tropical intraseasonal variability. This study investigated the following questions. Do inter-annual-to-decadal variations in tropical sea surface temperature (SST) lead to substantial changes in MJO activity? Was there a change in the MJO in the 1970s? Can this change be associated to SST anomalies? What was the level of MJO activity in the pre-reanalysis era? These questions were investigated with a stochastic model of the MJO. Reanalysis data (1948-2008) were used to develop a nine-state first order Markov model capable to simulate the non-stationarity of the MJO. The model is driven by observed SST anomalies and a large ensemble of simulations was performed to infer the activity of the MJO in the instrumental period (1880-2008). The model is capable to reproduce the activity of the MJO during the reanalysis period. The simulations indicate that the MJO exhibited a regime of near normal activity in 1948-1972 (3.4 events year(-1)) and two regimes of high activity in 1973-1989 (3.9 events) and 1990-2008 (4.6 events). Stochastic simulations indicate decadal shifts with near normal levels in 1880-1895 (3.4 events), low activity in 1896 1917 (2.6 events) and a return to near normal levels during 1918-1947 (3.3 events). The results also point out to significant decadal changes in probabilities of very active years (5 or more MJO events): 0.214 (1880-1895), 0.076 (1896-1917), 0.197 (1918-1947) and 0.193 (1948-1972). After a change in behavior in the 1970s, this probability has increased to 0.329 (1973-1989) and 0.510 (1990-2008). The observational and stochastic simulations presented here call attention to the need to further understand the variability of the MJO on a wide range of time scales.

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.

On the cutting stock problem under stochastic demand

This paper addresses the one-dimensional cutting stock problem when demand is a random variable. The problem is formulated as a two-stage stochastic nonlinear program with recourse. The first stage decision variables are the number of objects to be cut according to a cutting pattern. The second stage decision variables are the number of holding or backordering items due to the decisions made in the first stage. The problem`s objective is to minimize the total expected cost incurred in both stages, due to waste and holding or backordering penalties. A Simplex-based method with column generation is proposed for solving a linear relaxation of the resulting optimization problem. The proposed method is evaluated by using two well-known measures of uncertainty effects in stochastic programming: the value of stochastic solution-VSS-and the expected value of perfect information-EVPI. The optimal two-stage solution is shown to be more effective than the alternative wait-and-see and expected value approaches, even under small variations in the parameters of the problem.

A new scale-invariant ratio and finite-size scaling for the stochastic susceptible-infected-recovered model

The critical behavior of the stochastic susceptible-infected-recovered model on a square lattice is obtained by numerical simulations and finite-size scaling. The order parameter as well as the distribution in the number of recovered individuals is determined as a function of the infection rate for several values of the system size. The analysis around criticality is obtained by exploring the close relationship between the present model and standard percolation theory. The quantity UP, equal to the ratio U between the second moment and the squared first moment of the size distribution multiplied by the order parameter P, is shown to have, for a square system, a universal value 1.0167(1) that is the same for site and bond percolation, confirming further that the SIR model is also in the percolation class.

Stochastic lattice gas model describing the dynamics of the SIRS epidemic process

We study a stochastic process describing the onset of spreading dynamics of an epidemic in a population composed of individuals of three classes: susceptible (S), infected (I), and recovered (R). The stochastic process is defined by local rules and involves the following cyclic process: S -> I -> R -> S (SIRS). The open process S -> I -> R (SIR) is studied as a particular case of the SIRS process. The epidemic process is analyzed at different levels of description: by a stochastic lattice gas model and by a birth and death process. By means of Monte Carlo simulations and dynamical mean-field approximations we show that the SIRS stochastic lattice gas model exhibit a line of critical points separating the two phases: an absorbing phase where the lattice is completely full of S individuals and an active phase where S, I and R individuals coexist, which may or may not present population cycles. The critical line, that corresponds to the onset of epidemic spreading, is shown to belong in the directed percolation universality class. By considering the birth and death process we analyze the role of noise in stabilizing the oscillations. (C) 2009 Elsevier B.V. All rights reserved.

CRITICAL BEHAVIOR AND THRESHOLD OF COEXISTENCE OF A PREDATOR-PREY STOCHASTIC MODEL IN A 2D LATTICE

We investigate the critical behavior of a stochastic lattice model describing a predator-prey system. By means of Monte Carlo procedure we simulate the model defined on a regular square lattice and determine the threshold of species coexistence, that is, the critical phase boundaries related to the transition between an active state, where both species coexist and an absorbing state where one of the species is extinct. A finite size scaling analysis is employed to determine the order parameter, order parameter fluctuations, correlation length and the critical exponents. Our numerical results for the critical exponents agree with those of the directed percolation universality class. We also check the validity of the hyperscaling relation and present the data collapse curves.

Glassy states in the stochastic Potts model

We have studied by numerical simulations the relaxation of the stochastic seven-state Potts model after a quench from a high temperature down to a temperature below the first-order transition. For quench temperatures just below the transition temperature the phase ordering occurs by simple coarsening under the action of surface tension. For sufficient low temperatures however the straightening of the interface between domains drives the system toward a metastable disordered state, identified as a glassy state. Escaping from this state occurs, if the quench temperature is nonzero, by a thermal activated dynamics that eventually drives the system toward the equilibrium state. (C) 2009 Elsevier B.V. All rights reserved.

The stochastic nature of predator-prey cycles

We study by numerical simulations the time correlation function of a stochastic lattice model describing the dynamics of coexistence of two interacting biological species that present time cycles in the number of species individuals. Its asymptotic behavior is shown to decrease in time as a sinusoidal exponential function from which we extract the dominant eigenvalue of the evolution operator related to the stochastic dynamics showing that it is complex with the imaginary part being the frequency of the population cycles. The transition from the oscillatory to the nonoscillatory behavior occurs when the asymptotic behavior of the time correlation function becomes a pure exponential, that is, when the real part of the complex eigenvalue equals a real eigenvalue. We also show that the amplitude of the undamped oscillations increases with the square root of the area of the habitat as ordinary random fluctuations. (C) 2009 Elsevier B.V. All rights reserved.