DSpace Angular :: Browsing by Author "Perez Correa, JR"

Browsing by Author "Perez Correa, JR"

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Air-pollution modelling in an urban area: Correlating turbulent diffusion coefficients by means of an artificial neural network approach
(PERGAMON-ELSEVIER SCIENCE LTD, 2006) Perez Roa, R; Castro, J; Jorquera, H; Perez Correa, JR; Vesovic, V
The vertical pollutant dispersion is quite sensitive to the eddy diffusivity, K-V. Therefore, good estimations of K-V are essential for improving the predictive performance of Eulerian dispersion models; especially in urban areas where literature based K-V correlations are not always accurate. Here, we present a methodology to obtain a more accurate, but site-specific, Kv correlation. It is based on using artificial neural networks (ANN) to find the best Kv function for a particular urban area by minimizing, in a least-squares sense, the difference between ambient measurements of carbon monoxide and dispersion simulations of this tracer species. The resulting ANN-K-V correlation is a function of three parameters namely, the stability parameter (z/L), the height within the mixing layer (z/h), and the scaled height (zf(C)/u(*))-hence the Monin-Obukhov (L), mixing (h) and Ekman (u(*)/f(C)) lengths are used to predict Kv across the atmospheric boundary layer.
Control strategies for intermittently mixed, forcefully aerated solid-state fermentation bioreactors based on the analysis of a distributed parameter model
(PERGAMON-ELSEVIER SCIENCE LTD, 2004) von Meien, OF; Luz, LFL; Mitchell, DA; Perez Correa, JR; Agosin, E; Fernandez Fernandez, M; Arcas, JA
This paper tests different control strategies based on classic proportional integral derivative (PID) and advanced dynamic matrix control (DMC) algorithms for an intermittently stirred, forcefully aerated solid-state fermentation bioreactor. The study was done using a distributed parameter model to reproduce the main operating features of this type of bioreactor. There is predicted to be a remarkable improvement in the bioreactor productivity when control strategies are implemented. For this type of bioreactor, the temperature and water content of the substrate bed can be controlled by saturating the air at the air inlet but manipulating its temperature, coupled with a strategy of water replenishment when the water content of the bed falls below a threshold. Dynamic matrix control is superior to PID control; however, a specific convolution matrix for different stages of the fermentation is necessary due to the changing behavior of the system. This work shows the benefit of mathematical modeling, since the many different operating conditions investigated via simulations would not have been economically feasible to undertake experimentally with a large-scale bioreactor. The results obtained provide an excellent starting point for such large-scale experimental work. (C) 2004 Elsevier Ltd. All rights reserved.
Data reconciliation and parameter estimation in flux-balance analysis
(JOHN WILEY & SONS INC, 2003) Raghunathan, AU; Perez Correa, JR; Biegler, LT
Flux balance analysis (FBA) has been shown to be a very effective tool to interpret and predict the metabolism of various microorganisms when the set of available measurements is not sufficient to determine the fluxes within the cell. In this methodology, an underdetermined stoichiometric model is solved using a linear programming (LP) approach. The predictions of FBA models can be improved if noisy measurements are checked for consistency, and these in turn are used to estimate model parameters. In this work, a formal methodology for data reconciliation and parameter estimation with underdetermined stoichiometric models is developed and assessed. The procedure is formulated as a nonlinear optimization problem, where the LP is transformed into a set of nonlinear constraints. However, some of these constraints violate standard regularity conditions, making the direct numerical solution very difficult. Hence, a barrier formulation is used to represent these constraints, and an iterative procedure is defined that allows solving the problem to the desired degree of convergence. This methodology is assessed using a stoichiometric yeast model. The procedure is used for data reconciliation where more reliable estimations of noisy measurements are computed. On the other hand, assuming unknown biomass composition, the procedure is applied for simultaneous data reconciliation and biomass composition estimation. In both cases it is verified that the minimum number of measurements required to get unbiased and reliable estimations is reduced if the LP approach is included as additional constraints in the optimization. (C) 2003 Wiley Periodicals, Inc.
Dynamic simulation and control of direct rotary dryers
(ELSEVIER SCI LTD, 1998) Perez Correa, JR; Cubillos, F; Zavala, E; Shene, C; Alvarez, PI
Adaptive and conventional control of a direct rotary dryer has been assessed through simulations. A dynamic model of the process was developed specifically for this purpose. The model is based on mass and energy balances and includes a drying kinetic derived from mass transfer principles. In the modelling process, ten discrete perfectly mixed elements were considered for the dryer with each containing four differential equations. A well tuned discrete PID and an adaptive algorithm were used to control the outlet solid humidity Bath controllers can regulate the controlled variable for different disturbances, although the adaptive controller is more effective. (C) 1998 Elsevier Science Ltd. All rights reserved.
Energy and water balances using kinetic modeling in a pilot-scale SSF bioreactor
(ELSEVIER SCI LTD, 2004) Lekanda, JS; Perez Correa, JR
Direct monitoring of bed conditions in large scale solid-state fermentation (SSF) bioreactors is difficult due to lack of reliable and affordable instrumentation. Although, relevant variables such as average bed temperature and water content can be inferred from energy and water balances, these estimations are prone to significant error since the process is complex and measured variables are extremely noisy. Hence, to obtain better estimation of bed conditions, simple and robust models, and effective noise suppression methods should be developed. A kinetic model was applied to obtain noise free CO2 production rate (CPR) values, which in turn was used in water and energy balances. The evolution of other relevant variables including total and active biomass, O-2 consumption rate, secondary metabolite production and dry mass degradation were also calculated. The proposed model was calibrated with data obtained in an agitated aseptic SSF pilot-scale bioreactor of 200 kg, growing Gibberella fujikuroi on wheat bran and starch. The calibration was achieved by means of a non-linear optimization routine. With this model better average bed temperature estimates, compared with a model that uses noisy (CPR) measurements, were attained. Hence, the proposed model can be used on-line to estimate more reliable average bed conditions and to develop model based control strategies. In addition, a predictive model for bioreactor design can be derived from the proposed model, after good outlet gas temperature estimation has been achieved. (C) 2003 Elsevier Ltd. All rights reserved.
Modeling of yeast metabolism and process dynamics in batch fermentation
(JOHN WILEY & SONS INC, 2003) Sainz, J; Pizarro, F; Perez Correa, JR; Agosin, E
Much is known about yeast metabolism and the kinetics of industrial batch fermentation processes. In this study, however, we provide the first tool to evaluate the dynamic interaction that exists between them. A stoichiometric model, using wine fermentation as a case study, was constructed to simulate batch cultures of Saccharomyces cerevisiae. Five differential equations describe the evolution of the main metabolites and biomass in the fermentation tank, while a set of underdetermined linear algebraic equations models the pseudo-steady-state microbial metabolism. Specific links between process variables and the reaction rates of metabolic pathways represent microorganism adaptation to environmental changes in the culture. Adaptation requirements to changes in the environment, optimal growth, and homeostasis were set as the physiological objectives. A linear programming routine was used to define optimal metabolic mass flux distribution at each instant throughout the process. The kinetics of the process arise from the dynamic interaction between the environment and metabolic flux distribution. The model assessed the effect of nitrogen starvation and ethanol toxicity in wine fermentation and it was able to simulate fermentation profiles qualitatively, while experimental fermentation yields were reproduced successfully as well. (C) 2003 Wiley Periodicals, Inc.
Monitoring large scale wine fermentations with infrared spectroscopy
(ELSEVIER, 2004) Urtubia, A; Perez Correa, JR; Meurens, M; Agosin, E
Negative effects on wine quality and productivity caused by stuck and sluggish fermentations can be reduced significantly, if such problems are detected early through periodic chemical analysis. Infrared spectroscopy (IR) has been used successfully for monitoring fermentations, since many compounds can be measured quickly from a single sample without prior treatment. Nevertheless, few applications of this technology in large scale winemaking have been reported, and these do not cover the entire fermentation from must to finished wine. In this work, we developed IR calibrations for analyzing the fermenting must at any stage of fermentation. The calibration model was obtained with multivariable partial least squares and proved effective for analyzing Cabernet Sauvignon fermentations for glucose, fructose, glycerol, ethanol, and the organic acids; malic, tartaric, succinic, lactic, acetic, and citric. Upon external validation we found an average relative predictive error of 4.8%. Malic acid showed the largest relative predictive error (8.7%). In addition, external validation found that insufficient data for these calibrations made the analysis of fermenting musts using other grape varieties less reliable. (C) 2004 Elsevier B.V. All rights reserved.
Wine distillates: Practical operating recipe formulation for stills
(AMER CHEMICAL SOC, 2005) Osorio, D; Perez Correa, JR; Biegler, LT; Agosin, E
Consumer perceptions of flavors are associated with the chemical composition of foods. However, consumer preferences change; therefore, it is necessary for food manufacturers to be able to adapt their products. Unlike in aged spirits, the chemical composition of young spirits is determined during distillation; therefore, this is where distillers must tailor their operating recipes to the new trends. Even for an experienced distiller, the complexity of the process makes adapting the operating recipe far from straightforward. In this study, we developed a methodology for generating practical recipes that makes use of computer simulations and optimization techniques. We used Pisco Brandy, a young Muscat wine distillate from Chile and Peru as our case study. Even so, because our methodology is independent of the chemical composition of the broth, it can be applied throughout the industry. Drawing on the experience and preferences of industry enologists, we designed a preferred distillate and used our methodology to obtain the appropriate recipe, This recipe was validated in lab scale experiments, and we obtained a much closer distillate to the desired prescription than commercial products.

Browsing by Author "Perez Correa, JR"

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