Browsing by Author "Pérez Correa, José Ricardo"

Now showing 1 - 5 of 5
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    Dynamic modelling and thermal control of an integrated membrane distillation/heat pump process for hypersaline brines treatment
    (2025) Valenzuela Álvarez, Benjamín Enrique; Pérez Correa, José Ricardo; Díaz Quezada, Simón Diego; Pontificia Universidad Católica de Chile. Escuela de Ingeniería
    Control over membrane distillation-crystallization (MDCr) systems has gained considerable interest due to the benefits this technology offers in terms of water recovery and the concentration of hypersaline brines. This work presents the dynamic modeling and thermal control of a membrane distillation system integrated with a heat pump for energy recovery, designed for the treatment of hypersaline briners. The proposed fist-principles model, developed in MATLAB/Simulink represents an early-stage digital twin of a pilot-scale membrane distillation plant, incorporating mass and heat transfer phenomena across the membrane module and associated equipment. This system is currently under construction at the Advanced Mining Technology Center (AMTC), supporting the model’s relevance to real-world implementation and design workflows. Two control strategies were assessed to regulate the membrane and permeate temperatures: (i) a PID controller tuned using classical methods (Ziegler–Nichols and IMC-PI), and (ii) a Reinforcement Learning (RL) -based controller using a Deep Deterministic Policy Gradient (DDPG) agent. Both strategies were tested under realistic disturbances and structural variations in the membrane module to evaluate their robustness and adaptability. The PID control strategy resulted in energy savings of up to 45%,without significant losses in water recovery. The RL agent, trained for approximately two hours, achieved acceptable control performance, though it was outperformed by the PID strategy under the conditions tested. Results showed that the PID method outperformed the implemented RL agent by 88%. The results indicate that the PID control strategy outperformed in its ability to regulate the temperature of both tanks, while the RL controller showed potential to be used in this context. However, its performance was limited by the available computational. esources during training. This study contributes to advancing the technological maturity of membrane distillation systems by demonstrating model-based control design workflows aimed at improving scalability and energy efficiency.
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    Estabilización proteica de vinos blancos mediante adsorción con óxido de circonio soportado en alúmina porosa
    (2025) Silva Barbieri, Daniela Carolina; Pérez Correa, José Ricardo; Escalona Burgos, Néstor; Pontificia Universidad Católica de Chile. Escuela de Ingeniería
    La presencia de turbidez en las botellas de vino blanco es un defecto relevante para los consumidores, aun cuando no afecta su calidad. La turbidez en vinos es causada principalmente por proteínas inestables relacionadas con la patogénesis de la uva, que permanecen estables durante el proceso de vinificación, pero que pueden precipitar debido a cambios bruscos de temperatura después del embotellado. Existen métodos para reducir las proteínas en el vino, pero se sigue investigando la manera más adecuada de eliminarlas selectivamente. Tradicionalmente, se utiliza bentonita, pero este proceso es lento, genera pérdidas de vino y residuos perjudiciales para el medio ambiente. Además, es intensivo en mano de obra, difícil de automatizar, costoso y afecta negativamente el color y aroma del vino, ya que no es específico para las proteínas inestables. Por ello, se necesitan procedimientos alternativos que mejoren el proceso convencional en varios aspectos. El óxido de circonio (ZrO2) elimina eficazmente las proteínas sin afectar las características del vino. Sin embargo, la producción de materiales de ZrO2 rentables con capacidades eficientes de eliminación de proteínas representa un desafío significativo. Este proyecto investiga una manera más económica y eficaz de aprovechar el potencial del óxido de circonio mediante su impregnación en alúmina de bajo costo y gran superficie activa. El adsorbente óptimo logró una notable reducción en la turbidez, disminuyendo el ΔNTU de 42 a 18, junto con una significativa reducción del 44 % en el contenido total de proteínas, y una reducción de proteínas en el rango de peso molecular de 10 a 70 kDa. Este resultado se atribuye a la modificación de las propiedades texturales de ZrO2/Al2O3, caracterizadas por la reducción de sitios ácidos, el aumento de los diámetros de poro de 4,81 a 7,74 nm y la aparición de cúmulos de circonia en la superficie del soporte poroso.
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    Evaluación por simulación de estrategias de control automático para fermentadores industriales de cerveza
    (Institute of Electrical and Electronics Engineers Inc., 2024) Márquez Giordani, Cristóbal Alberto; Saa Higuera, Pedro; Pérez Correa, José Ricardo
    The operation and control of beer fermentation at an industrial scale (> 3000 hL) pose significant challenges due to the dynamic nature of the process and the large reactor volumes involved. Effective control of fermentation temperature, a critical parameter, is hindered by the lack of advanced control models that consider volume heterogeneity. To address this, we implemented a compartmentalized phenomenological model to simulate the fermentation process, focusing on temperature control in the reactor. The model was utilized to compare two control strategies: a conventional Proportional-Integral-Derivative (PID) control system and a Model Predictive Control (MPC) framework, both designed to track a reference temperature profile. Simulation results highlight significant temperature variations across reactor compartments, necessitating the adoption of spatially aware control strategies. The MPC-based control system demonstrated superior performance compared to the PID approach, offering more precise tracking of the temperature reference in all compartments. These findings underscore the potential of MPC for optimizing temperature control in large-scale fermentation processes. Future work will focus on the industrial validation of the model and the control strategies for implementation in operational settings.
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    Intelligent control applications on a binary distillation column
    (IEEE, 2016) Diaz Quezada, Simon Diego; Pérez Correa, José Ricardo; Cipriano, Aldo; Fernández-Fernández, Mario Alberto
    Distillation is fundamental in Chemical Engineering. It is a highly complex and no-linear process. Therefore, developing intelligent control systems for distillation columns is challenging. These control techniques are based on previous knowledge and intuitive rules. In this work, several intelligent control strategies, such as Expert, Fuzzy (Mamdani and Sugeno) and Neural-Network Control are applied to control a simulated distillation column, and their performance compared with a traditional PI controller. The controlled variable was the distillate molar fraction and the manipulated variable was the reflux ratio. All control strategies were tested in two scenarios: i) set-point changes, and ii) disturbance and setpoint changes. The best control strategy was the Neural-Network, using a NARMA-L2 controller. This control has a good disturbance rejection and a fast set-point tracking with a smooth control action.