Mathematical modeling and simulation of cryogenic tunnel freezers

Shaikh, Nazrul I.; Prabhu, Vittaldas V.

doi:10.1016/j.jfoodeng.2006.04.065

Cited by 19 publications

(11 citation statements)

References 14 publications

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“…The inverse model can be derived from Eqs. (2) and (3) as presented in (Stephanopoulos, 1983;Shaikh & Prabhu, 2002).…”

Section: Process Modelmentioning

confidence: 99%

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Model predictive controller for cryogenic tunnel freezers

Shaikh

Prabhu

2007

Journal of Food Engineering

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“…The inverse model can be derived from Eqs. (2) and (3) as presented in (Stephanopoulos, 1983;Shaikh & Prabhu, 2002).…”

Section: Process Modelmentioning

confidence: 99%

“…Here R 1 , R 2 , s 1 , and s 2 are system constants (see Shaikh & Prabhu, 2002). We use the feedback to ensure that the deviation between h 2 and H i is minimized by updating h 1 as follows:…”

Section: Feedback Algorithmmentioning

confidence: 99%

Model predictive controller for cryogenic tunnel freezers

Shaikh

Prabhu

2007

Journal of Food Engineering

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“…Se propone un controlador PID (Proporcional + Integral + Derivativo) para la velocidad de giro del rodillo de la banda transportadora del alimento y un controlador fuzzy del tipo Takagi-Sugeno que fija el valor de consigna del controlador PI (Proporcional + Integral) usado para regular la temperatura en el túnel de congelamiento. Se recurrió a un proceso de identificación para desarrollar los modelos matemáticos necesarios, logrando, de esta manera, superar las dificultades que en este sentido ofrece la dinámica no lineal del congelamiento criogénico causado por el cambio de fase y la dinámica térmica entre los productos congelados y el túnel [10].…”

Section: Introductionunclassified

Diseño de una estrategia de control difuso aplicada al proceso de ultracongelación de alimentos

García

Torres

Pinto

et al. 2017

Ingeniare. Rev. chil. ing.

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RESUMENEl control de la temperatura de los alimentos mediante la utilización de un equipo de congelación criogénico se torna complicado cuando se emplean técnicas de control clásico tipo PID (Proporcional + Integral + Derivativo), debido al fuerte acoplamiento entre las variables y las no linealidades propias del sistema. Actualmente, en la mayoría de las plantas procesadoras de alimentos que utilizan túneles de congelación criogénico, el control es llevado a cabo por medio del ajuste manual de los valores de consigna o setpoint de los lazos de control de velocidad y temperatura del túnel de congelación, lo que trae como consecuencia desviaciones en la salida del proceso, derivadas principalmente de la diferencia de criterios existentes entre los operadores y de la velocidad de respuesta de estos últimos ante variaciones en las condiciones del proceso. En este trabajo se tratan separadamente los lazos de control de velocidad y temperatura, se reconfiguran y entonan los lazos existentes, para luego desarrollar un controlador difuso tipo Takagi-Sugeno que permite ajustar el valor de consigna de la temperatura del túnel de congelación en función al producto y las condiciones de entrada del alimento al proceso. El comportamiento del sistema se comprueba mediante la simulación del mismo, verificándose que se mantiene la temperatura del producto en -18 ºC, pese a que fue sometido a cambios en la masa de producto a enfriar (de 200 kg a 220 kg) y en el flujo másico del producto (de 650 kg/h a 700 kg/h).Palabras clave: Congelación de alimentos, controlador PID, identificación de sistemas, control difuso, controlador Takagi-Sugeno. ABSTRACT

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“…Another solution is based on liquid nitrogen evaporation systems, in which the food is frozen by a mixture of air and nitrogen. The compressed liquid nitrogen is injected through nozzles in batch or tunnel freezers (Awonorin, 1997;Shaikh and Prabhu, 2007;Gazda, 2013) where it rapidly evaporates at ambient pressure, absorbing a large amount of heat from the food. These systems are operated with an open cycle as the refrigerant cannot be recovered at the end of the freezing process (Foster et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Reversed Brayton cycle for food freezing at very low temperatures: Energy performance and optimisation

Biglia

Comba

Fabrizio

et al. 2017

International Journal of Refrigeration

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Freezing is a valuable method to increase food shelf life and to ensure high quality standards during longterm storage. Additional benefits to frozen food quality can be achieved by freezing at very low temperatures (« -50 °C): small ice crystals formation during fast freezing reduces food cell wall rupture, preventing water and texture loss during thawing. This paper presents the design of an innovative food freezing system operating at very low temperatures, based on a modified reversed Brayton cycle (rB cycle). The plant is composed of two interconnected subsystems: a primary thermodynamic closed loop, operated by an rB cycle, and a secondary airflow loop which is devoted to food freezing by batch process. Relevant features of the designed rB cycle rely on the adopted environmentally safe working fluid, the optimised thermodynamics working conditions and the innovative cycle layout. A modelling framework for the system was developed to identify and design efficient operative settings for the plant components (turbo-machineries, heat exchangers, etc.) and to assess, via sensitivity analysis, the influence of the main design parameters on the global energy performance. The proposed system configuration, designed to maximise the Coefficient of Performance (CoP) value of the plant, was determined by means of nonlinear multivariable optimisation. In addition, the energy performance of the system can be increased by recovering waste heat available from the rB cycle.

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Mathematical modeling and simulation of cryogenic tunnel freezers

Cited by 19 publications

References 14 publications

Model predictive controller for cryogenic tunnel freezers

Model predictive controller for cryogenic tunnel freezers

Diseño de una estrategia de control difuso aplicada al proceso de ultracongelación de alimentos

Reversed Brayton cycle for food freezing at very low temperatures: Energy performance and optimisation

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