Dynamic study of the evaporation stage of an integrated first and second generation ethanol sugarcane biorefinery using EMSO software

Journal Pre-proof Dynamic study of the evaporation stage of an integrated first and second generation ethanol sugarcane biorefinery using EMSO software Erick Y. Emori Jimena Ferreira Argimiro R. Secchi Mauro A.S.S. Ravagnani Caliane B.B. Costa

PII:

S0263-8762(19)30520-9

DOI:

https://doi.org/doi:10.1016/j.cherd.2019.11.002

Reference:

CHERD 3885

To appear in:

Chemical Engineering Research and Design

Received Date:

16 April 2019

Revised Date:

30 October 2019

Accepted Date:

4 November 2019

Please cite this article as: Emori, E.Y., Ferreira, J., Secchi, A.R., Ravagnani, M.A.S.S., Costa, C.B.B.,Dynamic study of the evaporation stage of an integrated first and second generation ethanol sugarcane biorefinery using EMSO software, Chemical Engineering Research and Design (2019), doi: https://doi.org/10.1016/j.cherd.2019.11.002

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.

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The coupling of the first and second generation ethanol process is attractive Multi-effect evaporators dynamics in integrated process is analyzed in EMSO Disturbance in general lead to a loss in sugar concentration Last effects dynamics is far from linear and classical control is not suitable EMSO presents advantages when compared to other commercial simulators

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Dynamic study of the evaporation stage of an integrated first and second generation ethanol sugarcane biorefinery using EMSO software Erick Y. Emori1, Jimena Ferreira2, Argimiro R. Secchi3, Mauro A. S. S. Ravagnani1, Caliane B. B. Costa1*

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1 - Universidade Estadual de Maringá - UEM – Maringá, PR - [email protected] 2 - Facultad de Ingeniería- Universidad de la Republica, Montevideo - Uruguay 3 - Programa de Engenharia Química – COPPE - Universidade Federal do Rio de Janeiro UFRJ, Rio de Janeiro - RJ

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Abstract Brazil is the largest producer of sugarcane ethanol in the world. Among the technologies that aim to improve the process, second-generation ethanol is one of the most promising. Although still in development, it is a consensus that this process must be integrated into the production of first generation ethanol. Most of the work on this subject is involved in evaluating the steady-state process. However, the knowledge of the process dynamics plays an important role on the operational efficiency and control. In this work multiple effect evaporation is addressed. A dynamic phenomenological model of this step was developed in EMSO process simulator. A stream of glucose syrup is mixed with sugarcane juice stream at the entrance of the system and simulations were performed to analyze the integrated system dynamics. Step disturbances were applied in the sugar concentration, volumetric flow rate and temperature of the juice individually and simultaneously. Glucose syrup concentration and flow rate was also disturbed. PI/PID controllers were tested in order to control the system and the model consistency was verified in Aspen Dynamics. The analysis suggests that an adequate control system at the liquid and vapor output of each vessel cannot be achieved using only classical controllers.

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Keywords: Dynamic analysis, Sugarcane biorefinery, Multiple-effect evaporation, EMSO, Second generation ethanol.

1. Introduction

Multi-effect evaporation plays a significant role in a number of very important bulk chemical industries. It is one of the major energy consumers in pulp, food and sugar manufacturing, in desalinization plants and in biorefineries for concentrating fermentation broth (Luyben, 2018). Sugarcane processing is one of the main industries in Brazil, mainly due to its efficiency, development and influence on the economy. Sugarcane can be processed into sugar in sugar mill plants, into ethanol in autonomous ethanol distilleries and into both products in integrated sugar and ethanol plants. Ethanol production is complex and involves mainly the operations of

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evaporation, fermentation and distillation, in this order. Evaporation is used to properly concentrate sugarcane juice for the subsequent fermentation process. Its operation is of fundamental importance, as it is the first step of the production chain (after juice treatment) and it consumes great amounts of energy. The production capacity of this fuel can increase considerably by using sugarcane bagasse, a lignocellulosic material, as feedstock for second generation ethanol. As consequence, it may increase the ratio biofuel/land area, thus indirectly reducing the land demand for crop fuels (Furlan et al., 2012)

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The production of both first and second generation ethanol in an integrated process is

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interesting since the bagasse is readily available in the first generation plants. Also, both technologies are able to share process facilities and equipment. In general, the second generation process consists of biomass pre-treatment, cellulose hydrolysis, fermentation and distillation

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(Andrade et al., 2017). Since Saccharomyces cerevisae is used in fermentation of both sugarcane

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juice and glucose syrup, it is intuitive that hydrolysis product (glucose syrup) should be mixed with treated sugarcane juice stream to feed the evaporation process of autonomous distilleries.

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The concentrated mixture is then introduced into the fermentation process using the same yeast for the conversion of both sucrose and glucose into ethanol. Control of the evaporation system is an important feature in the sugarcane industry

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economy. This operation has a high influence on the regularity of sugar and ethanol quality. Also, a lot of energy is employed in form of steam usage. Sugarcane plants usually apply

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multiple-effect evaporators, introducing a complexity mainly due to their serial arrangement and the environmental factors that can affect its dynamic behavior. Also, there is an abundance of

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disturbances that have an influence on the operating conditions. These factors require a great amount of understanding of the process phenomenology in order to achieve a reliable control system (Cadet et al., 2000). Therefore, mathematical modeling and process dynamic simulation and analysis are essential for the design of an efficient control system. For this purpose, process simulators are an invaluable tool. Dynamic modeling and control of multi-effect evaporation process is subject of many papers. Miranda and Simpson (2005) developed a model and performed dynamic simulations of a five-effect evaporator for tomato juice concentration. Kumar et al. (2013) modeled and simulated in MATLAB a six-effect evaporation system used in the pulp and paper industry. Mazini et al. (2014) also used MATLAB to develop a dynamic model of a six-effect

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desalinization evaporator. Bojnourd et al. (2015) developed a dynamic model of a quadruple effect system for the production of milk powder. Díaz-Ovalle et al. (2017) modeled the dynamic behavior of liquids at the outer walls of the tubes of a multiple effect evaporator. Luyben (2018) used Aspen Plus and Aspen Dynamics process simulators to simulate and analyze the dynamic behavior of a quadruple effect evaporator for control and design purposes. As demonstrated, there is in the literature plenty research on the dynamics of evaporation process. However, none of the previous studies is dedicated to integrated first and second generation ethanol production

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context. Previous studies on this subject were concerned with steady state operation. Therefore,

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there is a need of studies on the dynamics of the multi-effect evaporation in the integrated first and second generation ethanol production process.

Most used simulators in academic research are commercial. In this context, EMSO

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(Environment for Modeling, Simulation and Optimization) was developed with the proposal of

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being an equation-oriented process simulator valuable and available free of charge (for academic purposes). It has an object-oriented modeling language following basic structures and syntax

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rules and, differently from MATLAB and SCILAB, EMSO is a process simulator provided with libraries of equipment models and thermodynamic and fluid properties packages. Powerful algebraic and differential equation solvers are available and users can build their own models or

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change model libraries efficiently, as well as estimate their parameters, perform sensitivity analysis and optimization studies (Ospino et al., 2017).

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The understanding of the integrated process transient behavior is essential to its control system design. However, there is a gap in the literature on this subject. This paper has the

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purpose of analyzing the dynamic behavior of a four-effect evaporator used in a sugarcane biorefinery integrating first and second generation ethanol production. EMSO coupled with the thermodynamic plugin VRTherm is used as the process simulator. Disturbances are applied on sugarcane juice temperature, volumetric flow rate and sugar concentration, individually and simultaneously. Glucose syrup concentration and flow rate is also disturbed. With the objective of evaluation of each evaporator effect transient response, disturbances are applied so that a better understanding of the evaporation stage dynamics in a first and second generation ethanol production process can be attained. PI controllers are used to test the control of the system. To verify the consistency of the model developed in this work, dynamic responses obtained using Aspen Dynamics, a dynamic process simulator widely recognized as reliable, are used.

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In order to clarify some terms commonly used in the sugarcane industry sector, they are here included in a short glossary. 

Bagasse: the lignocellulosic material that is left after sugarcane stalk is crushed.

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Calandria evaporator: device with vertical shell-and-tube heat transfer part (calandria), which makes use of natural convection for circulation.

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Brix degrees (or °Brix): the sugar mass concentration (percentage) in an aqueous solution.

Methodology 2.1 Mathematical model of the multiple effect evaporation system

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Vegetal steam: the steam withdrawn from the sugarcane juice.

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The schematic representation of the quadruple-effect evaporation system is shown in Fig. 1, which also brings main operating (steady-state) and design parameters. The system model,

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written in EMSO, consists of a set of four evaporators of the Robert type. The evaporation system simulated in this work makes use of the infrastructure already established for first

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generation sugarcane industry in Brazil, with the usage of co-current four-effect evaporators. For cold liquid streams, counter-current (backward-feed) multistage system is recommended (Smith, 2005). Co-current (forward-feed) multiple effect evaporators are recommended when the liquid

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stream to be concentrated is already heated up, so it is fed to the effect with the highest temperature. Co-current feeding also is advantageous because of the favorable pressure profile

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for the solution, which avoids pumping requirement to flow through the evaporator system (Chantasiriwan, 2015; Smith, 2005). Furthermore, in the sugar industry the co-current flow is

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used because it generates a low temperature in the last-effect vessel (where liquid is with the highest concentration), which minimizes color formation and sucrose degradation losses (Chantasiriwan, 2015). Each evaporator has steam and juice inlets, and liquid (concentrated juice) and steam (vegetal steam) outlets. Prior to be fed to the evaporators system, clarified juice stream is split into two parts. One of these branches is mixed with the hexose syrup generated with hydrolysis of the cellulose present in the sugarcane bagasse and is used as a feed stream to the evaporators. The remaining clarified juice is mixed with the fourth evaporator outlet liquid stream (concentrated juice) and sent to a buffer tank, which, in its turn, is responsible for providing the stream that feeds the fermentation system.

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Fig 1. Schematic representation of the evaporation system

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It is important to draw attention to the fact that the number of effects in the multi-effect system of evaporation varies in sugarcane mills in Brazil. Generally, the number of effects varies

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between three and five. Although the quantitative dynamics of such systems is different among themselves, the process dynamics remains (qualitative behavior) analogous, and, for that reason, a system with four effects is here specified. The last two stages are smaller than the first two. The

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smaller sizes can be attributed to the fact that the last two effects withdraw less steam when

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compared to the first two and, also, they are fed with lower liquid flow rates. The evaporator system is fed by a Steam stream composed of saturated steam at 389 K

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and 2.3 atm (Ferreira et al., 2014). The liquid and vapor outlets of the first evaporator (L1 and V1 in Fig. 1) are used as inlet streams of the second one, and so on. The Juice stream, based on the work of Ferreira et al. (2014) is at 373 K and 2.3 atm and represents the treated (clarified) sugarcane juice, consisting of a mixture of 15 weight % of sucrose in water, usual concentration for sucrose content in sugarcane. Its volumetric flow rate is 650 m³/h (equivalent to processing 600 t/h of sugarcane), of which 350 m³/h are bypassed (Bypass stream in Fig. 1). The remaining stream is mixed with the glucose syrup (Syrup stream in Fig. 1), forming feed stream F (with 13.3 °Brix at nominal condition), which is concentrated up to about 50 °Brix. The concentrated juice (L4) is then mixed with the bypassed juice to reach about 20 °Brix, ideal concentration for the fermentative process.

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Syrup stream is considered a mixture of water and glucose (10 weight %) at 373 K and 2.3 atm, based on one of the scenarios of the work of Furlan et al. (2012). Those authors presented a simulation of a pre-treatment process using the organosolv method, where cellulose is separated from lignin in solid form and diluted in a ratio of 1:10, then hydrolyzed by enzymes with 80% conversion to glucose. The syrup stream flow rate (145 m³/h) is calculated from the amount of cellulose present in sugarcane, whose mass composition adopted by the authors was 0.62 % glucose, 4.77 % cellulose, 13.30 % sucrose, 71.57 % water, 2.62 % lignin, 4.53 %

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hemicellulose and 2.59 % of other substances. In the scenario on which Syrup stream is based

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on, all bagasse surplus is pretreated, its cellulose is hydrolyzed while lignin is burned in the boilers and the hemicellulose portion is not used for the second generation ethanol production.

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The model of each evaporator is based on the work of Ferreira et al. (2014) and consists of a set of algebraic-differential phenomenological equations, consisting of mass and energy

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balances, heat transfer equations, phase equilibrium equations and equations describing the thermodynamic and physical parameters of the system components. The following hypotheses

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were made in the development of the model:

• The liquid stream is represented by a mixture of water, sucrose and glucose.

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• The phases are completely mixed.

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• There is no energy loss through the evaporator walls.

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• The solution is ideal.

• The liquid and gaseous streams are represented by ideal liquid and ideal gas models, respectively.

The material balance (Equation (1)) is applied to each component k of the system. Since it is a dynamic system, the equations are represented by differential equations composed by the accumulation, input, and output of matter in each evaporator i.

(1) The material holdup of component k in each evaporator i is represented by Equation (2).

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(2) in which Li-1 is the molar flow rate of the feed stream (for the first evaporator, L0 corresponds to F stream), Li and Vi are the molar flow rates of the liquid outlet and vegetal steam streams respectively,

and

are the quantities of matter in the liquid and vapor phases within each

evaporator i, respectively. output stream (

and

stand for the molar fraction of component k in each

for the liquid phase and

for the vapor one) and nk,i is the quantity of

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matter of component k in evaporator i. The control volume of the material balance is represented

juice in each evaporator does not appear in the balance. and

represent the molar fraction of each component in the liquid and

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Since

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by the inner shell of the evaporator and its tubes. Thus, the steam inlet that transfers heat to the

vapor phase, respectively, their sums in k must be unitary in each stream, as described in

(3)

(4)

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Equations (3)-(4), where NComp is the number of components.

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Equation (5) represents energy balance for each evaporator i, taking into account heat exchange between the juice inside the evaporator and the steam in the external walls of its tubes

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and the energy input and output by means of material streams i.

in which

,

i

and

(5) are the molar enthalpy of the feed, the liquid output and the

vegetal steam streams, respectively.

is the heat exchange rate between the juice and the steam

fed to the evaporator. Energy represents the internal energy of the control volume and is calculated with Equation (6), (6)

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in which Pi and Voli are the internal pressure and volume of evaporator i, respectively. In each evaporator i, the thermal, mechanical and chemical equilibrium between the liquid outlet and the vegetal steam streams are imposed by Equations (7)-(9). are liquid and vegetal steam temperatures, respectively, and

and

and

its pressures and

its fugacity.

(8) (9)

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(7)

Physical-chemical properties of components are obtained from EMSO library of

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properties and VRTherm thermodynamic database, which is a piece of software for thermodynamic and physical property prediction of mixtures, develop by VRTech Tecnologias

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Industriais Ltda., a Brazilian company. It uses state variables to perform the calculations on empirical correlations and state equations for determining properties of pure compounds and complex mixtures. From the individual properties, the molar fraction of each component in the

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mixture, the state variables, and the considered ideal liquid and ideal gas models, the database calculates the physicochemical properties of the mixture. In the case of the vapor phase, pure

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water was considered. In this context, the juice vapor pressure, as a function of the juice composition (sugar content) and temperature, is used as a mean to calculate its boiling

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temperature, being the temperature in which the vapor pressure equals to the evaporator internal pressure.

The heat transfer rate between steam and the liquid phase in each evaporator i is calculated by Equation (10), (10) where Ui is the global heat transfer coefficient, Ai is the thermal exchange area, temperature of the evaporator content and

is the

is the temperature of the saturated steam in

the outer wall of evaporator tubes, which is the outlet steam of the previous evaporator, being

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the temperature of the first effect feed steam. The heat transfer rate is also related to the amount of steam withdrawn from the juice, as established in Equation (11): (11) The internal volume of each evaporator is calculated with Equation (12), which uses the dimensions of the calandria and the tubes (detailed in Table 1).

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(12)

Dci is the diameter of the calandria, Hei is the evaporator height, Hti is the tubes height, Dti is their diameter, while Nti stands for the number of tubes. Internal volume is also related to the

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algebraic restriction of space, since the juice and vegetal steam occupy the entire internal volume of the calandria, considering that the tubes are completely filled with the liquid. This relationship and

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liquid, respectively.

are the molar volumes of the steam and the

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is presented in Equation (13), where

(13)

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The thermal exchange area of each effect is also calculated from the geometric properties

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of the equipment (Equation (14)):

(14)

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The concentration (Brix degrees) calculation of the juice content in each evaporator is performed from the mass (M) of each component in the liquid outlet, as demonstrated in Equation (15).

(15)

The flow rate of each effect outlet liquid stream is calculated with a simplified valve model flow, according to Equation (16).

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(16)

In this equation,

is the valve opening fraction,

is the valve coefficient,

is the valve

pressure drop and is the stream specific gravity. Table 1. Dimensions of the evaporators

Evaporator 2 5.2

Total height (He) (m)

7.2

7.2

Number of tubes (Nt)

8178

8178

Tubes diameter (Dt) (m)

0.0328

0.0328

0.0328

0.0328

Tubes height (Ht) (m)

3.6

3.6

3.6

3.6

4 4.2

7.2

7.2

5232

5232

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2.2 Simulation and dynamic analysis

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Calandria diameter (Dc) (m)

1 5.2

The dynamic analysis was performed in EMSO process simulator with implementation of

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step disturbances in different input stream variables related to the clarified juice and glucose syrup (Juice and Syrup streams in Fig. 1, respectively). The application of the step in the

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simulation can be performed by changing, at a given time t, a variable specified by means of ifelse statements. However, this introduces a discontinuity that creates numerical instabilities that

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hinder simulation convergence in EMSO. In this way the disturbance was modeled by multiplying the disturbed variable by an equation of sigmoidal nature (Equation (17)): (17)

X represents the disturbed variable, X0 is the variable value at steady state and Pf is the fraction of variation, in relation to the steady state value, the step imposes (e.g. in a variation of 5 %, the value of Pf would be 0.05). τ0 stands for the start time of the disturbance and τ is the time within the simulation. The disturbances were applied 600 seconds after the start of the simulation separately in three variables related to clarified juice: sucrose concentration, volumetric flow rate

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and temperature. The glucose concentration of the glucose syrup was also disturbed. Step disturbances were also applied to two variables simultaneously on the clarified juice. The disturbance in the sucrose concentration consisted in raising the sucrose mass percentage of the clarified juice (Brix degree) by 2 points, increasing its concentration from 15 to 17 °Brix. The disturbance in the volumetric flow rate consisted in increasing the volumetric flow rate of the clarified juice in 5 % of its steady state value (650 m³/h) and the disturbance in temperature consisted in raising the juice temperature in 5 K. The disturbance in the glucose

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syrup concentration consisted in decreasing its sugar content to a half of its steady-state value

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(10 % concentration in mass to 5 %). The disturbance in the glucose syrup flow rate consisted in the complete suspension of its flow rate, simulating an interruption of the biomass pre-treatment

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or hydrolysis step.

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3. Results and Discussion

The dynamic behavior of the variables related to the evaporators outputs is analyzed

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through the responses presented by the outlet liquid concentration and temperature of each effect.

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3.1 Dynamic responses to increase in juice sugar mass percentage (+ 2 °Brix) and volumetric flow rate (+ 5 %) The evaporation system presented a loss in concentration when disturbed simultaneously

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on juice sugar content and volumetric flow rate. The main reason is the fact that the third effect ceased evaporation when the temperature difference between its content and the vegetal steam

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that is fed to it reached a low value. As consequence, the content from both third and fourth effects stopped being concentrated, since the steam supply to the last evaporator was interrupted. Therefore, the juice temperature, pressure and concentration of the outlet of the multiple effect evaporation system reached the same values of the liquid outlet of the second effect after reaching steady state.

Each effect showed a different dynamic response. The first and second effects showed a relatively lower variation from both individual and simultaneous disturbances in comparison with the other two effects. It can be explained firstly by the fact that in the first evaporator the disturbances are applied only in the juice feed, while in the other vessels the disturbances affect both liquid and steam inlet. Secondly, the first two evaporators have higher size and content,

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generating a buffer effect on the response. Lastly, the response variations present increments as it passes through each effect, generating higher alterations in the juice concentration and temperature. Although presenting an initial increase on the first evaporator, the juice concentration decreases as it passes through the rest of the effects. As each evaporator steady-state temperature presented higher variation than the previous one, the temperature gradient reduced. As consequence, the heat transfer rate and the outlet concentration decreased. Therefore, it is clear

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that the temperature of each vessel can affect greatly the juice concentration.

The disturbances had opposite influence on the juice concentration. In the first effect, while the Brix concentration disturbance increased the feed concentration, the volumetric flow

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rate disturbance increased the amount of liquid inside the vessel. A larger juice volume decreases the evaporator effectiveness. When both disturbances were applied simultaneously, the response

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curve was located between the responses to separate disturbances. It indicates that both effects of each individual disturbance were present simultaneously as a sum of each variation. The same

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dynamics can be seen on the second effect. However, the larger gain in temperature reduced the heat transfer rate and, therefore, the outlet concentration. The response of each effect liquid

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outlet concentration and temperature are shown in Fig. 2 for the first, second and third evaporators. The fourth effect dynamic behavior is the same of the third since its steam supply is

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interrupted. Table 2 shows the steady-state variation achieved by each response in sugar

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concentration and temperature.

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f oo pr ePr al rn Jo u Fig. 2. Response of sugar concentration (left) and temperature (right) at the outlet of the first (a and b), second (c and d) and third (e and f) evaporators for step disturbances in sugar mass percentage and volumetric flow rate of the clarified juice.

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Table 2. Steady-state variations in concentration and temperature of each effect liquid outlet for step disturbances in sugar mass concentration (+ 2 °Brix), volumetric flow rate (+ 5 %) and temperature (+ 5 K) of the clarified juice.

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Sugar mass concentration (+ 2 °Brix) and volumetric flow rate (+ 5 %) Effect Concentration (°Brix) Temperature (K) 1 0.8 0.1 2 -2.3 1.3 3 -8.0 3.0 4 -13.3 3.9 Sugar mass concentration (+ 2 °Brix) and temperature (+ 5 K) Effect Concentration (°Brix) Temperature (K) 1 -0.7 5.8 2 -8.9 9.1 3 -14.9 10.7 4 -20.0 11.4 Volumetric flow rate (+ 5 %) and temperature (+ 5 K) Effect Concentration (°Brix) Temperature (K) 1 - 2.3 + 6.3 2 - 11.6 + 10.0 3 - 17.6 + 11.7 4 - 23.1 + 12.3

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3.2 Dynamic responses to increase in juice sugar mass percentage (+ 2 °Brix) and temperature (+ 5 K)

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Analogously to the previous topic, there was a loss in the juice concentration. After both juice sugar content and temperature were disturbed, a high increase in temperature was achieved

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by all effects. However, the third evaporator presented a greater increment in comparison with the second one. As a consequence, heat transfer reduced drastically and juice stopped being concentrated in the last two effects. The outlet juice transient response was a decrease in concentration in all four effects and the temperature increase. Although the sugar mass percentage disturbance increased the juice concentration, the temperature disturbance warmed the evaporators content. As consequence, the outlet sugar concentration was reduced as less heat was transferred since the temperature gradient lowered after the disturbances. The first, second and third effects response can be seen

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in Fig. 3. Table 2 shows the steady-state variation achieved by each response in sugar concentration and temperature. The third evaporator response to the simultaneous disturbances was distinct from the individual ones, as can be seen in Fig. 3 e) and f), with an inverse response on sugar mass percentage. The increase in temperature can be explained by the change in the evaporator holdup with an increase in the amount of vegetal steam molecules, demonstrating a direct relationship between the two variables. Although both second and third evaporators presented an increase in

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temperature, the third one exhibited an increase of higher magnitude. Therefore, a higher

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temperature gradient caused a change in the ratio of liquid to vapor within the device (holdup), increasing the amount of steam molecules. Consequently, an increase in pressure and boiling

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temperature is generated. As temperature increases, the rate of heat transfer decreases, leading to a drop in sugar concentration until the effect reaches the same temperature of the vegetal steam

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of the previous evaporator.

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f oo pr ePr al rn Jo u Fig. 3. Response of sugar concentration (left) and temperature (right) at the outlet of the first (a and b), second (c and d) and third (e and f) evaporators for step disturbances in sugar mass percentage and temperature of the clarified juice.

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3.3 Dynamic responses to increase in juice volumetric flow rate (+ 5 %) and temperature (+ 5 K) In this case, both disturbances induce a reduction of the outlet juice concentration. The increase in the volumetric flow rate generates a greater amount of liquid for the equipment to concentrate, reducing its effectiveness. In addition, the inlet stream, being warmed by the temperature disturbance, generates a higher thermal load. The temperature gain accompanies the loss in concentration due to a lower amount of vegetal steam withdrawn, consequence of the

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reduction of the temperature difference between the juice and the feed steam.

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Although individually the disturbances generated relatively low variations in the juice outlet properties, when applied simultaneously the gain in volumetric flow rate and temperature

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generates an even higher decrease in the outlet concentration and temperature. The first two effects presented very similar responses, with the simultaneous curve located as it was the sum of

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both individual disturbances curves. However, the third effect presented a much higher heating. As consequence, the evaporator effectiveness decreased drastically. A lower vegetal steam outlet

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flow rate also decreases the next effect evaporative capacity as it has no energy supply to generate the ebullition.

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The first effect response can be seen in Fig. 4 a) and b). The second one presented a behavior similar to the first one. Fig. 4 c) and d) show the response of the third effect. The fourth

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effect behavior is the same of the third since its steam supply is interrupted. The steady-state

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variation achieved by each response in sugar concentration and temperature can be seen in Table

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Fig. 4. Response of sugar concentration (left) and temperature (right) at the outlet of the first (a and b), and third (c and d) evaporators for step disturbances in volumetric flow rate and temperature of the clarified juice.

3.4 Dynamic responses to a reduction in the glucose syrup glucose concentration (from 10 % to 5 % in mass) and interruption of the glucose syrup flow rate Fig. 5 (left) demonstrates that a reduction in the glucose syrup sugar content from 10 % to 5 % in mass generates a reduction on all evaporators output sugar mass concentration. All effects presented a similar dynamic behavior with a decrease of 0.7 °Brix, 1.3 °Brix, 1.5 °Brix and 1.7 °Brix on the first, second, third and fourth effects, respectively, and an overall stabilization time of 122 minutes. Since the disturbance value in the sugar content is relatively small in comparison with the total juice concentration and due to the smaller flow rate of glucose

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syrup compared to that of sugarcane juice, the effects presented responses with low transient variations. The evaporators dynamic response on the total interruption of the glucose syrup flow rate presented a response with large increase in concentration, as can be seen in Fig. 5 (right). As glucose syrup stops being fed, the flow rate of the first effect feed decreases. Consequently, the evaporators content are reduced. With the same heat transfer rate and less juice flow rate, a gain on each effect outlet concentration occurs. There is an increase of 3.3 °Brix, 12.8 °Brix, 18.4

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°Brix and 24.9 °Brix and an overall stabilization time of 114 minutes. The fourth evaporator

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presented a relatively larger increase in concentration due to the lower amount of its content.

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Fig. 5. Response of sugar concentration at the outlet of the four effects for a step disturbance in the glucose concentration of the glucose syrup (left) and an interruption of the glucose syrup flow rate (right).

3.5 Percentage gain analysis

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To assess how close to linear behavior was an evaporator response, the percentage gain of the outlet juice sugar mass concentration on each vessel was calculated for different step magnitudes. These step magnitudes are here expressed as percentage of the default step magnitudes applied in previous sections (increase of 2 °Brix in sugar mass concentration, 5 K in temperature and 5 % in the volumetric flow rate). Table 3 presents values of each evaporator liquid outlet percentage gain for different percentages of each step disturbance applied in the clarified juice in a combination of a pair applied simultaneously. So, for example, in the first part of Table 3, the row corresponding to a percentage of 50 % brings the observed percentage gains for simultaneous steps of 1 °Brix in sugar mass concentration and 2.5 % in the volumetric flow rate, while in the row corresponding to a percentage of 150 % in the second part of Table 3,

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gains for simultaneous steps of 3 °Brix in sugar mass concentration and 7.5 K in temperature are exhibited. The percentage gain values are obtained by dividing the total percentage variation of sugar concentration (due to step disturbances simultaneously in two inputs) by the sum of values of each step magnitude percentage variation. Table 3. Percentage gain, for each evaporator, of the sugar mass concentration of the liquid outlet for simultaneous disturbances in temperature, volumetric flow rate and sugar mass concentration of the clarified juice on different percentages of the disturbances value.

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Sugar mass concentration and volumetric flow rate simultaneous disturbances Percentage First effect Second effect Third effect Fourth effect 50% 0.04 -0.07 -0.34 -0.38 100% 0.04 -0.06 -0.17 -0.22 150% 0.04 -0.06 -0.14 -0.16 200% 0.04 -0.05 -0.11 -0.13

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Sugar mass concentration and temperature simultaneous disturbances Percentage First effect Second effect Third effect Fourth effect 50% -0.04 -0.30 0.01 0.00 100% -0.03 -0.25 -0.36 -0.38 150% -0.03 -0.21 -0.28 -0.29 200% -0.03 -0.18 -0.23 -0.23

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Volumetric flow rate and temperature simultaneous disturbances Percentage First effect Second effect Third effect Fourth effect 50% -0.13 -0.40 0.13 0.14 100% -0.12 -0.32 -0.42 -0.44 150% -0.11 -0.27 -0.33 -0.33 200% -0.10 -0.24 -0.27 -0.27 This table shows that percentage gain values of the first evaporator present low variation, indicating a close to linear response. The second one presents percentage gain values varying with greater extent, although lower if compared to the third and fourth devices. One of the main reasons that carry the two last evaporators away from linearity is the fact that the third one stops evaporation, leading to a feed steam cease on the fourth one. As a consequence, the last evaporator also stops its outlet vegetal steam flow. This factor can be seen on percentages of 100 % of the disturbances value and higher, with the change to a negative value on the third and fourth evaporator percentage gain values.

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In almost all cases, the response shows a negative percentage gain, indicating a loss of sugar mass concentration after application of the simultaneous disturbances. Also, Table 3 shows an increase in the absolute value of the percentage gain (except in the first row of second and third parts of Table 3) as the disturbed flow goes through each evaporator. As each vessel outlet is the next one feed, the response change is accumulated through the process. The dynamic analysis showed that in the first two effects the simultaneous disturbances generated a small change on the outlet juice concentration and temperature in comparison with

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the last two devices. However, the overall variation in the juice properties from the entire

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evaporation system presented a response with variations of a higher magnitude, indicating that disturbances applied in feed concentration, volumetric flow rate and temperature leads to higher

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variations in the juice properties as it flows through each effect. Also, the fact that each evaporator has two outputs that are fed into the next one increases the distance from linearity of

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the system.

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3.6 PI and PID control test and analysis

A classical PI controller with the objective of controlling the first effect liquid outlet sugar concentration was used. The first evaporator liquid outlet sugar concentration was chosen

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to be controlled due to a desired faster response and a response with lower variations shown by the dynamic analysis. The manipulated variable was the steam inlet flow rate. Manipulating

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steam inlet flow rate to control mixer outlet sugar concentration did not show to be effective, due to the large time delay caused by the four effects. Also, the dynamic analysis showed that it was

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necessary level PI controllers on all evaporators and pressure PI controllers in the third and fourth effects to prevent high oscillations in the evaporators response. This type of controller was selected due to its tuning simplicity. In pressure and level control, the derivative term is usually discarded (although the derivative term can be necessary for higher order systems with oscillatory responses). Since level and pressure of each effect are related to the evaporator holdup, it is expected that such a scheme generates a more stable response on temperature and sugar mass concentration. Although not completely necessary for this system control, the pressure controllers in the last two effects decreases the total sugar concentration variation caused by the disturbances. Pressure and concentration controllers manipulate a valve opening

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fraction that is modeled according to Equation (18).

is the volumetric flow rate through the

valve, P is the evaporator pressure and T its temperature. (18)

The control scheme was tested applying the same step simultaneous disturbances presented on the dynamic analysis. The first evaporator concentration set point was established

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as 19.8 °Brix. Fig. 6 shows both open loop and PI controlled responses of each evaporator of all

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simultaneous disturbances applied. The control parameters, pressure drop and valve coefficients were adapted from Ferreira et al. (2019). To find the suitable values for this system, each

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evaporator was simulated separately, under the feeding and operating conditions of the four effects. Subsequently, changes in the values of the parameters were applied to obtain few

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oscillations in the responses. The control parameters, pressure drop and valve coefficients used are shown in Table 4. A dynamic model of the four-effect evaporator and the PI control scheme

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were simulated in Aspen Dynamics (Fig. 7) to verify consistency of the model simulated in EMSO. Based on Luyben (2018), a pressure-driven simulation was performed with the application of the same simultaneous disturbances applied in EMSO simulations. The responses

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obtained with Aspen Dynamics can also be seen in Fig. 6. Although presenting small differences in the quantitative values achieved by the control system, the qualitative response behavior was

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close in both simulators. These differences can be related to small differences in some models and thermodynamic properties estimations. Furthermore, valves and pumps are necessary to be

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used to run dynamic simulations in Aspen Dynamics, but they are not present in EMSO model (except for the control valves). These devices can lead to a change in the response of the controlled system. The Aspen Dynamics configuration can be seen in Fig. 7. It is important to draw attention to a major difference between the work of Luyben (2018) and this work, since the former considers the complete condensation of the steam fed into the evaporators. Here, this consideration is not applied. The condensation rate is calculated by the heat transfer rate taking place in the calandria in each effect. Therefore, a higher heat transfer rate leads to a higher condensation rate. For that, temperature and pressure are taken as free variables. The way we model the process also explains the higher response time exhibited by the

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simulations of the model developed here when compared to the simulations of Luyben’s model. The condensation of steam is related to the heat exchange rate that is calculated with the temperature difference. Therefore, first disturbances cause a temperature change and then this change will lead to a change in steam outlet flow rate, and, consequently, in condensation rate. Temperature change takes a long time when a disturbance occurs, since it is affected by a high residence time inside the vessels of each effect. This consideration may lead to a not complete condensation in each effect, as can be seen in the last row of Fig. 6. Since the Robert evaporator

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calandria has only one input and one output for the steam and condensate stream, it is considered

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that the uncondensed steam comes out alongside with the condensate. Fig. 6 shows that, while at the starting steady-state conditions, all steam condenses in the calandria, dynamically and at the

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final steady state a small fraction of the fed steam leaves the evaporator uncondensed. Although not completely necessary for this system control, pressure controllers were

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added in the last two effects for a better performance of the dynamic response (oscillations are generally lower), including lower variation in the total sugar concentration variation. It can be

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explained by the fact that a better controlled pressure leads to smaller variations in temperature and, consequently, in the heat transfer rate.

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As can be noted, in general, the sugar mass percentage variation value was reduced with the insertion of the controllers. However, although pressure and level were successfully

degree value.

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controlled, the fourth evaporator liquid outlet still presented a relevant change in the outlet Brix

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The first effect outlet concentration was successfully controlled. However, the variation in the inlet steam flow rate generates variations in the juice outlet temperature that changes the heat exchange rate in the second evaporator. As a consequence, this effect presented a higher variation in its outlet Brix value in comparison with the others. Also, in practice, real-time online measurements of sugar mass concentration with precision are difficult and expensive. Sugar solutions tend to become inhomogeneous as it becomes more concentrated. Consequently, deposition can occur in the measuring instrument, requiring constant cleaning and calibration (Tarrant et al., 2010). A more reliable alternative is the use of soft sensors that use other variables measurements and an internal model to infer the juice composition.

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Although being able to control the multiple-effect evaporator system, classical PI controllers are not completely suitable for this process since it still showed variations in the overall juice concentration. Table 4. Controller parameters of each PI controller and its corresponding valve coefficient (the valve coefficient measurement unit is m1.5h-1kg0.5kPa-0.5 for the level controller and m1.5h-1kg0.5K0.5kPa for pressure and concentration controllers).

Level controllers

Pressure controllers

Concentration controller

LC4

PC3

Proportional

7.0

30.0

4.0

4.0

2.26

Integral (s)

105.0

55.2

35.8

59.0

1.3

10

10

10

10

5

(kPa)

AC1

7.0

13.4

6.3

136.5

5

5

207.5 1050.4 7200.5 4500.9 22379.0

47643.5

10581.0

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Valve Cv

PC4

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LC3

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LC2

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LC1

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Fig. 6. Responses of open loop and PI controlled evaporators of step simultaneous disturbances in sugar concentration and volumetric flow rate (first row), sugar mass percentage and temperature (second row) and volumetric flow rate and temperature (third row) in EMSO and Aspen Dynamics. In the last row, the vapor fraction of the condensate outlet of each effect for each simultaneous disturbance.

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Fig. 7. Evaporation system configuration in Aspen Dynamics.

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Tests were also made using a PID composition control in the outlet of the fourth evaporator, manipulating the valve of feeding steam to the first effect. Although PI controllers

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were used in the previous configuration, due to the presence of oscillations, a derivative term was added. The controller was configured with a proportional gain of 1.0, an integral time of

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104.75 min, a derivative time of 15.2 min and a set-point of 47.0 Brix degrees. The PID controller, with this setting, shows more effective control of the concentration of the entire

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evaporation system (in terms of achievement of set-point), leading to lower variations of juice Brix degrees. However, due to the high residence time of the large vessels of each effect, this

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configuration took a long time to reach a stable response, as can be seen in Fig. 8. The results of PI and PID composition control shown suggest both are not completely

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successful in controlling the process. It suggests that more advanced control strategies could be more suitable for efficient control performance.

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Fig. 8. Responses of PI and PID controlled evaporators on the first and fourth effects to step simultaneous disturbances in sugar concentration and volumetric flow rate (up left), sugar mass percentage and temperature (up right) and volumetric flow rate and temperature (bottom).

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3.7 Remarks

The analysis performed in this paper suggests that an adequate control system at the liquid and vapor output of each vessel is needed. Although there is the need to control sugar

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mass concentration, it is difficult to directly measure it in line. However, it is possible to use

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other variables to achieve the desired Brix set point since the results showed a relation of the juice volumetric flow rate and sugar concentration with temperature.

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The coupling of the second generation ethanol process to the first generation ethanol process by means of mixing glucose syrup to the treated sugarcane juice to compose the feed of the evaporation system in an autonomous distillery is attractive. It generates the flexibility needed for the ethanol production facility to operate in a way to produce only first generation ethanol or both simultaneously, according to the economic viability of the bagasse usage. The usage of the same equipment on the main stages is a convenient and economical way to switch between the different products desired. In the dynamic context, glucose syrup generates another source of disturbances. Problems on the pre-treatment or hydrolysis stages could generate a less concentrated syrup stream and affect the evaporation stage. Fig. 5 shows that a diluted glucose syrup stream generated relatively lower variations if compared to other disturbances. However,

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other disturbances applied simultaneously have the potential to generate greater losses in concentration. Also, an interruption of the glucose syrup flow rate may generate an excessively concentrated juice that can damage the fermentation process. Therefore, an outlet concentration control is needed. The tests with classical PI and PID controllers showed that, although being able to control this evaporation system, the presence of a large number of interactions and different disturbances generated a difficulty to maintain a fast and effective control, as can be seen in Fig.

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6 and Fig. 8. EMSO demonstrated to be a useful and reliable equation-oriented tool for dynamic

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modeling and simulation in the process studied. The object-oriented modeling language coupled with simple syntax rules provided an easy and accessible structure to manage. The ordinary

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differential system model was solved by the program solvers with no stiff problems. However, problems with step integration appeared when variables values at the differential equation were

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too small. As it is able to run dynamic simulations, EMSO presented advantages when compared to other commonly used commercial simulators (e.g., Aspen Plus, HYSYS, CHEMCAD),

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alongside with the fact that it is a simulator with no costs (for academic purposes). Also, the usage of the VRTherm database reduced the difficulty of estimating physical-chemical and

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4. Conclusions

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thermodynamic properties of mixtures and pure compounds.

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In this paper dynamic phenomenological models were used to analyze the dynamic behavior of a quadruple effect evaporator used in sugarcane autonomous distillery industry, used for a first and second generation ethanol integrated production process. The non-commercial process simulator EMSO was used to model and simulate transient responses of each effect to step disturbances in input variables. The simulator was able to run the model solving its ordinary differential equations system and also perform step disturbances. It was possible to analyze and compare the outcome of each disturbance as well as the application of them simultaneously in pairs. The results demonstrated an initial small change of sugar mass concentration and temperature in the first vessel with an increase in the variation value as the juice pass through each effect. The percentage gain analysis showed how far from

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linear is the dynamic response of each effect. A higher percentage gain variation in the last two evaporators in comparison with the first two ones was noticed, demonstrating nonlinear behavior and, consequently, causing more difficulties in maintaining the system controllable. Classical PI and PID controllers were tested and the model consistency was verified using Aspen Dynamics, widely accepted as a reliable dynamic process simulator. Although being able to reduce the variation in sugar concentration due to the disturbances, classical controllers performance was

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still unsatisfactory.

5. Acknowledgements

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The authors gratefully acknowledge the financial support from the National Council for Scientific and Technological Development – Process 305055/2017-8 – CNPq (Brazil) and the Coordination for the Improvement of Higher Education Personnel – Process 88881.171419/2018-01- CAPES (Brazil).

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7506-8308-1.00028-0

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