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In this work, a generalized steady-state mathematical model has been developed for simulation of the multiple effect evaporator (MEE) system, used in the Indian sugar industry. The developed model is capable of handling exhaust steam (saturated/superheated) inputs in more than one effect, vapor bleeding from desired effects, heat loss from each eff...
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... Vapor bleeding is done to preheat the feed or liquor near to temperature of the effect it is entering into so that liquor can easily attain boiling temperature inside the effect. This increases evaporator capacity as a result steam consumption is reduced and steam economy improved (Bhargava et al., 2008a).Vapor bleeding not only reduces steam consumption and increases steam economy, but also it provides room for process improvement of the evaporation process (Srivastava et al., 2013). However, vapor bleeding comes with addition costs of installation and running heat exchangers in the evaporator station (Khanam and Mohanty, 2010;Yadav and Verma, 2020), giving more room for more research work on process performance and addition costs on vapor bleeding. ...
... Step 2: Overall solids balance to obtain mass flow rate of liquor in the final effect (B 5 ), was established as per Equation (1) (Bhargava et al., 2008a;Srivastava et al., 2013): ...
... Step 8: Solving for the bottoms (mass flowrate of liquor) from each effect (Bhargava et al., 2008a;Khanam and Mohanty, 2008;Srivastava et al., 2013), using mass balances around individual effects leads to solution for B 1 , B 2 , B 3 and B 4 , that is: ...
Improving process performance is always important in any processing industry with the aim of reducing operation costs and improving the profit.Vapor bleeding may be used in processing industries using multiple-effect evaporatorsto reduces steam consumption and increases steam economyThe effect of vapor bleeding on separation performance using multiple-effect sugarcane juice evaporator was analyzed. The effect of increasing percent of vapor bled and determination of the most effective bleeding configuration in terms of energy efficiency and operating costs. The performance factors assessed were: steam requirement, total heat transfer area (At), steam economy, total utilized heat (Qt), mass flow rate of bottoms (Bi), percent solids in the bottoms (XBi), and mass flow rate of vapors. To carry out this work, a five-effect evaporator, forward feed computer model was developed based on mass and energy balance equations, calibrated by data from steam tables. Simulations incorporating different configurations of vapor bleeding were carried out. Bleeding from each of the first four effects, Ei , and from a combination of effects (E1&E3, E2&E4) were carried out. The E1&E3 configuration showed a highest decrease in steam consumption by 23.73% and improved steam economy by 31.28%. Also, vapor bleeding reduced At and XBi while increasingBi. This work suggests that to improve energy efficiency during separation of mixtures using evaporators, vapor bleeding should be practiced while maintaining a balance between vapors used to preheat the feed and that used for heating the subsequent effects.
... If there are changes in the technological regime, it is necessary to adjust the technological parameters. Without automatic correction algorithms, the operator must make the decision to change these parameters (Geng et al., 2015;Machková et al., 2017;Sidletskyi et al., 2020;Srivastava et al., 2013). ...
... A complex indicator of disturbances in the operation of a diffusion plant is the decrease of its quality indicators, which are determined in the process of laboratory analysis of diffusion juice, pulp or determination of total sugar losses (Zayets, 2003). The complexity of the operator's work lies in the fact that deviations in the technological regime and deterioration of the process quality indicators can be caused by various reasons (Korobiichuk et al., 2018;Srivastava et al., 2013). At the same time, decision-making to eliminate them is also ambiguous. ...
... = overall heat transfer coefficient, W/m 2 .K, T = boiling temperature of the sugar solution, K. Any effect that has an extra heating load will require a proportionally larger ΔT. Prediction of the overall heat transfer coefficient involving three variables namely: sugar solution concentration, x, sugar solution temperature, Tf and feed flow rate, F, especially for Robert type evaporator is given bySrivastava (2013) with the following empirical equation[11]: Umaks = 5,71 kW/m 2 .°C; xmax = 0,57; Tmax = 122°C dan Fmax = 100 kg/s. ...
... = overall heat transfer coefficient, W/m 2 .K, T = boiling temperature of the sugar solution, K. Any effect that has an extra heating load will require a proportionally larger ΔT. Prediction of the overall heat transfer coefficient involving three variables namely: sugar solution concentration, x, sugar solution temperature, Tf and feed flow rate, F, especially for Robert type evaporator is given bySrivastava (2013) with the following empirical equation[11]: Umaks = 5,71 kW/m 2 .°C; xmax = 0,57; Tmax = 122°C dan Fmax = 100 kg/s. ...
strong>ABSTRACT. In maintaining the existence of sugar factories that exist and are still actively operating in Indonesia, efforts should be made to carry out intensification and extensification. In terms of the intensification of the process, it is necessary to periodically evaluate the performance of process tools, especially those that require utilities so that the process is effective and efficient. The process of making sugar passes through six stages, namely: milling, purification, evaporation (evaporation), cooking, screening, and packaging processes or the final stage. The evaporation process is a crucial process that determines the success of the entire process because the juice is concentrated from 11% to 64%. The evaporator is designed to use a multiple effect evaporator to increase the value of steam economy. The research objective is to optimize the number of effects that require a minimum total cost. To achieve this goal, it is necessary to survey the sugar factory to obtain the necessary valid data. Furthermore, a mathematical model is compiled based on the principle of mass and heat balance and then a software program is made so that the optimization solution can be done accurately. The conclusions that can be drawn are as follows: for a mass flow rate of 125,000 kg/hour with a concentration of 11% juice and a feed temperature of 100oC, the optimum conditions are obtained with a minimum annual production cost of IDR. 22,090,361,779.00 which is owned by the evaporator with 4 effects, total evaporator area = 2,443.81 m2, steam economy = 3.98 and steam demand = 26,028.2 kg/hour. The number of evaporator effects of 4 is common in Indonesia.
... Причиною цього може бути висока складність та вартість проведення такого дослідження. У роботі [12] також розглядаються варіанти удосконалення процесу випаровування та проводяться складні розрахунки. У [13] автори доводять, що швидкість випаровування помітно зменшується з часом, та проводять розрахунок, який показує, що дифузія в рідкій фазі є кроком, що обмежує швидкість для цієї системи, на відміну від випаровування чистої води. ...
The purpose of the presented research is to substantiate the methods of steam pressure regulation in the evaporator with the forecasting subsystem, which will allow predicting the behavior of the system and the study of the influence of the number of time intervals of the forecasting algorithm on the accuracy of the forecast of the evaporating plant operation. Development of a data exchange system between the level of the technological process and the level of production. The operation of the evaporator with the forecasting subsystem of steam pressure regulation is investigated. In the steam pressure control automation scheme, PC-28 pressure transducers are used as sensors. Pneumatic seat valves with a built-in throttle and an electro-pneumatic transducer are used as executive mechanisms. The use of neurofuzzy regulators occurs only in some specific cases of intelligent control of the evaporation process, there are no data comparing the use of intelligent regulators with classical ones, the possibility of combining the operation of several types of intelligent regulators, as well as clear means of predicting their operation. Therefore, in this work, the forecasting method was used to compare the methods of regulating the steam pressure in the apparatus, which made it possible to predict the behavior of the system during the formation of the control action and to display the ready forecast on the operatorʼs screen and, thus, to increase the efficiency of the evaporation station. Statistical data on the behavior of automation system circuits in different operating modes using intelligent and classical regulators were collected, and a forecasting model of the operation of the evaporation plant was built using the local trend method, and the forecasting algorithm was modified. The advantage of this method is its easy and quick implementation, which does not require large economic and energy costs. A model for forecasting the operation of the evaporation plant was built using the local trend method and a forecasting algorithm was developed. The accuracy of the obtained prediction model was also evaluated. The accuracy of the prediction model was 97 % for the PID controller, 97 % for the neurofuzzy controller, and 96,5 % for the neural network when using 9 intervals, which is higher than the accuracy when using 6 intervals. The proposed model for predicting the operation of the evaporation plant is characterized by high accuracy as a whole, but during the occurrence of fluctuations in the transient process, there is an insignificant delay in forecasting these fluctuations. The accuracy of this model directly depends on the increase in the number of time intervals during the development of the forecasting algorithm.
... That is why there is a high probability that the use of intelligent regulators can further increase the efficiency of steam. This work also contains the consideration of options for improving the evaporation process (Srivastava et al., 2013). These studies also feature complex calculations. ...
... They perform a calculation and demonstrate that diffusion in the liquid phase is a step, which limits the rate for this system, in contrast to the evaporation of pure water. A generalized stationary mathematical model for modeling a multichannel evaporator system was developed in the paper (Srivastava et al., 2013). Patan with co-authors (2005) have considered the problems of detection of malfunctions of industrial processes using dynamic neural networks on the example of an evaporating station. ...
... That is why there is a high probability that the use of intelligent regulators can further increase the efficiency of steam. This work also contains the consideration of options for improving the evaporation process (Srivastava et al., 2013). These studies also feature complex calculations. ...
... They perform a calculation and demonstrate that diffusion in the liquid phase is a step, which limits the rate for this system, in contrast to the evaporation of pure water. A generalized stationary mathematical model for modeling a multichannel evaporator system was developed in the paper (Srivastava et al., 2013). Patan with co-authors (2005) have considered the problems of detection of malfunctions of industrial processes using dynamic neural networks on the example of an evaporating station. ...
... Besides dynamic models, there are numerous publications concerning evaporators with di erent focuses, e.g., an estimation of the overall heat transfer coe cient [7], computational aspects [145,79], multiple stream concepts [140,76], usage of commercial software [94,149], energy saving mechanisms in counter ow FFEs [113], FFEs in the sugar industry [126], fouling [35,12,103], pressure drop along the Tubes and interactions between vapor and liquid phase [50], energy reduction schemes [75], or turbulence in evaporating falling lms [77]. ...
Due to their energy efficient operation and flexible designs, falling film evaporators (FFEs) have a wide field of application in the industry.
Besides questions about construction, dominant time delays pose a large challenge to modeling and control of this process.
Especially, the automation of production system requires digital twins, i.e., plant models to teach operators or to accelerate the design process.
The heart of an FFE consists in tubes, where a partially evaporating liquid film flows down on their insides.
Hence, the tubes represent the main source of delays being primarily related to the transport of important process factors, such as the liquid's concentration and mass flow.
Nevertheless, modeling of the corresponding dynamic behavior is challenging.
From the control perspective, time delays cause oscillations of the output concentration - in particular, during ramp-up processes.
Additionally, strong couplings between output mass flow and concentration further complicate multivariable control which, however, is required by modern production systems.
The present thesis presents solutions to all aforementioned challenges.
By dividing the FFE process into subsystems, different designs can be simulated in a simple manner.
In this context, a certain plant model is validated based on real-world data leading to a digital twin.
To develop new transport models of evaporating liquid film, fundamental balance equations are evaluated, which yields systems of hyperbolic partial differential equations.
Via the method of characteristics, a transformation into time-delay equations succeeds; the latter are advantageous regarding simulation and controller design.
Pilot plant experiments to identify and validate a chosen model underline the ability of our approach to map the measured input-output behavior.
To answer control-related questions, a simplified process model is developed, the loop pairing problem is solved, and a multivariable control concept is designed.
... Mesfun and Toffolo (2013) applied a process integration methodology to optimize the evaporator train and the CHP system of a Kraft pulp and paper mill [3]. Several other deterministic and non-deterministic approaches to simulate MEE trains and optimize their energy consumption have also been tried [10][11][12][13][14][15][16][17][18][19][20][21][22]. Verma et al. (2019) recently published a review of methods used evaporator train simulation and optimization [19]. ...
An equation-oriented process simulator was developed for simulating evaporation plants. The simulator graphical user interface was written in Python 2.7, and its engine, in C++. The simulator orders and partitions the system of equations that describe the evaporator system under study and solves the partitions sequentially using the Newton-Raphson method. If no good initial estimates can be provided by the user, the simulator solves a simplified problem to generate the estimates, which greatly facilitates convergence. Calculations are based on steam table correlations and on black liquor enthalpy correlations described in the literature. Two multiple-effect counter-current evaporator scenarios were extracted from the literature and used to validate the simulator: a simple 3-effect system and a realistic 6-effect system. The simulator converged to the solutions with relative ease, provided that the model equations were written as described, that equations were ordered and partitioned, and the simplified model was used to generate good initial estimates. Good agreement was found between the calculated values and those reported in the literature, indicating that the proposed simulation framework could be extended to accommodate more complex systems. Deviations from the reported values can be explained by the different choices of physical properties correlations.
... In the study [23] the authors prove that the rate of evaporation decreases with time and performs a calculation, which indicates that liquid phase diffusion is a step that limits the speed for this system, in contrast to the evaporation of pure water. The study [24] presents a generalized stationary mathematical model for modeling a multichannel evaporator system. In the study [25] problems of troubleshooting industrial processes using dynamic neural networks by example of evaporator plant were considered. ...
... Mesfun and Toffolo (2013) applied a process integration methodology to optimize the evaporator train and the CHP system of a Kraft pulp and paper mill [3]. Several other deterministic and non-deterministic approaches to simulate MEE trains and optimize their energy consumption have also been tried [10][11][12][13][14][15][16][17][18][19][20][21][22]. Verma et al. (2019) recently published a review of methods used evaporator train simulation and optimization [19]. ...
An equation-oriented process simulator was developed for simulating evaporation plants. The simulator graphical user interface was written in Python 2.7, and its engine, in C++. The simulator orders and partitions the system of equations that describe the evaporator system under study and solves the partitions sequentially using the Newton-Raphson method. If no good initial estimates can be provided by the user, the simulator solves a simplified problem to generate the estimates, which greatly facilitates convergence. Calculations are based on steam table correlations and on black liquor enthalpy correlations described in the literature. Two multiple-effect counter-current evaporator scenarios were extracted from the literature and used to validate the simulator: a simple 3-effect system and a realistic 7-effect system. The simulator converged to the solutions with relative ease, provided that the model equations were written as described, that equations were ordered and partitioned, and the simplified model was used to generate good initial estimates. Good agreement was found between the calculated values and those reported in the literature, indicating that the proposed simulation framework could be extended to accommodate more complex systems. Deviations from the reported values can be explained by the different choices of physical properties correlations.
