Showing papers in "Computer-aided chemical engineering in 2007"
TL;DR: In this article, a new methodology to design and optimize district energy systems is developed based on the combination of an evolutionary algorithm, a network design and optimization algorithm, and several thermo-economic models for the energy conversion technologies.
Abstract: The reduction of CO2 emissions is a challenge for the coming decade, especially with the implementation of the Kyoto protocol. Since energy services (mainly heating and cooling of buildings) contribute to over 40% of the final energy consumption in a country like Switzerland, it is essential to find ways to improve the efficiency of energy conversion technologies. This can be done by combining these energy conversion technologies into polygeneration systems for instance. However, to ensure that polygeneration systems operate as often as possible at or near their optimal load, it is meaningful to implement systems that meet the requirements of more than just one building, in order to take advantage of the various load profiles of the buildings by compensating the fluctuations and having therefore a smoother operation. Besides, because these systems are complex and defacto difficult to operate, there are usually not justified in an individual building where no continuous professional control can be guaranteed. It is much more advantageous to implement them in a small plant that serves several buildings, and that is managed by an energy service company. This means that a network needs to be designed, that optimally connects the buildings and the energy conversion technologies together. A new methodology to design and optimize district energy systems is therefore being developed. The method (see figure) is based on the combination of an evolutionary algorithm, a network design and optimization algorithm, and several thermo- economic models for the energy conversion technologies. The first step is to select a district for which an energy system has to be developed or modified. The available renewable energy sources existing near or in the district, and thus the possible energy conversion technologies, are identified. Besides, all the relevant information regarding the district have to be structured: the geographical coordinates of the buildings, the load profiles of the buildings and finally the constraints (legal regulations, topology, existing networks,…). Once this information structuring phase is completed, the method for the design of the network and the energy conversion technologies can be applied, resulting in a number of different configurations. The costs and CO2-emissions are computed for each configuration on a Pareto-curve and the results compared. In this presentation, we present the first results of the implementation of this method.
74 citations
TL;DR: This method yields least-squares estimates of the noise covariances, which can be used to compute the Kalman filter gain.
Abstract: The Kalman filter requires knowledge about the noise statistics. In practical applications, however, the noise covariances are generally not known. In this paper, a method for estimating noise covariances from process data has been investigated. This method yields least-squares estimates of the noise covariances, which can be used to compute the Kalman filter gain.
44 citations
TL;DR: In this paper, the authors present a literature review of the optimization techniques that have been used so far for building or DHC applications, and establish the basis for the development of an optimization tool for the synthesis and design of polygeneration systems for their use in district heating and cooling networks, that are optimized reducing their investment and operational cost.
Abstract: The current increasing energy prices and the limitation of the existing energy resources promotes the use of new energy production systems, like hybrid integrated systems (using fossil fuels and renewable energy sources) with high-energy efficiency. These integrated systems, known as polygeneration systems, produce electrical, heating and cooling at different conditions at a higher efficiency than a conventional system, and involve a wide range of technologies with several possible configurations. Sometimes the design of these systems is carried out with the aid of mathematical models that are solved and optimized minimizing the investment and operational costs, but these optimization techniques are applied frequently for industrial applications and rarely for building or district heating and cooling (DHC) applications. The objective of this paper is to present a literature review of the optimization techniques that have been used so far for building or DHC applications. The main purpose of this review is to establish the basis for the development of an optimization tool for the synthesis and design of polygeneration systems for their use in district heating and cooling networks, that are optimized reducing their investment and operational cost. An example is presented to illustrate the application of this tool.
42 citations
TL;DR: In this paper, a novel criterion based on global sensitivity analysis, and therefore independent of the parameters values, is presented, in order to illustrate the performance of this methodology, a semicontinuous bioreactor is considered as a case study.
Abstract: The starting values considered for the model parameters strongly affect standard techniques for experimental design. When these values are far from the optimal ones, poor quality experiments are achieved or several steps are required resulting in a large experimental burden. Here, a novel criterion based on global sensitivity analysis, and therefore independent of the parameters values, is presented. In order to illustrate the performance of this methodology, a semicontinuous bioreactor is considered as a case study.
34 citations
TL;DR: In this article, the authors address the problem of developing an optimisation structure to aid the operational decision-making of scheduling activities in a real-world pipeline network, where many batches are pumped from (or passing through) different areas.
Abstract: This paper addresses the problem of developing an optimisation structure to aid the operational decision-making of scheduling activities in a real-world pipeline network. During the scheduling horizon, many batches are pumped from (or passing through) different areas. Pipes are a disputed resource. Scheduling details must be given, including pumping sequence in each area, batches' volume, tankage constraints, timing issues, while respecting a series of operational constraints. In addition, the electric energy presents on-peak demand hours, typically, from 5:30 p.m. to 8:30 p.m., and this feature also influences operational decisions. The balance between demand requirements and production campaigns, while satisfying inventory management issues and pipeline pumping procedures, is a difficult task. The proposed approach has been successfully applied to industrial-size scenarios. Many insights have been derived from the obtained solutions.
30 citations
TL;DR: In this paper, the authors developed a model that is designed to simulate and predict the performance of an existing MCHE without knowing its physical details, based on the concept of superstructure representation.
Abstract: Recent growth in world-wide consumption of natural gas highlights its immense importance as a source of primary energy. Liquefied natural gas (LNG) is the most economic way to transport natural gas over long distances. Main Cryogenic Heat Exchanger (MCHE) is a very critical equipment in an energy intensive LNG plant. To that end, modeling MCHE is the inevitable first step in the optimization of LNG plant operation. In this paper, we develop a model that is designed to simulate and predict the performance of an existing MCHE without knowing its physical details. The concept of superstructure representation is employed to derive an equivalent 2-stream heat exchanger network. The objective is to address the rating of an existing MCHE or the prediction of its performance rather than finding the area for a design or minimizing the cost. We use a mixed-integer nonlinear programming (MINLP) approach to select the best network that describes an existing MCHE. An example case is also presented to assess the ability of our model in predicting the performance of a MCHE.
27 citations
TL;DR: In this paper, the authors developed a simulation model to aid the operational decision-making of scheduling activities in a real-world pipeline network, where different products can flow through the same pipe and each oil derivative has its proper tank farm at refineries, terminals or harbor.
Abstract: This paper addresses the problem of developing a simulation model to aid the operational decision-making of scheduling activities in a real-world pipeline network. Basically, the simulation model should represent three different behaviors: production, transport and demand of oil derivatives. Batches are pumped from (or pass through) many different areas and flow through pipes which are the shared resources at the network. It is considered that different products can flow through the same pipe and each oil derivative has its proper tankfarm at refineries, terminals or harbor. The simulator makes use of an optimal scheduling sequence of batches that balance demand requirements to the production planning, considering inventory management issues and pipeline pumping procedures. The simulation model represents a real-world pipeline network designed to aid typical activities of an operator such as inventory management at different and batch performance analysis by visualization tank levels and pipe utilization rate.
26 citations
TL;DR: In this article, a set of Partial Differential and Algebraic Equations (PDAE) is used to investigate two HSS classes, considering the case of air separation.
Abstract: Pressure swing adsorption (PSA) and membrane-based gas separation processes are two different alternatives for effective, continuous bulk gas separation at the industrial scale. Both these processes possess characteristics that render them advantageous over conventional cryogenic processes, and they can be combined into a Hybrid Separation System (HSS). Dynamic simulation and optimisation of a HSS must rely on all mathematical equations describing the dynamic behaviour of PSA and membrane permeation modules in a single flowsheet. The mathematical model is a set of Partial Differential and Algebraic Equations (PDAE) and has been used to investigate two HSS classes, considering the case of air separation. The paper considers two HSS concepts (for same and opposite separation selectivity), and presents dynamic simulation and optimisation results, focusing on the performance of the HSS flowsheet and demonstrating significant improvements over the standalone PSA and membrane processes.
26 citations
TL;DR: In this article, the authors investigated the recovery of aromatics which has an important commercial application such as benzene, toluene and xylenes from pyrolysis gasoline using a solvent called N-methylpyrolidone.
Abstract: Extractive distillation is widely used technology for recovering aromatics from different feedstock. This study investigates the recovery of aromatics which has an important commercial application such as benzene, toluene and xylenes from pyrolysis gasoline using a solvent called N-methylpyrolidone. The study also examines the procedures involved in implementing the energy-integrated extractive distillation technologies such as Petlyuk column, divided wall column and heat integrated extractive distillation column compared to conventional extractive distillation technique for processing petrochemical cuts in the range of C5 to C9. Design, modeling and simulation have been conducted for the examined extractive distillation configurations and the optimum design is selected based on minimum total annual cost as the objective function. Different solvent (S) /feed (F) ratios (2/2.5/3 vol%) have been investigated to reach the optimum separating ratio, the effect of solvent feed temperature is considered also. The designed extractive distillation columns meet all expectations regarding energy consumption and cuts purity. The economic analysis proved that heat-integrated configurations are the best candidates compared to Petlyuk column and divided-wall column. Solvent feed ratio of 2 vol % found to be the best from energy and material consumption point of view, reducing solvent temperature is improving extraction process and reducing the reflux ratio of extractive column.
25 citations
TL;DR: A control relevant dynamic model is derived using firstprinciples modeling and it is used to study the dynamic behavior of the process at high and low purity operating regimes and the results are used to analyze the performance of linear and nonlinear model predictive control in comparison to coupled PID control.
Abstract: The paper presents a detailed analysis of the dynamic behavior of a reactive distillation column. A control relevant dynamic model is derived using firstprinciples modeling and it is used to study the dynamic behavior of the process at high and low purity operating regimes. The results are used to analyze the performance of linear and nonlinear model predictive control in comparison to coupled PID control.
21 citations
TL;DR: In this paper, the authors outline the concept of process systems engineering and computer aided process engineering (CAPE), discuss the future developments in the area, and present a survey of the current state-of-the-art in this field.
Abstract: Publisher Summary Outlining the concept of process systems engineering and computer aided process engineering (CAPE), this chapter discusses the future developments in the area. Process systems engineering (PSE) has been traditionally concerned with the understanding and development of systematic procedures for the design, control, and operation of chemical process systems. Problems related to process optimization, process integration and process synthesis/design are currently routinely solved through knowledge-based techniques as well as mathematical optimization techniques. Also, systematic methods and tools have been developed and applied to solve industrial problems in the area of planning and scheduling, online optimization, solvent selection/design, and many more.
TL;DR: In the context of the climate change and with the perspective of rapid exhaustion of fossil hydrocarbon resources, the use of renewable raw materials becomes vital for the future of Chemical Process Industries as mentioned in this paper.
Abstract: In the context of the climate change and with the perspective of rapid exhaustion of fossil hydrocarbon resources, the use of renewable raw materials becomes vital for the future of Chemical Process Industries The first oil crisis from 1974 kicked-off the advent of process simulation Today the emergence of bio-fuels, boosted by a serious petroleum and environmental crisis, is an exiting challenge for developing new design methods and simulation tools, as well as a chance for CAPE rejuvenation
TL;DR: In this paper, the model formulations are reformulated to contain only continuous variables and the discrete decisions are relaxed and successively tightened in a sequential solution procedure to facilitate convergence and to obtain local optima of good quality.
Abstract: Process synthesis often involves the solution of large nonlinear discretecontinuous optimization problems, which are usually formulated as mixedinteger nonlinear programming (MINLP) or generalized disjunctive programming (GDP) problems and solved with MINLP solvers. This paper presents an efficient solution method for these problems named successive relaxed MINLP (SR-MINLP), where the model formulations are reformulated to contain only continuous variables. The discrete decisions are relaxed and successively tightened in a sequential solution procedure to facilitate convergence and to obtain local optima of good quality. The solution method is illustrated by a simple numerical example as well as a large and complex example from process synthesis.
TL;DR: In this article, an integrated product and process design approach for foods is proposed to quantify rationalization of ingredients and to realize its opportunity during process synthesis, in which the ingredients are used as inputs for process synthesis to find optimal process to deliver required analytical/sensorial attributes through desired microstructures.
Abstract: To quantify rationalization of ingredients and to realize its opportunity during process synthesis, in this contribution we propose an integrated product and process design approach for foods. According to this methodology, once the product concept and geographical market are decided, product attributes that drive consumer liking are identified and quantified. The product attributes are either of sensorial or analytical nature. The identification and quantification of this relationship is obtained by means of data mining techniques. Relevant sensorial and analytical attributes are used, afterwards, to create alternatives for possible microstructures and ingredients. Subsequently, the ingredients are used as inputs for process synthesis to find optimal process to deliver required analytical/sensorial attributes through desired microstructures. The ingredients are related to analytical and sensorial attributes through mathematical process and ingredients models, respectively. We integrate this methodology with a modified Douglas' methodology for food products. By putting together mathematical relationships between consumer liking attributes, product attributes and ingredients and processes, a quantitative rationalization can be achieved. An oil-in-water mayonnaise-like emulsion was used as case study.
TL;DR: In this paper, the authors describe the design and improvement of chemically active ship bottom paints known as antifouling paints, and discuss the challenges involved in working with such multicomponent, functional products.
Abstract: This chapter describes the design and improvement of chemically active ship bottom paints known as “antifouling paints.” The chapter describes the challenges involved in working with such multicomponent, functional products and presents the available scientific and engineering tools. The research in this field includes both purely empirical formulation and test methods and advanced tools including mathematical modelling of paint behavior. First, the background of and problems associated with marine biofouling are presented, which is followed by a concise historical review on the diverse ideas of biofouling control that have been tried over the years. The chapter also discusses the characterization and working mechanisms of antifouling paints, detailing the various components and their function. Practical laboratory and field tests of antifouling paints are presented. The chapter discusses several legislations related to paint products. The requirements given by environmental legislation severely limit the introduction of new active ingredients, controlling the release of most biocides.
TL;DR: The integration of ModDev, MoT and ICAS or any other external software or process simulator (using COM-Objects) permits the generation of different models and/or process configurations for purposes of simulation, design and analysis.
Abstract: Chemical processes are generally modeled through monoscale approaches, which, while not adequate, satisfy a useful role in product-process design. In this case, use of a multi-dimensional and multi-scale model-based approach has importance in product-process development. A computer-aided framework for model generation, analysis, solution and implementation is necessary for the development and application of the desired model-based approach for productcentric process design/analysis. This goal is achieved through the combination of a system for model development (ModDev), and a modelling tool (MoT) for model translation, analysis and solution. The integration of ModDev, MoT and ICAS or any other external software or process simulator (using COM-Objects) permits the generation of different models and/or process configurations for purposes of simulation, design and analysis. Consequently, it is possible to reduce time and human resources in the development and solution of models.
TL;DR: In this article, the design of the PID controller cascaded with first order filter has been proposed for the second order unstable time delay processes, which is based on the IMC criterion which has single tuning parameter to adjust the performance and robustness of the controller.
Abstract: The design of the PID controller cascaded with first order filter has been proposed for the second order unstable time delay processes The design algorithm is based on the IMC criterion which has single tuning parameter to adjust the performance and robustness of the controller The setpoint filter is used to diminish the overshoot in servo response The simulation results of the suggested method are compared with recently published tuning methods to demonstrate the superiority of the proposed method For the reasonable comparison the controllers are tuned to have the same degree of robustness by the measure of maximum sensitivity (Ms) A guideline is also provided for the ease of the selection of closed-loop time constant (λ)
TL;DR: The improving effect of rate promoters has been investigated by experiments at pilot plant scale in conditions close to the operating conditions of the top zone of a typical hot potassium carbonate industrial packed bed absorber.
Abstract: The improving effect of rate promoters has been investigated by experiments at pilot plant scale in conditions close to the operating conditions of the top zone of a typical hot potassium carbonate industrial packed bed absorber. The evaluation of promoter enhancement factor has been done by successive experiments with absorption of CO2 into water, into carbonate solution and into promoted carbonate solution.
TL;DR: In this article, the authors investigate that forecasting capability using linear models (such as ARX, ARMAX, output-error and Box-Jenkins), and neural networks, using meteorological variables and 24-h PM 10 concentration of the present day as input data.
Abstract: Particulate air pollution is associated with a range of effects on human health, including effects on the respiratory and cardiovascular systems, asthma and mortality. Hence, the development of an efficient forecasting and early warning system for providing air quality information towards the citizen becomes an obvious and imperative need. The objective of this work was to investigate that forecasting capability using linear models (such as ARX, ARMAX, output-error and Box-Jenkins), and neural networks. They were used meteorological variables and 24-h PM 10 concentration of the present day as input data. As output foreseen by the models, the 24-h PM 10 concentration is obtained, with horizon of prediction of up to three days ahead. The results showed that fairly good estimates can be achieved by all of the models, but Box-Jenkins model showed best fit and predictability.
TL;DR: In this article, an SDE-based software with Runge-Kutta routines, orthogonal collocation methods and sequential quadratic programming is proposed to simulate the HDS process.
Abstract: The hydrodesulfurization (HDS) processes research requires a lot of experimental work to define promotion and inhibition effects and find out correlations between the variables that participate on the sulphur removal. By means of modeling and simulation is possible to determine the scope of the process, and by means of the sequential design of experiments (SDE) is possible to reduce the experimental work required through comparison of kinetic models, at the same time that it predicts experimental conditions that allow to select a unique model and estimate its parameters. The purpose of this work was to simulate the HDS process using the mathematical model developed in previous work and several kinetic models founded in literature. Together simulation is proposed a SDE-based software with Runge-Kutta routines, orthogonal collocation methods an Sequential Quadratic Programming to develop the steps of the Design and to be used on pilot plant applications. The good agree between theoretical and experimental data led to the development of a user-friendly program to simulate the complex process, make easier the interpretation of simultaneous reactions, and become a useful tool for to improve the operation conditions of hydrotreating industrial reactors.
TL;DR: In this article, the authors discuss product-centered process synthesis and development of detergent products, including dishwashing liquids and laundry detergents, which constitute a significant portion of the household and personal care markets.
Abstract: This chapter discusses product-centered process synthesis and development. Detergent products, including dishwashing liquids and laundry detergents constitute a significant portion of the household and personal care markets. Contrary to the commodity chemical business, the key to win in the specialty products market does not lie in squeezing out profits by means of economies of scale or process optimization. Rather, it lies in the ability for fast new product launches to capture the largest market share as soon as possible. The procedure consists of three steps: (1) the first step is to identify all the desired product quality factors or attributes for the new product. (2) The selection of the appropriate product form and microstructure, a stable surfactant system with the right performance based on phase behavior, and the appropriate active ingredients to realize those quality factors previously identified. (3) Finally, the process flowsheet is created with the equipment units and process operating conditions determined.
TL;DR: In this article, the authors present a model for the investment planning of a poly-generation energy system, and uses this model for a case study addressing a system for production of methanol and electricity.
Abstract: The forecasted shortage of fossil fuels and the ever-increasing effect of greenhouse gas (GHG) emissions on global warming and environmental stability are two international problems with major technical, economic and political implications in the 21st century. Therefore, it is urgent to restructure present energy production and utilization systems in order to ensure that fossil fuels are used with high efficiency and low to zero emissions. Polygeneration energy systems combine power generation and chemical fuel synthesis in a single plant (producing both electricity and fuels) and thus provide a promising alternative pathway towards achieving sustainable and flexible economic development. Mixed-integer programming (MIP) is useful in constructing longterm decision models that are suitable for investment planning and design of polygeneration infrastructure systems. This paper presents a model for the investment planning of a polygeneration energy system, and uses this model for a case study addressing a system for production of methanol and electricity.
TL;DR: In this article, the authors discuss chemical product design related problems (case studies) highlighting the tasks where computer-aided molecular and mixture design (CAMD) techniques can be employed.
Abstract: This chapter discusses chemical product design related problems (case studies) highlighting the tasks where computer-aided molecular and mixture design (CAMD) techniques can be employed. Other computer-aided tools to be used are primarily methods for property prediction (product evaluation), product-process modeling (performance evaluation), and process simulation (design and verification). All computer-aided tools used in this case study were developed at CAPEC and are available as toolboxes within ICAS (Integrated Computer Aided System)—Gani. The case studies highlight mainly the product related issues through the use of CAMD techniques. Many of the unit operations found in the food processing, pharmaceutical, and agrochemical industries are still not available. The chapter presents the discussion by using the hybrid CAMD technique developed by Harper et al. and implemented in ProCAMD. The solution of all CAMD problems, can in principle, be divided into four main steps: (1) problem formulation, (2) initial search, (3) generate and test, and (4) verification. The case studies are related to (1) solvent design selection, (2) backbone generation, (3) polymer design, and (4) refrigerant design.
TL;DR: In this paper, a new control method based on a nonlinear predictive algorithm is developed for a pH neutralization process in order to control the plant to the desired setpoint with high-quality performances over the entire operation range.
Abstract: In this paper, a new control method based on a nonlinear predictive algorithm is developed for a pH neutralization process in order to control the plant to the desired setpoint with high-quality performances over the entire operation range. For testing the control structure, the process simulator together with the control algorithm were implemented in Matlab and simulation results are given.
TL;DR: In this paper, a model-based control strategy for membrane separation is presented which is based on an automated recognition of current dominant filtration mechanisms during the operation, and a model based optimization framework is proposed which includes parameter identifiability and estimation, as well as an enhanced model discrimination step.
Abstract: In this work, a new model-based control strategy for membrane separation is presented which is based on an automated recognition of current dominant filtration mechanisms during the operation. For this purpose, a model-based optimization framework is proposed which includes parameter identifiability and estimation, as well as an enhanced model discrimination step. Based on the developed approach, it is now possible to identify time points, i.e., time intervals where a certain model is valid or more appropriate. Thus, suitable control actions can be carried out in order to increase the permeability respective to each mechanism improving the filtration performance in membrane bioreactors (MBR). The validation of the novel approach is demonstrated using experimental data from a test cell as well as from an MBR pilot plant.
TL;DR: In this paper, a feed-forward neural network is used to predict liquid crystalline behavior of some organic compounds, which is correlated with molecular weight and a series of structural characteristics estimated by mechanical molecular simulation.
Abstract: This paper presents a new method of predicting the liquid crystalline behavior of some organic compounds, using feed-forward neural networks. The prediction of properties is correlated with molecular weight and a series of structural characteristics estimated by mechanical molecular simulation. An efficient genetic algorithm based method is used to determine optimal topology of the neural model.
TL;DR: A computer aided design method is presented for modeling of aqueous two-phase extraction of monoclonal antibodies (MAbs) and a conventional counter current extractor is compared with a fractional extractor in terms of purity and concentration of MAbs in the extract.
Abstract: Design of chemical processes is usually based on rigorous modeling of unit operations. Unfortunately, the use of physically grounded models in biotechnological applications is rare since their design is mainly based on heuristics and experiments. In this work a computer aided design method is presented for modeling of aqueous two-phase extraction of monoclonal antibodies (MAbs). A conventional counter current extractor is compared with a fractional extractor in terms of purity and concentration of MAbs in the extract. The purity of MAbs increased from 85% in the conventional to almost 100% in the fractional extractor.
TL;DR: In this article, two different process alternatives for the production of fuel ethanol from lignocellulosic feedstock are considered through a first-principle model of the process.
Abstract: The conversion of biomass into biofuels can increase fuel flexibility and reduce the related strategic vulnerability of petroleum based transportation fuel systems. Bioethanol has received considerable attention over the last years as a fuel extender or even neat liquid fuel. Lignocellulosic materials are very attractive substrates for the production of bioethanol because of their low cost and their huge potential availability. In this paper two different process alternatives for the production of fuel ethanol from lignocellulosic feedstock are considered through a first-principle model of the process. The main objective is the analysis of the energy balance of the different production processes.
TL;DR: In this paper, an industrial case study within Akzo Nobel Chemicals is presented, where reaction and separation are combined into one reactive divided-wall column (RDWC) to save 35% in capital and 15% in energy costs.
Abstract: This work presents an industrial case study within Akzo Nobel Chemicals. Due to the market demand changes, one of the by-products became more expensive, hence more attractive than the main product. However, the current plant design does not allow an increase of the by-product production rate at the cost of the main product. To solve this problem we propose an integrated design that combines reaction and separation into one reactive divided-wall column (RDWC) that allows 35% savings in capital and 15% savings in energy costs.
TL;DR: In this article, a numerical model was proposed to predict the evolution of the ice stock and the available cooling power in function of the tank geometry and the operating conditions, taking into account ice settling, fluid circulation, ice formation (in generator) and ice melting (in utilisation loop and because of heat losses).
Abstract: Ice slurries, composed of an aqueous solution and water ice crystals, are used in new environmentally friendly refrigeration systems in order to reduce the amount of refrigerant. The slurry storage tank is an equipment which is important to correctly design. A numerical model was proposed to predict the evolution of the ice stock and the available cooling power in function of the tank geometry and the operating conditions. It takes into account ice settling, fluid circulation, ice formation (in generator) and ice melting (in utilisation loop and because of heat losses) . It can be used to optimise the operating conditions and the geometrical parameters of the ice slurry storage tank.