No / Multi Stage Flash (MSF) desalination plants are a sustainable source of fresh water in arid regions. Modelling plays an important role in simulation, optimisation and control of MSF processes. In this work an MSF process model is developed, using gPROMS modelling tool. Accurate estimation of Temperature Elevation (TE) due to salinity is important in developing reliable process model. Here, instead of using empirical correlations from literature, a Neural Network based correlation is used to determine the TE. This correlation is embedded in the gPROMS based process model. We obtained a good agreement between the results reported by Rosso et. al. (1996) and those predicted by our model. Effects of seawater temperature (Tseawater) and steam temperature (Tsteam) on the performance of the MSF process are also studied and reported.

Yes / The shortage of fresh water resources is a global problem which requires a prompt solution. Thus, the multi effect distillation (MED) was successfully used for the production of fresh water from seawater. Despite the use of MED desalination system extensively, the influence of the number of effects on the fresh water production cost has not been covered in the open literature. Thus, this paper tries to rectify this specific challenge via simulation at given operating conditions of seawater salinity and temperature. The study is performed using a detailed mathematical model contains the suitable cost correlations. gPROMS model builder suite has been used to carry out an extensive simulation. The results of the study show that the lowest fresh water production cost can be achieved at an optimal number of effects of 17 for a certain operating conditions.

Yes / Multi-Stage Flash (MSF) desalination process has been used for decades for making fresh water from seawater and is the largest sector in desalination industries. In this work, dynamic optimisation of MSF desalination is carried out using powerful and robust dynamic simulation and optimisation software called gPROMS model builder. For a fixed freshwater demand, a number of optimal combinations of the factors such as heat transfer area, brine flow rate, cooling water flow rate, steam flow in brine heater, Top Brine Temperature, the number of stages, etc. are determined with the objective of maximising the performance ratio of the process (defined as the amount of fresh water produced per unit of energy input) considering the seasonal variations. An attempt has been made to develop an operational schedule for a particular day using dynamic optimisation.

Desalination is a technique of producing fresh water from the saline water. Industrial desalination of sea water is becoming an essential part in providing sustainable source of fresh water for a large number of countries around the world. Thermal process being the oldest and most dominating for large scale production of freshwater in today's world. Multi-Stage Flash (MSF) distillation process has been used for many years and is now the largest sector in the desalination industry. In this work, a steady state mathematical model of Multistage Flash (MSF) desalination process is developed and validated against the results reported in the literature using gPROMS software. The model is then used for further investigation. First, a steady state calcium carbonate fouling resistance model has been developed and implemented in the full MSF mathematical model developed above using gPROMS modeling tool. This model takes into consideration the effect of stage temperature on the calcium carbonate fouling resistance in the flashing chambers in the heat recovery section, heat rejection section, and brine heaters of MSF desalination plants. The effect of seasonal variation of seawater temperature and top brine temperature on the calcium carbonate fouling resistance has been studied throughout the flashing stage. In addition, the total annual operating cost of the MSF process is selected to minimise, while optimising the operating parameters such as seawater rejected flow rate, brine recycle flow rate and steam temperature at different seawater temperature and fouling resistance. Secondly, an intermediate storage between the plant and the client is considered to provide additional flexibility in design and operation of the MSF process throughout the day. A simple polynomial based dynamic seawater temperature and different freshwater demand correlations are developed based on actual data. For different number of flash stages, operating parameters such as seawater rejected flow rate and brine recycle flow rate are optimised, while the total annual operating cost of the MSF process is selected to minimise.The results clearly show that the advantage of using the intermediate storage tank adds flexible scheduling in the MSF plant design and operation parameters to meet the variation in freshwater demand with varying seawater temperatures without interrupting or fully shutting down the plant at any time during the day by adjusting the number of stages. Furthermore, the effect of non-condensable gases (NCG) on the steady state mathematical model of MSF process is developed and implemented in the MSF model developed earlier. Then the model is used to study effect of NCG on the overall heat transfer coefficient. The simulation results showed a decrease in the overall heat transfer coefficient values as NCG concentrations increased. The model is then used to study the effect of NCG on the design and operation parameters of MSF process for fixed water demand. For a given plant configuration (fixed design) and at different seawater and steam temperatures, a 0.015 wt. % of NCG results in significantly different plant operations when compared with those obtained without the presence of NCG. Finally, for fixed water demand and in the presence of 0.015 wt. % NCGs, the performance is evaluated for different plant configurations and seawater temperature and compared with those obtained without the presence of NCG.

Desalination is a technique of producing fresh water from the saline water. Industrial desalination of sea water is becoming an essential part in providing sustainable source of fresh water for a large number of countries around the world. Thermal process being the oldest and most dominating for large scale production of freshwater in today¿s world. Multi-Stage Flash (MSF) distillation process has been used for many years and is now the largest sector in the desalination industry. In this work, a steady state mathematical model of Multistage Flash (MSF) desalination process is developed and validated against the results reported in the literature using gPROMS software. The model is then used for further investigation. First, a steady state calcium carbonate fouling resistance model has been developed and implemented in the full MSF mathematical model developed above using gPROMS modeling tool. This model takes into consideration the effect of stage temperature on the calcium carbonate fouling resistance in the flashing chambers in the heat recovery section, heat rejection section, and brine heaters of MSF desalination plants. The effect of seasonal variation of seawater temperature and top brine temperature on the calcium carbonate fouling resistance has been studied throughout the flashing stage. In addition, the total annual operating cost of the MSF process is selected to minimise, while optimising the operating parameters such as seawater rejected flow rate, brine recycle flow rate and steam temperature at different seawater temperature and fouling resistance. Secondly, an intermediate storage between the plant and the client is considered to provide additional flexibility in design and operation of the MSF process throughout the day. A simple polynomial based dynamic seawater temperature and different freshwater demand correlations are developed based on actual data. For different number of flash stages, operating parameters such as seawater rejected flow rate and brine recycle flow rate are optimised, while the total annual operating cost of the MSF process is selected to minimise.The results clearly show that the advantage of using the intermediate storage tank adds flexible scheduling in the MSF plant design and operation parameters to meet the variation in freshwater demand with varying seawater temperatures without interrupting or fully shutting down the plant at any time during the day by adjusting the number of stages. Furthermore, the effect of non-condensable gases (NCG) on the steady state mathematical model of MSF process is developed and implemented in the MSF model developed earlier. Then the model is used to study effect of NCG on the overall heat transfer coefficient. The simulation results showed a decrease in the overall heat transfer coefficient values as NCG concentrations increased. The model is then used to study the effect of NCG on the design and operation parameters of MSF process for fixed water demand. For a given plant configuration (fixed design) and at different seawater and steam temperatures, a 0.015 wt. % of NCG results in significantly different plant operations when compared with those obtained without the presence of NCG. Finally, for fixed water demand and in the presence of 0.015 wt. % NCGs, the performance is evaluated for different plant configurations and seawater temperature and compared with those obtained without the presence of NCG.

Yes / The use of Reverse Osmosis (RO) membrane processes for the clarification and the concentration of apple juice is proposed as an alternative to the conventional concentration technique, which is based on evaporation and freezing. Several models have been published on RO process models relying on different assumptions that predict the permeate flux and aroma compounds rejections for aqueous solutions apple juice. The solution-diffusion model (Lumped model) has been applied for the previous models. The main instrument of this study is the use of the gPROMS software to develop a new distributed steady state model that will relax a number of earlier assumptions. The model has been validated with an observational data of apple juice filtration derived from the literature by analysing the permeate flux and the performance of membrane rejection at different concentrations, temperatures and pressures for a laboratory scale of spiral-wound RO module. Simulated results corroborate with experimental and model predictions.

Yes / Reverse osmosis system has been widely used for the separation of organic and non-organic pollutants present in wastewater. The main aim of this study is to develop a one dimensional steady state model based on the three-parameter Spiegler-Kedem methodology using the gPROMS software and validate it by assessing the performance of membrane rejection for the separation data of aqueous solutions of phenol under different concentrations and pressures. Considerations of the variance of pressure, flow rate, solute concentration, solvent and solute fluxes and mass transfer coefficient along the feed channel were included in the model. Furthermore, an optimization methodology for the gEST parameter estimation tool has been developed in the gPROMS and used with experimental data in order to estimate the best values of the separation membrane parameters and the friction parameter. The simulation results of this model have been corroborated by experimental data.

Yes / Steady state and dynamic modelling and simulation of catalytic reforming unit of Kaduna Refining & Petrochemical Company, NNPC (Nigeria) was carried to find out the behaviour of the reactions under both steady and unsteady state conditions. The basic model together with kinetic and thermodynamic parameters and properties were taken from the literature but is developed in gPROMS (an equation oriented modelling software) model building platform for the first time rather than in MATLAB or other modelling platform used by other researchers in the past. The simulation was performed using gPROMS and the predictions were validated against those available in the literature. The validated model was then used to monitor the behaviour of the temperature, concentrations of parafins, naphthenes and aromatics with respect to both time and height of the reactor of the industrial refinery of Nigeria. Hydrogen yield, Research octane number (RON) and temperature profiles are also reported. The components behave similarly in terms of reactions in the reactors but the time to attain quasi-steady state is different. The results are in good agreement with the industrial plant data.

Desalination technology provides fresh water to the arid regions around the world. Multi-Stage Flash (MSF) distillation process has been used for many years and is now the largest sector in the desalination industry. Top Brine Temperature (TBT) (boiling point temperature of the feed seawater in the first stage of the process) is one of the many important parameters that affect optimal design and operation of MSF processes. For a given pressure, TBT is a function of Boiling Point Temperature (BPT) at zero salinity and Temperature Elevation (TE) due to salinity. Modelling plays an important role in simulation, optimisation and control of MSF processes and within the model, calculation of TE is therefore important for each stages (including the first stage, which determines the TBT). Firstly, in this work, several Neural Network (NN) based correlations for predicting TE are developed. It is found that the NN based correlations can predict the experimental TE very closely. Also predictions of TE by the NN based correlations were found to be good when compared to those obtained using the existing correlations from the literature. Secondly, a hybrid steady state MSF process model is developed using gPROMS modelling tool embedding the NN based correlation. gPROMS provides an easy and flexible platform to build a process flowsheet graphically. Here a Master Model connecting (automatically) the individual unit model (brine heater, stages, etc.) equations is developed which is used repeatedly during simulation and optimisation. The model is validated against published results. Seawater is the main source raw material for MSF processes and is subject to seasonal temperature variation. With fixed design the model is then used to study the effect of a number of parameters (e.g. seawater and steam temperature) on the freshwater production rate. It is observed that, the variation in the parameters affect the rate of production of fresh water. How the design and operation are to be adjusted to maintain a fixed demand of fresh water through out the year (with changing seawater temperature) is also investigated via repetitive simulation. Thirdly, with clear understanding of the interaction of design and operating parameters, simultaneous optimisation of design and operating parameters of MSF process is considered via the application MINLP technique within gPROMS. Two types of optimisation problems are considered: (a) For a fixed fresh water demand throughout the year, the external heat input (a measure of operating cost) to the process is minimised; (b) For different fresh water demand throughout the year and with seasonal variation of seawater temperature, the total annualised cost of desalination is minimised. It is found that seasonal variation in seawater temperature results in significant variation in design and some of the operating parameters but with minimum variation in process temperatures. The results also reveal the possibility of designing stand-alone flash stages which would offer flexible scheduling in terms of the connection of various units (to build up the process) and efficient maintenance of the units throughout the year as the weather condition changes. In addition, operation at low temperatures throughout the year will reduce design and operating costs in terms of low temperature materials of construction and reduced amount of anti-scaling and anti-corrosion agents. Finally, an attempt was made to develop a hybrid dynamic MSF process model incorporating NN based correlation for TE. The model was validated at steady state condition using the data from the literature. Dynamic simulation with step changes in seawater and steam temperature was carried out to match the predictions by the steady state model. Dynamic optimisation problem is then formulated for the MSF process, subjected to seawater temperature change (up and down) over a period of six hours, to maximise a performance ratio by optimising the brine heater steam temperature while maintaining a fixed water demand.

Among many seawater desalination processes, the multistage flash (MSF) desalination process is a major source of fresh water around the world. The most costly design and operation problem in seawater desalination is due to scale formation and corrosion problems. Fouling factor is one of the many important parameters that affect the operation of MSF processes. This thesis therefore focuses on determining the optimal design and operation strategy of MSF desalinations processes under fouling which will meet variable demand of freshwater. First, a steady state model of MSF is developed based on the basic laws of mass balance, energy balance, and heat transfer equations with supporting correlations for physical properties. gPROMS software is used to develop the model which is validated against the results reported in the literature. The model is then used in further investigations. Based on actual plant data, a simple dynamic fouling factor profile is developed which allows calculation of fouling factor at different time (season of the year). The role of changing brine heater fouling factor with varying seawater temperatures (during the year) on the plant performance and the monthly operating costs for fixed water demand and fixed top brine temperature are then studied. The total monthly operation cost of the process are minimised while the operating parameters such as make up, brine recycle flow rate and steam temperature are optimised. It was found that the seasonal variation in seawater temperature and brine heater fouling factor results in significant variations in the operating parameters and operating costs. The design and operation of the MSF process are optimized in order to meet variable demands of freshwater with changing seawater temperature throughout the day and throughout the year. On the basis of actual data, the neural network (NN) technique has been used to develop a correlation for calculating dynamic freshwater demand/consumption profiles at different times of the day and season. Also, a simple polynomial based dynamic seawater temperature correlation is developed based on actual data. An intermediate storage tank between the plant and the client is considered. The MSF process model developed earlier is coupled with the dynamic model for the storage tank and is incorporated into the optimization framework within gPROMS. Four main seasons are considered in a year and for each season, with variable freshwater demand and seawater temperature, the operating parameters are optimized at discrete time intervals, while minimizing the total daily costs. The intermediate storage tank adds flexible scheduling and maintenance opportunity of individual flash stages and makes it possible to meet variable freshwater demand with varying seawater temperatures without interrupting or fully shutting down the plant at any-time during the day and for any season. Finally, the purity of freshwater coming from MSF desalination plants is very important when the water is used for industrial services such as feed of boiler to produce steam. In this work, for fixed water demand and top brine temperature, the effect of separation efficiency of demister with seasonal variation of seawater temperatures on the final purity of freshwater for both cleaned and fouled demister conditions is studied. It was found that the purity of freshwater is affected by the total number of stages. Also to maintain the purity of freshwater product, comparatively large number of flash stage is required for fouled demister.