50,984 research outputs found
Selecting the best control methodology to improve the efficiency of discontinuous reactors
No full textThis work investigates in detail several methodologies to improve the optimal control of discontinuous processes. It shows that whenever a batch dynamic optimization is solved, the optimum is related to the control methodology adopted and the result is a sub-optimum since other more (or apparently less!) appealing control methodologies might lead to better optimal solutions. The selection of the best control methodology for the dynamic optimization is broached for batch reactors using gPROMS models builder 3.5.2 for dynamic modeling and BzzMath 6.0 optimizers to handle control and optimization issues
Optimization of batch and semi-batch reactors
No full textBatch and semi-batch reactors are widely used for fine chemical productions. The target in the fine chemical industry is to produce a high quality product and operational optimization is the key-element to match it. This work investigates how batch and semibatch reactors can be optimized in order to increase the yield of a desired product. Optimization problem is formulated and applied to calculate the optimal operating parameters such as the reactor temperature and the feed flow rate. Comparison and considerations on the two reactor configurations are given
Neural network based correlation for estimating water permeability constant in RO desalination process under fouling
No full textYesThe water permeability constant, (Kw) is one of many important parameters that affect optimal design and operation of RO processes. In model based studies, e.g.within the RO process model, estimation of Kw is therefore important. There are only two available literature correlations for calculating the dynamic Kw values. However, each of them are only applicable for a given membrane type, given feed salinity over a certain operating pressure range. In this work, we develop a time dependent neural network (NN) based correlation to predict Kw in RO desalination processes under fouling conditions. It is found that the NN based correlation can predict the Kw values very closely to those obtained by the existing correlations for the same membrane type, operating pressure range and feed salinity. However, the novel feature of this correlation is that it is able to predict Kw values for any of the two membrane types and for any operating pressure and any feed salinity within a wide range. In addition, for the first time the effect of feed salinity on Kw values at low pressure operation is reported. While developing the correlation, the effect of numbers of hidden layers and neurons in each layer and the transfer functions is also investigated.The water permeability constant, (Kw) is one of many important parameters that affect optimal design and operation of RO processes. In model based studies, e.g.within the RO process model, estimation of Kw is therefore important. There are only two available literature correlations for calculating the dynamic Kw values. However, each of them are only applicable for a given membrane type, given feed salinity over a certain operating pressure range. In this work, we develop a time dependent neural network (NN) based correlation to predict Kw in RO desalination processes under fouling conditions. It is found that the NN based correlation can predict the Kw values very closely to those obtained by the existing correlations for the same membrane type, operating pressure range and feed salinity. However, the novel feature of this correlation is that it is able to predict Kw values for any of the two membrane types and for any operating pressure and any feed salinity within a wide range. In addition, for the first time the effect of feed salinity on Kw values at low pressure operation is reported. While developing the correlation, the effect of numbers of hidden layers and neurons in each layer and the transfer functions is also investigated
Performance analysis of hybrid system of multi effect distillation and reverse osmosis for seawater desalination via modeling and simulation
No full textYesThe coupling of thermal (Multi Stage Flash, MSF) and membrane processes (Reverse Osmosis, RO) in desalination systems has been widely presented in the literature to achieve an improvement of performance compared to an individual process. However, very little study has been made to the combined Multi Effect Distillation (MED) and Reverse Osmosis (RO) processes. Therefore, this research investigates several design options of MED with thermal vapor compression (MED_TVC) coupled with RO system. To achieve this aim, detailed mathematical models for the two processes are developed, which are independently validated against the literature. Then, the integrated model is used to investigate the performance of several configurations of the MED_TVC and RO processes in the hybrid system. The performance indicators include the fresh water productivity, energy consumption, fresh water purity, and recovery ratio. Basically, the sensitivity analysis for each configuration is conducted with respect to seawater conditions and steam supply variation. Most importantly, placing the RO membrane process upstream in the hybrid system generates the overall best configuration in terms of the quantity and quality of fresh water produced. This is attributed to acquiring the best recovery ratio and lower energy consumption over a wide range of seawater salinity.The coupling of thermal (Multi Stage Flash, MSF) and membrane processes (Reverse Osmosis, RO) in desalination systems has been widely presented in the literature to achieve an improvement of performance compared to an individual process. However, very little study has been made to the combined Multi Effect Distillation (MED) and Reverse Osmosis (RO) processes. Therefore, this research investigates several design options of MED with thermal vapor compression (MED_TVC) coupled with RO system. To achieve this aim, detailed mathematical models for the two processes are developed, which are independently validated against the literature. Then, the integrated model is used to investigate the performance of several configurations of the MED_TVC and RO processes in the hybrid system. The performance indicators include the fresh water productivity, energy consumption, fresh water purity, and recovery ratio. Basically, the sensitivity analysis for each configuration is conducted with respect to seawater conditions and steam supply variation. Most importantly, placing the RO membrane process upstream in the hybrid system generates the overall best configuration in terms of the quantity and quality of fresh water produced. This is attributed to acquiring the best recovery ratio and lower energy consumption over a wide range of seawater salinity
Operation and Modeling of RO Desalination Process in Batch Mode
No full textYesThe performance of a batch reverse osmosis (RO) desalination process in terms of permeate quantity and salinity as a function of feed pressure and feed salinity is evaluated by using laboratory experiments and process modelling. Special attention is paid to the water and salt permeability constants (Kw, Ks) which affect the permeate and salt flux across the membrane. Kw and Ks are found to be strongly pressure-dependent for the batch system which is in-line with earlier observations for continuous RO systems. However, the most important findings of this work are the dependence of Kw and Ks on feed salinity, something that have never been observed or reported in the literature. In order to better qualify these observations, further experiments with the batch system are conducted with a constant feed salinity so that the operating condition resembles that of a continuous RO process.The performance of a batch reverse osmosis (RO) desalination process in terms of permeate quantity and salinity as a function of feed pressure and feed salinity is evaluated by using laboratory experiments and process modelling. Special attention is paid to the water and salt permeability constants (Kw, Ks) which affect the permeate and salt flux across the membrane. Kw and Ks are found to be strongly pressure-dependent for the batch system which is in-line with earlier observations for continuous RO systems. However, the most important findings of this work are the dependence of Kw and Ks on feed salinity, something that have never been observed or reported in the literature. In order to better qualify these observations, further experiments with the batch system are conducted with a constant feed salinity so that the operating condition resembles that of a continuous RO process
Neural-network approach to dynamic optimization of batch distillation - Application to a middle-vessel column
No full textDesign and economic evaluation of solar-powered hybrid multi effect and reverse osmosis system for seawater desalination
No full textYesReducing the cost of fresh water has always been a major concern in the desalination industry. A solar powered hybrid multi-effect distillation and reverse osmosis desalination plant (MED+RO) has been designed and optimised from an economical point of view in a previous work by the same authors. In the present study, the possibility of coupling the desalination plant with a photovoltaic (PV) solar farm is investigated, with the aim of generating electricity at low cost and in a sustainable way. A detailed mathematical model for the PV system has been implemented from the literature. Interestingly, the model can predict the cost of the PV system in terms of capital cost and electricity cost per kWh considering the input data of solar irradiation, duration of daylight and technical specification of a real solar module. Consequently, the solar PV model has been combined with the desalination model, which enables to estimate the cost of fresh water per cubic meter. Data about four locations, namely Isola di Pantelleria (IT), Las Palmas (ES), Abu Dhabi (UAE), and Perth (AUS), have been used to economically test the feasibility of installing the proposed plant, and especially of the PV solar farm.Reducing the cost of fresh water has always been a major concern in the desalination industry. A solar powered hybrid multi-effect distillation and reverse osmosis desalination plant (MED+RO) has been designed and optimised from an economical point of view in a previous work by the same authors. In the present study, the possibility of coupling the desalination plant with a photovoltaic (PV) solar farm is investigated, with the aim of generating electricity at low cost and in a sustainable way. A detailed mathematical model for the PV system has been implemented from the literature. Interestingly, the model can predict the cost of the PV system in terms of capital cost and electricity cost per kWh considering the input data of solar irradiation, duration of daylight and technical specification of a real solar module. Consequently, the solar PV model has been combined with the desalination model, which enables to estimate the cost of fresh water per cubic meter. Data about four locations, namely Isola di Pantelleria (IT), Las Palmas (ES), Abu Dhabi (UAE), and Perth (AUS), have been used to economically test the feasibility of installing the proposed plant, and especially of the PV solar farm
Dynamic Optimisation of Batch Distillation with a Middle Vessel using Neural Network Techniques
No full textA rigorous model (validated against experimental pilot plant data) of a Middle Vessel
Batch Distillation Column (MVC) is used to generate a set of data, which is then used to
develop a neural network (NN) based model of the MVC column. A very good match
between the “plant” data and the data generated by the NN based model is eventually
achieved. A dynamic optimisation problem incorporating the NN based model is then
formulated to maximise the total amount of specified products while optimising the
reflux and reboil ratios. The problem is solved using an efficient algorithm at the
expense of few CPU seconds
Cost evaluation and optimisation of hybrid multi effect distillation and reverse osmosis system for seawater desalination
No full textYesIn this research, the effect of operating parameters on the fresh water production cost of hybrid Multi Effect Distillation (MED) and Reverse Osmosis (RO) system is investigated. To achieve this, an earlier comprehensive model developed by the authors for MED + RO system is combined with two full-scale cost models of MED and RO processes collected from the literature. Using the economic model, the variation of the overall fresh water cost with respect to some operating conditions, namely steam temperature and steam flow rate for the MED process and inlet pressure and flow rate for the RO process, is accurately investigated. Then, the hybrid process model is incorporated into a single-objective non-linear optimisation framework to minimise the fresh water cost by finding the optimal values of the above operating conditions. The optimisation results confirm the economic feasibility of the proposed hybrid seawater desalination plant
Optimisation of multi effect distillation based desalination system for minimum production cost for freshwater
No full textThe multi effect distillation (MED) process has been extensively used for seawater desalination as a prominent process to produce high quality freshwater. However, the impact of number of effects in the MED process-based seawater desalination on the fresh water production cost has not been critically evaluated in the literature. Therefore, the aim of this study is to resolve this particular challenge via the simulation for a given seawater concentration and temperature conditions. The simulation is carried out using a comprehensive MED process model coupled with appropriate cost functions within gPROMS model builder software. The simulation results show that selecting the optimal number of the MED effects as 17 is important to achieve the lowest fresh water production cost for a given seawater operating conditions
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