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Computer simulation for the optimization of reverse osmosis seawater desalination pretreatment
Title
Computer simulation for the optimization of reverse osmosis seawater desalination pretreatment.
Creator
Corlay, Brieuc., Florida Atlantic University, Haky, Jerome E.
Abstract/Description
A computer program was developed to simulate and optimize the chemical pretreatment of seawater prior to desalination by reverse osmosis. The model was created using LabViewRTM programming language. The automation of the process was achieved using a PID (proportional, integrative, derivative) controller. The effects of a variety of operating conditions were modeled to optimize the chemical pretreatment. We focused on three parameters: hardness removal, iron removal and control of biogrowth....
Show moreA computer program was developed to simulate and optimize the chemical pretreatment of seawater prior to desalination by reverse osmosis. The model was created using LabViewRTM programming language. The automation of the process was achieved using a PID (proportional, integrative, derivative) controller. The effects of a variety of operating conditions were modeled to optimize the chemical pretreatment. We focused on three parameters: hardness removal, iron removal and control of biogrowth. The validity of the model was verified with laboratory scale experiments. In the range of the model, the predicted values differ by a maximum of 11% from experimental results.
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Date Issued
2003
PURL
http://purl.flvc.org/fcla/dt/13026
Subject Headings
Saline water conversion--Reverse osmosis process, Reverse osmosis--Computer simulation
Format
Document (PDF)
Design and implementation of intelligent control methodologies for reverse osmosis plants
Title
Design and implementation of intelligent control methodologies for reverse osmosis plants.
Creator
Jafar, Mutaz M., Florida Atlantic University, Zilouchian, Ali, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
This dissertation presents the design, implementation and application of soft computing methodologies to Reverse Osmosis (RO) desalination technology. A novel intelligent control scheme based on the integration of Neural Network (NN) and Fuzzy Logic (FL) is presented to optimize plants' performance. In the first part of the research work, two optimal NN predictive models, based on backpropagation and Radial Basis Function Networks (RBFN), were developed for three types of RO feed intakes. The...
Show moreThis dissertation presents the design, implementation and application of soft computing methodologies to Reverse Osmosis (RO) desalination technology. A novel intelligent control scheme based on the integration of Neural Network (NN) and Fuzzy Logic (FL) is presented to optimize plants' performance. In the first part of the research work, two optimal NN predictive models, based on backpropagation and Radial Basis Function Networks (RBFN), were developed for three types of RO feed intakes. The predictive models utilized actual operating data for the three RO plants in order to predict system recovery, total dissolved solids and ion product concentration in brine stream A predictive model is proposed based on redistributed receptive fields of RBFN. The proposed algorithm utilizes integration of supervised learning of centers and unsupervised learning of output layer weights. Extensive simulations are presented to demonstrate the effectiveness of the proposed method for generalization on prediction of nonlinear input-output mappings. In the second part of the study, the design of FL control strategy for direct seawater RO system is carried out. The real-time controller design is based on integration of sensory information, predicted outputs, mathematical calculations, and expert knowledge of the process to yield a constant recovery, constant salt rejection and minimum scaling under variable operating conditions. To implement the designed methodology, a 250/800 Gallon per Day (GPD) prototype RO plant with direct Atlantic Ocean intake is constructed at FAU Gumbo Limbo research laboratory. Two types of membrane modules were used for this study: Spiral Wound (SW) and Hollow Fine Fiber (HFF). The prototype plant indeed demonstrated the effectiveness and optimum performance of the proposed design under variable operating conditions. The system achieved a constant recovery of 30% and salt passage of 1.026% while ion product concentration for six major salts were kept below their solubility limits at all time. The implementation of the proposed intelligent control methodology achieved a 4% increase in availability and a 50% reduction in manpower requirements, as well as reduction in overall chemical consumption of the plant. Therefore, it is expected that the cost of producing fresh water from seawater desalination will be decreased using the proposed intelligent control strategy.
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Date Issued
2000
PURL
http://purl.flvc.org/fcla/dt/12650
Subject Headings
Saline water conversion--Reverse osmosis process, Intelligent control systems
Format
Document (PDF)
Human powered reverse osmosis for providing portable water for developing countries
Title
Human powered reverse osmosis for providing portable water for developing countries.
Creator
Drake, Dustin, Su, Tsung-Chow
Date Issued
2012-04-06
PURL
http://purl.flvc.org/fcla/dt/3348818
Subject Headings
Drinking water --Health aspects, Water-supply, Reverse osmosis, Manually operable reverse osmosis apparatus, Developing countries, Human powered water purification
Format
Document (PDF)
Technical Feasibility of Nanofiltration Concentrate Treatment with Low Pressure Reverse Osmosis
Title
Technical Feasibility of Nanofiltration Concentrate Treatment with Low Pressure Reverse Osmosis.
Creator
Toro, Adriana M., Bloetscher, Frederick, Florida Atlantic University, College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
Abstract/Description
This study evaluated the technical feasibility o f increasing the typical water recovery of a pilot scale membrane system (85-90%) to 97% by treatment of nanofiltration concentrate with low-pressure reverse osmosis. The study used Biscayne aquifer water (freshwater), and determined that it may be technically feasible to increase the recovery up to approximately 95% when the RO flux is —10 gfd, the feed water pH is reduced to -6.1 with H2 SO4 , and antiscalant in the NF process. The tested...
Show moreThis study evaluated the technical feasibility o f increasing the typical water recovery of a pilot scale membrane system (85-90%) to 97% by treatment of nanofiltration concentrate with low-pressure reverse osmosis. The study used Biscayne aquifer water (freshwater), and determined that it may be technically feasible to increase the recovery up to approximately 95% when the RO flux is —10 gfd, the feed water pH is reduced to -6.1 with H2 SO4 , and antiscalant in the NF process. The tested membranes showed stable and similar performance under the pilot conditions. However, pilot tests were sensitive to pH variations (pH>6.2). The main barrier for increasing the water recovery was fouling caused by iron, carbonate hardness, and iron bacteria. A preliminary cost analysis showed that there is an apparent econom ic advantage when the recovery is greater than 90%. Estimated water cost at 95% recovery is $1.99 compared with $2.69 at the typical 85% recovery.
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Date Issued
2007
PURL
http://purl.flvc.org/fau/fd/FA00012564
Subject Headings
Saline water conversion--Reverse osmosis process, Water--Purification--Reverse osmosis process, Membrane separation, Membranes (Technology)
Format
Document (PDF)
Modeling of reverse osmosis plants using system identification and neural networks
Title
Modeling of reverse osmosis plants using system identification and neural networks.
Creator
Saengrung, Anucha, Florida Atlantic University, Zilouchian, Ali, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
Modeling of two reverse osmosis plants at FAU Gumbo Limbo facility and at the city of Boca Raton are investigated. System identification as well as artificial neural networks are utilized to carried out the tasks. The data for a six months operational period of both plants are utilized. The prediction error method and subspace method are utilized to estimate state-space model while the auto regression with extra input (ARX) model is estimated by using the least square method and the...
Show moreModeling of two reverse osmosis plants at FAU Gumbo Limbo facility and at the city of Boca Raton are investigated. System identification as well as artificial neural networks are utilized to carried out the tasks. The data for a six months operational period of both plants are utilized. The prediction error method and subspace method are utilized to estimate state-space model while the auto regression with extra input (ARX) model is estimated by using the least square method and the approximately optimal four-stage instrumental variable method. The training algorithms for artificial neural networks are based on backpropagation and radial basis network function (RBNF). The implementation of each methodology is performed step by step and finally, the results from both methodologies are analyzed and discussed. The results of the proposed study indicate that both system identification and neural networks algorithms can predict the outputs of both RO plants with the acceptable accuracy. Among all methodologies utilized in the thesis, the least square method for the auto regression with the extra input (ARX) model, can provide the best prediction for both RO plants.
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Date Issued
2002
PURL
http://purl.flvc.org/fcla/dt/12963
Subject Headings
Saline water conversion--Reverse osmosis process, System identification, Neural networks (Computer science)
Format
Document (PDF)
Experimental and numerical analysis of solute transport through saturated porous media
Title
Experimental and numerical analysis of solute transport through saturated porous media.
Creator
Ranganathan, Sridhar., Florida Atlantic University, Abtahi, Homayoon, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description
The problem of solute transport through saturated porous media is considered in this thesis. The end application of this study is to evaluate the option of spray irrigation as a means of disposing reverse osmosis effluent. Reverse osmosis effluent was sprayed on an experimental field composed of typical area soil. The changes in groundwater quality were monitored at intervals of ten to twenty days. Applying the experimentally obtained data to a basic numerical model, which uses the convection...
Show moreThe problem of solute transport through saturated porous media is considered in this thesis. The end application of this study is to evaluate the option of spray irrigation as a means of disposing reverse osmosis effluent. Reverse osmosis effluent was sprayed on an experimental field composed of typical area soil. The changes in groundwater quality were monitored at intervals of ten to twenty days. Applying the experimentally obtained data to a basic numerical model, which uses the convection-diffusion equation, the key parameter of the soil, D* the diffusion coefficient, is obtained for the Myakka sand. While the numerical model can predict the qualitative behavior of hardness and conductivity, hysteresis is observed for the response of the total organic carbon (TOC) content. Further studies are needed to understand and model the inherent capacitance of the soil for hardness and the observed hysteresis in TOC response.
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Date Issued
1990
PURL
http://purl.flvc.org/fcla/dt/14629
Subject Headings
Groundwater flow, Groundwater--Quality, Water--Purification--Reverse osmosis process
Format
Document (PDF)
Predicting removal efficiency of reverse osmosis membranes with respect to emerging substances of concern using a discriminant function analysis
Title
Predicting removal efficiency of reverse osmosis membranes with respect to emerging substances of concern using a discriminant function analysis.
Creator
Pleitez Herrera, Fernando J., College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
Abstract/Description
This paper presents the results of the spike tests performed in the alternative water supply pilot testing program for the City of Pembroke Pines. It establishes the effectiveness of a protocol that can be used to gain further insight on the rejection capacities of RO membranes. An in-depth study of the molecular descriptors affecting rejection by RO membranes is presented and used in the development of a discriminant function analysis. This analysis proved to be an effective way to predict...
Show moreThis paper presents the results of the spike tests performed in the alternative water supply pilot testing program for the City of Pembroke Pines. It establishes the effectiveness of a protocol that can be used to gain further insight on the rejection capacities of RO membranes. An in-depth study of the molecular descriptors affecting rejection by RO membranes is presented and used in the development of a discriminant function analysis. This analysis proved to be an effective way to predict the passage of Emerging Substances of Concern (ESOCs) through RO membrane. Further, a principal component (PC) analysis was performed to determine which factors accounted the largest variation in RO permeability. Additionally, this paper defines the groundwork for a discriminant analysis model that, if further developed, could serve as an important tool to predict the rejection capabilities of RO treatment when handling with ESOCs.
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Date Issued
2012
PURL
http://purl.flvc.org/FAU/3355869
Subject Headings
Membranes (Technology), Water, Purification, Reverse osmosis process, Industrial water supply, Water, Pollution, Chemoinformatics
Format
Document (PDF)