Reverse Osmosis Process Control

Optimizing reverse osmosis water desalination systems using machine learning to reduce operating costs and improve performance by predicting when to clean the membranes. The system measures parameters like feed pressure, flow, salinity, temperature, etc. and uses a trained ML model to determine fouling levels and optimize flow rates through the stages. This allows reducing energy use while maintaining permeate production. By predicting when fouling will inflect and decline, cleaning can be timed to minimize energy vs waiting for a 10% flux drop. The ML model also balances flow across stages for energy savings.

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ABSTRACT This article presents a model-predictive controller (MPC) for the maximization of energy efficiency closed-circuit desalination reverse osmosis (CCRO) system. CCRO is process producing drinking water that based on cyclic operation with following two phases: (a) filtration and (b) drain. In this article, we test model predictive control optimal process. The most important features our approach are as follows: selection structure enables reliable forecasts phase (up to 3 h), an on-line calibration strategy ensures forecast reliability, (c) satisfaction equipment safety operational constraints selected setpoints. We challenge through deliberate introduction changes in unmeasured feed concentration applied constraints. Our results indicate frequent parameter updates critical maintain reliability MPC purposes. addition, illustrate identifiability not guaranteed variation flow rates necessary even though never operates steady state. Finally, can compute rate setpoints maximize while satisfying applicable

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Reverse osmosis system with optimized energy consumption for water treatment applications like desalination or wastewater reclamation. The system uses a chain of membrane units connected in sequence. Each membrane unit has an inlet, outlet, and concentrate outlet. The concentrate outlet of a unit feeds into the inlet of the next unit. The final unit's concentrate outlet connects to a hydraulic motor. This motor is connected to an electric generator. The generator can drive a pump upstream of a membrane unit to boost feed pressure. This recycles concentrate energy to drive the system. It eliminates wasteful high-pressure feed pumps. The motor can be variable frequency to adapt to changing conditions. Sensors on the axial piston machines monitor flow and pressure.

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Water treatment method and apparatus to prevent biofouling of reverse osmosis (RO) membranes without harming the membranes. The method involves intermittently adding biocides to the water feed to the RO membrane. The biocide dose and frequency are adjusted based on membrane fouling levels. This prevents excessive biocide concentrations that can harm the membrane. The biocide addition is tuned to keep oxidation potential below a threshold without exceeding it. This prevents biocide-induced membrane fouling while still providing adequate biocide dosing to prevent organic growth.

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Access to clean and potable water is a growing global concern, particularly in coastal arid regions where freshwater sources are scarce. Traditional desalination tech- niques, such as thermal distillation conventional reverse osmosis, rely heavily on fossil fuel-based energy sources, leading high operational costs significant environmental impacts, including greenhouse gas emissions. Additionally, these systems often require complex infrastructure, making them inaccessible remote off-grid communities. To address challenges, this research presents novel solar-powered machine that integrates Reverse Osmosis (RO) Ultraviolet (UV) purification technologies. The proposed system harnesses solar power high-pressure pumps, eliminating dependency non-renewable sources. RO unit effectively removes dissolved salts contaminants, while the UV stage ensures microbial disinfection, delivering high-quality drinking water. By utilizing renewable energy, significantly reduces minimizes carbon emissions, mak- ing it an environmentally sustainable economically viable solution. impact of extends enhancin... Read More

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Osmotic membrane separation system with feed and draw recirculation loops in each module to improve efficiency and prevent fouling. The system has a series of osmosis modules where feed and draw solutions are circulated co-currently through each module. Feed recirculation loops connect feed inlet to outlet of each module. Draw recirculation loops connect draw inlet to outlet. This allows controlled flow rates, solute concentrations, and hydrostatic pressures in each loop. The bulk feed and draw streams flow counter-currently through the system as a whole. The recirculation loops prevent boundary layer buildup and fouling. They also allow mixing of partially concentrated streams to reduce driving force and enhance membrane efficiency.

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Pure water production system with optimized water quality and energy efficiency when flow rate varies. The system has sensors to detect effective membrane pressure in the reverse osmosis section. Based on the sensor readings, it adjusts the number of parallel membranes treating the water. This allows maintaining stable membrane performance and water quality as flow rate changes, preventing deterioration. By dynamically matching membrane capacity to flow, it can save pump energy compared to fixed membrane systems.

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Automatic flow control for membrane water purification systems to optimize water production and membrane life while reducing waste. The method involves using a controller to dynamically adjust the diaphragm valve opening based on parameters like membrane performance, pump pressure, and water quality. This ensures the right balance of purified water flow and wastewater flow without manual intervention. The controller calculates an optimal ratio of wastewater to purified water to prevent excessive waste or membrane fouling. It also monitors factors like membrane temperature and pressure to detect fouling conditions and flush the membrane.

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A support system for optimizing water treatment processes using membrane filtration. The system uses machine learning to analyze water quality, filtration conditions, and membrane performance data to determine optimal permeation flux, cleaning frequencies, and cleaning conditions for the membrane filtration device. This provides recommendations to the water treatment operator on how to optimize their processes for better water treatment efficiency and membrane longevity.

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A system to adjust the flow rate of water coming out of a water purifier. It uses sensors to measure the inlet water temperature, pressure, and flow, and then adjusts the output pressure and/or flow of the water pump in the purifier. This allows correcting the water output to meet requirements for membranes like reverse osmosis. It solves the issue that existing water purifiers cannot adjust pump performance to match membrane needs. The system can also have buttons to change flow rates.

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Operating a water filtration system using a membrane module to identify clogged areas and clean them efficiently. The method involves monitoring pressure drops during filtration, backwashing, and water discharge. By comparing changes in these resistance values, it can determine if clogging is worse in certain areas. If so, it performs targeted cleaning like air washing, longer discharge time, or pressurized discharge. The idea is to proactively identify and address localized fouling without wasting water by blindly cleaning the whole module.

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Monitoring and optimizing the performance of membrane filters in filtration systems by continuously measuring the flow rate of permeate fluid and comparing it to a predefined flux rate. If the measured flux falls below the threshold, the system switches to a flux tolerant mode that allows higher fouling and lower filtration efficiency. This prevents unnecessary filter replacements when flux degradation is minor. The system also determines a normalized water permeability value based on the flux measurements to further assess filter health.

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A reverse osmosis water purification system with dynamic parameter adjustment to improve efficiency and stability compared to fixed settings. The system uses a control unit to monitor the operating conditions of the reverse osmosis device and adjust parameters like pump speeds, feedwater flow, and flushing frequency based on real-time data. This allows optimizing performance as components wear and conditions change over time. The control unit also provides warnings and alarms based on critical parameters like water levels.

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Reverse osmosis system with adjustable drain flow control based on feed water TDS. A self-regulating valve restricts concentrate flow to the drain in response to the feed water TDS level. A TDS sensor measures the concentration before the RO filter. The valve receives TDS signals and adjusts the drain flow accordingly. This allows optimized drain flow for varying feed water quality.

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A reverse osmosis water filtration system that automatically regulates the flow of concentrated wastewater based on the incoming raw water TDS level. The system has an adjustable valve that controls the flow of wastewater to drain. A TDS sensor measures the incoming raw water TDS and sends a signal to the valve. The valve adjusts the wastewater flow based on the TDS level to optimize membrane performance and extend membrane life for varying raw water qualities.

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Stable and energy-saving reverse osmosis system that adjusts recovery rate based on feed water quality to improve system stability and efficiency. The system has a control system that monitors feed water quality and adjusts the recovery rate of the reverse osmosis membrane group to maintain target concentrations in the permeate and concentrated streams. This prevents scaling, fouling, or waste due to fluctuating feed water quality. The control system uses sensors like conductivity, hardness, and SiO2 meters to measure feed water quality.

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A dynamic control system for reverse osmosis membrane fouling based on real-time monitoring of operating conditions. The system uses sensors on the inlet and outlet pipes of each membrane group to monitor parameters like pressure, conductivity, and flow rate. These signals are fed back to a control system to determine the best cleaning time for each membrane based on flux and transmembrane pressure differences. This allows targeted cleaning of fouled membranes instead of full system shutdowns.

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A method and device for maintaining constant water flow rate from a water purifier like a reverse osmosis system. It involves monitoring the inlet temperature and flow of the reverse osmosis filter element, and then controlling a heater and pump to maintain the inlet conditions within a range. This ensures a consistent outlet flow rate from the filter element.

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Optimizing reverse osmosis water treatment systems for higher recovery rates and longer operating cycles by using parallel connected membrane sections and valves to dynamically switch between single-stage and two-stage operation based on performance metrics like flow, pressure, and salt rejection. This allows flexible configuration to maintain optimal system efficiency and prevent fouling.

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An apparatus and method for controlling a reverse osmosis seawater desalination plant to optimize chemical dosing during pretreatment without impacting downstream filtration performance. The method involves monitoring turbidity, iron, and pressure increases in the ultrafiltration and reverse osmosis stages. If turbidity exceeds a threshold, chemical dosing is adjusted to lower it. If ultrafiltration or reverse osmosis pressure increases exceed limits, chemical dosing is adjusted to prevent excessive pressure rises. This coordinated chemical dosing optimization ensures downstream filtration performance while maintaining upstream turbidity control.

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