Data-driven models of steady state and transient operations of spiral-wound RO plant

Pascual, Xavier; Gu, Hanyang; Bartman, Alex R.; Zhu, Aihua; Rahardianto, Anditya; Giralt, Jaume; Ralló, Robert; Christofides, Panagiotis D.; Cohen, Yoram

doi:10.1016/j.desal.2013.02.006

Cited by 20 publications

(14 citation statements)

References 29 publications

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“…It has been shown that irreversible resistance arises in the short and initial period of the process. The efficiency is determined by reversible resistance, confirmed by the literature [ 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 ]. The values of individual resistances are much higher, relating to the values in other membrane processes.…”

Section: Resultssupporting

confidence: 65%

“…The values of individual resistances are much higher, relating to the values in other membrane processes. It is related to the more significant pressure difference occurring on both sides of the membrane, which is characteristic of this process [ 6 , 9 , 13 , 26 , 27 , 32 ]. Based on the research, it was found that the value of irreversible resistance increases over time and is much greater than the reversible resistance.…”

Section: Resultsmentioning

confidence: 99%

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Model of Hydraulic Resistance When Forecasting Reverse Osmosis in Water Treatment

Piekutin

Kotowska

2021

Membranes

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The article presents research on the treatment of infiltration water with increased ammonium ion and nitrate(V) content through reverse osmosis. Then, research was conducted on the phenomena related to the decrease in the permeability of the membrane used for the research. The search for an appropriate interpretation of the phenomena was carried out using mathematical modeling. Based on the assumptions of the hydraulic model of the filtration resistance, calculations were made to forecast the efficiency of the osmotic membrane used in the discussed process. For this purpose, the following indicators were determined experimentally for the membrane: change in the volumetric flow of treated wastewater during low-pressure filtration, total hydraulic resistance, and component resistances, i.e., the resistance of the “new” membrane and resistances resulting from the reversible and irreversible fouling phenomena. It has been observed that irreversible resistance arises in the short and early stages of the process. The efficiency is determined by reversible resistance, which is confirmed by the literature.

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Section: Resultssupporting

confidence: 65%

Section: Resultsmentioning

confidence: 99%

Model of Hydraulic Resistance When Forecasting Reverse Osmosis in Water Treatment

Piekutin

Kotowska

2021

Membranes

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“…Instead, for the lowest filtration duration (20 min), all the conditions tested for the concentration of 97 mgNPs L −1 are viable as well as the two lowest pressure for the concentration of 251 mgNPs L −1 . Moreover, simulation of dead-end filtration mode indicated that only one suspension (97 mgNPs L −1 ) presents noticed characteristics about the filtration duration for TMP between 0.2 to 0.4 bar, and this respecting filtration times mentioned in the literature (20-60 min) (Cordier et al, 2018;Payant, 2016). Overall, results of this study clearly indicate that dead-end filtration is not suitable for CMP effluents whose concentration exceeds 100 mgNPs L −1 .…”

Section: Dead-end Model Simulationmentioning

confidence: 64%

“…However, the BW duration can influence the number of filtration cycles, as already observed by Akhondi et al (2014), who indicated that the net permeate volume increases to a maximum value with increasing the BW duration up to 2 min. Finally, Payant (2016) and Cordier et al (2018) mentioned that UF membranes are frequently physically washed every 20-60 min with a BW duration of 1-2 min. It is also mentioned that after each filtration/backwash cycle the membrane does not recover 100% of its initial permeability, but rather 90-97% (Payant, 2016;Remize et al, 2010), due to the irreversible fouling.…”

Section: Uf Units Modellingmentioning

confidence: 99%

“…Finally, Payant (2016) and Cordier et al (2018) mentioned that UF membranes are frequently physically washed every 20-60 min with a BW duration of 1-2 min. It is also mentioned that after each filtration/backwash cycle the membrane does not recover 100% of its initial permeability, but rather 90-97% (Payant, 2016;Remize et al, 2010), due to the irreversible fouling. Remize et al (2010) showed 97% of membrane permeability recovery under 2 bar of TMP during 20-40 s of BW duration.…”

Section: Uf Units Modellingmentioning

confidence: 99%

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Dead-end and crossflow ultrafiltration process modelling: Application on chemical mechanical polishing wastewaters

Ohanessian

Monnot

Moulin

et al. 2020

Chemical Engineering Research and Design

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Optimal operation of reverse osmosis desalination process with deep reinforcement learning methods

Golabi,

Erradi,

Qiblawey

et al. 2024

Appl Intell

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The reverse osmosis (RO) process is a well-established desalination technology, wherein energy-efficient techniques and advanced process control methods significantly reduce production costs. This study proposes an optimal real-time management method to minimize the total daily operation cost of an RO desalination plant, integrating a storage tank system to meet varying daily freshwater demand. Utilizing the dynamic model of the RO process, a cascade structure with two reinforcement learning (RL) agents, namely the deep deterministic policy gradient (DDPG) and deep Q-Network (DQN), is developed to optimize the operation of the RO plant. The DDPG agent, manipulating the high-pressure pump, controls the permeate flow rate to track a reference setpoint value. Simultaneously, the DQN agent selects the optimal setpoint value and communicates it to the DDPG controller to minimize the plant’s operation cost. Monitoring storage tanks, permeate flow rates, and water demand enables the DQN agent to determine the required amount of permeate water, optimizing water quality and energy consumption. Additionally, the DQN agent monitors the storage tank’s water level to prevent overflow or underflow of permeate water. Simulation results demonstrate the effectiveness and practicality of the designed RL agents.

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Data-driven models of steady state and transient operations of spiral-wound RO plant

Cited by 20 publications

References 29 publications

Model of Hydraulic Resistance When Forecasting Reverse Osmosis in Water Treatment

Model of Hydraulic Resistance When Forecasting Reverse Osmosis in Water Treatment

Dead-end and crossflow ultrafiltration process modelling: Application on chemical mechanical polishing wastewaters

Optimal operation of reverse osmosis desalination process with deep reinforcement learning methods

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