Modeling and evaluating performance of full-scale reverse osmosis system in industrial water treatment plant

Jeong, Kwanho; Son, Moon; Yoon, Nakyung; Park, Sanghun; Shim, Jaegyu; Kim, Jihye; Lim, Jae-Lim

doi:10.1016/j.desal.2021.115289

Cited by 27 publications

(6 citation statements)

References 40 publications

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“…Additionally, simulation techniques may oversimplify certain aspects of water treatment processes or neglect important factors that can affect treatment performance. For example, simulation models may not fully account for variability in influent water quality, changes in operating conditions, or the impact of fouling and scaling on treatment efficiency (Jeong et al, 2021). As a result, the predictions generated by simulation models may not always align with real-world observations, leading to discrepancies between model results and actual performance.…”

Section: Challenges and Considerationsmentioning

confidence: 99%

Simulation-Driven Strategies for Enhancing Water Treatment Processes in Chemical Engineering: Addressing Environmental Challenges

Nwankwo Constance Obiuto,

Nwakamma Ninduwezuor-Ehiobu,

Emmanuel Chigozie Ani

et al. 2024

Eng. sci. technol. j.

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Water treatment processes in chemical engineering play a critical role in addressing environmental challenges and ensuring the sustainability of water resources. This paper examines simulation-driven strategies aimed at enhancing water treatment processes within the domain of chemical engineering. By leveraging advanced simulation techniques and methodologies, engineers can optimize the design, operation, and performance of water treatment systems, thereby mitigating environmental impacts and improving overall efficiency. The review highlights the importance of addressing environmental challenges through innovative approaches in water treatment processes. It underscores the role of simulation-driven strategies in chemical engineering to achieve sustainable solutions for water management. Through a comprehensive review of simulation techniques and case studies, this paper elucidates how simulation-driven approaches can enhance the effectiveness and sustainability of water treatment processes. Furthermore, the review emphasizes the interdisciplinary nature of this research, bridging chemical engineering principles with environmental science and technology. By integrating simulation tools with knowledge of water chemistry, fluid dynamics, and process engineering, engineers can develop robust strategies for optimizing water treatment processes while minimizing environmental footprints. Key topics covered include the application of computational fluid dynamics (CFD), process simulation software, and advanced modeling techniques in the analysis and design of water treatment systems. Case studies illustrating the successful implementation of simulation-driven strategies in various water treatment applications are presented to provide practical insights and demonstrate the potential benefits. Overall, this paper underscores the pivotal role of simulation-driven strategies in advancing water treatment processes in chemical engineering. It advocates for the adoption of innovative approaches to address environmental challenges and promote sustainability in water management practices within the oil and gas industry and other sectors reliant on chemical engineering processes. Keywords: Water treatment, Environmental Challenges, Chemical Engineering, Processes, Simulation Driven Strategies.

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Section: Challenges and Considerationsmentioning

confidence: 99%

Simulation-Driven Strategies for Enhancing Water Treatment Processes in Chemical Engineering: Addressing Environmental Challenges

Nwankwo Constance Obiuto,

Nwakamma Ninduwezuor-Ehiobu,

Emmanuel Chigozie Ani

et al. 2024

Eng. sci. technol. j.

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“…This process incorporates the use of a semipermeable membrane onto which wastewater is passed with applied pressure more than the osmotic pressure, restricting the entry of pollutants through it . Although this method is very effective for removing inorganic pollutants and various bacteria from wastewater, it is not optimum for removing small organic pollutants from water as well as the overall installation and semipermeable membrane costs are high …”

Section: Introductionmentioning

confidence: 99%

“…15 Although this method is very effective for removing inorganic pollutants and various bacteria from wastewater, it is not optimum for removing small organic pollutants from water as well as the overall installation and semipermeable membrane costs are high. 17 Flocculation/coagulation: This process entails the formation of flocs from suspended solids with or without the use of a chemical reagent; 5 negatively charged solid particles are neutralized by treating them with positively charged coagulants. This process mainly deals with oily wastewater.…”

Section: Introductionmentioning

confidence: 99%

Cyclodextrin-Based Nanosponges as an Environmentally Sustainable Solution for Water Treatment: A Review

Goyal

Amar

Gulati

et al. 2023

ACS Appl. Nano Mater.

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Over the past few decades, the disposal of various industrial pollutants such as organic dyes, heavy metal ions, pesticides, and phenolic compounds has led to the deterioration of the quality of freshwater; even with the 70% water coverage over the earth, there is meager access to freshwater sources. Against the drawbacks of conventional water purification methods such as sludge production and generation of toxic byproducts, the adsorption process is regarded as an efficient and economical strategy for the treatment of wastewater. Among various available adsorbents, cyclodextrin-based nanosponges have evolved as prominent adsorbents for treating wastewater and are considered a cost-effective option with minimal energy and time requirements. Owing to their porous nature, cone-like structure, cross-linked three-dimensional network, and special architecture of the hydrophilic and hydrophobic moieties wherein the hydrophobic core can form inclusion complexes with pollutants via host−guest interactions while hydrophilic edges interact with pollutants through hydrogen-bonding and electrostatic interactions, they are effective adsorbents for the removal of a variety of pollutants such as heavy metals, organic dyes, phenols, and pesticides. Additionally, the number of active sites in these nanosponges could be enhanced by hybridizing with other adsorbents or by functionalization with magnetic nanoparticles. This review deliberates various water purification methods and underlines the limitations of using other conventional methods over adsorption. The strategies to synthesize β-cyclodextrin-based nanosponges deploying various cross-linkers and their further modifications have been discussed in detail. Finally, the application of these nanosponges for the effective removal of assorted pollutants from wastewater highlighting the adsorption mechanism in certain cases is cogitated.

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“…Hence, the nature of the historical data influences the outcome of the generated models [20]. Other research on AI and wastewater can be found in [21][22][23][24][25][26]. Additionally, ensemble methods have been employed to improve the performance of trained single models by summing or averaging their individual outputs [27].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Hydroponic Wastewater Treatment Plant Integrated with Ensemble Learning Techniques: A Feature Selection Approach

et al. 2023

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Wastewater treatment and reuse are being regarded as the most effective strategy for combating water scarcity threats. This study examined and reported the applications of the Internet of Things (IoT) and artificial intelligence in the phytoremediation of wastewater using Salvinia molesta plants. Water quality (WQ) indicators (total dissolved solids (TDS), temperature, oxidation-reduction potential (ORP), and turbidity) of the S. molesta treatment system at a retention time of 24 h were measured using an Arduino IoT device. Finally, four machine learning tools (ML) were employed in modeling and evaluating the predicted concentration of the total dissolved solids after treatment (TDSt) of the water samples. Additionally, three nonlinear error ensemble methods were used to enhance the prediction accuracy of the TDSt models. The outcome obtained from the modeling and prediction of the TDSt depicted that the best results were observed at SVM-M1 with 0.9999, 0.0139, 1.0000, and 0.1177 for R2, MSE, R, and RMSE, respectively, at the training stage. While at the validation stage, the R2, MSE, R, and RMSE were recorded as 0.9986, 0.0356, 0.993, and 0.1887, respectively. Furthermore, the error ensemble techniques employed significantly outperformed the single models in terms of mean square error (MSE) and root mean square error (RMSE) for both training and validation, with 0.0014 and 0.0379, respectively.

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Modeling and evaluating performance of full-scale reverse osmosis system in industrial water treatment plant

Cited by 27 publications

References 40 publications

Simulation-Driven Strategies for Enhancing Water Treatment Processes in Chemical Engineering: Addressing Environmental Challenges

Simulation-Driven Strategies for Enhancing Water Treatment Processes in Chemical Engineering: Addressing Environmental Challenges

Cyclodextrin-Based Nanosponges as an Environmentally Sustainable Solution for Water Treatment: A Review

Performance Evaluation of Hydroponic Wastewater Treatment Plant Integrated with Ensemble Learning Techniques: A Feature Selection Approach

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