Modelling and experimental validation of osmotic driven energy efficient process for tea solution concentration

Bardhan, Ananya; Subbiah, Senthilmurugan; Mohanty, Kaustubha

doi:10.1016/j.eti.2020.101065

Cited by 12 publications

(9 citation statements)

References 31 publications

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“…The performance of the developed models was evaluated using frequently used statistical indices, including the coefficient of determination (R 2 ), root-mean-square error (RMSE), mean absolute error (MAE), relative squared error (RSE), relative root-mean-square error (RRMSE), Nash–Sutcliffe efficiency (NSE), and performance index (ρ), in accordance with previous literature [ 41 , 42 , 43 ].…”

Section: Methodsmentioning

confidence: 99%

Investigating the Bond Strength of FRP Laminates with Concrete Using LIGHT GBM and SHAPASH Analysis

et al. 2022

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The corrosion of steel reinforcement necessitates regular maintenance and repair of a variety of reinforced concrete structures. Retrofitting of beams, joints, columns, and slabs frequently involves the use of fiber-reinforced polymer (FRP) laminates. In order to develop simple prediction models for calculating the interfacial bond strength (IBS) of FRP laminates on a concrete prism containing grooves, this research evaluated the nonlinear capabilities of three ensemble methods—namely, random forest (RF) regression, extreme gradient boosting (XGBoost), and Light Gradient Boosting Machine (LIGHT GBM) models—based on machine learning (ML). In the present study, the IBS was the desired variable, while the model comprised five input parameters: elastic modulus x thickness of FRP (EfTf), width of FRP plate (bf), concrete compressive strength (fc′), width of groove (bg), and depth of groove (hg). The optimal parameters for each ensemble model were selected based on trial-and-error methods. The aforementioned models were trained on 70% of the entire dataset, while the remaining data (i.e., 30%) were used for the validation of the developed models. The evaluation was conducted on the basis of reliable accuracy indices. The minimum value of correlation of determination (R2 = 0.82) was observed for the testing data of the RF regression model. In contrast, the highest (R2 = 0.942) was obtained for LIGHT GBM for the training data. Overall, the three models showed robust performance in terms of correlation and error evaluation; however, the trend of accuracy was obtained as follows: LIGHT GBM > XGBoost > RF regression. Owing to the superior performance of LIGHT GBM, it may be considered a reliable ML prediction technique for computing the bond strength of FRP laminates and concrete prisms. The performance of the models was further supplemented by comparing the slopes of regression lines between the observed and predicted values, along with error analysis (i.e., mean absolute error (MAE), and root-mean-square error (RMSE)), predicted-to-experimental ratio, and Taylor diagrams. Moreover, the SHAPASH analysis revealed that the elastic modulus x thickness of FRP and width of FRP plate are the factors most responsible for IBS in FRP.

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Section: Methodsmentioning

confidence: 99%

Investigating the Bond Strength of FRP Laminates with Concrete Using LIGHT GBM and SHAPASH Analysis

et al. 2022

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“…The same was experimentally confirmed by conducting HPLC and FTIR analysis for the DS after each batch of experiments as reported in the authors' previous study. 21 The osmotic pressure plays a significant role in determining the overall FO performance. Therefore, the determination of appropriate osmotic pressure is crucial.…”

Section: Modeling Of the Forward Osmosis Processmentioning

confidence: 99%

“…The detailed HFFO membrane specifications are mentioned in the authors' previously reported work. 21 3.2. Feed Solution.…”

Section: Membranesmentioning

confidence: 99%

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Modeling and Experimental Validation for the Preparation of Concentrated Tea Extract Using a Forward Osmosis Process Using a Food-Grade Inorganic Draw Solute

Bardhan

Subbiah

Mohanty

2023

Ind. Eng. Chem. Res.

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In this study, a one-dimensional mathematical model was developed for the concentration of tea extract using a forward osmosis (FO) process. The membrane transport parameters were estimated by minimizing the error between the model output and the experimental results. The model equations were solved to predict the FO performance within allowable error limits. Further, a series of process flow sheet simulation studies were performed to investigate the effect of different operating conditions on the overall FO performance. Based on the simulation results, a multicriteria optimization was developed to attain the maximum permeate and minimum specific reverse solute flux (SRSF). Using the best-performing process flow sheet model, the feasibility of seawater and high-concentration reject brine as a draw solution was also investigated for the concentration of tea extract. The high-concentration reject brine (105.17 g L–1) can result in rapid dewatering with minimal SRSF (0.14 g L–1) along with simultaneous seawater dilution (81.38 g L–1).

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“…23 Bardhan et al demonstrated that the aquaporin incorporated commercial hollow fiber membranes demonstrated enhanced water transport during the concentration of tea leaf extract and hindered the passage of ionic species (reducing the RSF). 29 Apart from the concentration of juices or compounds from fruits/vegetables, FO can also be employed in other liquid food processing, such as dewatering liquid egg white 29 and beer de-alcoholization. 31,32…”

Section: Applications Of Forward Osmosismentioning

confidence: 99%

Engineered osmosis – sustainable technology for water recovery, product concentration and energy generation

Kaleekkal

Nambikkattu

Satheesh

et al. 2022

Environ. Sci.: Water Res. Technol.

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Modelling and experimental validation of osmotic driven energy efficient process for tea solution concentration

Cited by 12 publications

References 31 publications

Investigating the Bond Strength of FRP Laminates with Concrete Using LIGHT GBM and SHAPASH Analysis

Investigating the Bond Strength of FRP Laminates with Concrete Using LIGHT GBM and SHAPASH Analysis

Modeling and Experimental Validation for the Preparation of Concentrated Tea Extract Using a Forward Osmosis Process Using a Food-Grade Inorganic Draw Solute

Engineered osmosis – sustainable technology for water recovery, product concentration and energy generation

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