Numerical performance of thermal conductivity in Bioconvection flow of cross nanofluid containing swimming microorganisms over a cylinder with melting phenomenon

This study investigates the effects of melting phenomena and non-linear thermal radiation in Cross nanofluid bioconvection flow with motile microorganisms with a convective boundary over a cylinder. Brownian motion and thermophoresis diffusion are also taken into account in this mathematical model. A governing partial differential equation is used to represent the given flow phenomena. The proper dimensionless transformation is then employed to convert the PDE controlling system into an ordinary one. Bvp4c numerically solves redesigned ODE problems using a shooting strategy in the computational tool MATLAB. Figures versus velocity, temperature distribution, nanoparticle concentration, and microbe concentration profiles are used to analyze and expound on the notably involved aspects thoroughly. It has been demonstrated that increasing the estimates of a mixed convection parameter can enhance velocity. By increasing the Prandtl number, the temperature and concentration of nanoparticles decrease. A high Peclet value lowers the microorganism\u27s profile

Isotherm, kinetic and modeling studies

Funding Information: Funding: The Deanship of Scientific Research at King Khalid University General Research Project under the grant number (R.G.P.2/138/42) and Taif University researchers supporting project number (TURSP–2020/157), Taif University, Taif, Saudi Arabia. Funding Information: Acknowledgments: The co‐author Ali E. Anqi would like to extend his appreciation to the Deanship of Scientific Research at King Khalid University for the support he received through General Re‐ search Project under the grant number (R.G.P.2/138/42). This work was supported by Taif Univer‐ sity researchers supporting project number (TURSP–2020/157), Taif University, Taif, Saudi Arabia. The first author was thankful to the Directorate of Minorities, Govt. of Karnataka for providing PhD fellowship to conduct the research. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.The first-ever use of halloysite nanotube (HNT), a relatively low-cost nanomaterial abun-dantly available with minor toxicity for removing brilliant green dye from aqueous media, is re-ported. The factors affecting adsorption were studied by assessing the adsorption capacity, kinetics, and equilibrium thermodynamic properties. All the experiments were designed at a pH level of around 7. The Redlich-Peterson isotherm model fits best amongst the nine isotherm models studied. The kinetic studies data confirmed a pseudo model of the second order. Robotic investigations pro-pose a rate-controlling advance being overwhelmed by intraparticle dispersion. The adsorbent fea-tures were interpreted using infrared spectroscopy and electron microscopy. Process optimization was carried out using Response Surface Methodology (RSM) through a dual section Fractional Fac-torial Experimental Design to contemplate the impact of boundaries on the course of adsorption. The examination of fluctuation (ANOVA) was utilized to consider the joined impact of the boundaries. The possibilities of the use of dye adsorbing HNT (“sludge”) for the fabrication of the composites using plastic waste are suggested.publishersversionpublishe

A recent study on remediation of direct blue 15 dye using halloysite nanotubes

R.G.P.2/138/42 TURSP–2020/157A set of lab‐scale experiments were designed and conducted to remedy Direct Blue 15 (DB15) dye using nontoxic halloysite nanotubes (HNT) with the view to be utilized in a textile industrial effluent (TIE). The DB15 adsorbed‐HNT “sludge” was used as a reinforcing agent and plas-tic waste to fabricate the composite. To advance the knowledge and further understand the chemical phenomena associated with DB15 adsorption on HNT, different factors like pH value, adsorbate initial concentration, adsorbent dosage, and temperature on the composite were affected experi-mentally tested. To estimate the adsorption capacity of HNT, nine isotherm models were applied, and it was identified that the Brouers–Sotolongo adsorption isotherm model represented the best accuracy for predicting the adsorption behavior of the HNT. Likewise, the pseudo‐second‐order reaction was the predominant mechanism for the overall rate of the multi‐step dye adsorption pro-cess. Additionally, it was demonstrated that the mass transfer during the process is diffusion‐con-trolled, and thermodynamic assessments showed that the process is physisorption.publishersversionpublishe

Machine learning modeling for optimization of sulfur compounds separation from fuels: Process optimization for reduction of environmental pollution

Development of theoretical models for reduction of sulfur emission and also the material consumption is of great importance for petroleum refinery to obtain high-quality fuels. The latter can be done by employing advanced optimization techniques. In this study, we have developed a modeling methodology for optimization of petroleum refinery in fuel production. Some measured data have been collected for the modeling and computational optimization. Each data point is comprised of four input characteristics: reactor pressure (bar), reactor temperature (°C), initial sulfur concentration (ppm), and dose (g). Outputs for the modeling include sulfur concentration (ppm), emission (%), and HDS cost ($). For modeling, the Adaboost ensemble model is applied on top of the three fundamental models Linear Regression, Gaussian Process Regression, and Bayesian Ridge. On the available dataset, the models are tweaked using the grasshopper optimization algorithm (GOA) method, and then the optimal combination of models and parameters is selected for each output. For sulfur content and emission characteristics, the ADA-GPR model is the most accurate; however, the ADA-BRR algorithm performs the best for calculating the HDS cost. Using these models, the R2-score for outputs is 0.970, 0.950, and 0.999, respectively for sulfur concentration, emission percentage of SO2, and HDS cost

Evaluating Critical Influencing Factors of Desalination by Membrane Distillation Process—Using Multi-Criteria Decision-Making

Water desalination by membrane distillation (MD) can be affected by a wide range of operating parameters. The present work uses combinational approach of Analytical Hierarch process (AHP) and Fuzzy Analytical Hierarchy process (Fuzzy-AHP) to identify the most important parameters in the MD desalination. Five process parameters and key-performance indicators, named derivable outputs (DOs), are considered, along with the critical factors affecting these DOs in the current study. The DOs and the critical influencing factors (CIFs) are selected based on their experimental feasibility. The investigation involves five DOs, which are liquid entry pressure, thermal power consumption, permeate quality, permeate flux, and pumping (feed circulation) power. A total of twenty-five critical influencing factor were associated with the DOs. The identification of the DOs and CIFs was based on the literature review, and further analyses were performed. Both methods, AHP and Fuzzy-AHP, determined six extremely important CIFs in the desalination MD, which are feed temperature, feed concentration, or feed salinity; feed flow rate; membrane hydrophobicity; pore size; and membrane material. Moderately important CIFs are found to be four by both methods. These common CIFs are feed solution properties, membrane thickness, feed channel geometry, and pressure difference along the feed channel. Finally, the least preferred CIFs are four common in both methods that are MD configuration, duration of test, specific heat of feed solution, and viscosity

Evaluating Critical Influencing Factors of Desalination by Membrane Distillation Process—Using Multi-Criteria Decision-Making

Water desalination by membrane distillation (MD) can be affected by a wide range of operating parameters. The present work uses combinational approach of Analytical Hierarch process (AHP) and Fuzzy Analytical Hierarchy process (Fuzzy-AHP) to identify the most important parameters in the MD desalination. Five process parameters and key-performance indicators, named derivable outputs (DOs), are considered, along with the critical factors affecting these DOs in the current study. The DOs and the critical influencing factors (CIFs) are selected based on their experimental feasibility. The investigation involves five DOs, which are liquid entry pressure, thermal power consumption, permeate quality, permeate flux, and pumping (feed circulation) power. A total of twenty-five critical influencing factor were associated with the DOs. The identification of the DOs and CIFs was based on the literature review, and further analyses were performed. Both methods, AHP and Fuzzy-AHP, determined six extremely important CIFs in the desalination MD, which are feed temperature, feed concentration, or feed salinity; feed flow rate; membrane hydrophobicity; pore size; and membrane material. Moderately important CIFs are found to be four by both methods. These common CIFs are feed solution properties, membrane thickness, feed channel geometry, and pressure difference along the feed channel. Finally, the least preferred CIFs are four common in both methods that are MD configuration, duration of test, specific heat of feed solution, and viscosity

Temperature Impact on Reverse Osmosis Permeate Flux in the Remediation of Hexavalent Chromium

Reverse osmosis technique was applied in removing hexavalent chromium ions from artificial wastewater. Different operating conditions were studied to monitor the separation process using commercial Reverse Osmosis BW30XFR membrane. Different concentrations of hexavalent chromium; 5, 30, and 100 ppm were tested. Samples were subjected to incrementally increasing operating pressure; 10, 30, and 45 bar and flow rates; 2.2, 3.4, and 4.5 L/min under various temperatures; 25, 35, 45, and 55 °C. Collected permeate and concentrations were measured after each experiment using a UV spectrophotometer. Results obtained presented a higher rejection percentage at lower feed concentrations with a value up to 99.8% for 5 ppm in comparison to 94.3% for 30 ppm and 77.2% for 100 ppm concentration due to concentration polarization; however, it showed no effect of increasing operating flow rates. Moreover, the increase in feed temperature from 25 to 55 °C had positively increased permeate flux to more than 300 times. The permeate flux at 25 °C is recorded for all tested samples in the range of 30 to 158 kg/h·m2, this range has risen at 55 °C under the same conditions to the range of 70 to 226 kg/h·m2, indicating alteration within the membrane pore size due to temperature increase and high applied pressure concluding high sensitivity of polymeric membranes towards changing permeate flow rate with increasing temperatures

Temperature Impact on Reverse Osmosis Permeate Flux in the Remediation of Hexavalent Chromium

Reverse osmosis technique was applied in removing hexavalent chromium ions from artificial wastewater. Different operating conditions were studied to monitor the separation process using commercial Reverse Osmosis BW30XFR membrane. Different concentrations of hexavalent chromium; 5, 30, and 100 ppm were tested. Samples were subjected to incrementally increasing operating pressure; 10, 30, and 45 bar and flow rates; 2.2, 3.4, and 4.5 L/min under various temperatures; 25, 35, 45, and 55 °C. Collected permeate and concentrations were measured after each experiment using a UV spectrophotometer. Results obtained presented a higher rejection percentage at lower feed concentrations with a value up to 99.8% for 5 ppm in comparison to 94.3% for 30 ppm and 77.2% for 100 ppm concentration due to concentration polarization; however, it showed no effect of increasing operating flow rates. Moreover, the increase in feed temperature from 25 to 55 °C had positively increased permeate flux to more than 300 times. The permeate flux at 25 °C is recorded for all tested samples in the range of 30 to 158 kg/h·m2, this range has risen at 55 °C under the same conditions to the range of 70 to 226 kg/h·m2, indicating alteration within the membrane pore size due to temperature increase and high applied pressure concluding high sensitivity of polymeric membranes towards changing permeate flow rate with increasing temperatures

Multi-criteria/comparative analysis and multi-objective optimization of a hybrid solar/geothermal source system integrated with a carnot battery

Among the different electrical energy storage technologies, the Carnot batteries are promising options with low specific cost that do not suffer from geographical limitations and power-capacity coupling. In addition to power balancing, this approach can also be unique for multi-vector energy management. A comprehensive evaluation (thermodynamic design and exergoenvironmental and exergoeconomic evaluations), comparison, and multi-objective optimization of four Carnot battery configurations based on solar-electric energy and a geothermal source is presented. Geothermal energy can simultaneously improve the thermodynamic and environmental performances of the Carnot battery. The main structure of all configurations is based on electrical energy obtained from PV and captured thermal energy from a geothermal source. The four Brayton, heat pump, flash, and organic Rankine cycle (ORC) units are periodically integrated. The outcomes point out that the discharging process is based on an ORC unit and a flash-heat pump cycle (F-HPC)-based charging process makes more optimal heat-to-power efficiency. Moreover, the Carnot battery based on the regenerative-Brayton cycle (R-BC) unit has a higher investment cost rate compared to the ORC unit (in the discharging process). When integrating the geothermal, the third configuration (R-HPC/R-BC) experiences the greatest improvement (5.3-fold) due to the increase in thermal energy received from the geothermal source