A comprehensive mathematical structuring of magnetically effected Sutterby fluid flow immersed in dually stratified medium under boundary layer approximations over a linearly stretched surface

Bilal, S.; Shah, Imtiaz Ali; Akgül, Ali; Tekin, Merve Taştan; Botmart, Thongchai; Yousef, El Sayed; Yahia, I.S.

doi:10.1016/j.aej.2022.05.044

Cited by 50 publications

(11 citation statements)

References 31 publications

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“…Different researchers have tried different numerical and mathematical algorithm to model the system from input-output data where process phenomenology is not known. Alternative route of numerical analysis currently emerging is artificial intelligence (AI)-based modeling technique [7,23,28,33,42]. In this scenario, an artificial intelligence-based data-driven modeling technique can be a feasible alternative where process phenomenology is not required.…”

Section: Graphical Abstract 1 Backgroundmentioning

confidence: 99%

“…Inoculum size was varied from 2 to 10%, and it is observed that the removal of Cr(VI) monotonically increases with inoculum size. Kinetic study was performed with respect to the initial concentration (10-25 mg/L), pH (7)(8)(9)(10)(11), and inoculum size (2-10%). In all the cases of kinetic study, it is seen that removal of Cr(VI) increases with time.…”

Section: Generation Of Explainable Model Equationsmentioning

confidence: 99%

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Application of multi-gene genetic programming technique for modeling and optimization of phycoremediation of Cr(VI) from wastewater

Sarkar

Sen

Dutta

et al. 2023

Beni-Suef Univ J Basic Appl Sci

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Background Removal of Cr(VI) from wastewater is essential as it is potentially toxic and carcinogenic in nature. Bioremediation of heavy metals using microalgae is a novel technique and has several advantages such as microalgae remove metals in an environmentally friendly and economic manner. The present study deals with modeling and optimization of the phycoremediation of Cr(VI) from synthetic wastewater. The initial concentration of Cr(VI), initial pH, and inoculum size were considered as input factors, and the percentage removal of Cr(VI) was chosen as a response. Results An accurate data-driven genetic programming model was developed with the experimental data of other scientists to find a relation between the percentage removal of Cr(VI) and all input parameters. To maximize the removal of Cr(VI), the grey wolf optimization technique was applied to determine the optimal values of input parameters. Conclusion These optimum input parameters are difficult to get through experimentation using the trial-and-error method. The established modelling and optimization technique is generic and can be applied to any other experimental study. Graphical Abstract

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Section: Graphical Abstract 1 Backgroundmentioning

confidence: 99%

Section: Generation Of Explainable Model Equationsmentioning

confidence: 99%

Application of multi-gene genetic programming technique for modeling and optimization of phycoremediation of Cr(VI) from wastewater

Sarkar

Sen

Dutta

et al. 2023

Beni-Suef Univ J Basic Appl Sci

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“…Simulations of tangentially‐hyperbolic nanofluids reveal a recent development in the efficiency of mass‐ and heat‐transmitting fluids in boundary‐layer flows. Different NNF model were discussed by [1–4]. Abbas et al.…”

Section: Introductionmentioning

confidence: 99%

Second law analysis in Darcy‐Forchheimer flow of tangent hyperbolic nanofluid in the presence of gyrotactic microorganisms

et al. 2023

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This article investigates the creation of entropy and the thermal transport of fluids during hyperbolic tangent flow with Darcy-Forchheimer flow over a stretching surface. Because of the role of shear-thinning that the hyperbolic tangent fluid displays, the mechanics of the fluid are described with the assistance of a connected system of differential models that are constructed from a partial differential equation. The bvp4c routine, a three-stage Lobatto-IIIA method numerical analysis is utilized in the study. The effects of varying values of dimensionless parameters including Forchheimer number, inertia parameter, thermal radiation, Brownian motion, Prandtl number, Scimdth number, chemical reaction, Peclet number an Bioconvection Lewis number are simulated numerically. In addition, to this, the numerical values of the skin friction coefficient, the local Nusselt and Sherwood number and motile density are shown in the form of graphs and tables respectively. It has been discovered that increasing the value of the Fr and 𝛾 results in an upsurging velocity profile while a reverse trend is noted for the unsteady parameter. In addition to this, higher values of the radiation parameter Rd cause the operating fluid to be subjected to a greater quantity of heat, which results in an associated increase in the temperature profile.

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“…[7][8][9][10][11][12][13][14] A powerful and effective tool for describing physical systems with long-term memory is such an operator. [15][16][17] Moreover, the source of fractional differential equations can be traced to power-type, non-local interacting systems with power-law memory when modeling complicated dynamic systems. [18][19][20][21] As a result of their numerous real-world applications, fractional differential equations (FDEs) are becoming increasingly important.…”

Section: Introductionmentioning

confidence: 99%

“…A powerful and effective tool for describing physical systems with long‐term memory is such an operator 15‐17 . Moreover, the source of fractional differential equations can be traced to power‐type, non‐local interacting systems with power‐law memory when modeling complicated dynamic systems 18‐21 .…”

Section: Introductionmentioning

confidence: 99%

A highly accurate artificial neural networks scheme for solving higher multi‐order fractal‐fractional differential equations based on generalized Caputo derivative

Shloof

Ahmadian

Senu

et al. 2023

Numerical Meth Engineering

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Artificial neural networks have great potential for learning and stability in the face of tiny input data changes. As a result, artificial intelligence techniques and modeling tools have a growing variety of applications. To estimate a solution for fractal‐fractional differential equations (FFDEs) of high‐order linear (HOL) with variable coefficients, an iterative methodology based on a mix of a power series method and a neural network approach was applied in this study. In the algorithm's equation, an appropriate truncated series of the solution functions was replaced. To tackle the issue, this study uses a series expansion of an unidentified function, where this function is approximated using a neural architecture. Some examples were presented to illustrate the efficiency and usefulness of this technique to prove the concept's applicability. The proposed methodology was found to be very accurate when compared to other available traditional procedures. To determine the approximate solution to FFDEs‐HOL, the suggested technique is simple, highly efficient, and resilient.

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A comprehensive mathematical structuring of magnetically effected Sutterby fluid flow immersed in dually stratified medium under boundary layer approximations over a linearly stretched surface

Cited by 50 publications

References 31 publications

Application of multi-gene genetic programming technique for modeling and optimization of phycoremediation of Cr(VI) from wastewater

Application of multi-gene genetic programming technique for modeling and optimization of phycoremediation of Cr(VI) from wastewater

Second law analysis in Darcy‐Forchheimer flow of tangent hyperbolic nanofluid in the presence of gyrotactic microorganisms

A highly accurate artificial neural networks scheme for solving higher multi‐order fractal‐fractional differential equations based on generalized Caputo derivative

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