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With impressive thermal outcomes, the nanofluids present multidisciplinary applications in the cooling processes, thermal systems, extrusion processes, heat storage devices and many more. The aim of current research is to inspect thermal impact of Jeffrey fluid with tiny particles under the assumptions of variable thermal conductivity. The problem is supported with applications of chemical reaction, activation energy and magnetic force. For heat and mass transfer phenomenon, Cattaneo-Christov diffusion theories have been implemented. The formulated model is solved by using the homotopy analysis method (HAM) with excellent accuracy. The graphical analysis is performed with specified range of parameters like 0.2⩽H⩽0.8, 0.1⩽ϖ⩽1.7, 0.0⩽N⩽1.5, 0.0⩽Π⩽3.1, 0.3⩽γ⩽0.6, 0.6⩽Ψ⩽3.2, 0.5⩽Ω⩽2.0, 0.0⩽Σ⩽1.5, 0.2⩽Nt⩽1.7, 1.0⩽Pr⩽1.9, 0.5⩽Sc⩽1.4,0.3⩽β⩽1.5, 0.1⩽ε⩽1.0, 0.2⩽Nb⩽1.7. The assessment of flow parameters is graphically evaluated. It is observed that both velocity profiles periodically enhance for Deborah number while temperature, microorganisms and concentration distributions decelerate. The greater estimates of variable thermal conductivity and heat generation improve the temperature distribution while conflicting scenario ensures for thermic relaxation constant.

With impressive thermal outcomes, the nanofluids present multidisciplinary applications in the cooling processes, thermal systems, extrusion processes, heat storage devices and many more. The aim of current research is to inspect thermal impact of Jeffrey fluid with tiny particles under the assumptions of variable thermal conductivity. The problem is supported with applications of chemical reaction, activation energy and magnetic force. For heat and mass transfer phenomenon, Cattaneo-Christov diffusion theories have been implemented. The formulated model is solved by using the homotopy analysis method (HAM) with excellent accuracy. The graphical analysis is performed with specified range of parameters like 0.2⩽H⩽0.8, 0.1⩽ϖ⩽1.7, 0.0⩽N⩽1.5, 0.0⩽Π⩽3.1, 0.3⩽γ⩽0.6, 0.6⩽Ψ⩽3.2, 0.5⩽Ω⩽2.0, 0.0⩽Σ⩽1.5, 0.2⩽Nt⩽1.7, 1.0⩽Pr⩽1.9, 0.5⩽Sc⩽1.4,0.3⩽β⩽1.5, 0.1⩽ε⩽1.0, 0.2⩽Nb⩽1.7. The assessment of flow parameters is graphically evaluated. It is observed that both velocity profiles periodically enhance for Deborah number while temperature, microorganisms and concentration distributions decelerate. The greater estimates of variable thermal conductivity and heat generation improve the temperature distribution while conflicting scenario ensures for thermic relaxation constant.

The problem of freshwater shortage is increasing a day after day. Solar distillers are suitable devices to overcome this problem for remote areas and small families. However, these devices suffer from their low productivities. Here, two different modified designs for the distillers of rotating wick types were tested. One distiller contained a rotating wick belt with a path of “L” character shape (l-RWSS), and the other with a path of “LC” shape (LC-RWSS). In addition, the wick type was investigated for black jute and cotton wicks. Moreover, the effect of belt-rotation direction (clockwise and counterclockwise) on the still performance has been studied. The period of wick belt rotation was tested (ON = 5 min and OFF = zero, 10, 20, 30, 40, 50, and 60 min). Also, the impact of using graphene quantum dots nanofluid on the distiller performance was investigated. Experimental results obtained that the jute wick obtained more distillate than the cotton cloth. Furthermore, the productivity of LC-RWSS with counterclockwise movement of wick belt was always larger than that with clockwise direction under all different OFF times. Also, the LC-RWSS (jute wick-counterclockwise-0.1 rpm) increased the freshwater productivity by about 17 % over l-RWSS. Besides, the LC-RWSS provided higher accumulated daily productivity than l-RWSS by 19 % and 17 % with and without nanofluid, respectively. Also, the cost of freshwater obtained is 0.018 and 0.021 $/L for LC-RWSS with and without nanofluids, respectively.

The problem of freshwater shortage is increasing a day after day. Solar distillers are suitable devices to overcome this problem for remote areas and small families. However, these devices suffer from their low productivities. Here, two different modified designs for the distillers of rotating wick types were tested. One distiller contained a rotating wick belt with a path of “L” character shape (l-RWSS), and the other with a path of “LC” shape (LC-RWSS). In addition, the wick type was investigated for black jute and cotton wicks. Moreover, the effect of belt-rotation direction (clockwise and counterclockwise) on the still performance has been studied. The period of wick belt rotation was tested (ON = 5 min and OFF = zero, 10, 20, 30, 40, 50, and 60 min). Also, the impact of using graphene quantum dots nanofluid on the distiller performance was investigated. Experimental results obtained that the jute wick obtained more distillate than the cotton cloth. Furthermore, the productivity of LC-RWSS with counterclockwise movement of wick belt was always larger than that with clockwise direction under all different OFF times. Also, the LC-RWSS (jute wick-counterclockwise-0.1 rpm) increased the freshwater productivity by about 17 % over l-RWSS. Besides, the LC-RWSS provided higher accumulated daily productivity than l-RWSS by 19 % and 17 % with and without nanofluid, respectively. Also, the cost of freshwater obtained is 0.018 and 0.021 $/L for LC-RWSS with and without nanofluids, respectively.

Abstract Many architectural systems are modelled by boundary value problems. Though there are many numerical and analytical methods to solve such problems, this paper suggests a simple but effective way to the third-order ordinary differential equations by the Taylor series technology. The governing equation is differentiated to obtain high order derivatives of a certain point, and solution is expanded into a Taylor series of the point, the boundary conditions are then used to identify the unknowns involved in the approximate solution. An example is given to elucidate the solution process, the maximal error is less 2%, and its accuracy can be further improved if a higher order series is solved. The approximate solution is compared with that by the variational iteration method, showing the present method is simpler and more straightforward. The comparison with the numerical solution culminates in its reliability and effectiveness. The method can be extended to fractal calculus.

Abstract Many architectural systems are modelled by boundary value problems. Though there are many numerical and analytical methods to solve such problems, this paper suggests a simple but effective way to the third-order ordinary differential equations by the Taylor series technology. The governing equation is differentiated to obtain high order derivatives of a certain point, and solution is expanded into a Taylor series of the point, the boundary conditions are then used to identify the unknowns involved in the approximate solution. An example is given to elucidate the solution process, the maximal error is less 2%, and its accuracy can be further improved if a higher order series is solved. The approximate solution is compared with that by the variational iteration method, showing the present method is simpler and more straightforward. The comparison with the numerical solution culminates in its reliability and effectiveness. The method can be extended to fractal calculus.

This paper presents an implementation of the stochastic fractal search (SFS) algorithm to solve the distribution network reconfiguration (DNR) problem in the presence of distributed generations (DGs). The SFS is a meta-heuristic algorithm inspired by the fractal theory for solving optimization problems. For dealing with the formulated DNR problem, the loss sensitivity factor (LSF) was first used to determine the optimal location of DGs and SFS was then applied to find the best size of DGs and configuration of the network. The proposed SFS algorithm was tested on 33-bus, 69-bus, 84-bus, 119-bus, and 136-bus distribution networks with seven different scenarios. The results obtained from SFS were compared to those from other methods in the literature and the result comparison has showed that SFS obtained better solutions than other methods. Therefore, SFS can be a very favorable method for solving the reconfiguration problem considering the participation of DGs in distribution networks.

This paper presents an implementation of the stochastic fractal search (SFS) algorithm to solve the distribution network reconfiguration (DNR) problem in the presence of distributed generations (DGs). The SFS is a meta-heuristic algorithm inspired by the fractal theory for solving optimization problems. For dealing with the formulated DNR problem, the loss sensitivity factor (LSF) was first used to determine the optimal location of DGs and SFS was then applied to find the best size of DGs and configuration of the network. The proposed SFS algorithm was tested on 33-bus, 69-bus, 84-bus, 119-bus, and 136-bus distribution networks with seven different scenarios. The results obtained from SFS were compared to those from other methods in the literature and the result comparison has showed that SFS obtained better solutions than other methods. Therefore, SFS can be a very favorable method for solving the reconfiguration problem considering the participation of DGs in distribution networks.