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The purpose of this paper is to reduce the destructive effects of existing unavoidable noises contaminating temperature data in inverse heat conduction problems (IHCP) utilizing the wavelets.

For noise reduction, sensor data were treated as input to the filter bank used for signal decomposition and implementation of discrete wavelet transform. This is followed by the application of wavelet denoising algorithm that is applied on the wavelet coefficients of signal components at different resolution levels. Both noisy and de‐noised measurement temperatures are then used as input data to a numerical experiment of IHCP. The inverse problem deals with an estimation of unknown surface heat flux in a 2D slab and is solved by the variable metric method.

Comparison of estimated heat fluxes obtained using denoised data with those using original sensor data indicates that noise reduction by wavelet has a potential to be a powerful tool for improvement of IHCP results.

Noise reduction using wavelets, while it can be implemented very easily, may also significantly relegate (or even eliminate) conventional regularization schemes commonly used in IHCP.

The paper aims to apply Buckingham Pi dimensional analysis method for assessing direct evaporative cooler performance with a cooling pad made of banana midrib and ramie fiber. The saturation efficiency acted as the indicator performance of the evaporative cooler.

The paper describes an experimental study of the direct evaporative cooler with a cooling pad made of banana midrib and rami fiber. There were six parameters in the experiment: absorbed water as a dependent variable was affected by independent parameters such as air velocity and temperature, cooling pad cross-section area and thickness. Based on these variables, we arranged three dimensionless numbers and their correlation.

The paper provides three calculated dimensionless numbers plotted on a curve with a specific correlation. The curve trends for 30 mm and 50 mm pad thickness were almost similar. The range of Reynolds number for 10 mm pad was narrower than other pad thicknesses. The thicker the cooling pad, the more extensive was the calculated Reynolds number range. A new curve exhibited the relationship between the evaporation rate with the μA/t number. The broader cooling pad cross-section, the thinner pad thickness, and the lower pad temperature were factors that increased the evaporation rate, even though the increase was less significant.

A new material in cooling pad from banana midrib fiber was tested and compared to ramie fiber and conventional cooling pad.

The purpose of this paper is to investigate the hydromagnetic third-grade non-Newtonian fluid flow and heat transfer between two coaxial pipes with a variable radius ratio.

To solve the approximate nonlinear and linear problems with variable coefficients, a trial function was applied. Methods include collocation, least square and Galerkin that can be applied for obtaining these coefficients.

It is revealed that an increase of the non-Newtonian parameter, Hartmann number, and radius ratio leads to an augmentation of the absolute value of the dimensionless velocity, temperature, velocity gradient, and temperature gradient of about 10-60%. Further, the augmentation of Bi₁ reduces the absolute value of the dimensionless temperature profile and dimensionless temperature gradient about three to four times; hence, the dimensionless heat transfer rate reduces. However, the growth of Bi₂ has a contrary impact. Besides, the increase of Pr and Ec leads to an increase in the dimensionless temperature profile and dimensionless temperature gradient; therefore, the dimensionless heat transfer rate increases.

The convection heat transfer on the walls of the pipes is considered, and the nonlinear coupled momentum and energy equations are solved using the least squared method and collocation methods, respectively.

The purpose of this paper is to present novel search formulations in gradient‐type methods for prediction of boundary heat flux distribution in two‐dimensional nonlinear heat conduction problems.

The performance of gradient‐type methods is strongly contingent upon the effective determination of the search direction. Based on the definition of this parameter, gradient‐based methods such as steepest descent, various versions of both conjugate gradient and quasi‐Newton can be distinguished. By introducing new search techniques, several examples in the presence of noise in data are studied and discussed to verify the accuracy and efficiency of the present strategies.

The verification of the proposed methods for recovering time and space varying heat flux. The performance of the proposed methods via comparisons with the classical methods involved in its derivation.

The innovation of the present method is to use a hybridization of a conjugate gradient and a quasi‐Newton method to determine the search directions in gradient‐based approaches.

The present study aims to perform inverse analysis of a conjugate heat transfer problem including conduction and forced convection via the quasi-Newton method. The inverse analysis is defined for a heat source that is surrounded by a solid medium which is exposed to a free stream in external flow.

The objective of the inverse design problem is finding temperature distribution of the heat source as thermal boundary condition to establish a prescribed temperature along the interface of solid body and fluid. This problem is a simplified version of thermal-based ice protection systems in which the formation of ice is avoided by maintaining the interface of fluid and solid at a specified temperature.

The effects of the different pertinent parameters such as Reynolds number, interface temperature and thermal conductivity ratio of fluid and solid mediums are analyzed.

This paper fulfils the analysis to study how thermal based anti-icing system can be used with different heat source shapes.

The purpose of this paper is to numerically investigate the convective heat transfer of water-based CuO nanofluids flowing through a square cross-section duct under constant heat flux in the turbulent flow regime.

The numerical simulation is carried out at various Peclet numbers and particle concentrations (0.1, 0.2, 0.5, and 0.8 vol%). The finite volume formulation is used with the semi-implicit method for pressure-linked equations algorithm to solve the discretized equations derived from the partial nonlinear differential equations of the mathematical model.

The heat transfer coefficients and Nusselt numbers of CuO-water nanofluids increase with increases in the Peclet number as well as particle volume concentration. Also, enhancement of the heat transfer coefficient is much greater than that of the effective thermal conductivity at the same nanoparticle concentration.

Simulation of nanofluids turbulent forced convection at very high Reynolds number is worth for further study.

The heat transfer rates through non-circular ducts are smaller than the circular tubes. Nevertheless, the pressure drop of the non-circular duct is less than that of the circular tube. This study clearly presents that the nanoparticles suspended in water enhance the convective heat transfer coefficient, despite low volume fraction between 0.1 and 0.8 percent. Adding nanoparticles to conventional fluids may enhance heat transfer performance through the non-circular ducts, leading to extensive practical applications in industries for the non-circular ducts.

Few papers have numerically studied convective heat transfer properties of nanofluids through non-circular ducts. The present numerical results show a good agreement with the published experimental data.

Many a times, the information about the boundary heat flux is obtained only through inverse approach by locating the thermocouple or temperature sensor in accessible boundary. Most of the work reported in literature for the estimation of unknown parameters is based on heat conduction model. Inverse approach using conjugate heat transfer is found inadequate in literature. Therefore, the purpose of the paper is to develop a 3D conjugate heat transfer model without model reduction for the estimation of heat flux and heat transfer coefficient from the measured temperatures.

A 3 D conjugate fin heat transfer model is solved using commercial software for the known boundary conditions. Navier–Stokes equation is solved to obtain the necessary temperature distribution of the fin. Later, the complete model is replaced with neural network to expedite the computations of the forward problem. For the inverse approach, genetic algorithm (GA) and particle swarm optimization (PSO) are applied to estimate the unknown parameters. Eventually, a hybrid algorithm is proposed by combining PSO with Broyden–Fletcher–Goldfarb–Shanno (BFGS) method that outperforms GA and PSO.

The authors demonstrate that the evolutionary algorithms can be used to obtain accurate results from simulated measurements. Efficacy of the hybrid algorithm is established using real time measurements. The hybrid algorithm (PSO-BFGS) is more efficient in the estimation of unknown parameters for experimentally measured temperature data compared to GA and PSO algorithms.

Surrogate model using ANN based on computational fluid dynamics simulations and in-house steady state fin experiments to estimate the heat flux and heat transfer coefficient separately using GA, PSO and PSO-BFGS.

Non‐linear reaction‐diffusion processes with cross‐diffusion in two‐dimensional, anisotropic media are analyzed by means of an implicit, iterative, time‐linearized approximate factorization technique as functions of the anisotropy of the heat and species diffusivity tensors, the Soret and Dufour cross‐diffusion effects, and five types of boundary conditions. It is shown that anisotropy and cross‐diffusion deform the reaction front and affect the front velocity, and the magnitude of these effects increases as the magnitude of the off‐diagonal components of the heat and species diffusivity tensors is increased. It is also shown that the five types of boundary conditions employed in this study produce similar results except when there is either strong anisotropy in the species or heat diffusivity tensors and there are no Soret and Dufour effects, or the species and heat diffusivity tensors are isotropic, but the anisotropy of the Soret and Dufour effects is important. If the species and heat diffusivity tensors are isotropic, the effects of either the Soret or the Dufour cross‐diffusion effects are small for the cases considered in this study. The time required to achieve steady state depends on the anisotropy of the heat and diffusivity tensors, the cross‐diffusion effects, and the boundary conditions.

Students of mixed-ability learning together in one class is a challenge for all educators, especially in English as foreign language (EFL) contexts. Timed reading activity (TRA) is an activity that can help educators address the learning needs of students in such a context. The present study investigated the effectiveness of the TRA in enhancing EFL students' reading rate and reading comprehension as well as in making them aware of potentially wrong reading strategies that they may be using.

A classroom intervention was designed for a group of preparatory year (PY) students at a Saudi university. The study sample consisted of one intact class of 29 students. Data were collected from pre- and post-tests of students' reading rate and reading comprehension as well as progress charts. In addition, a questionnaire was used to identify the reading strategies used by the students.

The results showed that the TRA generally enhanced the reading comprehension and the reading rate of EFL mixed-ability students as well as raised their awareness of their use of wrong fast reading strategies.

The results of the study support the use of TRA as a remedial reading activity in EFL mixed-ability classes.

The present study aims at developing a model to quantify supply chain resilience as a single numerical value. The numerical value is called resilience index that measures the resilience capability of the case company's supply chain. The model calculates the index value based on the interactions between the enablers of supply chain resilience and its dimensions.

Graph theoretic approach (GTA) is used to evaluate the resilience index for the case company's supply chain. In GTA, the dimensions of resilience enablers and their interdependencies are modelled through a digraph. The digraph depicting the influence of each dimension is converted into an adjacency matrix. The permanent function value of the adjacency matrix is called the resilience index (RI).

The proposed approach has been illustrated in context of an Indian automobile organization, and value of the RI is evaluated. The best case and the worst-case values are also obtained with the help of GTA. It is noted from the model that strategic level dimension of enablers is most important in contributing towards supply chain resilience. They are followed by tactical and operational level enablers. The GTA framework proposed will help supply chain practitioners to evaluate and benchmark the supply chain resilience of their respective organizations with the best in the industry.

A firm can compare the RI of its own supply chain with other's supply chain or with the best in the industry for benchmarking purpose. Benchmarking of resilience will help organizations in developing strategies to compete in dynamic market scenario.