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A C° continuous finite element higher‐order displacement model is developed for the dynamic analysis of laminated composite plates. The displacement model accounts for non‐linear distribution of inplane displacement components through the plate thickness and the theory requires no shear correction coefficients. Explicit time marching schemes are adopted for integration of the dynamic equilibrium equation and a diagonal ‘lumped’ mass matrix is employed with a special procedure applicable to Lagrangian parabolic isoparametric elements. The parametric effects of the time step, finite element mesh, lamination scheme and orthotropy on the transient response are investigated. The effect of the coupling on the transient response is also investigated. Numerical results for deflections and stresses are presented for rectangular plates under various boundary conditions and loadings and compared with results from other sources.

The purpose of this paper is to study the effects of Soret and Dufour effects on convective heat and mass transfer flow through a porous medium in a rectangular duct in the presence of inclined magnetic field.

Using the non-dimensional variables, the governing equations have been transformed into a set of differential equations, which are non-linear and cannot be solved analytically, therefore finite element method has been used for solving the governing equations.

The influence of thermo-diffusion, diffusion thermo, radiation, dissipation, heat sources and the inclined magnetic field on all the flow, heat and mass transfer characteristics has been found to be significant.

The problem is relatively original as it combines many effects as Soret and Dufour effects and chemical reaction under inclined magnetic field.

The purpose of this study is to experimentally investigate the large deformation compression characteristics of fused deposition modelling (FDM)-printed poly lactic acid (PLA), considering the combined effect of infill density and strain rate, and to develop a constitutive viscoplastic model that can incorporate the infill density to predict the experimental result.

The experimental approach focuses on strain rate-dependent (2.1 × 10⁻⁴, 2.1 × 10⁻³, and 2.1 × 10⁻² s⁻¹) compression testing for varied infill densities. Scanning electron microscopy (SEM) imaging of compressed materials is used to investigate deformation processes. A hyperelastic-viscoplastic constitutive model is constructed that can predict mechanical deformations at different strain rates and infill densities.

The yield stress of PLA increased with increase in strain rate and infill density. However, higher degree of strain-softening response was witnessed for the strain rate corresponding to 2.1 × 10⁻² s⁻¹. While filament splitting and twisting were identified as the damage mechanisms at higher strain rates, matrix crazing was observed as the primary deformation mechanism for higher infill density (95%). The developed constitutive model captured yield stress and post-yield softening behaviour of FDM build PLA samples with a high R² value of 0.99.

This paper addresses the need to analyse and predict the mechanical response of FDM print polymers (PLA) undergoing extensive strain-compressive loading through a hyperelastic-viscoplastic constitutive model. This study links combined effects of the printing parameter (infill density) with the experimental parameter (strain rate).

The purpose of this paper is to explore the novel aspects of activation energy in the nonlinearly convective flow of Walter-B nanofluid in view of Cattaneo–Christov double-diffusion model over a permeable stretched sheet. Features of nonlinear thermal radiation, dual stratification, non-uniform heat generation/absorption, MHD and binary chemical reaction are also evaluated for present flow problem. Walter-B nanomaterial model is employed to describe the significant slip mechanism of Brownian and thermophoresis diffusions. Generalized Fourier’s and Fick’s laws are examined through Cattaneo–Christov double-diffusion model. Modified Arrhenius formula for activation energy is also implemented.

Several techniques are employed for solving nonlinear differential equations. The authors have used a homotopy technique (HAM) for our nonlinear problem to get convergent solutions. The homotopy analysis method (HAM) is a semi-analytical technique to solve nonlinear coupled ordinary/partial differential equations. The capability of the HAM to naturally display convergence of the series solution is unusual in analytical and semi-analytic approaches to nonlinear partial differential equations. This analytical method has the following great advantages over other techniques:

• It provides a series solution without depending upon small/large physical parameters and applicable for not only weakly but also strongly nonlinear problems.

• It guarantees the convergence of series solutions for nonlinear problems.

• It provides us a great choice to select the base function of the required solution and the corresponding auxiliary linear operator of the homotopy.

It provides a series solution without depending upon small/large physical parameters and applicable for not only weakly but also strongly nonlinear problems.

It guarantees the convergence of series solutions for nonlinear problems.

It provides us a great choice to select the base function of the required solution and the corresponding auxiliary linear operator of the homotopy.

Brief mathematical description of HAM technique (Liao, 2012; Mabood et al., 2016) is as follows. For a general nonlinear equation:

where N denotes a nonlinear operator, x the independent variables and u(x) is an unknown function, respectively. By means of generalizing the traditional homotopy method, Liao (1992) creates the so-called zero-order deformation equation:

here q∈[0, 1] is the embedding parameter, H(x) ≠ 0 is an auxiliary function, h(≠ 0) is a nonzero parameter, L is an auxiliary linear operator, u_o(x) is an initial guess of u(x) and u ˆ ( x ; q ) is an unknown function, respectively. It is significant that one has great freedom to choose auxiliary things in HAM. Noticeably, when q=0 and q=1, following holds:

Expanding u ˆ ( x ; q ) in Taylor series with respect to (q), we have:

If the initial guess, the auxiliary linear operator, the auxiliary h and the auxiliary function are selected properly, then the series (4) converges at q=1, then we have:

By defining a vector u → = ( u o ( x ) , u 1 ( x ) , u 2 ( x ) , … , u n ( x ) ) , and differentiating Equation (2) m-times with respect to (q) and then setting q=0, we obtain the mth-order deformation equation:

where:

Applying L⁻¹ on both sides of Equation (6), we get:

In this way, we obtain u_m for m ⩾ 1, at mth-order, we have:

It is evident from obtained results that the nanoparticle concentration field is directly proportional to the chemical reaction with activation energy. Additionally, both temperature and concentration distributions are declining functions of thermal and solutal stratification parameters (P₁) and (P₂), respectively. Moreover, temperature Θ(Ω₁) enhances for greater values of Brownian motion parameter (N_b), non-uniform heat source/sink parameter (B₁) and thermophoresis factor (N_t). Reverse behavior of concentration ϒ(Ω₁) field is remarked in view of (N_b) and (N_t). Graphs and tables are also constructed to analyze the effect of different flow parameters on skin friction coefficient, local Nusselt number, Sherwood numbers, velocity, temperature and concentration fields.

The novelty of the present problem is to inspect the Arrhenius activation energy phenomena for viscoelastic Walter-B nanofluid model with additional features of nonlinear thermal radiation, non-uniform heat generation/absorption, nonlinear mixed convection, thermal and solutal stratification. The novel aspect of binary chemical reaction is analyzed to characterize the impact of activation energy in the presence of Cattaneo–Christov double-diffusion model. The mathematical model of Buongiorno is employed to incorporate Brownian motion and thermophoresis effects due to nanoparticles.

The purpose of this paper is to theoretically investigate the boundary layer nature of magnetohydrodynamic nanofluid flow past a vertical expanding surface in a rotating geometry with viscous dissipation, thermal radiation, Soret effect and chemical reaction.

The self-similarity variables are deliberated to transmute the elementary governing equations. The analytical perturbation technique is used to elaborate the united nonlinear ODEs.

To check the disparity on the boundary layer nature, the authors measured two nanofluids, namely, Cu-water and Cu-Kerosene based nanofluids. It is found that the Cu-water is effectively enhancing the thermal conductivity of the flow when compared with the Cu-kerosene.

Till now no analytical studies are reported on heat transfer enhancement of the rotating nanofluid flow by considering two different base fluids.

The purpose of study is to examine the dual nature of the branches for the problem of Darcy–Forchheimer porous medium flow of rotating nanofluid on a linearly stretching/shrinking surface under the field of magnetic influence. The dual nature of the branches confronts the uniqueness and existence theorem, moreover, mathematically it is a great achievement. For engineering purposes, this study applied a linear stability test on the multiple branches to determine which solution is physically reliable (stable).

Nanofluid model has been developed with the help of Buongiorno model. The partial differential equations in space coordinates for the law of conservation of mass, momentum and energy have been transformed into ordinary differential equations by introducing the similarity variables. Two numerical techniques, namely, the shooting method in Maple software and the three-stage Lobatto IIIA method in Matlab software, have been used to find multiple branches and to accomplish stability analysis, respectively.

The parametric investigation has been executed to find the multiple branches and explore the effects on skin friction, Sherwood number, Nusselt number, concentration and temperature profiles. The findings exhibited the presence of dual branches only in the case of a shrinking sheet.

The originality of work is a determination of multiple branches and the performance of the stability analysis of the branches. It has also been confirmed that such a study has not yet been considered in the previous literature.

In this paper the effects of viscous dissipation and ohmic heating on the fluid flow and resulting heat and mass transfer caused by vertically moving rotating disk are explored with magnetic field acting perpendicular to disk rotation. The flow regime is also under the influence of Dufour and Soret effects.

An approach of similarity transformation is used to transform the governing set of equations into non-linear ordinary differential equations. Numerical simulations are carried out in Maple software to study the influence of incorporated non-dimensional parameters viz. disk movement parameter (−0.3 < S < 0.2), magnetic parameter (0.1 < M < 0.4), Eckert number (0.1 < Ec < 1), Schmidt number (0.1 < Sc < 1), Soret parameter (0.1 < Sr < 1) and Dufour number (0.1 < Du < 1) on velocity, temperature and concentration profiles.

The upward/downward motion of the disk along with rotation set up a three-dimensional flow over the disk surface and exerts the same effects as injection/suction through the wall. It is also observed that incorporated parameters along with disk movement greatly affect the flow regime and associated heat and mass transfer.

The present study examines the heat and mass transfer characteristics of incompressible Newtonian fluid over an impermeable rotating disk moving vertically. The effect of viscous dissipation and ohmic heating is considered. To the best of the authors’ knowledge, such consideration is yet to be published in the literature.

This paper aims to focus on the mathematical modeling of magnetohydrodynamic natural convective boundary layer flow of nanofluids past a stationary and moving inclined porous plate considering temperature and concentration gradients with suction effects.

The transformed non-dimensional and coupled governing partial differential equations are solved numerically using the finite element method.

The obtained numerical results for physical governing parameters on the velocity, temperature and concentration distributions are exemplified graphically and presented quantitatively. The boundary layer thickness increased with the increasing values of Soret, Dufour and Grashof numbers, while the thickness of boundary layer decreased with increasing values of suction for both stationary and moving plate cases. The primary and secondary velocity profiles are decreasing with an angle of inclination for moving plate and inclination has no significant effect for the stationary plate. An increase of the Soret number and Dufour number tend to increase the heat and mass transfer, while an increase of suction reduces the heat and mass transfer.

The problem is an important contribution to the field of nanofluid science and technology and is relevant to high temperature rotating chemical engineering systems exploiting magnetized nanofluids. This study is relatively original in nanofluids.

Acrylonitrile butadiene styrene is an important material in 3D printing due to its strength, durability, heat resistance and cost-effectiveness. These properties make it suitable for various applications, from functional prototypes to end-use products. This study aims to model and predict the mechanical properties of acrylonitrile butadiene styrene parts produced using the fused deposition modeling process.

The experiment was carefully designed to determine the optimal print parameters, including layer thickness, nozzle temperature and infill density. Tensile tests were performed on all printed samples following industry standards to gauge the mechanical properties such as elastic modulus, ultimate tensile strength, yield strength and breakpoint. Taguchi optimization and variable analysis were used to explore the relationship between mechanical properties and print parameters. Furthermore, an artificial neural network (ANN) regression model was implemented to predict mechanical properties based on varying print conditions.

The results demonstrated that layer thickness has the most significant influence on mechanical properties when compared to other print conditions. The optimization approaches indicated a clear relationship between the selected print parameters and the material’s mechanical response. For acrylonitrile butadiene styrene material, the optimal print settings were determined to be a 0.25 mm layer thickness, a 270 °C nozzle temperature and a 30 % infill density. Moreover, the ANN model notably excelled in predicting the yield strength of the material with greater accuracy than other mechanical properties.

Comparing the accuracy and capabilities of the Taguchi and ANN models in analyzing mechanical properties, it was found that both models closely matched the experimental data. However, the ANN model showed superior accuracy in predicting tensile outcomes. In conclusion, while the ANN model offers higher predictive accuracy for tensile results, both Taguchi and ANN methods are effective in modeling the mechanical properties of 3D-printed acrylonitrile butadiene styrene materials.

The purpose of this study is to develop and test a new deep learning model to predict aircraft fuel consumption. For this purpose, real data obtained from different landings and take-offs were used. As a result, a new hybrid convolutional neural network (CNN)-bi-directional long short term memory (BiLSTM) model was developed as intended.

The data used are divided into training and testing according to the k-fold 5 value. In this study, 13 different parameters were used together as input parameters. Fuel consumption was used as the output parameter. Thus, the effect of many input parameters on fuel flow was modeled simultaneously using the deep learning method in this study. In addition, the developed hybrid model was compared with the existing deep learning models long short term memory (LSTM) and BiLSTM.

In this study, when tested with LSTM, one of the existing deep learning models, values of 0.9162, 6.476, and 5.76 were obtained for R², root mean square error (RMSE), and mean absolute percentage error (MAPE), respectively. For the BiLSTM model when tested, values of 0.9471, 5.847 and 4.62 were obtained for R², RMSE and MAPE, respectively. In the proposed hybrid model when tested, values of 0.9743, 2.539 and 1.62 were obtained for R², RMSE and MAPE, respectively. The results obtained according to the LSTM and BiLSTM models are much closer to the actual fuel consumption values. The error of the models used was verified against the actual fuel flow reports, and an average absolute percent error value of less than 2% was obtained.

In this study, a new hybrid CNN-BiLSTM model is proposed. The proposed model is trained and tested with real flight data for fuel consumption estimation. As a result of the test, it is seen that it gives much better results than the LSTM and BiLSTM methods found in the literature. For this reason, it can be used in many different engine types and applications in different fields, especially the turboprop engine used in the study. Because it can be applied to different engines than the engine type used in the study, it can be easily integrated into many simulation models.