Abstract Shot peening is a widely used cold-working process. Physical phenomena of shot peening are analyzed using the developed fluid-particle-structure coupled solver. The influences of the flow ...field and shot peening parameters such as the shot impact velocity and shot size are investigated in the case of the falling, impacting, and rebounding single particle. The weakly coupled solver applies the immersed boundary method which enables direct evaluation of the interactions between the unsteady flow field and moving/deforming objects. The elastoplastic object of AISI4340 during the collision of rigid steel shot is analyzed dynamically using the finite element method. Consequently, it is clarified that the flow field of the post-collision between the shot and structure can be characterized by the relative Reynolds number, which is based on the shot diameter and relative velocity between the uniform flow and rebounding shot velocities. As the relative Reynolds number increases, the complex flow field and vortex structures are generated at the collision location. These fluid structures affect the collision phenomena resulting in the random behavior of the shot and the asymmetric indentation in the structure.
Motivated by the temporal variations in fuel flow and chemical composition from biogas generation, this work investigates the flame stability behavior of porous media burners (PMBs) under dynamic ...operating conditions. Experiments were performed using an interface-stabilized PMB subjected to different amplitudes of sinusoidal equivalence ratio (Φ) while holding mass flux constant, simulating the potential volatility in gas production of biomass gasification. Eight initial conditions from the steady stability regime were selected for oscillatory experiments. Then, tests were conducted across a range of Φ amplitudes and forcing frequencies from 1/180 Hz to 1/30 Hz. The linearity of the system response was used to determine stability, which revealed a non-monotonic relationship between mixture pore scale Reynolds number (Repore) and dynamic stabilization. A limiting condition of Φ = 0.2 was sustained at an initial condition of Φ0 = 0.6 and Repore of 112, corresponding to the location within the steady stability map featuring the widest range of flammability. As expected, the largest amplitudes in flow oscillations were sustained at the highest forcing frequency, 1/30 Hz. Emissions were recorded for both steady and dynamic experiments, revealing the total accumulation of CO during sinusoidal experiments is greater than that of baseline for the starting condition. Notably, a transfer function derived from a single stable data set predicts system response at other stable conditions. This study quantifies the dynamic thermal response of a PMB and demonstrates the potential for controlling porous media combustion in application to bio-derived fuels from inherently unsteady sources.
Mixed convective flow over a revolving sphere is of immense interest in several industrial and engineering applications starting from polymer deposition, electrolysis management, drug transport, ...spin-stabilized missiles, cooling of spinning machinery slices, etc. Hybrid nanofluid exhibits promising efficiency in heat transport compared to mono nanofluid. They are widely introduced in nuclear power plants, solar collectors, heat exchangers, microfluidic heat sinks, etc. Such unique promising applicative features drive this investigation to analyse the magnetized mixed convective unsteady Ag/MgO-water hybrid nanofluid stream over a whirling sphere near the stagnation zone. Moreover, the nanofluid motion is treated as thermally radiative. The foremost flow profiles are made dimensionless using appropriate similarity translation. The renovated equations associated with the boundary restrictions are treated numerically. Several schematics are extracted to reconnoiter the requisite noteworthy influence of flow parameters on thermal, velocity, heat transport, and skin frictional profiles. Consequences indicate the increase in x-direction velocity for the unsteadiness parameter and mono nanofluid exhibits higher velocity compared to hybrid nanofluid, while the reverse is detected for z-direction velocity. Thermal enhancement is assured for radiation parameters and nanoparticle concentration, where hybrid nanofluid illustrates a higher magnitude. Heat transport is also higher for hybrid nanofluid compared to the usual nanofluid.
The focus of the current study is to obtain the dual solutions via simulation for the two dimensional Casson fluid over the stretching sheet. Both the upper and lower branch solutions of the ...corresponding streamline profiles for the Casson fluid over the stretching sheet are obtained under the influences of the pertinent parameters. Both the steady and unsteady forms of the Casson fluid over the stretching sheet are valuable in performing the sensitivity analysis. Here is the graphical illustrations of the dual solutions for the Casson fluid over the stretching sheet.
The aim of the current study is to find out the dual solutions of the two-dimensional magnetohydrodynamic (MHD) flow of Casson fluid and heat transfer over the stretching sheet. The focus of the study is to examine the linear thermal radiation effects on dual solutions for both the steady and unsteady flow of Casson fluid over the stretching sheet under the influence of uniform magnetic field. The governing equations are formed as system of partial differential equations (PDEs). Using suitable transformations, the system of PDEs are converted into favorable nonlinear system of ordinary differential equations (ODEs). Simulations are performed in Maple 2015 to form the dual solutions in order to achieve the velocity, temperature, skin friction and heat transfer profiles of the Casson fluid over the stretching sheet. It is concluded that the dual solutions for the corresponding model are numerically stable. Furthermore, the upper branch solutions of the Casson fluid profiles are numerically stable as compared to the lower branch solutions. Results indicate that positive Eigen values of the MHD flow of Casson fluid provide stable profiles as compared to the negative Eigen values. It is believed that the current study would provide a base for the dual solution of the other types of the non-Newtonian fluid flows over various categories of surfaces.
•MHD flow of Casson fluid and heat transfer is analyzed.•Thermal radiation effects on both the steady and unsteady Casson fluid is examined.•Dual nature solutions for the proposed model are found.•The stability of the dual solutions are presented.
•By GCI evaluation method to study grid independence and discrete error of hydrofoil.•Numerical simulation of the hydrofoil using various turbulence models.•Simulation results consistent with the ...experiments are obtained through the DCMFBM turbulence model.•Revealing the mechanism of hydrofoil cavities instability and shedding.
To improve the accuracy of hydrofoil unsteady cavitation simulations, we investigate grid irrelevance and discrete error using the GCI evaluation method to determine the optimal number of grids. Numerous turbulent viscosity correction approaches are used to improve the turbulence model, and numerical simulations are conducted in conjunction with unsteady cavitation of the hydrofoil with a 3° angle of attack, as well as application evaluation. The results indicate that the DCMFBM model produces the most accurate unsteady cavity shape of the hydrofoil surface. The details of the cavity's primary and secondary shedding are captured during the cavitation process. The DCMFBM turbulence model with a density correction index of 10 and a filter parameter of 0.15c has the highest simulation accuracy. The flow structures of sheet cavitation, transition state cavitation, cloud cavitation, and cavitation shedding are analyzed. The mechanism of hydrofoil cavitation instability and shedding is revealed, providing a theorem.
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Unsteady flow fields over a circular cylinder are used for training and then prediction using four different deep learning networks: generative adversarial networks with and without consideration of ...conservation laws; and convolutional neural networks with and without consideration of conservation laws. Flow fields at future occasions are predicted based on information on flow fields at previous occasions. Predictions of deep learning networks are made for flow fields at Reynolds numbers that were not used during training. Physical loss functions are proposed to explicitly provide information on conservation of mass and momentum to deep learning networks. An adversarial training is applied to extract features of flow dynamics in an unsupervised manner. Effects of the proposed physical loss functions and adversarial training on predicted results are analysed. Captured and missed flow physics from predictions are also analysed. Predicted flow fields using deep learning networks are in good agreement with flow fields computed by numerical simulations.
•The unsteady flow and heat transfer past a stretching/shrinking sheet in a hybrid nanofluid is studied.•The governing equations of the problem are transformed to the similarity equations.•The ...problem is solved numerically using the boundary value problem solver (bvp4c) in Matlab software.•It is found that dual solutions exist for a certain range of the unsteadiness parameter.•A temporal stability analysis is performed to determine the stability of the dual solutions.
The unsteady flow and heat transfer past a stretching/shrinking sheet in a hybrid nanofluid is studied. The governing equations of the problem are transformed to the similarity equations by using similarity transformation technique. The problem is solved numerically using the boundary value problem solver (bvp4c) in Matlab software. The plots of the skin friction coefficient and the local Nusselt number as well as the velocity and temperature profiles for selected parameters are presented. It is found that dual solutions exist for a certain range of the unsteadiness parameter. A temporal stability analysis is performed to determine the stability of the dual solutions in a long run, and it is reveals that only one of them is stable while the other is unstable.
A non-intrusive reduced-basis (RB) method is proposed for parametrized unsteady flows. A set of reduced basis functions are extracted from a collection of high-fidelity solutions via a proper ...orthogonal decomposition (POD), and the coefficients of the reduced basis functions are recovered by a feedforward neural network (NN). As a regression model of the RB method for unsteady flows, the neural network approximates the map between the time/parameter value and the projection coefficients of the high-fidelity solution onto the reduced space. The generation of the reduced basis and the training of the NN are accomplished in the offline stage, thus the RB solution of a new time/parameter value can be recovered via direct outputs of the NN in the online stage. Due to its non-intrusive nature, the proposed RB method, referred as the POD-NN, fully decouples the online stage and the high-fidelity scheme, and is thus able to provide fast and reliable solutions of complex unsteady flows. To test this assertion, the POD-NN method is applied to the reduced order modeling (ROM) of the quasi-one dimensional Continuously Variable Resonance Combustor (CVRC) flow. Numerical results demonstrate the efficiency and robustness of the POD-NN method.
•A non-intrusive POD-NN RB method for parametrized unsteady flows.•Feedforward neural network as the regression model.•Time treated as a parameter to account for unsteadiness of the flow.•Capability of POD-NN RB method for ROM of local space/time domain of interest.•Robustness and efficiency of the POD-NN RB method for a complex combustion problem.
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