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This paper aims to present the development of a highly parallel finite-difference computational fluid dynamics code in generalized curvilinear coordinates system. The objectives are to handle internal and external flows in fairly complex geometries including shock waves, compressible turbulence and heat transfer.

The code is equipped with high-order discretization schemes to improve the computational accuracy of the solution algorithm. Besides, a new method to deal with the geometrical singularities, so-called domain decomposition method (DDM), is implemented. The DDM consists of using two different meshes communicating with each other, where the base mesh is Cartesian and the overlapped one a hollow cylinder.

The robustness of the present implemented code is appraised through several numerical test cases including a vortex advection, supersonic compressible flow over a cylinder, Poiseuille flow, turbulent channel and pipe flows. The results obtained here are in an excellent agreement when compared to the experimental data and the previous direct numerical simulation (DNS). As for the DDM strategy, it was successful as simulation time is clearly decreased and the connection between the two subdomains does not create spurious oscillations.

In sum, the developed solver was capable of solving, accurately and with high-precision, two- and three-dimensional compressible flows including fairly complex geometries. It is noted that the data provided by the DNS of supersonic pipe flows are not abundant in the literature and therefore will be available online for the community.

Fluid flows in pipes whose cross-sectional area are increasing in the stream-wise direction are prone to separation of the recirculation region. This paper aims to investigate such fluid flow in expansion pipe systems using direct numerical simulations. The flow in circular diverging pipes with different diverging half angles, namely, 45, 26, 14, 7.2 and 4.7 degrees, are considered. The flow is fed by a fully developed laminar parabolic velocity profile at its inlet and is connected to a long straight circular pipe at its downstream to characterise recirculation zone and skin friction coefficient in the laminar regime. The flow is considered linearly stable for Reynolds numbers sufficiently below natural transition. A perturbation is added to the inlet fully developed laminar velocity profile to test the flow response to finite amplitude disturbances and to characterise sub-critical transition.

Direct numerical simulations of the Navier–Stokes equations have been solved using a spectral element method.

It is found that the onset of disordered motion and the dynamics of the localised turbulence patch are controlled by the Reynolds number, the perturbation amplitude and the half angle of the pipe.

The authors clarify different stages of flow behaviour under the finite amplitude perturbations and shed more light to flow physics such as existence of Kelvin–Helmholtz instabilities as well as mechanism of turbulent puff shedding in diverging pipe flows.

This paper aims to study the fluid flow and heat transfer through a spiral double-pipe heat exchanger. Nowadays using spiral double-pipe heat exchangers has become popular in different industrial segments due to its complex and spiral structure, which causes an enhancement in heat transfer.

In these heat exchangers, by converting the fluid motion to the secondary motion, the heat transfer coefficient is greater than that of the straight double-pipe heat exchangers and cause increased heat transfer between fluids.

The present study, by using the Fluent software and nanofluid heat transfer simulation in a spiral double-tube heat exchanger, investigates the effects of operating parameters including fluid inlet velocity, volume fraction of nanoparticles, type of nanoparticles and fluid inlet temperature on heat transfer efficiency.

After presenting the results derived from the fluid numerical simulation and finding the optimal performance conditions using a genetic algorithm, it was found that water–Al₂O₃ and water–SiO₂ nanofluids are the best choices for the Reynolds numbers ranging from 10,551 to 17,220 and 17,220 to 31,910, respectively.