Plesiosaurs are an enigmatic, diverse extinct group of Mesozoic marine reptiles well known for their unique body plan with two pairs of flippers and usually an elongated neck. The long neck evolved several times within the clade, yet the evolutionary advantages are not well understood. Previous studies have mainly focused on swimming speeds or flipper locomotion. We evaluated the hydrodynamics of neck length and thickness in plesiosaurs using computational fluid dynamics (CFD) simulations based on the Reynolds-averaged Navier-Stokes (RANS) approach. Simulations were performed of flow patterns forming around five distinctive plesiosaur models, three of different neck lengths (neck/body ratios of 0.2, 0.41, and 0.63) and two of different neck thicknesses (100% and 343% increase compared with cervical vertebrae width). By simulating water flow past the three-dimensional digital plesiosaur models, our results demonstrated that neck elongation does not noticeably affect the force of drag experienced by forward-swimming plesiosaurs. Thicker necks did reduce drag compared with thinner necks, however. The consistent drag coefficient experienced by the three neck lengths used in this study indicates that, at least for forward motion at speeds from 1 to 10 m/s, hydrodynamic implications were not a limiting selective pressure on the evolution of long necks in plesiosaurs. We also tested the effects of bending the long neck during forward motion. Bending a plesiosaur neck evenly in lateral flexion increased the surface area normal to flow and subsequently increased drag force. This effect was most noticeable in the longest-necked forms.

A direct numerical simulation investigation of a transient flow in a channel with a smooth top wall and a roughened bottom wall made of close-packed pyramids is presented. An initially stationary turbulent flow is accelerated rapidly to a new flow rate and the transient flow behaviour after the acceleration is studied. The equivalent roughness heights of the initial and final flows are and 41.5, respectively. Immediately after the acceleration ends, the induced change behaves in a ‘plug-flow’ manner. Above the roughness crests, the additional velocity due to the perturbation flow is uniform; below the crest, it reduces approximately linearly to zero at the bottom of the roughness elements. The interaction of the perturbation flow with the rough wall is characterised by a series of events that resemble those observed in roughness-induced laminar–turbulent transitions. The process has two broad stages. In the first of these, large-scale vortices, comparable in extent to the roughness wavelength, develop around each roughness element and high-speed streaks form along the ridge lines of the elements. After a short time, each vortex splits into two, namely (i) a standing vortex in front of the element and (ii) a counter-rotating hairpin vortex behind it. The former is largely inactive, but the latter advects downstream with increasing strength, and later lifts away from the wall. These hairpin vortices wrap around strong low-speed streaks. The second stage of the overall process is the breakdown of the hairpin vortices into many smaller multi-scale vortices distributed randomly in space, leading eventually to a state of conventional turbulence. Shortly after the beginning of the first stage, the three components of the r.m.s of the velocity fluctuation all increase significantly in the near-wall region as a result of the vortical structures, and their spectra bear strong signatures of the surface topology. During the second stage, the overall turbulence energy in this region varies only slightly, but the spectrum evolves significantly, eventually approaching that of conventional turbulence. The direct effect of roughness on the flow is confined to a region up to approximately three element heights above the roughness crests. Turbulence in the core region does not begin to increase until after the transition near the wall is largely complete. The processes of transition over the smooth and rough walls of the channel are practically independent of each other. The flow over the smooth wall follows a laminar–turbulent transition and, as known from previous work, resembles a free-stream turbulence-induced boundary layer bypass transition.

This review paper investigates the use of air lubrication to reduce ship hull skin frictional drag, a technology whose fundamental drag-reduction mechanisms and impact on seakeeping are increasingly being studied through Computational Fluid Dynamics (CFD). Simulating this process is challenging, as the air phase often manifests as dispersed bubbles rather than a continuous film, necessitating high-fidelity models. Traditional simulations treating air and water as distinct phases fall short, and while Direct Numerical Simulation (DNS) captures bubble behaviour, its computational cost is prohibitive for practical application. This paper, therefore, reviews numerical simulation methods for air lubrication systems, evaluating their capabilities and limitations in capturing the system’s hydrodynamics and structural interaction, in contrast to traditional towing tank testing. The evaluation reveals a critical trade-off: methods with high computational feasibility (e.g., standard LES with VOF) provide an adequate estimation of overall drag reduction but consistently fail to accurately model the detailed bubble breakup and coalescence dynamics crucial for predicting system performance across different vessel speeds and pressures. Specifically, the review establishes that current mainstream CFD approaches underestimate the pressure-induced stability effects on bubbles. The paper concludes that accurate and practical simulation requires the integration of advanced techniques, such as Population Balance Models or Lagrangian Particle Tracking, to account for these distinct, flow-dependent phenomena, thereby highlighting the path forward for validated numerical models in marine air lubrication.

The turbulence behaviour of current-dominated pulsating flows has been investigated. Direct numerical simulations have been carried out for Stokes lengths over a range of $l_s^+=5\unicode{x2013}26$ , and amplitudes spanning 90 % of the current-dominated regime, about a mean flow of $\overline {Re}=6275$ . The results show that the turbulence response in intermediate and low-frequency pulsations is governed by a multistage turbulent–turbulent transition process, which bears a strong similarity to the multistage response of non-periodic acceleration. During the early acceleration period, the flow enters a pretransition stage, in which a new laminar perturbation boundary layer forms at the wall, and the streamwise velocity streaks are stretched. If the low-speed streaks destabilise prior to the deceleration period, then the flow enters a transition stage in which the perturbation boundary layer undergoes a bypass-like transition process. A unique feature of pulsating flows is the ongoing mechanism of turbulence decay, which initiates during the deceleration period and constitutes the main transient turbulence mechanism for much of the cycle. For high-frequency pulsations, the perturbation boundary layer fails to reach the pretransition stage prior to the deceleration period. Instead, the flow alternates between two inertial stages which are characterised by two layers of amplified viscous force; one growing at the wall, and one detached and moving towards the core.

It is common that industry‐standard packages are used in teaching professional engineering courses in final‐year undergraduate and postgraduate levels. To improve the competency of students in using such professional packages, it is important that students develop a good understanding of theoretical/fundamental concepts used on the packages. However, it is always a challenge to teach theoretical/fundamental concepts in the computational‐related courses. The teaching of such subjects can be improved by the use of advanced open‐source web applications. The present research proposes an approach based upon the combination of Jupyter Notebook and an industry‐standard package to teach an applied, computationally related course. We investigate the use of backward design and a novel tool called IPython (Jupyter) Notebook to redesign a postgraduate Computational Fluid Dynamics (CFD) course. IPython Notebook is used to design a series of integrated lecture slides and tutorial tasks, and also one of the assignments for the blended‐learning‐based, semester‐run, CFD course. The tool allows the implementation of backward curriculum design and a learn‐by‐doing approach in redesigning the course. The materials produced were used on the first part of the course which contributed 40% towards the course's final mark and delivered the fundamental concepts of CFD over the first half of the semester. The remaining 60% of the mark was based on a final project from the materials taught on using an industry‐standard CFD package in solving complex CFD problems during the second half of the semester. It was shown that the Ipython environment is a very useful tool which provides learning‐by‐doing practices allowing students to have a coherent integrated lecture, tutorial, and assignment material in a highly interactive way. It improved (a) students' engagement in teaching complex theoretical concepts, (b) students satisfaction of the course and (c) students performance in working with the industry‐standard package over the second half of the semester.

Large-eddy simulations of turbulent channel flow subjected to a step-like acceleration have been performed to investigate the effect of high Reynolds number ratios on the transient behaviour of turbulence. It is shown that the response of the flow exhibits the same fundamental characteristics described in He & Seddighi (J. Fluid Mech., vol. 715, 2013, pp. 60–102 and vol. 764, 2015, pp. 395–427)—a three-stage response resembling that of the bypass transition of boundary layer flows. The features of transition are seen to become more striking as the Re-ratio increases—the elongated streaks become stronger and longer, and the initial turbulent spot sites at the onset of transition become increasingly sparse. The critical Reynolds number of transition and the transition period Reynolds number for those cases are shown to deviate from the trends of He & Seddighi (2015). The high Re-ratio cases show double peaks in the transient response of streamwise fluctuation profiles shortly after the onset of transition. Conditionally-averaged turbulent statistics based on a λ_2-criterion are used to show that the two peaks in the fluctuation profiles are due to separate contributions of the active and inactive regions of turbulence generation. The peak closer to the wall is attributed to the generation of “new” turbulence in the active region, whereas the peak farther away from the wall is attributed to the elongated streaks in the inactive region. In the low Re-ratio cases, the peaks of these two regions are close to each other during the entire transient, resulting in a single peak in the domain-averaged profile.