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Power minimisation in branched fluidic networks has gained significant attention in biology and engineering. The optimal network is defined by channel radii that minimise the sum of viscous dissipation and the volumetric energetic cost of the fluid. For limit cases including laminar flows, high-Reynolds-number turbulence or smooth-channel approximations, optimal solutions are known. However, current methods do not allow optimisation for a large intermediate part of the parameter space which is typically encountered in realistic fluidic networks that exhibit turbulent flow. Here, we present a unifying optimisation approach based on the Darcy friction factor, which has been determined for a wide range of flow regimes and fluid models and is applicable to the entire parameter space: (i) laminar and turbulent flows, including networks that exhibit both flow types, (ii) non-Newtonian fluids (powerlaw, Bingham and Herschel–Bulkley) and (iii) networks with arbitrary wall roughness, including non-uniform relative roughness. The optimal channel radii are presented analytically and graphically. All existing limit cases are recovered, and a concise framework is presented for systematic optimisation of fluidic networks. Finally, the parameter $x$ in the optimisation relationship $Q\propto R^{x}$, with $Q$ the flow rate and $R$ the channel radius, was approximated as a function of the Reynolds number, revealing in which case the entire network can be optimised based on one optimal channel radius, and in which case all radii must be optimised individually. Our approach can be extended to a wide range of fluidic networks for which the friction factor is known, such as different channel curvatures, bubbly flows or specific wall slip conditions.
This practical guide to optimization combines mathematical theory with hands-on coding examples to explore how Python can be used to model problems and obtain the best possible solutions. Presenting a balance of theory and practical applications, it is the ideal resource for upper-undergraduate and graduate students in applied mathematics, data science, business, industrial engineering and operations research, as well as practitioners in related fields. Beginning with an introduction to the concept of optimization, this text presents the key ingredients of an optimization problem and the choices one needs to make when modeling a real-life problem mathematically. Topics covered range from linear and network optimization to convex optimization and optimizations under uncertainty. The book's Python code snippets, alongside more than 50 Jupyter notebooks on the author's GitHub, allow students to put the theory into practice and solve problems inspired by real-life challenges, while numerous exercises sharpen students' understanding of the methods discussed.
The spatiotemporal dynamics of a turbulent boundary layer subjected to an unsteady pressure gradient are studied. A dynamic sequence of favourable to adverse pressure gradients (FAPGs) is imposed by deforming a section of the wind tunnel ceiling, transitioning the pressure gradient from zero to a strong FAPG within 0.07 s. At the end of the transient, the acceleration parameter is $K$ = $6 \times 10^{-6}$ in the favourable pressure gradient (FPG) region and $K$ = $-4.8 \times 10^{-6}$ in the adverse pressure gradient (APG) region. The resulting unsteady response of the boundary layer is compared with equivalent steady pressure gradient cases in terms of turbulent statistics and coherent structures. While the steady FAPG effects, as shown by Parthasarathy & Saxton-Fox (2023), caused upstream stabilisation in the FPG, a milder APG response downstream, and the formation of an internal layer, the unsteady case presented in this paper shows a reduced stabilisation in the FPG region, a stronger APG response and a weaker internal layer. This altered response is hypothesised to stem from the different spatiotemporal pressure gradient histories experienced by turbulent structures when the pressure gradient changes at a time scale comparable to their convection.
This paper investigates the weakly nonlinear isotropic bidirectional Benney–Luke (BL) equation, which is used to describe oceanic surface and internal waves in shallow water, with a particular focus on soliton dynamics. Using the Whitham modulation theory, we derive the modulation equations associated with the BL equation that describe the evolution of soliton amplitude and slope. By analysing rarefaction waves and shock waves within these modulation equations, we derive the Riemann invariants and modified Rankine–Hugoniot conditions. These expressions help characterise the Mach expansion and Mach reflection phenomena of bent and reverse bent solitons. We also derive analytical formulae for the critical angle and the Mach stem amplitude, showing that as the soliton speed is in the vicinity of unity, the results from the BL equation align closely with those of the Kadomtsev–Petviashvili (KP) equation. Corresponding numerical results are obtained and show excellent agreement with theoretical predictions. Furthermore, as a far-field approximation for the forced BL equation – which models wave and flow interactions with local topography – the modulation equations yield a slowly varying similarity solution. This solution indicates that the precursor wavefronts created by topography moving at subcritical or critical speeds take the shape of a circular arc, in contrast to the parabolic wavefronts observed in the forced KP equation.
The recently proposed near-wall turbulence predictive model quantifies the degree of the superposition and the amplitude modulation exerted by large-scale coherent structures on small scales in the linear and nonlinear terms of the formula, respectively, and achieves the prediction of streamwise velocity in the inner region. However, the multiscale effect and the time shift confirmed in the amplitude modulation have not yet been simultaneously taken into account in the model, which could limit the prediction accuracy especially at high Reynolds numbers. In this study, the role of the nonlinear term in the model is clarified based on high-quality flow data obtained in atmospheric surface layers: it redistributes the energy of the universal signal in the time domain and determines the accuracy of the predictive odd moments. An analysis of the multiscale effect and the time shifts in the nonlinear term is subsequently conducted, followed by a demonstration of the refinement in the quality of the universal signal after separately incorporating them into the model. The amplitude modulation is revealed when the two factors are simultaneously considered, and profiles of the scales that dominate the modulation and time shifts with height is provided. Thus, the nonlinear term of the existing model is modified, proposing an polished scheme that can quantify the nonlinear modulation terms more accurately.
Today, innovative vehicle designs explore the possibility of employing distributed propulsion systems with multiple rotors and propellers. Distributed propulsion systems create complex interactional aerodynamics, that remain largely unexplored and not fully understood. This paper presents a high-fidelity aerodynamic analysis of a tip-mounted propeller combined with over-the-wing propellers. Different configurations were tested using fully resolved simulations with the HMB3 CFD solver. The results indicate that interactional effects in all configurations influence the propeller and wing performance. The proposed configuration, featuring a tip-mounted propeller and over-the-wing propellers, produced 3.5% more thrust compared to the configuration with only a tip-mounted propeller, while also enhancing efficiency. Wing performance was also improved, yielding more lift and less drag, resulting in a higher lift-to-drag ratio. These benefits were due to the thrust and power distributions, and of favourable propeller slipstream/wing interactions. The over-the-wing distributed propulsion system resulted in higher pitching moments, suggesting that moment balancing using different thrust settings and propeller installation positions, or the entire vehicle should be considered to pave the way for practical applications.
This paper presents a peridynamics-based computational approach for modelling coupled fluid flow and heat transfer problems. A new thermo-hydrodynamic peridynamics model is formulated with the semi-Lagrangian scheme and non-local operators. To enhance accuracy and numerical stability, a multi-horizon scheme is developed to introduce distinct horizons for the flow field and thermal field. The multi-horizon scheme helps to capture the convective zone and complex thermal flow pattern while effectively mitigating possible oscillations in temperature. We validate the computational approach using benchmarks and numerical examples including heat conduction, natural convection in a closed cavity, and Rayleigh–Bénard convection cells. The results demonstrate that the proposed method can accurately capture typical thermal flow behaviours and complex convective patterns. This work offers a new foundation for future development of a unified peridynamics framework for robust, comprehensive multi-physics analysis of thermal fluid–solid interaction problems with complex evolving discontinuities in solids.
Miscible Rayleigh–Taylor (RT) turbulence exhibits a wide range of length scales in both the velocity and density fields, leading to complex deformations of isoscalar surfaces and enhanced mixing due to nonlinear interactions among different scales. Through high-resolution numerical simulations and a coarse-graining analysis, we demonstrate that the variance of the heavy fluid concentration, initially maximised by the unstable stratification, progressively cascades from larger to smaller scales, eventually dissipates at the smallest scale. The transfer of scalar variance, $\Pi ^Y$, primarily governed by the filtered strain rate tensor, is effectively captured by a nonlinear model that links $\Pi ^Y$ to the isoscalar surface stretching. On the other hand, the backscatter of scalar variance transfer, represented by the negative component of $\Pi ^Y$, is influenced by the filtered vorticity field. Furthermore, we examine the directional anisotropy of scalar transfer in RT turbulence, enhancing the accuracy of the nonlinear model by separating the horizontal mean of the mass fraction from its fluctuating part.
The dispersion behaviour of solutes in flow is crucial to the design of chemical separation systems and microfluidics devices. These systems often rely on coupled electroosmotic and pressure-driven flows to transport and separate chemical species, making the transient dispersive behaviour of solutes highly relevant. However, previous studies of Taylor dispersion in coupled electroosmotic and pressure-driven flows focused on the long-term dispersive behaviour and the associated analyses cannot capture the transient behaviour of solute. Further, the radial distribution of solute has not been analysed. In the current study, we analyse the Taylor dispersion for coupled electroosmotic and pressure-driven flows across all time regimes, assuming a low zeta potential (electric potential at the shear plane), the Debye–Hückel approximation and a finite electric double layer thickness. We first derive analytical expressions for the effective dispersion coefficient in the long-time regime. We also derive an unsteady, two-dimensional (radial and axial) solute concentration field applicable in the latter regime. We next apply Aris’ method of moments to characterise the unsteady propagation of the mean axial position and the unsteady growth of the variance of the solute zone in all time regimes. We benchmark our predictions with Brownian dynamics simulations across a wide and relevant dynamical regime, including various time scales. Lastly, we derive expressions for the optimal relative magnitudes of electroosmotic versus pressure-driven flow and the optimum Péclet number to minimise dispersion across all time scales. These findings offer valuable insights for the design of chemical separation systems, including the optimisation of capillary electrophoresis devices and electrokinetic microchannels and nanochannels.
This study presents an automatic differentiation (AD)-based optimisation framework for flow control in compressible turbulent channel flows. Using a differentiable solver, JAX-Fluids, we designed fully differentiable boundary conditions that allow for the precise calculation of gradients with respect to boundary control variables. This facilitates the efficient optimisation of flow control methods. The framework’s adaptability and effectiveness are demonstrated using two boundary conditions: opposition control and tunable permeable walls. Various optimisation targets are evaluated, including wall friction and turbulent kinetic energy (TKE), across different time horizons. In each optimisation, there were around $4\times 10^4$ control variables and $3\times 10^{9}$ state variables in a single episode. Results indicate that TKE targeted opposition control achieves a more stable and significant reduction in drag, with effective suppression of turbulence throughout the channel. In contrast, strategies that focus directly on minimising wall friction were found to be less effective, exhibiting instability and increased turbulence in the outer region. The tunable permeable walls also show potential to achieve stable drag reduction through a ‘flux-inducing’ mechanism. This study demonstrates the advantages of AD-based optimisation in complex flow control scenarios and provides physical insight into the choice of the quantity of interest for improved optimisation performance.
We perform a comprehensive linear non-modal stability analysis of the Rayleigh–Bénard convection with and without a Poiseuille/Couette flow in Oldroyd-B fluids. In the absence of shear flow, unlike the Newtonian case in which the perturbation energy decays monotonically with time, the interaction between temperature gradient and polymeric stresses can surprisingly cause a transient growth up to 104. This transient growth is maximized at the Hopf bifurcation when the stationary instability dominant in the weakly elastic regime transitions to the oscillatory instability dominant in the strongly elastic regime. In the presence of a Poiseuille/Couette flow, the streamwise-uniform disturbances may achieve the greatest energy amplification, and similar to the pure bounded shear flows, Gmax ∝ Re2 and tmax ∝ Re, where Gmax is the maximum energy growth, tmax the time to attain Gmax, Re the Reynolds number. It is noteworthy that there exist two peaks during the transient energy growth at high-Re cases. Different from the first one which is less affected by the temperature gradient and elasticity, the second peak, at which the disturbance energy is the largest, is simultaneously determined by the temperature gradient, elasticity and shear intensity. Specifically, the polymeric stresses field absorbs energy from the temperature field and base flow, which is partially transferred into the perturbed hydrodynamic field eventually, driving the transient amplification of the perturbed wall-normal vorticity.
This paper presents the development and implementation of a comprehensive system for acquiring telemetry from Alsat-2A and Alsat-2B satellites, whose orbits are phased 180 degrees apart, utilising the CDM600 demodulator. Integral to this system is an automatic learning module leveraging machine learning algorithms to optimise circular polarisation selection based on reception conditions. The software segment manages the demodulator, user interface, and coordinates the machine learning algorithm, drawing insights from historical polarisation data to construct predictive models for optimal polarisation selection. Through the integration of machine learning, this system aims to enhance telemetry signal reception quality, contributing to the success (Alsat-2A was launched on 12 July 2010, and Alsat-2B on 26 September 2016) of satellite missions.
Feigenbaum universality is shown to occur in subcritical shear flows. Our testing ground is the counter-rotation regime of the Taylor–Couette flow, where numerical calculations are performed within a small periodic domain. The accurate computation of up to the seventh period-doubling bifurcation, assisted by a purposely defined Poincaré section, has enabled us to reproduce the two Feigenbaum universal constants with unprecedented accuracy in a fluid flow problem. We have further devised a method to predict the bifurcation diagram up to the accumulation point of the cascade based on the detailed inspection of just the first few period-doubling bifurcations. Remarkably, the method is applicable beyond the accumulation point, with predictions remaining valid, in a statistical sense, for the chaotic dynamics that follows.
The influence of parametric forcing on a viscoelastic fluid layer, in both gravitationally stable and unstable configurations, is investigated via linear stability analysis. When such a layer is vertically oscillated beyond a threshold amplitude, large interface deflections are caused by Faraday instability. Viscosity and elasticity affect the damping rate of momentary disturbances with arbitrary wavelength, thereby altering the threshold and temporal response of this instability. In gravitationally stable configurations, calculations show that increased elasticity can either stabilize or destabilize the viscoelastic system. In weakly elastic liquids, higher elasticity increases damping, raising the threshold for Faraday instability, whereas the opposite is observed in strongly elastic liquids. While oscillatory instability occurs in Newtonian fluids for all gravity levels, we find that parametric forcing below a critical frequency will cause a monotonic instability for viscoelastic systems at microgravity. Importantly, in gravitationally unstable configurations, parametric forcing above this frequency stabilizes viscoelastic fluids, until the occurrence of a second critical frequency. This result contrasts with the case of Newtonian liquids, where under the same conditions, forcing stabilizes a system for all frequencies below a single critical frequency. Analytical expressions are obtained under the assumption of long wavelength disturbances predicting the damping rate of momentary disturbances as well as the range of parameters that lead to a monotonic response under parametric forcing.
We explore the instability and oscillation dynamics of barrel-shaped droplets on cylindrical fibres, contributing to a deeper understanding of fibre–droplet interactions critical to both natural systems and industrial applications. Unlike sessile droplets on flat surfaces, droplets on fibres exhibit unique behaviours due to the curvature of the fibre, such as transitions from axisymmetric (barrel) to non-axisymmetric (clamshell) shapes governed by droplet volume, contact angle and fibre radius. Using a linear inviscid theory, we compute the frequency spectrum of barrel-shaped droplets and identify stability thresholds for the barrel-to-clamshell transition by examining the first rocking mode, with a focus on the role of contact line conditions. This analysis resolves experimental anomalies concerning the stability of half-barrel-shaped droplets on hydrophobic fibres. Our findings also reveals diverse frequency spectra: droplets on thin fibres exhibit Rayleigh–Lamb-like spectral features, while those on thicker fibres show reduced sensitivity to azimuthal wavenumber. Interestingly, the instability of sectoral modes on thick fibres resembles the Rayleigh–Plateau instability of static rivulets, with fibre curvature slightly reducing growth rates at small axial wavenumbers but increasing them at larger ones.
Being thicker and lighter than the oceanic lithosphere, the continental lithosphere exerts a thermal blanket effect on the convective mantle by locally accumulating heat and altering the flow structure, which in turn affects continent motion. This thermal–mechanic feedback has been studied through a simplified model of a thermally insulating plate floating over a bottom-heated convective fluid, which shows that plate mobility enhances with plate size and a unidirectionally moving mode (UMM) emerges for sufficiently large plates. Nevertheless, apart from bottom heating, the mantle is also subject to internal heating induced by radioactive decay. How the addition of internal heating affects the dynamic coupling is still unclear, which motivates the present study. Numerical simulation results show that the effect varies with plate size. For small plates, as internal heating intensifies, plate motion becomes increasingly persistent and the critical plate size for the UMM decreases. This results from the enhanced thermal blanket effect under intensified internal heating, which enables a faster generation of hot plumes to boost plate motion during its slowdown. Most notably, the addition of internal heating brings a new mode for large plates – a permanently stagnant mode (PSM) – in which the plate oscillates permanently above a hot up-welling with down-wellings locating far away. The critical size for the PSM decreases as internal heating intensifies. In the PSM, the symmetry between cold and hot plumes breaks. Implications of these findings for the dynamic coupling on Earth and Mars are discussed.
A new lattice Boltzmann model (LBM) is presented to describe chemically reacting multicomponent fluid flow in homogenised porous media. In this work, towards further generalising the multicomponent reactive lattice Boltzmann model, we propose a formulation which is capable of performing reactive multicomponent flow computation in porous media at the representative elementary volume (REV) scale. To that end, the submodel responsible for interspecies diffusion has been upgraded to include Knudsen diffusion, whereas the kinetic equations for the species, the momentum and the energy have been rewritten to accommodate the effects of volume fraction of porous media through careful choice of the equilibrium distribution functions. Verification of the mesoscale kinetic system of equations by a Chapman–Enskog analysis reveals that at the macroscopic scale, the homogenised Navier–Stokes equations for compressible multicomponent reactive flows are recovered. The dusty gas model (DGM) capability hence formulated is validated over a wide pressure range by comparison of experimental flow rates of component species counter diffusing through capillary tubes. Next, for developing a capability to compute heterogeneous reactions, source terms for maintaining energy and mass balance across the fluid phase species and the surface adsorbed phase species are proposed. The complete model is then used to perform detailed chemistry simulations in porous electrodes of a solid oxide fuel cell (SOFC), thereby predicting polarisation curves which are of practical interest.
The effect of nucleation on cavitation inception in a high-Reynolds-number von Kármán wake from a bluff two-dimensional hydrofoil is studied experimentally in a variable pressure water tunnel. Nucleation effects are studied by seeding the flow with sparse monodisperse nuclei populations, with the critical pressure nominally equal to vapour pressure. The injected nuclei population and incipient cavitation events were imaged simultaneously using high-speed cameras to precisely quantify the number of activated nuclei of the total available. Three-dimensional spatial characterisation (orientation and location) of the incipient structures is obtained using two high-speed cameras mounted to the side and below the tunnel test section. Inception was observed predominantly in the stretched cores of secondary structures, with a negligible proportion of events occurring in the primary vortices. A broad peak in the vertical angle distribution is observed about the streamwise axis; however, events at all angles are seen. A symmetric distribution was observed for the horizontal angle, with a dominant orientation $45^{\circ }$ from the free-stream direction. The majority of events occur at approximately one hydrofoil thickness downstream of the hydrofoil trailing edge, with a bimodal symmetric distribution about the hydrofoil vertical centre plane. Nuclei activation rate is determined from the acoustic measurements, and was found to be proportional to the number of the injected nuclei. A power law increase in activation rate was observed following a decrease in cavitation number and an increase in Reynolds number. The nuclei activation rate was of the order of $0.1{-}10 \, \mathrm {s^{-1}}$, which combined with seeding rates of the orderof $100{-}1000 \, \mathrm {s^{-1}}$ reveals inception to be a rare occurrence (0.001 %–10 % of nuclei being activated), requiring the confluence of two unlikely events, the occurrence of a subvapour pressure vortex core with capture of a sufficiently weak nuclei. The presented study provides new insights into the physics of cavitation nucleation and inception and provides a comprehensive dataset for development of computational models.
This publication presents the results of a numerical analysis aimed at assessing the applicability of thermal tip clearance control (TCC) to the fore-to-last stage of a 10-stage high-pressure compressor system. The chosen geometry is representative for the HPC rear stages of a modern middle-sized turbofan, designed for large business jets and regional airliners. Simplified models for two TCC concepts were implemented, isolated and in combination: external impingement cooling and heat pipes. The analysis was performed by means of finite-element thermostructural simulations. Transient operational cycles, derived from a meanline model, along with empiric correlations for heat convection provided the required boundary conditions. Qualitative similarity to selected previous works in terms of temperature, stress and clearance evolutions was achieved. The combination of concepts demonstrated its potential as a TCC system with up to 0.45% reductions in rotor and stator clearances. Calculated heat pipe temperatures and heat fluxes were inside the estimated operational limitations. Regarding stresses, some local concentrations were observed, without significant impact in critical stress regions. A slam cycle analysis showed that, while blade rubbing remains a possibility, it can be mitigated by robust cooling control. All in all, the concept was deemed worthy of more detailed studies.
We experimentally identify a rotational motion of a single microalga (Chlamydomonas reinhardtii) within a microcontainer believed to be induced by one defective flagellum. We numerically adapt the classic two-dimensional squirmer model to replicate this unique motion by partially inhibiting the slip velocity on the boundaries of the squirmer. Subsequently, we employ a lattice Boltzmann method to simulate the motion of the single microalga with one defective flagellum. We examine the influence of swimming Reynolds numbers, self-propelling strength ($\beta$) and angle ($\alpha$) on the locomotion of the squirmer with one defective flagellum. The results indicate that a large $\beta$ leads to a large rotational diameter, positively correlating with the speed. Additionally, we observe that a low self-propelling strength ($\beta =0.5$) yields a monotonically increasing speed for the squirmer with $\alpha$. In general, high $\beta$ values result in fast speeds for the squirmer. This differs from the behaviour observed in a classic squirmer ($\alpha =360^{\circ }$), where high $\beta$ leads to a slow speed of puller ($\beta \gt 0$) owing to weak fluid inertia effects. Meanwhile, the energy expenditure increases monotonically with $\alpha$, contrasting with the non-monotonic trends observed for swimming speed and rotational diameter.