A mapping technique for enhancing the visualisation and analysis of the flow structure in regions near the wall is presented. After identifying a near-wall region of interest, the output of the proposed mapping technique is an analytical expression of the flow variables, satisfying the governing PDEs and boundary conditions, on a stencil of standardised morphology.The approach firstly involves selecting a local surface region of interest from the computational domain to be mapped. Subsequently a structured mesh of arbitrary height on top of the cropped surface is generated, thus forming the target volume region, which is termed the physical space. The solution data comprising of flow properties such as velocity and pressure from the computational domain is interpolated onto the physical space. The physical space and the data are consequently mapped onto an unwrapped domain with standard shape, termed the mapped space. For simplicity, the mapped space is chosen here to be a cuboid. Finally, the data is expressed as a best fit polynomial, satisfying the governing PDEs and boundary conditions.The method is validated by direct pointwise comparison and from the velocity streamlines mapped from the physical space, for a set of test problems. The mapping technique effectiveness is demonstrated firstly on a 90 degree bend pipe as a benchmark investigation and subsequently on a nasal cavity anatomy. For the latter, three scenarios covering different flow structures in the near-wall region are scrutinised, demonstrating the ability of the techniques proposed to uncover the details of the near-wall flow in complex physiological flows. The regions of interest can be identified using near-wall measures such as wall shear stress, shear lines, and wall shear stress critical points.The mapping technique has potential applications in the fields of fluid dynamics and specifically near-wall flows, as the interface region describing the dynamics of exchanges. It is furthermore capable of inferring the velocity field from reduced data available to enhance the use of deep learning or regression methods.

We consider the scattering of in-plane waves that interact with an edge of a structured penetrable inertial line defect contained in a triangular lattice, composed of periodically placed masses interconnected by massless elastic rods. The steady state problem for a time-harmonic excitation is converted into a vector Wiener–Hopf equation using the Fourier transform. The matrix Wiener–Hopf kernel of this equation describes the dynamic phenomena engaged in the scattering process, which includes instances where localised interfacial waves can emerge along the structured defect. This information is exploited to identify the dependency of the existence of these waves on the incident wave parameters and the properties of inertial defect. Symmetry in the structure of the scattering medium allows us to convert the vectorial problem into a pair of uncoupled scalar Wiener–Hopf equations posed along the lattice row containing the defect. The solution embodies an exact representation of the scattered field, in terms of a contour integral in the complex plane, that includes the contributions of evanescent and propagating waves. The solution reveals that in the remote lattice, the reflected and transmitted components of incident field are accompanied by dynamic modes from three symmetry classes, which include localised interfacial waves. These classes correspond to tensile modes acting transverse to the defected lattice row, shear modes that act parallel to this row, and wave modes represented as a mixture of these two responses. Benchmark finite element calculations are also provided to validate the results against our semi-analytical solution which involves, in particular, numerical computation of the contour integrals. Graphical illustrations demonstrate special dynamic responses encountered during the wave scattering process, including dynamic anisotropy, negative reflection and negative refraction.

Soft transduction technology is rapidly adopting soft active elastomer-based minimum energy structures because of their distinctive programmable shape-morphing characteristics. For effective device design, an understanding of the nonlinear dynamic behavior is crucial as they often experience time-dependent motion while operating. Moreover, there has been an increasing scientific interest in enhancing the actuation performance of soft active elastomers by imparting particle reinforcements. This article provides a theoretical framework for investigating the nonlinear dynamics of smart composite elastomer-based minimum energy structures (SCEMES) with the provision of non-aligned electric and magnetic fields, leading to an actively programmable pre-stretch paradigm. Unlike conventional actuators, the proposed SCEMES is made up of a polymer that has electro-magnetic properties and is filled with appropriate fillers with specific volume fractions. An electromagneto-viscoelastic model is developed here to predict actuator behavior and investigate the effects of particle reinforcement on equilibrium and actuated configurations. Besides strengthening the polymer, particle reinforcement is observed to enhance the equilibrium angle achieved by the structure with enhanced functionality. The proposed nonlinear dynamic model is extended to investigate a number of critically influential parameters, including shear modulus ratio of fiber to matrix, frame bending stiffness, membrane pre-stretching, and electro-magnetic loading with time-dependent DC and AC modes of actuation. The results reveal that the combined electro-magnetic actuation enhances the actuation range significantly. The attained tip angle of the actuator increases appreciably when the magnetic and electric fields are applied mutually perpendicular to each other, indicating that the direction of applied magnetic field governs the attained actuated configuration. Further, particle reinforcement enrichments result in a depletion in oscillation amplitudes and an increase in excitation frequencies under the AC actuation mode. The efficient semi-analytical framework presented here would be crucial in developing new actuators, smart devices and soft robots for a variety of advanced engineering and medical applications.