What question did this study set out to answer?

The study aims to evaluate the effect of surface geometry and roughness on lubrication and friction.

January 14, 2026

Study on Mixed Lubrication Properties and Geometric Parameters Optmisation of the Bionic Shield Scale Textured Surface With Non‐ G aussian Surface Roughness

SHSenao HeXi'an University of Technology QWQ. Y. WangXi'an University of Technology LWLei WangTongji University

Key Points

The study aims to evaluate the effect of surface geometry and roughness on lubrication and friction.
Designed asymmetric, converging–diverging shield scale surface textures.
Conducted numerical modelling and experimental validation of tribological performance.
Employed genetic algorithms and artificial neural networks for parameter optimisation of textures.
Investigated different geometric parameters including area ratio and depth gradient.
Optimised shield scale textures showed better lubrication performance than unoptimised samples.
Numerical predictions aligned with experimental results in terms of friction behaviour.
Surface textures were fabricated using laser surface texturing techniques.

Abstract

ABSTRACT Inspired by the structure of shield scales on the surface of a shark skin, a surface texture of the shield scale with asymmetric, converging–diverging depth profiles is designed and its tribological performance is investigated through a combination of numerical modelling, optimisation and experimental validation. The primary objective is to explore how complex depth‐direction geometries and non‐Gaussian surface roughness influence lubrication and friction behaviour under mixed lubrication conditions. To this end, a comprehensive numerical model is developed, which incorporates a modified Reynolds equation with mass‐conserving cavitation (JFO) boundary conditions, coupled with a Kogut–Etsion contact model and a statistical description of non‐Gaussian surface roughness using skewness and kurtosis. Using the developed numerical model, the lubrication performance of bionic shield scale texture with different geometric parameters has been calculated. Then a hybrid method combining artificial neural networks (ANN) and genetic algorithms (GA) is employed to optimise the geometric parameters of bionic shield scale texture and the optimal combination of area ratio, depth gradient and aspect ratio has been found. Representative samples with circle, hexagon and shield scale textures are fabricated by laser surface texturing technique and comparison tribology experiments are carried out. The better performance of the shield scale texture with optimised parameters is observed, which is consistent with numerical predictions.

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