Fluid–Structure Interaction of High Aspect-Ratio Hair-Like Micro-Structures Through Dimensional Transformation Using Lattice Boltzmann Method

3D printed hair-like micro-structures have been previously demonstrated in a novel micro-fluidic flow sensor aimed at sensing air flows down to rates of a few milliliters per second. However, there is a lack of in-depth understanding of the structural response of these ‘micro-hairs' under a fluid flow field. This paper demonstrates the use of lattice Boltzmann methods (LBM) to understand this structural response towards a better optimization of the micro-hair flow sensors designed to suit the end applications' needs. The LBM approach was chosen as an efficient alternative to simulate Navier–Stokes equations for modeling fluid flow around complex geometries primarily for improved accuracy and simplicity with lesser computational costs. As the spatial dimensions of the sensor's flow channel are much larger in comparison to the actual micro-hairs (the sensing element), a multidimensional approach of combining two-dimensional (D2Q9) and three-dimensional (D3Q19) lattice configurations were implemented for imp...