IC-integrated flexible shear-stress sensor skin

This paper reports the successful development of the first IC-integrated flexible MEMS shear-stress sensor skin. The sensor skin is 1 cm wide, 2 cm long, and 70 /spl mu/m thick. It contains 16 shear-stress sensors, which are arranged in a 1-D array, with on-skin sensor bias, signal-conditioning, and multiplexing circuitry. We further demonstrated the application of the sensor skin by packaging it on a semicylindrical aluminum block and testing it in a subsonic wind tunnel. In our experiment, the sensor skin has successfully identified both the leading-edge flow separation and stagnation points with the on-skin circuitry. The integration of IC with MEMS sensor skin has significantly simplified implementation procedures and improved system reliability

A discontinuity and cusp capturing PINN for Stokes interface problems with discontinuous viscosity and singular forces

In this paper, we present a discontinuity and cusp capturing physics-informed neural network (PINN) to solve Stokes equations with a piecewise-constant viscosity and singular force along an interface. We first reformulate the governing equations in each fluid domain separately and replace the singular force effect with the traction balance equation between solutions in two sides along the interface. Since the pressure is discontinuous and the velocity has discontinuous derivatives across the interface, we hereby use a network consisting of two fully-connected sub-networks that approximate the pressure and velocity, respectively. The two sub-networks share the same primary coordinate input arguments but with different augmented feature inputs. These two augmented inputs provide the interface information, so we assume that a level set function is given and its zero level set indicates the position of the interface. The pressure sub-network uses an indicator function as an augmented input to capture the function discontinuity, while the velocity sub-network uses a cusp-enforced level set function to capture the derivative discontinuities via the traction balance equation. We perform a series of numerical experiments to solve two- and three-dimensional Stokes interface problems and perform an accuracy comparison with the augmented immersed interface methods in literature. Our results indicate that even a shallow network with a moderate number of neurons and sufficient training data points can achieve prediction accuracy comparable to that of immersed interface methods

A parametrized three-dimensional model for MEMS thermal shear-stress sensors

This paper presents an accurate and efficient model of MEMS thermal shear-stress sensors featuring a thin-film hotwire on a vacuum-isolated dielectric diaphragm. We consider three-dimensional (3-D) heat transfer in sensors operating in constant-temperature mode, and describe sensor response with a functional relationship between dimensionless forms of hotwire power and shear stress. This relationship is parametrized by the diaphragm aspect ratio and two additional dimensionless parameters that represent heat conduction in the hotwire and diaphragm. Closed-form correlations are obtained to represent this relationship, yielding a MEMS sensor model that is highly efficient while retaining the accuracy of three-dimensional heat transfer analysis. The model is compared with experimental data, and the agreement in the total and net hotwire power, the latter being a small second-order quantity induced by the applied shear stress, is respectively within 0.5% and 11% when uncertainties in sensor geometry and material properties are taken into account. The model is then used to elucidate thermal boundary layer characteristics for MEMS sensors, and in particular, quantitatively show that the relatively thick thermal boundary layer renders classical shear-stress sensor theory invalid for MEMS sensors operating in air. The model is also used to systematically study the effects of geometry and material properties on MEMS sensor behavior, yielding insights useful as practical design guidelines