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  1. Pressure is important in virtually all problems in fluid dynamics from macro-scale to micro/nano-scale flows. Although technologies are well developed for its measurement at the macroscopic scale, pressure quantification at the microscopic scale is still not trivial. This study reports the design and fabrication of an on-chip sensor that enables quantification of pressure in microfluidic devices based on a novel technique called astigmatic particle tracking. With this technique, thin membranes that sense pressure variations in the fluid flow can be characterized conveniently by imaging the shapes of the particles embedded in the membranes. This innovative design only relies on the reflected light from the back of the microchannel, rendering the sensor to be separate and noninvasive to the flow of interest. This sensor was then applied to characterize the pressure drop in single-phase flows with an accuracy of ∼70 Pa and good agreement was achieved between the sensor, a commercial pressure transducer and numerical simulation results. Additionally, the sensor successfully measured the capillary pressure across an air–water interface with a 7% deviation from the theoretical value. To the best of our knowledge, this pore-scale capillary pressure quantification is achieved for the first time using an on-chip pressure sensor of this kind. This study provides a novel method for in situ quantification of local pressure and thus opens the door to a renewed understanding of pore-scale physics of local pressure in multi-phase flow in porous media. 
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  2. Fluid–structure interaction (FSI) plays a significant role in the deformation of flapping insect wings. However, many current FSI models are high-order and rely on direct computational methods, thereby limiting parametric studies as well as insights into the physics governing wing dynamics. We develop a novel flapping wing FSI framework that accommodates general wing geometry and fluid loading. We use this framework to study the unilaterally coupled FSI of an idealized hawkmoth forewing considering two fluid models: Reynolds-averaged Navier–Stokes computational fluid dynamics (RANS CFD) and blade element theory (BET). We first compare aerodynamic modal forces estimated by the low-order BET model to those calculated via high fidelity RANS CFD. We find that for realistic flapping kinematics, BET estimates modal forces five orders of magnitude faster than CFD within reasonable accuracy. Over the range flapping kinematics considered, BET and CFD estimated modal forces vary maximally by 350% in magnitude and approximately π/2 radians in phase. The large reduction in computational time offered by BET facilitates high-dimensional parametric design of flapping-wing-based technologies. Next, we compare the contributions of aerodynamic and inertial forces to wing deformation. Under the unilateral coupling assumption, aerodynamic and inertial-elastic forces are on the same order of magnitude—however, inertial-elastic forces primarily excite the wing’s bending mode whereas aerodynamic forces primarily excite the wing’s torsional mode. This suggests that, via conscientious sensor placement and orientation, biological wings may be able to sense independently inertial and aerodynamic forces. 
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