Measurement of surface shear stress vector distribution using shear-sensitive liquid crystal coatings

The global wall shear stress measurement tech- nique using shear-sensitive liquid crystal （SSLC） is extended to wind tunnel measurements. Simple and common every- day equipment is used in the measurement; in particular a tungsten-halogen light bulb provides illumination and a saturation of SSLC coating color change with time is found. Spatial wall shear stress distributions of several typical flows are obtained using this technique, including wall-jet flow, vortex flow generated by a delta wing and junction flow behind a thin cylinder, although the magnitudes are not fully calibrated. The results demonstrate that SSLC technique can be extended to wind tunnel measurements with no complicated facilities used.

Application of shear-sensitive liquid crystal coating to visualization of transition and reattachment in compressor cascade

The present paper aims at introducing Shear-Sensitive Liquid Crystal Coating(SSLCC)technology into compressor cascade measurement for the first time and serves as a basis for better understanding of the influence from the boundary layers. Optical path layout, which is the most significant difficulty in internal flow field measurement, will be solved in this paper by selfdesigned image acquisition device. Massive experiments with different Mach number and incidence are conducted at a continuous subsonic cascade wind tunnel to capture the boundary layer phenomenon. Image processing methods, such as Three-Dimensional(3-D) reconstruction and Hue conversion, are used to improve the accuracy for transition position detection. The analysis of the color-images indicates that complex flow phenomena including transition, flow separation,and reattachment are captured successfully, and the effect of Mach number and incidence on the boundary layer flow is also discussed. The results show that: the Mach number has a significant effect on transition position; the incidence has little effect on transition position, but it has a great impact on the transition distance and leading-edge separation; influenced by the end-walls, the reattachment occurs in advance under positive angle of attack conditions.

A learning-based approach for solving shear stress vector distribution from shear-sensitive liquid crystal coating images

A learning-based approach for solving wall shear stresses from Shear-Sensitive Liquid Crystal Coating(SSLCC) color images is presented in this paper. The approach is able to learn and establish the mapping relationship between the SSLCC color-change responses in different observation directions and the shear stress vectors, and then uses the mapping relationship to solve wall shear stress vectors from SSLCC color images. Experimental results show that the proposed approach can solve wall shear stress vectors using two or more SSLCC images, and even using only one image for symmetrical flow field. The accuracy of the approach using four or more observations is found to be comparable to that of the traditional multi-view Gauss curve fitting approach;the accuracy is slightly reduced when using two or fewer observations. The computational efficiency is significantly improved when compared with the traditional Gauss curve fitting approach, and the wall shear stress vectors can be solved in nearly real time. The learning-based approach has no strict requirements on illumination direction and observation directions and is therefore more flexible to use in practical wind tunnel measurement when compared with traditional liquid crystal-based methods.