We investigated numerically flow patterns in the air suction gun and dependence of the flow pattern on the supplied air pressure in order to clarify the working mechanism of an air suction gun. The compressed air issued from compressed-air inflow tubes into a yarn passage accelerates with sucked ambient air owing to negative pressure generated by the compressed air, and attains a critical speed near the throat of the de Laval tube and a supersonic speed in the divergent part of the de Laval tube. The supersonic flow generates a normal shock wave and changes into a subsonic flow. Then, the air is discharged into the atmosphere. Since this compressed air has a circumferential component, it forms a helical flow along the wall of the yarn propulsion tube composed of the de Laval tube and the straight tube. Velocity and density of the helical airflow near the wall are larger than those near the centerline. The suction efficiency is promoted greatly owing to this high focusing ability (bias of high speed and density flow toward the vicinity of the wall) and a large yarn length in the helical airflow. Increased supplied air pressure brings about increases in both air density and supersonic flow region, which promotes the yarn suction force.

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We propose a new method to enhance the cloth stain, such as the weak coffee stain in image. Our method is composed of two steps. At the first step, we obtain the principal component images by making the RGB components of each pixel to be uncorrelated. At this step, the texture structure is still left in the uncorrelated images, so it is difficult to recognize the stain. Then, at the second step, we reduce the texture structure by using Principal Component Analysis. We divide the uncorrelated images into the blocks, and those blocks are approximated by several principal eigen vectors which represent the texture structure. The approximation image represents the average texture structure without the cloth stain. So, the cloth stain is recognized without endeavor in the residual image which is obtained by subtracting the approximation image from the principal component image. As our method is robust for the number of observation data, we need only one color image whose size is not so big and whose resolution is not so high. The results of our experiment under different conditions show that the proposed method is effective for the image enhancement of the small weak cloth stain.

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A forming method of spherical fiber assembly using carbon fibers was devised, and the microorganism adhesive property was evaluated for application as a garbage disposer substrate. Examination of the relationship between the density and microorganism adhesive property of the obtained spherical fiber assembly revealed that the adhesion of bacteria increases as the density increases. It was confirmed that a spherical fiber assembly using carbon fibers can be used as a substrate in a garbage disposer, which is reproducible. Moreover, by supplying water in the processing tank, the growth of bacteria was promoted comparably to a case using woodchips as a substrate.

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Thickness-recovery behaviors of tufted artificial turf with long pile for static loading were examined. A novel thickness gauge with circular presser foot of 82mm diameter and capable of measuring thickness to an accuracy of 0.01 mm at standard pressure of 0.10 kPa was designed for tufted artificial turf with long pile. Static loading tests were carried out by using an equipment improved static loading machine as defined in ISO 3416. The static loading equipment was capable of applying a pressure of 50 kPa through a steel square pressure foot of 120mm×120mm. Experiments were conducted using samples - tufted artificial turfs with long pile of five types - to determine characteristics on thickness loss and recovery behaviors for static loading. Thickness-recovery behaviors obtained from each sample were able to use an approximation with exponential equation and apply the simplest Voigt element model. Retardation times calculated from a Voigt element equation considering thickness loss after prolonged - recovery period of 24 hours - indicated rational results.

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