Characteristics of mean droplet size of spray produced by spinning disk atomizers were experimentally investigated. The phase-doppler particle analyzer (PDPA) was used to measure the droplet size of water spray in the downstream distance along the spray trajectory. Effects of various operating conditions on the mean diameter had been studied. The studied variables were: the rotational speed in the range of 838 to 1677 rad/s (8,000–16,000 rpm), the liquid flow rate in the range of 0.56 to 2.8  106 m3/s (2–10 L/h), the disk diameter in the range of 0.04 to 0.12 m, and the downstream tangential distance along the spray trajectory of up to 0. 24 m. The Sauter mean diameter (d32) was used to represent the mean of generated spray droplet sizes. The results indicated that the Sauter mean diameter can be correlated with dimensionless groups, such as the Reynolds number, Weber number, flow coefficient, and the ratio of downstream distance to disk diameter. Based on this correlation, it was found that the Sauter mean diameter (d32) increases as the downstream tangential distance, and liquid flow rate increase. Similarly, a decrease of rotational speed and disk diameter results in an increase in the Sauter mean diameter (d32). A comparison between the developed correlation and correlations obtained by other researchers has been presented and discussed in detail. [DOI: 10.1115/1.4006819]

Vertical loads effect on the lateral response of a 3× 5 pile group embedded in sand is studied through a two-dimensional finite element analysis. The soil-pile interaction in three- dimensional type is idealized in the two-dimensional analysis using soil-pile interaction springs with a hysteretic nonlinear load displacement relationship. Vertical loads inducing a vertical pile head displacement of 0.1-pile diameter increase the lateral resistance of the single pile at a 60 mm lateral deflection by 8%. Vertical loads inducing the same vertical .

We propose an automatic pose invariant approach for Face Recognition At a Distance (FRAD). Since face alignment is a crucial step in face recognition systems, we propose a novel facial features extraction model, which guides extended ASM to accurately align the face. Our main concern is to recognize human faces under uncontrolled environment at far distances accurately and fast. To achieve this goal, we perform an offline stage where 3D faces are reconstructed from stereo pair images. These 3D shapes are used to synthesize virtual 2D views in novel poses. To obtain good synthesized images from the 3D shape, we propose an accurate 3D reconstruction framework, which carefully handles illumination variance, occlusion, and the disparity discontinuity. The online phase is fast where a 2D image with unknown pose is matched with the closest virtual images in sampled poses. Experiments show that our approach outperforms the-state-of-the-art approaches.