Two-phase flow patterns and pressure drop inside horizontal tubes containing twisted-tape inserts

This paper presents an experimental study on two-phase flow patterns and pressure drop of R134a inside a 15.9 mm ID tube containing twisted-tape inserts. Experimental results were obtained in a horizontal test section for twisted-tape ratios of 3, 4, 9 and 14, mass velocities ranging from 75 to 250 kg/m(2) s and saturation temperatures of 5 and 15 degrees C. An unprecedented discussion on two-phase flow patterns inside tubes containing twisted-tape inserts is presented and the flow pattern effects on the frictional pressure drop are carefully discussed. Additionally, a new method to predict the frictional pressure drop during two-phase flow inside tubes containing twisted-tape inserts is proposed. (C) 2012 Elsevier Ltd. All rights reserved.

Evaluation of peak cough flow in Brazilian healthy adults

Abstract Introduction In this study we aimed to evaluate the peak cough flow (PCF) in healthy Brazilian subjects. Methods We evaluated 484 healthy subjects between 18 and 40 years old. Subjects were seated and oriented were asked to perform a maximal inspiration followed by a quick, short and explosive expiration on the peak flow meter. Three measures were carried out and recorded the average of the three results for each individual. Results The PCF values ranged between 240 and 500 L/min. The PCF values were lower in females than in males. The PCF was inversely proportional to age. Conclusion The values for Brazilian adult healthy subjects regarding PCF were between 240 and 500 L/min.

Dynamic texture segmentation based on deterministic partially self-avoiding walks

Recently there has been a considerable interest in dynamic textures due to the explosive growth of multimedia databases. In addition, dynamic texture appears in a wide range of videos, which makes it very important in applications concerning to model physical phenomena. Thus, dynamic textures have emerged as a new field of investigation that extends the static or spatial textures to the spatio-temporal domain. In this paper, we propose a novel approach for dynamic texture segmentation based on automata theory and k-means algorithm. In this approach, a feature vector is extracted for each pixel by applying deterministic partially self-avoiding walks on three orthogonal planes of the video. Then, these feature vectors are clustered by the well-known k-means algorithm. Although the k-means algorithm has shown interesting results, it only ensures its convergence to a local minimum, which affects the final result of segmentation. In order to overcome this drawback, we compare six methods of initialization of the k-means. The experimental results have demonstrated the effectiveness of our proposed approach compared to the state-of-the-art segmentation methods.