Hugo Pineda

Bamboo fiber composite (BFC) is a unidirectional and continuous bamboo fiber composite manufactured by consolidation and gluing of flattened, partially separated bamboo culm strips into thick and dense panels. The composite mechanical properties are primarily influenced by panel density, its variation and uniformity. This paper characterized the horizontal density distribution (HDD) within BFC panels and its controlling factors. It revealed that HDD follows a normal distribution, with its standard deviation (SD) strongly affected by sampling specimen size, panel thickness and panel locations. SD was lowest in the thickest (40 mm) panel and largest-size (150 × 150-mm²) specimens. There was also a systematic variation along the length of the BFC due to the tapering effect of bamboo culm thickness. Density was higher along panel edges due to restraint from the mold edges during hot pressing. The manual BFC mat forming process is presented and found to effectively minimize the density variation compared to machine-formed wood composites. This study provides a basic understanding of and a quality control guide to the formation uniformity of BFC products.

A way to predict two-phase liquid-gas flow patterns is presented for horizontal, vertical and inclined pipes. A set of experimental data (7702 points, distributed among 22 authors) and a set of synthetic data generated using OLGA Multiphase Toolkit v.7.3.3 (59 674 points) were gathered. A filtering process based on the experimental void fraction was proposed. Moreover, a classification of the pattern flows based on a supervised classification and a probabilistic flow pattern map is proposed based on a Bayesian approach using four pattern flows: Segregated Flow, Annular Flow, Intermittent Flow, and Bubble Flow. A new visualization technique for flow pattern maps is proposed to understand the transition zones among flow patterns and provide further information than the flow pattern map boundaries reported in the literature. Following the methodology proposed in this approach, probabilistic flow pattern maps are obtained for oil–water pipes. These maps were determined using an experimental dataset of 11 071 records distributed among 53 authors and a numerical filter with the water cut reported by OLGA Multiphase Toolkit v7.3.3.

This study presents the results of a Computational Fluid Dynamics (CFD) simulation of two-phase medium viscosity oil-air flow in a 50.8 mm internal diameter horizontal pipe. Void fraction and pressure gradient predictions were validated using experimental data for four different oil viscosities (0.039, 0.06, 0.108 and 0.166 Pa s) and different flow rates varying from 0.1 to 2.9 m/s for the gas phase and from 0.01 to 2.95 m/s for the liquid phase, where four flow patterns were predicted (stratified, dispersed bubble, bubble elongated and slug flow). The obtained results of void fraction and pressure gradient presented a mean relative error of 30.04 and 21.38%, respectively. Furthermore, the CFD results were compared against 66 empirical correlations and predictions from OLGA. It was found that between the three studied methods (CFD, OLGA and empirical correlations) the CFD model outperformed the other two methods regarding the predicted flow patterns, pressure gradients and void fractions on most cases.