flow front
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Abstract Determination of permeability of thick-section glass fabric preforms with fabric layers of different architectures is critical for manufacturing large, thick composite structures with complex geometry, such as wind turbine blades. The thick-section reinforcement permeability is inherently three-dimensional and needs to be obtained for accurate composite processing modeling and analysis. Numerical simulation of the liquid stage of vacuum-assisted resin infusion molding (VARIM) is important to advance the composite manufacturing process and reduce processing-induced defects. In this research, the 3D permeability of thick-section E-glass fabric reinforcement preforms is determined and the results are validated by a comparison between flow front progressions from experiments and from numerical simulations using ANSYS Fluent software. The orientation of the principal permeability axes were unknown prior to experiments. The approach used in this research differs from those in literature in that the through-thickness permeability is determined as a function of flow front positions along the principal axes and the in-plane permeabilities and is not dependent on the inlet radius. The approach was tested on reinforcements with fabric architectures which vary through-the-thickness direction, such as those in a spar cap of a wind turbine blade. The computational simulations of the flow-front progression through-the-thickness were consistent with experimental observations.

Abstract This paper presents a new approach to formulating an analytical model for the underfill process in flip-chip packaging to predict the flow front and the filling time. The new approach is based on the concept of surface energy along with the energy conservation principle. This approach avoids the need of modeling the flow path to predict the flow front and the filling time and thus it is suitable to different configurations of solder bumps, including different shapes and arrangements of solder bumps in flip-chip packaging. An experiment along with the CFD simulation was performed based on a proprietarily developed testbed to verify the effectiveness of this approach. Both the experimental and simulation results show that the proposed approach along with its model is accurate for flip-chip packages with different configurations besides the configuration of a regular triangle arrangement of solder bumps and a spherical shape of the solder bump.

AbstractFerrovolcanism, yet to be directly observed, is the most exotic and poorly understood predicted manifestation of planetary volcanism. Large-scale experiments carried out at the Syracuse Lava Project offer insight into the emplacement dynamics of metallic flows as well as coeval metallic and silicate flows. Here, we find that, under the same environmental conditions, higher-density/lower-viscosity metallic lava moves ten times faster than lower-density/higher-viscosity silicate lava. The overall morphology of the silicate flow is not significantly affected by the co-emplacement of a metallic flow. Rather, the metallic flow is largely decoupled from the silicate flow, occurring mainly in braided channels underneath the silicate flow and as low-relief breakouts from the silicate flow front. Turbulent interactions at the metallic-silicate flow interface result in mingling of the two liquids, preserved as erosional surfaces and sharp contacts. The results have important implications for the interpretation of possible ferrovolcanic landscapes across our solar system.

Steep-creek beds are macroscopically rough. This roughness causes channelised flow material to decelerate and dissipate energy, which are accounted for by depth-averaged mobility models (DMM). However, practical DMM implementations do not explicitly account for grain-scale basal interactions which influence macroscopic flow dynamics. In this study, we model flows using physical tests with smooth and macroscopically rough bases, and hence evaluate Discrete Element Method (DEM) and DMM models. A scaling effect is identified relating to roughened beds: increasing the number of grains per unit depth tends to suppress dispersion, such that small-scale flows on smooth beds resemble large-scale flows on roughened beds, at least in terms of bulk density. Furthermore, the DEM shows that rougher beds reduce the peak bulk density by up to 15% compared to a smooth bed. Rough beds increase the vertical momentum transfer tenfold, compared to smooth ones. The DMM cannot account for density change or vertical momentum, so DMM flow depths are underestimated by 90% at the flow front and 20% in the body. The Voellmy model implicitly captures internal energy dissipation for flows on rough beds. The parameter ξ can allow velocity reductions due to rough beds observed in the DEM to be captured.

Abstract. Vacuum Assisted Resin Infusion (VARI) process is suitable for manufacturing complex large-scale composite structures and has the potential for low cost and mass production. However, the inappropriate process parameters such as incomplete resin flow and the uneven cure occurred will lead to some defects such as dry spots and delamination. In the present work, the concept of Networked Elements for Resin Visualization and Evaluation (NERVE) with the piezoelectric lead-zirconate-titanate (PZT) sensors as the base unit was used to monitor the internal state of composite struture during its life-time. The capability of PZT sensors in the NERVE to monitor two important parameters during the manufacturing process including the flow front of resin and progress of reaction (POR), was investigated. The Lamb waves generated by PZT, propagating in the mold/composite, was used to measure the parameters. The resin flow front was analyzed using optical detection at the same time. The flow front position over time and the influence of the length of sensing path covered by resin were delivered. The effects of different resin cure state on Lamb signal attenuation and energy leakage were also obtained. The change of amplitude was integrated to get the POR curves, so the resin cure state could be also monitored. After the composite was demoulded, the network was used contiously to identify the artifical damages with the fused probability-based diagnostic imaging (PDI). Experimental results indicate that the NERVE has the ability to realize the full life-cycle health monitoring of composite structures.

ABSTRACT Debris flows evolve in both time and space in complex ways, commonly starting as coherent failures but then quickly developing structures such as roll waves and surges. These processes are readily observed but difficult to study or quantify because of the speed at which they evolve. Many methods for studying debris flows consist of point measurements (e.g., flow height or basal stresses), which are inherently limited in spatial coverage and cannot fully characterize the spatiotemporal evolution of a flow. In this study, we use terrestrial lidar to measure debris-flow profiles at high sampling rates to examine debris-flow movement with high temporal and spatial precision and accuracy. We acquired measurements during gate-release experiments at the U.S. Geological Survey debris-flow flume, a unique experimental facility where debris flows can be artificially generated at a large scale. A lidar scanner was used to record repeat topographic profiles of the moving debris flows along the length of the flume with a narrow swath width (∼1 mm) at a rate of 60 Hz. The high-resolution lidar profiles enabled us to quantify flow front velocity of the debris flows and provided an unprecedented record of the development and evolution of the flow structure with a sub-second time resolution. The findings of this study demonstrate how to obtain quantitative measurements of debris-flow movement. In addition, the data help us to quantitatively define the development of a saltating debris-flow front and roll waves behind the debris-flow front. Such measurements may help constrain future modeling efforts.