The high-temperature wettability of alumina particulate preforms by copper is investigated by means of infiltration experiments conducted at 1473 K under low oxygen partial pressure. Wetting is quantified in terms of drainage curves, which plot the volume fraction of metal in the porous medium vs. the applied pressure. Mercury porosimetry is also used on similar preforms for comparison. The effect of volume fraction, particle geometry and capillary parameters on the drainage curve are studied and compared with the expression proposed by Brooks and Corey. The influence of the particle volume fraction and capillary parameters characterizing wetting in the two systems is discussed to derive an effective contact angle for wetting of alumina particles by molten copper.
The important problem of Simultaneous Localization and Mapping (SLAM) in dynamic environments is less studied than the counterpart problem in static settings. In this paper, we present a solution for the feature-based SLAM problem in dynamic environments. We propose an algorithm that integrates SLAM with multi-target tracking (SLAMMTT) using a robust feature-tracking algorithm for dynamic environments. A novel implementation of RANdomSAmple Consensus (RANSAC) method referred to as multilevel-RANSAC (ML-RANSAC) within the Extended Kalman Filter (EKF) framework is applied for multi-target tracking (MTT). We also apply machine learning to detect features from the input data and to distinguish moving from stationary objects. The data stream from LIDAR and vision sensors are fused in real-time to detect objects and depth information. A practical experiment is designed to verify the performance of the algorithm in a dynamic environment. The unique feature of this algorithm is its ability to maintain tracking of features even when the observations are intermittent whereby many reported algorithms fail in such situations. Experimental validation indicates that the algorithm is able to perform consistent estimates in a fast and robust manner suggesting its feasibility for real-time applications.
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