Analysis of Ni-coating's influence on wetting of Ag solder
Ni-coating's influence on the wetting progress in metal-ceramic bonding was analysed in this paper. Firstly Ag's contact angle was measured through high-temperature experiments, which turned out to be 100° and 25° on non-coated and Ni-coated ceramic substrates, respectively. Then a mathematical model was originally built up to catch the phase interface's motion on different substrates, considering fluid dynamics, melting and solidification, surface tension and liquid-solid heat transfer. Results indicated that Ni-coating affected the angle α directly and could reduce abnormity of joint structure through enhancing Ag solder's wettability on ceramic.
Residual stress and distortion calculation of laser beam welding for aluminum lap joints
Abstract A numerical simulation model of the laser beam welding (LBW) process is developed, aiming to a reliable prediction of the residual stress and distortion fields. As LBW is a thermo-mechanical process, a thermal analysis is conducted to analyze the spatial temperature distribution history, coupled to a mechanical analysis to calculate the residual stresses and distortions. An innovative and efficient keyhole model, independent of any empirical parameter, is introduced for the prediction of the keyhole size and shape required for the thermal analysis. All the major physical phenomena associated to the LBW process, such as, heat radiation, thermal conduction and convection heat losses are taken into account in the model development. The thermal and mechanical material properties are introduced as temperature dependent functions, due to the high temperature variations and the material phase changes occurring during the welding. The simulation algorithm is programmed as a macro routine within the ANSYS finite element code. The model is validated for the case of butt joint welding DH-36 steel plates and its efficiency is demonstrated for the lap-joint welding of two aluminum 6061-T6 plates. The main advantage of the developed model is its generality and flexibility, as it is independent of any empirical parameter, enabling its application in parametric studies of a wide range of LBW problems of different geometrical, material and joint type, requiring only the basic mechanical and thermal material properties.
Benchmark database for fine-grained image classification of benthic macroinvertebrates
Abstract Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and proportion of certain species. This paper presents a benchmark database for automatic visual classification methods to evaluate their ability for distinguishing visually similar categories of aquatic macroinvertebrate taxa. We make publicly available a new database, containing 64 types of freshwater macroinvertebrates, ranging in number of images per category from 7 to 577. The database is divided into three datasets, varying in number of categories (64, 29, and 9 categories). Furthermore, in order to accomplish a baseline evaluation performance, we present the classification results of Convolutional Neural Networks (CNNs) that are widely used for deep learning tasks in large databases. Besides CNNs, we experimented with several other well-known classification methods using deep features extracted from the data.