The role of tool composition and tool geometry in controlling the surface finish in machining wood

An examination of several brazed cemented carbide tool inserts that were used in service for cutting cured (dry) pine is described. A laboratory test is also described where the relative resistance to chipping of the brazed tool inserts was measured.It is shown that tool wear occurs through a continuous increase in the tool cutting edge radius that produces a deterioration in the appearance of the machined surface. It is also shown that an increase in either the binder volume fraction or the tool wedge angle produces an increase in the energy absorbed on impact. It is suggested that if progressive wear determines the useful life of a cemented carbide cutting tool then a low volume fraction of binder is required whereas if tool edge chipping determines the useful life of a cutting tool then a large volume fraction of binder and a large tool wedge angle are required.     

Performance of genetic algorithms in search for water splitting perovskites

We examine the performance of genetic algorithms (GAs) in uncovering solar water light splitters over a space of almost 19,000 perovskite materials. The entire search space was previously calculated using density functional theory to determine solutions that fulfill constraints on stability, band gap, and band edge position. Here, we test over 2500 unique GA implementations in finding these solutions to determine whether GA can avoid the need for brute force search, and thereby enable larger chemical spaces to be screened within a given computational budget. We find that the best GAs tested offer almost a 6 times efficiency gain over random search, and are comparable to the performance of a search based on informed chemical rules. In addition, the GA is almost 10 times as efficient as random search in finding half the solutions within the search space. By employing chemical rules, the performance of the GA can be further improved to approximately 12–17 better than random search. We discuss the effect of population size, selection function, crossover function, mutation rate, fitness function, and elitism on the final result, finding that selection function and elitism are especially important to GA performance. In addition, we determine that parameters that perform well in finding solar water splitters can also be applied to discovering transparent photocorrosion shields. Our results indicate that coupling GAs to high-throughput density functional calculations presents a promising method to rapidly search large chemical spaces for technological materials.     

Three-dimensional distinct element modelling and dynamic runout analysis of a landslide in gneissic rock, British Columbia, Canada

The McAuley Creek Landslide is a 6?million m³ gneissic rock slope failure that occurred in British Columbia (Canada) in late May–early June 2002. The geological strength index was used to characterize the quality of the overall rock mass and its reduced (damaged) quality near tectonic structures and alteration zones. Potential slope failure mechanisms were investigated using four analysis techniques including: kinematic analysis, surface wedge limit equilibrium (combination) analysis, block theory and three-dimensional distinct element models. Results from all four analyses suggested that the dominant slope failure mechanism was wedge sliding along the intersection of the gneissic foliation and a steeply dipping discontinuity set striking perpendicular to the slope. Of the 6?million m³ of material involved in the landslide, an estimated 5 million?m³ was deposited immediately below the source area against the opposite valley wall, with the remaining 1 million m³ travelling an additional 1.6?km downstream. The runout behaviour was investigated using a three-dimensional dynamic analysis code.     

Electrodeposition of copper into high aspect ratio PCB micro-via using megasonic agitation

This paper presents the use of micro-particle imaging velocimetry (micro-PIV) to analyse fluid flow and hence ion replenishment in PCB micro-via during the electroplating process. The cross section of a PCB via is fabricated in PMMA to allow optical access to the sample. Fluid flow within two 1:1 aspect ratio blind micro-vias, one with straight side walls and the other with tapered side walls were compared. Flow is also analysed in a 1:1 aspect ratio through via. Flow rates measured using micro-PIV are used to validate simulated flow models. The results show that there are increased flow rates within the blind via with tapered side walls. This goes some way to explaining the improved electroplating results obtained in industry when tapered vias are used. Initial experimental results using megasonic streaming to remove bubbles from blind micro-via and promote ion transportation within high aspect ratio PCB micro-via to enhance electrodeposition are also reported.     

Implications of Weak Link Effects on Thermal Characteristics of Transition-Edge Sensors

Weak link behavior in transition-edge sensor (TES) microcalorimeters creates the need for a more careful characterization of a device’s thermal characteristics through its transition. This is particularly true for small TESs where a small change in the bias current results in large changes in effective transition temperature. To correctly interpret measurements, especially complex impedance, it is crucial to know the temperature-dependent thermal conductance, G(T), and heat capacity, C(T), at each point through the transition. We present data illustrating these effects and discuss how we overcome the challenges that are present in accurately determining G and T from I–V curves. We also show how these weak link effects vary with TES size. Additionally, we use this improved understanding of G(T) to determine that, for these TES microcalorimeters, Kaptiza boundary resistance dominates the G of devices with absorbers while the electron-phonon coupling also needs to be considered when determining G for devices without absorbers     

A 360-Degree Panoramic Image Inpainting Network Using a Cube Map

Inpainting has been continuously studied in the field of computer vision. As artificial intelligence technology developed, deep learning technology was introduced in inpainting research, helping to improve performance. Currently, the input target of an inpainting algorithm using deep learning has been studied from a single image to a video. However, deep learning-based inpainting technology for panoramic images has not been actively studied. We propose a 360-degree panoramic image inpainting method using generative adversarial networks (GANs). The proposed network inputs a 360-degree equirectangular format panoramic image converts it into a cube map format, which has relatively little distortion and uses it as a training network. Since the cube map format is used, the correlation of the six sides of the cube map should be considered. Therefore, all faces of the cube map are used as input for the whole discriminative network, and each face of the cube map is used as input for the slice discriminative network to determine the authenticity of the generated image. The proposed network performed qualitatively better than existing single-image inpainting algorithms and baseline algorithms.