Design of Adaptive Porous Micro-structures for Additive Manufacturing

AbstractThe emerging field of additive manufacturing with biocompatible materials has led to customized design of porous micro- structures. Complex micro-structures are characterized by freeform surfaces and spatially varying porosity. Today, there is no CAD system that can handle the design of these microstructures due to their high complexity. In this paper we propose a novel approach for generating a 3D adaptive model of a porous micro-structure based on predefined design. Using our approach a designer can manually select a region of interest (ROI) and define its porosity. In the core of our approach, the multi-resolution volumetric model is used. The generation of an adaptive model may contain topological changes that should be considered. In our approach, the process of designing a customized model is composed of the following stages (a) constructing a multi- resolution volumetric model of a porous structure (b) defining regions of interest (ROI) and their resolution properties (c) constructing the adaptive model. In this research, the approach was initially tested on 2D models and then extended to 3D models. The resulted adapted model can be used for design, mechanical analysis and manufacturing. The feasibility of the method has been applied on bone models that were reconstructed from micro-CT images

Asymmetry of Daily Temperature Records

The authors study the NCEP–NCAR reanalysis temperature records and find that surface daily mean temperature cools rapidly and warms gradually at the midlatitudes (around 40°N and 40°S). This “asymmetry” is partially related to the midlatitude cyclone activity, in which cold fronts are significantly faster and steeper than warm fronts, and to intrusions of cold air. The gradual warming may be attributed also to the radiative relaxation to average atmospheric conditions after the passage of cold fronts or other intrusions of cold air. At the high latitudes there is an opposite asymmetry with rapid warming and gradual cooling; this asymmetry may be attributed to the radiative relaxation to average cold atmospheric conditions after the passage of warm fronts or intrusions of warm air.Earth and Planetary Science

CloudWalker: Random walks for 3D point cloud shape analysis

Point clouds are gaining prominence as a method for representing 3D shapes, but their irregular structure poses a challenge for deep learning methods. In this paper we propose CloudWalker, a novel method for learning 3D shapes using random walks. Previous works attempt to adapt Convolutional Neural Networks (CNNs) or impose a grid or mesh structure to 3D point clouds. This work presents a different approach for representing and learning the shape from a given point set. The key idea is to impose structure on the point set by multiple random walks through the cloud for exploring different regions of the 3D object. Then we learn a per-point and per-walk representation and aggregate multiple walk predictions at inference. Our approach achieves state-of-the-art results for two 3D shape analysis tasks: classification and retrieval