Dev2PQ: Planar Quadrilateral Strip Remeshing of Developable Surfaces

We introduce an algorithm to remesh triangle meshes representing developable surfaces to planar quad dominant meshes. The output of our algorithm consists of planar quadrilateral (PQ) strips that are aligned to principal curvature directions and closely approximate the curved parts of the input developable, and planar polygons representing the flat parts of the input. Developable PQ-strip meshes are useful in many areas of shape modeling, thanks to the simplicity of fabrication from flat sheet material. Unfortunately, they are difficult to model due to their restrictive combinatorics and locking issues. Other representations of developable surfaces, such as arbitrary triangle or quad meshes, are more suitable for interactive freeform modeling, but generally have non-planar faces or are not aligned to principal curvatures. Our method leverages the modeling flexibility of non-ruling based representations of developable surfaces, while still obtaining developable, curvature aligned PQ-strip meshes. Our algorithm optimizes for a scalar function on the input mesh, such that its level sets are extrinsically straight and align well to the locally estimated ruling directions. The condition that guarantees straight level sets is nonlinear of high order and numerically difficult to enforce in a straightforward manner. We devise an alternating optimization method that makes our problem tractable and practical to compute. Our method works automatically on any developable input, including multiple patches and curved folds, without explicit domain decomposition. We demonstrate the effectiveness of our approach on a variety of developable surfaces and show how our remeshing can be used alongside handle based interactive freeform modeling of developable shapes

Redundant motor drive system

A drive system characterized by a base supporting a pair of pillars arranged in spaced parallelism, a shaft extended between and supported by the pillars for rotation about the longitudinal axis thereof, a worm gear affixed to the shaft and supported in coaxial relation therewith is described. A bearing housing of a sleeve like configuration is concentrically related to the shaft and is supported thereby for free rotation. A first and a second quiescent drive train, alternatively activatable, is provided for imparting rotation into said bearing housing. Each of the drive trains is characterized by a selectively energizable motor connected to a spur gear

Design, manufacture and spin test of high contact ratio helicopter transmission utilizing Self-Aligning Bearingless Planetary (SABP)

A 450 hp high ratio Self-Aligning Bearingless Planetary (SABP) for a helicopter application was designed, manufactured, and spin tested under NASA contract NAS3-24539. The objective of the program was to conduct research and development work on a high contact ratio helical gear SABP to reduce weight and noise and to improve efficiency. The results accomplished include the design, manufacturing, and no-load spin testing of two prototype helicopter transmissions, rated at 450 hp with an input speed of 35,000 rpm and an output speed of 350 rpm. The weight power density ratio of these gear units is 0.33 lb hp. The measured airborne noise at 35,000 rpm input speed and light load is 94 dB at 5 ft. The high speed, high contact ratio SABP transmission appears to be significantly lighter and quieter than comtemporary helicopter transmissions. The concept of the SABP is applicable not only to high ratio helicopter type transmissions but also to other rotorcraft and aircraft propulsion systems

Learning quadrangulated patches for 3D shape parameterization and completion

We propose a novel 3D shape parameterization by surface patches, that are oriented by 3D mesh quadrangulation of the shape. By encoding 3D surface detail on local patches, we learn a patch dictionary that identifies principal surface features of the shape. Unlike previous methods, we are able to encode surface patches of variable size as determined by the user. We propose novel methods for dictionary learning and patch reconstruction based on the query of a noisy input patch with holes. We evaluate the patch dictionary towards various applications in 3D shape inpainting, denoising and compression. Our method is able to predict missing vertices and inpaint moderately sized holes. We demonstrate a complete pipeline for reconstructing the 3D mesh from the patch encoding. We validate our shape parameterization and reconstruction methods on both synthetic shapes and real world scans. We show that our patch dictionary performs successful shape completion of complicated surface textures.Comment: To be presented at International Conference on 3D Vision 2017, 201