A hierarchical O(N log N) force-calculation algorithm

Nature ◽  
1986 ◽  
Vol 324 (6096) ◽  
pp. 446-449 ◽  
Author(s):  
Josh Barnes ◽  
Piet Hut
2001 ◽  
Author(s):  
Richard Y. Chiou ◽  
Bing Zhao

Abstract This paper presents an analytical convolution model of dynamic cutting forces in ball end milling of 3-D plane surfaces. The model takes into account the instantaneous slope on a sculptured surface to establish the chip geometry in cutting force calculation algorithm. A three-dimensional model of cutting forces in ball end milling is presented in terms of material properties, cutting parameters, machining configuration, and tool/work geometry. Based on the relationship of the local cutting force, chip load and engaged boundary, the total cutting force model is established via the angle domain convolution integration of the local forces in the feed, cross feed, axial direction, and inclination angle. The convolution integral leads to a periodic function of cutting forces in the angle domain and an explicit expression of the dynamic cutting force components in the frequency domain. Following the theoretical analysis, experimental study is discussed to illustrate the implementation procedure for force identification, and frequency domain data are presented to verify the analytical results.


Author(s):  
Bin Fang ◽  
Hongxiang Xue ◽  
Fuchun Sun ◽  
Yiyong Yang ◽  
Renxiang Zhu

PurposeThe purpose of the paper is to present a novel cross-modal sensor whose tactile is computed by the visual information. The proposed sensor can measure the forces of robotic grasping.Design/methodology/approachThe proposed cross-modal tactile sensor consists of a transparent elastomer with markers, a camera, an LED circuit board and supporting structures. The model and performance of the elastomer are analyzed. Then marker recognition method is proposed to determine the movements of the marker on the surface, and the force calculation algorithm is presented to compute the three-dimension force.FindingsExperimental results demonstrate that the proposed tactile sensor can accurately measure robotic grasping forces.Originality/valueThe proposed cross-modal tactile sensor determines the robotic grasping forces by the images of markers. It can give more information of the force than traditional tactile sensors. Meanwhile, the proposed algorithms for forces calculation determine the superior results.


2018 ◽  
Vol 175 ◽  
pp. 03057
Author(s):  
Ying Ma ◽  
Youqi Wang ◽  
Tiantian He

A modified digital element approach (DEA) is applied to simulate fabric perforation process under ballistic impact. The previous version of the DEA is capable of simulating ballistic impact of textile fabric using rigid body spherical and cylindrical projectiles only. Fragment simulating projectile (FSP) and real bullets are not modeled. The subject of this research is to perform ballistic penetration process against projectile of arbitrary shape and validate the modified DEA. A fabric to solid body projectile contact search and contact force calculation algorithm is established. Ballistic impact of textile fabrics against spherical and cylindrical projectiles is performed using the previous DEA and the modified DEA separately. Numerical results are compared to the well published DEA results to investigate the fabric bullet resistant performance.


2019 ◽  
Author(s):  
Robert Gove

This paper proposes a linear-time repulsive-force-calculation algorithm with sub-linear auxiliary space requirements, achieving an asymptotic improvement over the Barnes-Hut and Fast Multipole Method force-calculation algorithms. The algorithm, named random vertex sampling (RVS), achieves its speed by updating a random sample of vertices at each iteration, each with a random sample of repulsive forces. This paper also proposes a combination algorithm that uses RVS to derive an initial layout and then applies Barnes-Hut to refine the layout. An evaluation of RVS and the combination algorithm compares their speed and quality on 109 graphs against a Barnes-Hut layout algorithm. The RVS algorithm performs up to 6.1 times faster on the tested graphs while maintaining comparable layout quality. The combination algorithm also performs faster than Barnes-Hut, but produces layouts that are more symmetric than using RVS alone. Data and code: https://osf.io/nb7m8/


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