Graduation Semester and Year
2016
Language
English
Document Type
Thesis
Degree Name
Master of Science in Mechanical Engineering
Department
Mechanical and Aerospace Engineering
First Advisor
Robert M Taylor
Abstract
Additive manufacturing has made us realize that we can fabricate complex shapes that were difficult to manufacture with subtractive processes. Topology optimizations results have complex shapes and have rough surfaces which are difficult to manufacture even by additive manufacturing. To automate the process of converting rough surfaces into smooth surfaces for the benefit of manufacturability would be very desirable. Computing curve segments to approximate point cloud data that represents rough surfaces and then lofting it to have a smooth surface seems to be a promising methodology to achieve automation. We implement B-spline formulation along with Pottmann’s iterative method based on Squared Distance Minimization to automate the process of smoothening of rough surfaces. Calculation of foot points is a repetitive step within Squared Distance Minimization (SDM) method and accounts for considerable amount of computation time. In this research work, we proposed and implemented an algorithm on simple and complex shapes to help gain reduction in time required for foot point calculation. We will discuss ways to use this method effectively, dealing with instability, steps to reduce computation time and future work.
Keywords
B-spline, Squared Distance Minimization (SDM), SD error term, Foot point calculation, Point cloud data, Control points, Curve fitting
Disciplines
Aerospace Engineering | Engineering | Mechanical Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Mhala, Vinay Vivek, "FITTING B-SPLINES CURVES TO COARSE DATA CLOUD USING MODIFIED SQUARED DISTANCE MINIMIZATION METHOD" (2016). Mechanical and Aerospace Engineering Theses. 913.
https://mavmatrix.uta.edu/mechaerospace_theses/913
Comments
Degree granted by The University of Texas at Arlington