Immersogeometric analysis with point cloud geometry towards practical applications
Date
2021-05
Authors
Khristy, Joel
Major Professor
Advisor
Krishnamurthy, Adarsh
Hsu, Ming-Chen
Ganapathysubramanian, Baskar
Committee Member
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Abstract
Recently, immersogeometric analysis (IMGA) was successfully applied to simulate compressible
and incompressible fluid flows over CAD models represented using triangles, non-uniform rational
B-splines (NURBS), and analytic surfaces. However, performing flow analysis over real-life objects
requires CAD model reconstruction, which can be as tedious as the mesh generation process itself.
In a point cloud geometry, the object is represented as an unstructured collection of points. Point
cloud representation has proliferated as a form of acquiring geometric information in digital format
using LIDAR scanners, optical scanners, or other passive methods like multi-view stereo images.
In this work, we perform IMGA directly on point cloud representation of geometry, thus enabling
flow analysis over as-manufactured components. Due to the absence of topological information
in a point cloud, there are no guarantees that the geometric representation is watertight, which
makes performing inside-outside tests on the background mesh challenging. To address this, we
first develop methods for generating topological properties on a point cloud and compute inside-
outside information directly from the resulting topology. Then, validations are performed for these
geometric estimation methods, as well as for point cloud IMGA (PC-IMGA) incompressible flow
results. We finally demonstrate additional features and scalability of our approach by performing
PC-IMGA on large construction machinery represented by a dense cloud of more than 12 million
points, along with our other PC-IMGA developments, including weak thermal boundary conditions
and transient boundaries.
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