Research Papers

Heterogeneous Composition Adaptation With Material Convolution Control Features

[+] Author and Article Information
Vikas Gupta

Ch. Devi Lal State Institute of
Engineering and Technology,
Panniwala Mota,
Sirsa, Haryana 125055, India
e-mail: vikasbrcm@rediffmail.com

Puneet Tandon

PDPM Indian Institute of
Information Technology,
Design and Manufacturing,
Jabalpur 482001, India
e-mail: ptandon@iiitdmj.ac.in

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received February 11, 2016; final manuscript received August 20, 2016; published online February 16, 2017. Assoc. Editor: Yong Chen.

J. Comput. Inf. Sci. Eng 17(2), 021008 (Feb 16, 2017) (10 pages) Paper No: JCISE-16-1075; doi: 10.1115/1.4034741 History: Received February 11, 2016; Revised August 20, 2016

Controlling and accomplishing the desired functional material composition in a heterogeneous object (HO) is a close loop process and requires frequent remodeling-and-analysis. Thus, flexibility and capability to efficiently modify the existing CAD model of a heterogeneous object are essential aspects of heterogeneous object modeling. The current work unfolds such capabilities of the developed material convolution surface approach. The geometric and material control features associated with the approach demonstrate the potential to modify existing material-distributions to remodel complex material variations and assure rapid heterogeneous composition adaptations. Convolution material primitives (CMPs), material potential functions, and heterogeneous and grading enclosure are manipulated to achieve desired material compositions across the heterogeneous region. The manipulation process for each control feature has been established. A few examples of modeling and modifying complex material-distributions have been reported for the validation of work.

Copyright © 2017 by ASME
Topics: Modeling , Geometry
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Fig. 1

Heterogeneous object and heterogeneous enclosure (A)

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Fig. 2

(a) Grading enclosure (A) and (b) heterogeneous region

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Fig. 3

Modeling multiple materials in an object

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Fig. 4

Effect of shifting CMPs: (a) shifting plane CMP, (b) shifting axis CMP, and (c) shifting point CMP

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Fig. 5

Changing the orientation of CMPs: (a) reorienting plane CMP and (b) reorienting axis CMP

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Fig. 6

Manipulating the grading enclosure: (a) changing the parameter of axis CMP and (b) changing the parameter of point CMP

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Fig. 7

Manipulating material potential function

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Fig. 8

Effect of change in material-distribution function in radial direction along the cylinder thickness “t

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Fig. 9

Effect of manipulating heterogeneous enclosure: (a) reducing A around point CMP, (b) shifting one plane of A, and (c) orienting one plane of A

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Fig. 10

Relationship between primitives and heterogeneous enclosure: (a) nonassociative and (b) associative

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Fig. 11

Adding same/different membership functions: (a) two point CMPs, (b) two points and one line CMPs, (c) one point and two line CMPs, and (d) one plane, line, and point CMPs

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Fig. 12

Adding same/different grading enclosures: (a) two point grading enclosures and (b) two points and one line grading enclosures

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Fig. 13

Insertion at freeform surfaces

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Fig. 14

Heterogeneous object modeling in a freeform surface patch using axis and plane CMPs

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Fig. 15

Two-dimensional material modeling in a cylinder

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Fig. 16

Heterogeneous articular surfaces for different persons with weight range: (a) below 55 kg, (b) between 55 and 70 kg, (c) between 70 and 85 kg, and (d) above 85 kg

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Fig. 17

Artificial heterogeneous tooth profiles with 2.5D material modeling




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