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. 2020 Apr 17;13(8):1887.
doi: 10.3390/ma13081887.

A Novel Approach to Discrete Representative Volume Element Automation and Generation-DRAGen

Manuel Henrich  1 , Felix Pütz  1 , Sebastian Münstermann  1
Affiliations

A Novel Approach to Discrete Representative Volume Element Automation and Generation-DRAGen

Manuel Henrich et al. Materials (Basel). .

Abstract

In this study, a novel approach for generating Representative Volume Elements (RVEs) is introduced. In contrast to common generators, the new RVE generator is based on discrete methods to reconstruct synthetic microstructures, using simple methods and a modular structure. The plain and uncomplicated structure of the generator makes the extension with new features quite simple. It is discussed why certain features are essential for microstructural simulations. The discrete methods are implemented into a python tool. A Random Sequential Addition (RSA)-Algorithm for discrete volumes is developed and the tessellation is realized with a discrete tessellation function. The results show that the generator can successfully reconstruct realistic microstructures with elongated grains and martensite bands from given input data sets.

Keywords: discrete tessellation; microstructure; random sequential addition algorithm; representative volume elements; voronoi tessellation.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Microstructure analysis of DP800.
Figure 2
Figure 2
Distributions of Grain Size and Aspect Ratio used as Input data for the Representative Volume Element (RVE)-Generation.
Figure 3
Figure 3
Stages of Random Sequential Addition (RSA).
Figure 4
Figure 4
Schematic figure of an ellipsoid with the different radii a, b and c. For modeling the microstructures it was assumed that a=b.
Figure 5
Figure 5
Three different crosssections of the materials microstructures show that it can be assumed that ellipsoids with a = b and a ≠ c describes the microstructure better than regular spheres. The three crosssections show metallographic pictures of the Microstructure in the TD x RD-Plane (a), the ND × RD-Plane (b) and the ND × TD-Plane in (c).
Figure 6
Figure 6
Log probability density of grain volumes shows that most grain volumes are in the range between 0 μm3 and 50 μm3.
Figure 7
Figure 7
Final result after the discrete tessellation.
Figure 8
Figure 8
Log probability density of grain volumes shows that most grain volumes are in the range between 0 μm3 and 50 μm3.
Figure 9
Figure 9
RVE with a martensite band shown in red color. The martensite band is defined as a volume within the cube that must contain at least 60% of martensite.
Figure 10
Figure 10
Log probability density of grain volumes shows that most grain volumes are in the range between 0 μm3 and 50 μm3.
Figure 11
Figure 11
Schematic drawing of a 2D ellipse in a discrete and continuous volume. It is shown that the continuous volume for ellipses and therefore also for ellipsoids is in general bigger than the discrete volume.
Figure 12
Figure 12
Log probability density of the input values as well as the output values for an RVE created with 128×128×128 points.
See this image and copyright information in PMC

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