Christianne Mulat

Fibre-scale Modeling of C/C Processing by Chemical Vapour Infiltration Using Xray CMT Images and Random Walkers

We present a computational tool for the modeling of Chemical Vapor Infiltration of carbon/carbon composites, which is based on 3D images acquired by X-ray Computerized Micro-Tomography with a very fine resolution, such that the fibers are clearly distinguishable from each other. Preliminary image processing is necessary in order to perform segmentation between solid and void phases. Then, morphological and transport properties are computed in the images. Random walkers are used for the simulation of gas transport in continuum and rarefied regimes. The image modification under chemical deposition is handled by a specific surface discretization technique and a pseudo-VOF method. Results are presented and discussed: the notion of infiltrability is introduced as a design tool for the CVI engineer.

Axis detection of cylindrical objects in three-dimensional images

We introduce an algorithm dedicated to the detection of the axes of cylindrical objects in a 3D block. The proposed algorithm performs 3D axis detection without prior segmentation of the block. This approach is specifically appropriate when the gray levels of the cylindrical objects are not homogeneous and are thus difficult to distinguish from the background. The method relies on gradient and curvature estimation and operates in two main steps. The first one selects candidate voxels for the axes, and the second one refines the determination of the axis of each cylindrical object. Applied to fiber-reinforced composite materials, this algorithm detects the axes of fibers in order to obtain the geometrical characteristics of the reinforcement. Knowing the reinforcement characteristics is an important issue in the quality control of the material but also in the prediction of the thermal and mechanical performances. We detail the various steps of the algorithm and then present some results, obtained with both synthetic blocks and real data acquired by synchrotron X-ray micro-tomography on carbon-fiber-reinforced carbon composites.

Modelling Infiltration of Fibre Preforms From X-Ray Tomography Data

The production of high-quality Ceramic-Matrix Composites often includes matrix deposition by Chemical Vapour Infiltration (CVI), a process which involves many phenomena such as gas transport, chemical reactions, and structural evolution of the preform. Control and optimization of this high-tech process are demanding for modelling tools. In this context, a numerical simulation of CVI in complex 3D images, acquired e.g. by X-ray Computerized Microtomography, has been developed. The approach addresses the two length scales which are inherent to a composite with woven textile reinforcement (i.e. inter- and intra-bundle), with two numerical tools. The small-scale program allows direct simulation of CVI in small intra-bundle pores. Effective laws for porosity, internal surface area and transport properties as infiltration proceeds are produced by averaging. They are an input for the next modelling step. The second code is a large-scale solver which accounts for the locally heterogeneous and anisotropic character of the pore space. Simulation of the infiltration of a whole composite material part is possible with this program. Validation of these tools on test cases, as well as some examples on actual materials, are shown and discussed.

Axis detection method for cylindrical objects

This paper introduces an algorithm dedicated to the detection of the axes of cylindrical objects in a 3-D block. The proposed algorithm performs the 3-D axis detection without prior segmentation of the block. This approach is specifically appropriate when the grey levels of the cylindrical object are not homogeneous and thus difficult to distinguish from the background. The method relies on gradient and curvature estimation and operates in two main steps. The first one selects candidate voxels for the axis and the second one refines the determination of the axis of each cylindrical object. Applied to fiber reinforced composite materials, this algorithm allows detecting the axes of fibers in order to obtain the geometrical characteristics of the reinforcement. Knowing the reinforcement characteristics is an important issue in the quality control of the material but also in the prediction of the thermal and mechanical behavior. In this paper, the various steps of the algorithm are detailed. Then, results obtained with synthetic blocks and with blocks acquired by synchrotron X-ray microtomography on actual carbon-fiber reinforced carbon (C/C) composites are presented.