Experimental-Numerical Hybrid Reinforcement Characterization Framework
This chapter gives an overview of the hybrid characterization framework and detailed specifications are provided for the required hardware and software to created material digital twin using CT scans. The hybrid approach consists of three major steps, the
- PDF / 2,471,486 Bytes
- 22 Pages / 439.37 x 666.142 pts Page_size
- 97 Downloads / 257 Views
Experimental-Numerical Hybrid Reinforcement Characterization Framework
4.1 Overview In the experimental permeability measurements, a number of test samples are prepared for each fiber volume fraction and tested in test tools having a number of flow and pressure measuring sensors. The flow related data such as flow rate, pressure difference, and flow front progression etc. obtained from the sensors installed on the test rig are then used to compute the permeability. On the other hand, in a numerical permeability computation approach, a computational model is setup from reinforcement geometrical models. Computational fluid dynamics (CFD) codes are used to generate flow field data that is used to compute the reinforcement permeability. Here, in the proposed hybrid approach, we have combined the first step of the experimental procedure with the second step of the numerical method, as shown in Fig. 4.1. The hybrid approach consists of three major steps, (i) the non-destructive acquisition of X-ray micro computed tomography data of the test reinforcement at different levels of compaction utilizing a single sample, (ii) reconstruction of the micro CT data and extraction of a unit cell, (iii) Numerical solutions of boundary value problems on a unit cell using governing equations of fluid dynamics. The methodology is described in detail in the following sections. The characterization framework consists of a laboratory-sized micro CT device and a miniaturized in situ compression fixture. The compression fixture is specifically designed for in situ micro CT applications capable of tensile, compression and torsion testing. The compression fixture is remotely controlled via an integrated software through which displacement and load data can be acquired. The compression fixture consists of 40 mm diameter steel plates attached to a 5 kN load cell at the bottom. This compression module is mounted on the testing platform of the micro CT device for obtaining X-ray images as seen in the flow chart in Fig. 4.2.
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020 M. A. Ali et al., CT Scan Generated Material Twins for Composites Manufacturing in Industry 4.0, https://doi.org/10.1007/978-981-15-8021-5_4
73
74
4 Experimental-Numerical Hybrid Reinforcement Characterization …
Fig. 4.1 Illustration of the hybrid characterization framework
Geometry Model
Mesh
Voxel Model from XCT
Hybrid Method
Test Sample
Flow Simulation
Numerical Method
Fluid Injection
Test Fixture
Permeability
Permeability
Experimental Method
X-ray Source
Compaction Fixture
X-ray Detector 3D Model
Slicing
Segmentation
1 2
Voxel Model
Test Sample
Stress
Warp Peak Stresses
1 2
Flow Simulation Weft
Time
CompactionCurve
Geometry Variability
Permeability
Fig. 4.2 Overview of the hybrid characterization framework illustrating its versatility
4.2 The In Situ Computed Tomography System
75
0.2 m
Detector
0.5 m
Source
Stage
Fig. 4.3 The experimental setup for the in situ mic
Data Loading...
