Abstract
Mesoscale heterogeneous material systems are efficient and adaptive to real world environments, owing to the non-uniform stress fields that result from the convolution of component geometries, loading conditions, and environmental changes. With the advent of multi-material additive manufacturing, the production of heterogeneous material systems with a pre-defined mesoscale material distribution becomes feasible. This unlocks the design freedom at a characteristic length scale between the macroscale geometry and microstructures, but also calls for a new design framework to optimize the mesoscale material distribution in multi-material additive manufacturing. Here, we propose and demonstrate such a design framework by incorporating digital image correlation-based deformation mapping with 3D finite element modeling-based computational optimization. The constitutive behavior of each constituent material or their mixtures is calibrated by matching the local deformation data. The optimal mesoscale material distribution can then be determined using global optimization algorithms and validated experimentally.
Highlights
Abundant in nature, as exemplified by bones, bamboos, and mollusk shells,[1,2,3,4,5,6,7,8,9,10,11] mesoscale heterogeneous material systems are more efficient and adaptive to thermal and mechanical environments than theirContributing Editor: Paolo Colombo a)Address all correspondence to this author.58 J
While many previous approaches assumed that the mechanical response of a mesostructured system can be simulated with mechanical properties of the individual constituent materials measured from uniaxial tension testing,[37,38] we found that this type of prediction can severely deviate from the reality
The proposed design framework consists of six major components: (i) fabrication of heterogeneous material systems with pre-defined mesostructure designs, (ii) deformation mapping using digital image correlation (DIC) or digital volume correlation (DVC), (iii) modeling of the deformation behavior of the mesostructured material systems, (iv) model calibration using voxel-level deformation data, (v) mesostructure design and optimization for given applications, and (vi) manufacturing and experimental validation of the optimal mesostructure
Summary
As exemplified by bones, bamboos, and mollusk shells,[1,2,3,4,5,6,7,8,9,10,11] mesoscale heterogeneous material systems are more efficient and adaptive to thermal and mechanical environments than their. Demonstrated in directed energy deposition, especially in laser engineered net shaping (LENS).[31,32,33,34] The right side shows a second type of mesoscale heterogeneous material systems, where each material voxel is assigned to be a specific constituent material Such a material system can be fabricated by multi-nozzle extrusion,[35,36] inkjet 3D printing,[37,38] or directed energy deposition.[31,32,33,34]. While many previous approaches assumed that the mechanical response of a mesostructured system can be simulated with mechanical properties of the individual constituent materials measured from uniaxial tension testing,[37,38] we found that this type of prediction can severely deviate from the reality This is primarily because external loading results in a multi-axial stress state in each material voxel of the heterogeneous mesostructured system. We demonstrate and validate the design framework using a beam-shaped mesostructured material system made from a hyperelastic material and a linear elastic material, which is fabricated using dual extrusion-based additive manufacturing
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