Data-driven and User-Driven Material Modeling

Data-driven and User-Driven Material Modeling

Heterogeneous Material Modelling for High-Resolution Multi-Material 3D Printing
2016, 3D Printing
MIT Media Lab

Christoph Bader,Dominik Kolb,Prof. Neri Oxman

Current advancements in additive manufacturing enable the fabrication of geometrically complex and materially heterogeneous objects with high spatial resolution in manufacturing. Such advancements challenge designers, architects and engineers alike, to move beyond shells designed with pre-determined shape, and material composition; and to consider an expanded design space encompassing internal material compositions such as, amongst others, variable density, variable elasticity, and variable opacity. This new technical approach proposes that the “anatomy” of objects and building components can be designed to promote functionally graded properties enhancing overall structural and environmental performance. However, current off-the-shelf software tools, do not typically take these recent advancements into consideration, thereby missing out on significant design opportunities that lie at the intersection of digital modelling and fabrication. This research area explores a hybrid approach to heterogeneous material modelling enabling the designer to augment current CAD workflows by combining them with user-driven heterogeneous material modelling methods. Such methods include:

1. Free-form Material Sculpting from Medial Axis
2. Material Primitives and Morphological Operations
3. Parameterization-Based Material Assignment
4. Curve-Based Material Assignment
5. Implicit Function Modelling

This research utilizes unifying software platform for the generation of descriptions used for the production of highly complex and materially highly heterogeneous 3D models through multi-material 3D printing. Moreover, our approach accounts for arbitrary external geometric data sets such as point-clouds (3D Scanning), scalar and vector fields (Medical Imaging), curves and polygons (CAD), tetrahedral meshes (Simulations), with their associated attributes. Effectively enabling the incorporation of material data-sets generated by the above methods. Additionally, through external data sources, it is possible to drive the computation of hybrid evaluated and unevaluated heterogeneous material modelling methods during slice generation for 3D-bitmap-printing.  As such, this approach is designed to handle data-sources and to generate material-distributions during slice generation (on-slice-time) and, therefore, it permits the incorporation of external data as the primary design element in the creative process for multi-material 3D-printed objects. Arriving at a highly flexible and robust framework, this approach and related methods enables the control of and production-ready digital fabrication of arbitrary geometries with equal complex material compositions.

Related publications include Data-driven Material Modeling and Grown, Printed and Biologically-augmented. The authors wish to thank and to acknowldege Stratasys Ltd. for thier help and support. 

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