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Mechanical and Civil Engineering Seminar: PhD Thesis Defense

Thursday, August 11, 2022
10:00am to 11:00am
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Methods for Control of Granular Material Attributes
Robert Buarque de Macedo, Graduate Student, Applied Mechanics,


A granular material is a collection of discrete, solid particles. This substance is ubiquitous in nature and industry, with examples ranging from soils, jointed rocks, foodstuffs, ball bearings, powders and even asteroids. As such, understanding granular materials is necessary for making sense of the physical world. Tremendous progress has been made in directly simulating granular materials in the previous decades, in particular via the discrete element method (DEM). Nevertheless, there remains ample opportunity for manipulating granular materials to achieve specific outcomes by leveraging the DEM.

The research presented in this thesis utilizes DEM simulations to develop tools and strategies for manipulating granular material to achieve desired attributes. These attributes include the shape of individual grains, the structure of granular tunnels and mesoscopic packing characteristics such as packing fraction and coordination number. Optimization of granular materials is considered at 3 different scales: at the single grain scale, at the scale of granular structures such as arches, and at the mesoscopic scale.

The first component of this thesis considers automated design of individual grain shapes that embody user-specified morphological properties via genetic algorithms. Next, excavation in granular materials is considered. It is studied how ants can so successfully manipulate granular materials to achieve stable systems by mapping the forces around real ant tunnels. Ant tunnels are simulated using a DEM which can handle arbitrary shaped grains: the Level-Set Discrete Element Method (LS-DEM). Finally, tools are developed for controlling mesoscopic attributes of granular materials as a function of grain shape.

To do so, genetic algorithms and a deep generative model are combined with LS-DEM. The methodologies introduced in this thesis serve as a foundation for controlling granular material attributes. Such techniques can be leveraged to engineer granular materials, with applications ranging from swarm robotics, robotic grippers, mechanically tunable fabrics for armor and robotic excavation.

Please attend this thesis defense: Guggenheim 133 (Lees-Kubota Lecture Hall) or Zoom Link: https://caltech.zoom.us/j/87652861147

For more information, please contact Stacie Takase by email at [email protected].