Bio-inspired Network Dynamics and Geomechanics
GOALS: To predict the influence of grain crushing and crack propagation on the mechanical and physical properties of soils, rocks and ceramics; recommend self-healing materials for geological storage of energy and waste; test crack reparation techniques in concrete; design infrastructure networks inspired by the growth and adaptation of living organisms.
METHODS & TECHNOLOGIES: Simulations of granular assemblies, mechanical tests on granular mixtures, microstructure observations, image analysis, MATLAB programming, Finite Element simulations, slime mold growth experiments, network dynamics modeling.
RESEARCH/DESIGN ISSUES: Why do some granular materials get crushed upon cyclic loading and others do not? Why does some salt rock self-heal? Is it sustainable to repair cracks in geomaterials? Are biological networks more efficient and versatile than engineering systems? Specific research areas include:
Modeling particle crushing as a phase change ("crushing")
Discrete Element simulation of particle crushing in a granular assembly
Geometric description and modeling of microstructure changes during particle crushing
Continuum-based prediction of energy dissipation by crushing with MATLAB.
Microstructure-enriched modeling of healing in salt rock ("healing")
Temperature- and moisture- controlled creep tests on granular salt
Microscope image analysis and statistical description of microstructure
Mathematical modeling of damage and healing from microstructure descriptors
MATLAB programming for damage and healing models at the sample scale
Finite Element simulation of salt rock damage and healing around cavities.
Design of crack reparation techniques in concrete structures ("reparation")
Simulation of crack propagation in steel-reinforced concrete beams
Modeling and calibration of concrete/epoxy interfaces
Design epoxy injection techniques to repair concrete structures
Simulation of bridge decks supported by repaired steel-reinforced concrete beams.
Biologically inspired network optimization ("bionetworks")
Experimental and numerical analysis of the mechanism driving slime mold growth. Code development for bio-inspired design of engineering systems and network algorithms, including water lines, road alignments, information cables, and any network subjected to several constraints and optimization criteria.
MEETING TIME: Mon, 4:30-5:20
ADVISORS: Chloé Arson (CEE).
PARTNERS & SPONSORS: National Science Foundation (NSF); Georgia Department of Transportation (G-DOT); Center for Bio-inspired and Bio-mediated Geotechnics (CBBG)
MAJORS, PREPARATION AND INTERESTS:
EE, CmpE, CS - Interest in programming, image analysis, and numerical simulation (MATLAB, ABAQUS, PFC3D).
ME/CEE: background in solid mechanics required; geology, mechanics of materials and dynamics recommended.
BIOSCI: Background or knowledge on biological systems, cultures growth and/or interest in growing them.
CONTACT: Dr. C. Arson, 404-385-0143, email@example.com