S5E4

Abstract

Nanocrystalline (NC) materials (d<100nm) show remarkably different functional and mechanical behaviour in comparison to their coarse-grained counterparts. For instance, recent experiments on NC shape memory alloys reveal that grain refinement leads to suppression of the underlying martensitic transformation as the grain size is reduced to the nanoscale. This may lead to the complete loss of functionality – the property which makes these materials interesting in the first place. We hypothesize that such suppression effects arise due to an additional energy penalty when the grain boundary transforms from austenite into martensite. This allows us to establish a thermodynamically consistent phase-field framework and investigate less conventional grain size distribution designs that can potentially recover the functionality while retain the mechanical strength (Hall-Petch strengthening). Other experimental and atomistic simulation studies on fcc NC metals indicate interesting transitions from intra-granular dislocation-mediated plasticity to inter-granular plasticity, where the deformation becomes accommodated by grain boundary motion, sliding or grain rotation. In some cases, deformation twinning may emerge as a dominant mechanism carrying the plastic deformation. Such mechanisms may serve cooperatively or compete against each other. In an effort to incorporate such mechanisms into a holistic modelling framework, I will present a phase field model that couples grain boundary migration with intra- granular plasticity (dislocation slip or deformation twinning).

Introduction of speaker

Employment:

2019 – Present:

Scientist I, Institute of High Performance Computing, A*STAR, Singapore

Involved in projects:

(1) Integrated Large Format Hybrid Manufacturing using Wire-fed and Powder-blown Technology for LAAM process:

(2) Digital Design and Additive Manufacturing Workflows

Education:

PhD, National University of Singapore, (SINGA (Singapore International Graduate Award) scholarship)

Master’s degree: Brno University of Technology, Czech Republic

Bachelor’s degree: Brno University of Technology, Czech Republic

Research interests:

Phase field models, plasticity, high cycle fatigue, crack growth, additive manufacturing, microstructure evolution.

Abstract

Centrifuge modeling is a cost-effective method to simulate the seismic response of scaled soil-foundation-structure systems under realistic confining pressures. In recent years, particle image velocimetry (GeoPIV-RG) has been implemented in the analysis of centrifuge experiments to monitor deformation mechanisms within a visible soil section. This paper presents a new system for particle image velocimetry (PIV) analysis designed at the University of Colorado (CU) Boulder’s 400g-ton, 5.5m radius centrifuge facility. We detail the design objectives and construction challenges for the system’s different components: a) a rigid container with one side made of Perspex to visualize various mechanisms of deformation in a stratigraphically variable and layered liquefiable soil profile, b) a high-speed camera capable of recording up to 2000 frames/seconds to avoid signal aliasing, c) a camera and lens mounting system to avoid independent movement of these systems, d) adequate LED lighting, and e) a linear-elastic single-degree of freedom (SDOF) structure to represent plane strain (2D) conditions and the key dynamic properties of a typical 4-story moment-resisting frame structure founded on a stiff strip foundation.

Introduction of speaker

Lianne Brito is a doctoral student in the Department of Civil, Environmental and Architectural Engineering at the University of Colorado Boulder. She completed her undergraduate studies at the University of Central Florida, and she earned her M.S. from CU Boulder. Her doctoral thesis focuses on the influence of stratigraphic variability and layering on liquefaction manifestation and consequences near and away from structures. She is the recipient of the Graduate Assistance in Areas of National Need (GAANN) Fellowship and the National Science Foundation (NSF) Graduate Research Fellowship (GRF).