Damage development in an armor ceramic under quasi-static indentation

The objective of the present study is to assess the capabilities of a recently developed mechanism-based model for inelastic deformation and damage in structural ceramics. In addition to conventional lattice plasticity, the model accounts for microcrack growth and coalescence as well as granular flow following comminution. The assessment is made through a coupled experimental/computational study of the indentation response of a commercial armor ceramic. The experiments include examinations of subsurface damage zones along with measurements of residual surface profiles and residual near-surface stresses. Extensive finite element computations are conducted in parallel. Comparisons between experiment and simulation indicate that the most discriminating metric in the assessment is the spatial extent of subsurface damage following indentation. Residual stresses provide additional validation. In contrast, surface profiles of indents are dictated largely by lattice plasticity and thus provide minimal additional insight into the inelastic deformation resulting from microcracking or granular flow. A satisfactory level of correlation is obtained using property values that are either measured directly or estimated from physically based arguments, without undue reliance on adjustable (nonphysical) parameters. © 2011 The American Ceramic Society.

Stability Of Adhesion Clusters And Cell Reorientation Under Lateral Cyclic Tension

This work is motivated by experimental observations that cells on stretched substrate exhibit different responses to static and dynamic loads. A model of focal adhesion that can consider the mechanics of stress fiber, adhesion bonds, and substrate was developed at the molecular level by treating the focal adhesion as an adhesion cluster. The stability of the cluster under dynamic load was studied by applying cyclic external strain on the substrate. We show that a threshold value of external strain amplitude exists beyond which the adhesion cluster disrupts quickly. In addition, our results show that the adhesion cluster is prone to losing stability under high-frequency loading, because the receptors and ligands cannot get enough contact time to form bonds due to the high-speed deformation of the substrate. At the same time, the viscoelastic stress fiber becomes rigid at high frequency, which leads to significant deformation of the bonds. Furthermore, we find that the stiffness and relaxation time of stress fibers play important roles in the stability of the adhesion cluster. The essence of this work is to connect the dynamics of the adhesion bonds (molecular level) with the cell's behavior during reorientation (cell level) through the mechanics of stress fiber. The predictions of the cluster model are consistent with experimental observations.

Molecular/Cluster Statistical Thermodynamics Methods To Simulate Quasi-Static Deformations At Finite Temperature

The rapid evolution of nanotechnology appeals for the understanding of global response of nanoscale systems based on atomic interactions, hence necessitates novel, sophisticated, and physically based approaches to bridge the gaps between various length and time scales. In this paper, we propose a group of statistical thermodynamics methods for the simulations of nanoscale systems under quasi-static loading at finite temperature, that is, molecular statistical thermodynamics (MST) method, cluster statistical thermodynamics (CST) method, and the hybrid molecular/cluster statistical thermodynamics (HMCST) method. These methods, by treating atoms as oscillators and particles simultaneously, as well as clusters, comprise different spatial and temporal scales in a unified framework. One appealing feature of these methods is their "seamlessness" or consistency in the same underlying atomistic model in all regions consisting of atoms and clusters, and hence can avoid the ghost force in the simulation. On the other hand, compared with conventional MD simulations, their high computational efficiency appears very attractive, as manifested by the simulations of uniaxial compression and nanoindenation. (C) 2008 Elsevier Ltd. All rights reserved.

The Newest Developments Of Load-Unload Response Ratio (Lurr)

The Load Unload Response Ratio (LURR) method is an intermediate-term earthquake prediction approach that has shown considerable promise. It is inspiring that its predictions using LURR have been improving. Since 2004 we have made a major breakthrough in intermediate-term earthquake forecasting of the strong earthquakes on the Chinese mainland using LURR and successfully predicted the Pakistan earthquake with magnitude M 7.6 on October 8, 2005. The causes for improving the prediction in terms of LURR have been discussed in the present paper.

Effect Of Load Triaxiality On Polymorphic Transitions In Zinc Oxide

Molecular dynamics (MD) simulations and first-principles calculations are carried out to analyze the stability of both newly discovered and previously known phases of ZnO under loading of various triaxialities. The analysis focuses on a graphite-like phase (FIX) and a body-centered-tetragonal phase (BCT-4) that were observed recently in [0 1 (1) over bar 0]- and [0 0 0 1]-oriented nanowires respectively under uniaxial tensile loading as well as the natural state of wurtzite (WZ) and the rocksalt (RS) phase which exists under hydrostatic pressure loading. Equilibrium critical stresses for the transformations are obtained. The WZ -> HX transformation is found to be energetically favorable above a critical tensile stress of 10 GPa in [0 1 (1) over tilde 0] nanowires. The BCT-4 phase can be stabilized at tensile stresses above 7 GPa in [0 0 0 1] nanowires. The RS phase is stable at hydrostatic pressures above 8.2 GPa. The identification and characterization of these phase transformations reveal a more extensive polymorphism of ZnO than previously known. A crystalline structure-load triaxiality map is developed to summarize the new understanding. (c) 2007 Elsevier Ltd. All rights reserved.

An approximate likelihood method for estimating static parameters in multi-target tracking models

This paper considers a class of dynamic Spatial Point Processes (PP) that evolves over time in a Markovian fashion. This Markov in time PP is hidden and observed indirectly through another PP via thinning, displacement and noise. This statistical model is important for Multi object Tracking applications and we present an approximate likelihood based method for estimating the model parameters. The work is supported by an extensive numerical study.