Brown University
Joint Materials/Solid Mechanics Seminar Series
Head, Department of Civil & Environmental Engineering M.T. Geoffrey Yeh Endowed Chair Department of Civil & Environmental Engineering, University of Illinois, Urbana, IL 61801 |
Abstract:
Plasticity induced closure often strongly influences the behavior
of fatigue cracks at engineering scales in metallic materials.
Current predictive models generally adopt the effective
stress-intensity factor $(\Delta K_{eff}= K_{max} - K_{op})$
in a Paris law type relationship to quantify crack growth rates.
This work describes 3-D computational studies of mode I fatigue
crack growth in the small-scale yielding (SSY) regime under
a constant amplitude cyclic loading and variable T-stress
ratios for $R = K_{min}/K_{max}\geq 0 $. Dimensional analysis
suggests, and the computational results confirm, that the
normalized remote opening load value,
$K_{op}/K_{max}$ ,
at each location along the crack front remains unchanged
when the peak load $(K_{max})$, thickness $(B)$ and
material flow stress $(\sigma_{0})$ all vary to maintain a
fixed value of ${\overline K}=K_{max}/ \sigma_{0}\sqrt{B}$.
Through parametric computations at various ${\overline K}$
levels, the results illustrate the effects of normalized peak
loads on the through-thickness, opening-closing behavior and the
effects of $\sigma_{0}/E$, where $E$ denotes material elastic
modulus. Subsequent studies have demonstrated the applicability of
the new scaling relationship for closure in overload situations
and for $ R < 0$ loadings. This new scaling relationship and the
computational results provide the needed framework to rationalize
and extend existing simplified models of the crack closure
process in industrial codes now used for life assessment of
critical structures.
Brown Analysis Seminar
Scientific Computing Seminar
New Late Posting as of 2/23/2006
Pop Code Seminar
Abstract: Simultaneous mapping of preferred location and orientation onto the primary visual cortex creates heterogeneity in the neuronal population, which influences the encoding and estimation of the orientation of short stimulus lines. A model of population response is constructed by combining realistic response properties of individual neurons and cortical maps of orientation and location preferences. The encoding error, computed from Fisher information, and the error of the population vector (PV) estimator are mapped as a function of location and orientation of the stimulus. The encoding error, and the variance and the bias of the PV estimator are modulated by the underlying orientation preference map.
PDE Seminar
Department of Mathematics Colloquium
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