There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

Deformation twinning in nanocrystalline materials

Refining a metal’s grain size can result in dramatic increases in strength, and the magnitude of this strengthening increment can be estimated using the Hall–Petch equation. Since the Hall–Petch equation was proposed, there have been many experimental studies supporting its applicability to pure metals, intermetallics and multi-phase alloys. In this article, we gather the grain-size strengthening data from the Hall–Petch studies on pure metals and use this aggregated data to calculate best estimates of these metals’ Hall–Petch parameters. We also use this aggregated data to re-evaluate the various models developed to physically support the Hall–Petch scaling.

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Six decades of the Hall–Petch effect – a survey of grain-size strengthening studies on pure metals

A dislocation-based constitutive law for pure Zr including temperature effects

Plate impact experiments have been carried out to examine the influence of grain boundary characteristics on the dynamic tensile response of Cu samples with grain sizes of 30, 60, 100, and 200 μm. The peak compressive stress is ∼1.50 GPa for all experiments, low enough to cause an early stage of incipient spall damage that is correlated to the surrounding microstructure in metallographic analysis. The experimental configuration used in this work permits real-time measurements of the sample free surface velocity histories, soft-recovery, and postimpact examination of the damaged microstructure. The resulting tensile damage in the recovered samples is examined using optical and electron microscopy along with micro x-ray tomography. The free surface velocity measurements are used to calculate spall strength values and show no significant effect of the grain size. However, differences are observed in the free surface velocity behavior after the pull-back minima, when reacceleration occurs. The magnitude of th...

Ellen K. Cerreta

Papers

Effects of grain size and boundary structure on the dynamic tensile response of copper

Grain size and boundary structure on the dynamic tensile response of copper

Quantitative analysis of deformation twinning in zirconium

An experimental and numerical study of the localization behavior of tantalum and stainless steel

A dislocation-based multi-rate single crystal plasticity model