Scientific instruments and computer simulations are creating vast data stores that require new scientific methods to analyze and organize the data. Data volumes are approximately doubling each year. Since these new instruments have extraordinary precision, the data quality is also rapidly improving. Analyzing this data to find the subtle effects missed by previous studies requires algorithms that can simultaneously deal with huge datasets and that can find very subtle effects --- finding both needles in the haystack and finding very small haystacks that were undetected in previous measurements.

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In mathematical models, very simple communities consisting of three or more species frequently display chaotic dynamics which implies that long-term predictions of the population trajectories in time are impossible. Communities in the wild tend to be more complex, but evidence for chaotic dynamics from such communities is scarce. We used supercomputing power to test the hypothesis that chaotic dynamics become less frequent in model ecosystems when their complexity increases. We determined the dynamical stability of a universe of mathematical, nonlinear food web models with varying degrees of organizational complexity. We found that the frequency of unpredictable, chaotic dynamics increases with the number of trophic levels in a food web but decreases with the degree of complexity. Our results suggest that natural food webs possess architectural properties that may intrinsically lower the likelihood of chaotic community dynamics.

Microstructurally small fatigue crack (MSFC) formation includes stages of incubation, nucleation and microstructurally small propagation. In AA 7075-T651, the fracture of Al 7 Cu 2 Fe constituent particles is the major incubation source. In experiments, it has been observed that only a small percentage of these Fe-bearing particles crack in a highly stressed volume. The work presented here addresses the identification of the particles prone to cracking and the prediction of particle cracking frequency, given a distribution of particles and crystallographic texture in such a volume. Three-dimensional elasto-viscoplastic finite element analyses are performed to develop a response surface for the tensile stress in the particle as a function of the strain level surrounding the particle, parent grain orientation and particle aspect ratio. A technique for estimating particle strength from fracture toughness, particle size and intrinsic flaw size is developed. Particle cracking is then determined by comparing particle stress and strength. The frequency of particle cracking is then predicted from sampling measured distributions of grain orientation, particle aspect ratio and size. Good agreement is found between the predicted frequency of particle cracking and two preliminary validation experiments. An estimate of particle cracking frequency is important for simulating the next

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