Molecular dynamics simulations of sliding in an Fe-Cu tribopair system

Experimental evidence suggests that high strain rates, stresses, strains and temperatures are experienced near sliding interfaces. The associated microstructural changes are due to several dynamic an interacting phenomena. 3D non-equilibrium molecular dynamics (MD) simulations of sliding were conducted with the aim of understanding the dynamic processes taking place in crystalline tribopairs, with a focus on plastic deformation and microstructural evolution. Embedded atom potentials were employed for simulating sliding of an Fe-Cu tribopair. Sliding velocity, crystal orientation and presence of lattice defects were some of the variables in these simulations. Extensive plastic deformation involving dislocation and twin activity, dynamic recrystallization, amorphization and/or nanocrystallization, mechanical mixing and material transfer were observed. Mechanical mixing in the vicinity of the sliding interface was observed even in the Fe-Cu system, which would cluster under equilibrium conditions, hinting at the ballistic nature of the process. Flow localization was observed at high velocities implying the possible role of adiabatic heating. The presence of preexisting defects (such as dislocations and interfaces) played a pivotal role in determining friction and microstructural evolution. The study also shed light on the relationship between adhesion and plastic deformation, and friction. Comparisons with experiments suggest that such simulations can indeed provide valuable insights that are difficult to obtain from experiments.

Oxygen desorption from high Tc YBa2Cu3O7−δ (δ = 0.05, 0.5)

From a temperature programmed desorption study employing a quadrupole mass spectrometer, the superconducting oxide YBa2Cu3O7−δ (δ = 0.05) showed two distinct oxygen desorption peaks, one below and one above 470°C. The activation energy of oxygen desorption of the superconducting oxide was 28 Kcals/mole and that of non-superconducting oxide (YBa2Cu3O6.5) was 54 Kcals/mole. No impurity peaks due to H2O, CO and CO2 from the bulk or adsorbed on surfaces could be observed when a well prepared superconducting oxide was heated up to 650°C.

Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster-Shafer and Bayesian approaches

Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change. (C) 2010 Elsevier Ltd. All rights reserved.

A finite population model of mlecular evolution: theory and computation

This article is concerned with the evolution of haploid organisms that reproduce asexually. In a seminal piece of work, Eigen and coauthors proposed the quasispecies model in an attempt to understand such an evolutionary process. Their work has impacted antiviral treatment and vaccine design strategies. Yet, predictions of the quasispecies model are at best viewed as a guideline, primarily because it assumes an infinite population size, whereas realistic population sizes can be quite small. In this paper we consider a population genetics-based model aimed at understanding the evolution of such organisms with finite population sizes and present a rigorous study of the convergence and computational issues that arise therein. Our first result is structural and shows that, at any time during the evolution, as the population size tends to infinity, the distribution of genomes predicted by our model converges to that predicted by the quasispecies model. This justifies the continued use of the quasispecies model to derive guidelines for intervention. While the stationary state in the quasispecies model is readily obtained, due to the explosion of the state space in our model, exact computations are prohibitive. Our second set of results are computational in nature and address this issue. We derive conditions on the parameters of evolution under which our stochastic model mixes rapidly. Further, for a class of widely used fitness landscapes we give a fast deterministic algorithm which computes the stationary distribution of our model. These computational tools are expected to serve as a framework for the modeling of strategies for the deployment of mutagenic drugs.

Stalagmite growth perturbations from the Kumaun Himalaya as potential earthquake recorders

The central part of the Himalaya (Kumaun and Garhwal Provinces of India) is noted for its prolonged seismic quiescence, and therefore, developing a longer-term time series of past earthquakes to understand their recurrence pattern in this segment assumes importance. In addition to direct observations of offsets in stratigraphic exposures or other proxies like paleoliquefaction, deformation preserved within stalagmites (speleothems) in karst system can be analyzed to obtain continuous millennial scale time series of earthquakes. The Central Indian Himalaya hosts natural caves between major active thrusts forming potential storehouses for paleoseismological records. Here, we present results from the limestone caves in the Kumaun Himalaya and discuss the implications of growth perturbations identified in the stalagmites as possible earthquake recorders. This article focuses on three stalagmites from the Dharamjali Cave located in the eastern Kumaun Himalaya, although two other caves, one of them located in the foothills, were also examined for their suitability. The growth anomalies in stalagmites include abrupt tilting or rotation of growth axes, growth termination, and breakage followed by regrowth. The U-Th age data from three specimens allow us to constrain the intervals of growth anomalies, and these were dated at 4273 +/- 410 years BP (2673-1853 BC), 2782 +/- 79 years BP (851-693 BC), 2498 +/- 117 years BP (605-371 BC), 1503 +/- 245 years BP (262-752 AD), 1346 +/- 101 years BP (563-765 AD), and 687 +/- 147 years BP (1176-1470 AD). The dates may correspond to the timings of major/great earthquakes in the region and the youngest event (1176-1470 AD) shows chronological correspondence with either one of the great medieval earthquakes (1050-1250 and 1259-1433 AD) evident from trench excavations across the Himalayan Frontal Thrust.