The Effect of Microstructural Heterogeneity on Ductile Failure

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Flow convergence caused by a salinity minimum in a tidal channel

© 2006 The Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The definitive version was published in San Francisco Estuary and Watershed Science 4 (2006): Issue 3, Article 1.Residence times of dissolved substances and sedimentation rates in tidal channels are affected by residual (tidally averaged) circulation patterns. One influence on these circulation patterns is the longitudinal density gradient. In most estuaries the longitudinal density gradient typically maintains a constant direction. However, a junction of tidal channels can create a local reversal (change in sign) of the density gradient. This can occur due to a difference in the phase of tidal currents in each channel. In San Francisco Bay, the phasing of the currents at the junction of Mare Island Strait and Carquinez Strait produces a local salinity minimum in Mare Island Strait. At the location of a local salinity minimum the longitudinal density gradient reverses direction. This paper presents four numerical models that were used to investigate the circulation caused by the salinity minimum: (1) A simple one-dimensional (1D) finite difference model demonstrates that a local salinity minimum is advected into Mare Island Strait from the junction with Carquinez Strait during flood tide. (2) A three-dimensional (3D) hydrodynamic finite element model is used to compute the tidally averaged circulation in a channel that contains a salinity minimum (a change in the sign of the longitudinal density gradient) and compares that to a channel that contains a longitudinal density gradient in a constant direction. The tidally averaged circulation produced by the salinity minimum is characterized by converging flow at the bed and diverging flow at the surface, whereas the circulation produced by the constant direction gradient is characterized by converging flow at the bed and downstream surface currents. These velocity fields are used to drive both a particle tracking and a sediment transport model. (3) A particle tracking model demonstrates a 30 percent increase in the residence time of neutrally buoyant particles transported through the salinity minimum, as compared to transport through a constant direction density gradient. (4) A sediment transport model demonstrates increased deposition at the near-bed null point of the salinity minimum, as compared to the constant direction gradient null point. These results are corroborated by historically noted large sedimentation rates and a local maximum of selenium accumulation in clams at the null point in Mare Island Strait.The authors acknowledge support for this research from the California Department of Fish and Game, the California Coastal Conservancy, the U.S. Fish and Wildlife Service Coastal Program, and the U.S. Geological Survey Federal/State Cooperative and Priority Ecosystem Science Programs

Scalable Implementation of Finite Elements by NASA _ Implicit (ScIFEi)

Scalable Implementation of Finite Elements by NASA (ScIFEN) is a parallel finite element analysis code written in C++. ScIFEN is designed to provide scalable solutions to computational mechanics problems. It supports a variety of finite element types, nonlinear material models, and boundary conditions. This report provides an overview of ScIFEi (\Sci-Fi"), the implicit solid mechanics driver within ScIFEN. A description of ScIFEi's capabilities is provided, including an overview of the tools and features that accompany the software as well as a description of the input and output le formats. Results from several problems are included, demonstrating the efficiency and scalability of ScIFEi by comparing to finite element analysis using a commercial code

Modeling tax evasion with genetic algorithms

The U.S. tax gap is estimated to exceed $450 billion, most of which arises from non-compliance on the part of individual taxpayers (GAO 2012; IRS 2006). Much is hidden in innovative tax shelters combining multiple business structures such as partnerships, trusts, and S-corporations into complex transaction networks designed to reduce and obscure the true tax liabilities of their individual shareholders. One known gambit employed by these shelters is to offset real gains in one part of a portfolio by creating artificial capital losses elsewhere through the mechanism of “inflated basis” (TaxAnalysts 2005), a process made easier by the relatively flexible set of rules surrounding “pass-through” entities such as partnerships (IRS 2009). The ability to anticipate the likely forms of emerging evasion schemes would help auditors develop more efficient methods of reducing the tax gap. To this end, we have developed a prototype evolutionary algorithm designed to generate potential schemes of the inflated basis type described above. The algorithm takes as inputs a collection of asset types and tax entities, together with a rule-set governing asset exchanges between these entities. The schemes produced by the algorithm consist of sequences of transactions within an ownership network of tax entities. Schemes are ranked according to a “fitness function” (Goldberg in Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Boston, 1989); the very best schemes are those that afford the highest reduction in tax liability while incurring the lowest expected penalty.Mitre Corporation (Innovation Program

A Computationally-Efficient Probabilistic Approach to Model-Based Damage Diagnosis

This work presents a computationally-efficient, probabilistic approach to model-based damage diagnosis. Given measurement data, probability distributions of unknown damage parameters are estimated using Bayesian inference and Markov chain Monte Carlo (MCMC) sampling. Substantial computational speedup is obtained by replacing a three-dimensional finite element (FE) model with an efficient surrogate model. While the formulation is general for arbitrary component geometry, damage type, and sensor data, it is applied to the problem of strain-based crack characterization and experimentally validated using full-field strain data from digital image correlation (DIC). Access to full-field DIC data facilitates the study of the effectiveness of strain-based diagnosis as the distance between the location of damage and strain measurements is varied. The ability of the framework to accurately estimate the crack parameters and effectively capture the uncertainty due to measurement proximity and experimental error is demonstrated. Furthermore, surrogate modeling is shown to enable diagnoses on the order of seconds and minutes rather than several days required with the FE model

The polaroid image as photo-object

This article is part of a larger project on the cultural history of Polaroid photography and draws on research done at the Polaroid Corporate archive at Harvard and at the Polaroid company itself. It identifies two cultural practices engendered by Polaroid photography, which, at the point of its extinction, has briefly flared into visibility again. It argues that these practices are mistaken as novel but are in fact rediscoveries of practices that stretch back as many as five decades. The first section identifies Polaroid image-making as a photographic equivalent of what Tom Gunning calls the ‘cinema of attractions’. That is, the emphasis in its use is on the display of photographic technologies rather than the resultant image. Equally, the common practice, in both fine art and vernacular circles, of making composite pictures with Polaroid prints, draws attention from image content and redirects it to the photo as object

Quantifying Low Energy Proton Damage in Multijunction Solar Cells

An analysis of the effects of low energy proton irradiation on the electrical performance of triple junction (3J) InGaP2/GaAs/Ge solar cells is presented. The Monte Carlo ion transport code (SRIM) is used to simulate the damage profile induced in a 3J solar cell under the conditions of typical ground testing and that of the space environment. The results are used to present a quantitative analysis of the defect, and hence damage, distribution induced in the cell active region by the different radiation conditions. The modelling results show that, in the space environment, the solar cell will experience a uniform damage distribution through the active region of the cell. Through an application of the displacement damage dose analysis methodology, the implications of this result on mission performance predictions are investigated