Monte Carlo simulation of grain growth and recrystallization in polycrystalline materials

The prediction and control of metal grain structures during processing have been major objectives of materials science. However, methodologies that are accurate and can be easily generalized to a variety of processing conditions have been difficult to formulate due to the complexity of the grain interactions. A novel Monte Carlo-based approach that explicitly incorporates these interactions has been developed to simulate the microstructural evolution driven by the minimization of grain boundary energy and lattice defect density. The applicability of this procedure has been demonstrated by the good correspondence between simulation results and experimental observations. This article reviews recent advances in the application of this technique to the investigation of a variety of phenomena, including normal and abnormal grain growth as well as static and dynamic recrystallization.     

Forming the optimal union of multiple databases

Many organizations, best illustrated by libraries, have access to hundreds of databases possessing varying degrees of complimentary and overlapping records. While users may receive positive marginal benefits from data duplications, all databases and their services cannot be supported because of resource limitations. This paper attempts to conceptualize the problem of database collection in an environment of multiple databases, with differential content and performance characteristics, diverse users, and limited resources. It defines the database collection problem as a constrained zero-one integer programming problem and solves for the optimal combination or union of databases. Several extensions are shown, where special conditions are imposed on the relationships between databases and/or their availability.     

Improved Poisson intensity estimation: denoising application using Poisson data

Recently, Timmermann and Nowak developed algorithms for estimating the means of independent Poisson random variables. The algorithms are based on a multiscale model where certain random variables are assumed to obey a beta-mixture density function. Timmermann and Nowak simplify the density estimation problem by assuming the beta parameters are known and only one mixture parameter is unknown. They use the observed data and the method of moments to estimate the unknown mixture parameter. Taking a different approach, we generate training data from the observed data and compute maximum likelihood estimates of all of the beta-mixture parameters. To assess the improved performance obtained by the proposed modification, we consider a denoising application using Poisson data.     

Suppression of void coalescence in thermal aging of tin-silver-copper-X solder joints

Addressing the potential for drop impact failure of Pb-free interconnects, the shear ductility after extensive aging of Sn-Ag-Cu (SAC) solders has been improved radically by Co or Fe modifications. Several other SAC+X candidates (X=Mn, Ni, Ge, Ti, Si, Cr, and Zn) now have been tested. Solder joint microstructures and shear strength results show that new SAC+X alloys also suppress void formation and coalescence at the Cu (substrate)/Cu₃Sn interface (and embrittlement) after aging at 150°C for up to 1,000 h. Microprobe measurements of 1,000 h aged samples suggest that Cu substitution by X is usually accentuated in the intermetallic layers, consistent with X=Co and Fe results.     

PV system sizing using observed time series of solar radiation

Sizing represents an important part of photovoltaic system design. This paper describes a sizing procedure based on the observed time series of solar radiation. Using a simple geometrical construction, the sizing curve is determined as a superposition of contributions from individual climatic cycles of low daily solar radiation. Unlike the traditional methods based on loss-of-load probability, the reliability of supply enters in this method through the length of the time series of data used in the analysis. The method thus resembles techniques used in other branches of engineering where extreme values are considered as functions of certain recurrence intervals.     

Outcome of different treatment mixes in a multidimensional neuropsychological rehabilitation program.

Within a clinical demonstration program, 59 traumatically brain-injured patients were treated with 1 of 3 mixes of treatment. Mix 1 included cognitive remediation (CGR), small-group interpersonal (SGI) communication training, therapeutic community activities, and personal counseling. Mix 2 was similar to Mix 1 but stressed SGI exercises and eliminated CGR. Mix 3 emphasized CGR and eliminated SGI exercises. The efficacy of the treatment mixes was evaluated with performance on neuropsychological tests, improved independence in functional activities, measures of intra- and interpersonal functioning, and vocational outcome. Ss' participation in the program, irrespective of treatment mix, yielded improvements in (1) self-image, (2) quality of interpersonal relatedness and interaction, (3) involvement with others in naturalistic settings, and (4) vocational outcome. Overall, data point to the superiority of the balanced mix (Mix 1) over Mixes 2 and 3. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Influence of the deposition atmosphere on the characteristics of Pd–Mg thin films prepared by pulsed laser deposition

Bilayered palladium (30 nm thick)–magnesium (350 nm thick) thin films were prepared using the pulsed laser deposition technique in the presence of various background gases (Ar, He and a mixture He + H₂) under different partial pressures (47 and 27 Pa). According to the deposition atmosphere, the Pd/Mg interface shows either a sharp or an extended transition. The electrochemical hydriding properties and the mechanical stability upon cycling of the Pd/Mg film are greatly improved when an extended «intermixing» zone between the Pd and Mg layers is present. The Pd–Mg films prepared under pure helium fulfill these conditions.     

Embedded micromachined fiber-optic Fabry-Perot pressure sensors in aerodynamics applications

Small size, high bandwidth pressure sensors are required for instrumentation of probes and test models in aerodynamic studies of complex unsteady flows. Optical-fiber pressure sensors promise potential advantages of small size and low cost in comparison with their electrical counterparts. We describe miniature Fabry-Perot cavity pressure sensors constructed by micromachining techniques in a turbine test application. The sensor bodies are 500 /spl mu/m squared, 300 /spl mu/m deep with a /spl sim/2 /spl mu/m-thick copper diaphragm electroplated on one face. The sensor cavity is formed between the diaphragm and the cleaved end of a single mode fiber sealed to the sensor by epoxy. Each sensor is addressed interferometrically in reflection by three wavelengths simultaneously, giving an unambiguous phase determination; a pressure sensitivity of 1.6 radbar/sup -1/ was measured, with a typical range of vacuum to 600 kPa. Five sensors were embedded in the trailing edge of a nozzle guide vane installed upstream of a rotor in a full-scale turbine stage transient test facility. Pressure signals in the trailing edge flow show marked structure at the 8 kHz blade passing frequency. To our knowledge, this is the first report of sensors located at the trailing edge of a normal-sized turbine blade.     

Linear and nonlinear methods for brain-computer interfaces

At the recent Second International Meeting on Brain-Computer Interfaces (BCIs) held in June 2002 in Rensselaerville, NY, a formal debate was held on the pros and cons of linear and nonlinear methods in BCI research. Specific examples applying EEG data sets to linear and nonlinear methods are given and an overview of the various pros and cons of each approach is summarized. Overall, it was agreed that simplicity is generally best and, therefore, the use of linear methods is recommended wherever possible. It was also agreed that nonlinear methods in some applications can provide better results, particularly with complex and/or other very large data sets.