Multiphysics modelling of the metals casting process

Metals casting is a process governed by the interaction of a range of physical phenomena. Most computational models of this process address only what are conventionally regarded as the primary phenomena-heat conduction and solidification. However, to predict the formation of porosity (a factor of key importance in cast quality) requires the modelling of the interaction of the fluid flow, heat transfer, solidification and the development of stress-deformation in the solidified part of a component. In this paper, a model of the casting process is described which addresses all the main continuum phenomena involved in a coupled manner. The model is solved numerically using novel finite volume unstructured mesh techniques, and then applied to both the prediction of shape deformation (plus the subsequent formation of a gap at the metal-mould interface and its impact on the heat transfer behaviour) and porosity formation in solidifying metal components. Although the porosity prediction model is phenomenologically simplistic it is based on the interaction of the continuum phenomena and yields good comparisons with available experimental results. This work represents the first of the next generation of casting simulation tools to predict aspects of the structure of cast components.

Reliability analysis of flip chip designs via computer simulation

A flip chip component is a silicon chip mounted to a substrate with the active area facing the substrate. This paper presents the results of an investigation into the relationship between a number of important material properties and geometric parameters on the thermal-mechanical fatigue reliability of a standard flip chip design and a flip chip design with the use of microvias. Computer modeling has been used to analyze the mechanical conditions of flip chips under cyclic thermal loading where the Coffin-Manson empirical relationship has been used to predict the life time of the solder interconnects. The material properties and geometry parameters that have been investigated are the Young's modulus, the coefficient of thermal expansion (CTE) of the underfill, the out-of-plane CTE (CTEz) of the substrate, the thickness of the substrate, and the standoff height. When these parameters vary, the predicted life-times are calculated and some of the features of the results are explained. By comparing the predicted lifetimes of the two designs and the strain conditions under thermal loading, the local CTE mismatch has been found to be one of most important factors in defining the reliability of flip chips with microvias.

Fitting host-parasitoid models with CV² > 1 using hierarchical generalized linear models

The powerful general Pacala-Hassell host-parasitoid model for a patchy environment, which allows host density–dependent heterogeneity (HDD) to be distinguished from between-patch, host density–independent heterogeneity (HDI), is reformulated within the class of the generalized linear model (GLM) family. This improves accessibility through the provision of general software within well–known statistical systems, and allows a rich variety of models to be formulated. Covariates such as age class, host density and abiotic factors may be included easily. For the case where there is no HDI, the formulation is a simple GLM. When there is HDI in addition to HDD, the formulation is a hierarchical generalized linear model. Two forms of HDI model are considered, both with between-patch variability: one has binomial variation within patches and one has extra-binomial, overdispersed variation within patches. Examples are given demonstrating parameter estimation with standard errors, and hypothesis testing. For one example given, the extra-binomial component of the HDI heterogeneity in parasitism is itself shown to be strongly density dependent.