Performance evaluation of a distributed algorithm for an inverse heat conduction problem

Numerical solutions of realistic 2-D and 3-D inverse problems may require a very large amount of computation. A two-level concept on parallelism is often used to solve such problems. The primary level uses the problem partitioning concept which is a decomposition based on the mathematical/physical problem. The secondary level utilizes the widely used data partitioning concept. A theoretical performance model is built based on the two-level parallelism. The observed performance results obtained from a network of general purpose Sun Sparc stations are compared with the theoretical values. Restrictions of the theoretical model are also discussed.

Parallel genetic algorithms for the solution of inverse heat conduction problems

A parallel genetic algorithm (PGA) is proposed for the solution of two-dimensional inverse heat conduction problems involving unknown thermophysical material properties. Experimental results show that the proposed PGA is a feasible and effective optimization tool for inverse heat conduction problems

A domain decomposition based algorithm for non-linear 2D inverse heat conduction problems

Inverse heat conduction problems (IHCPs) appear in many important scientific and technological fields. Hence analysis, design, implementation and testing of inverse algorithms are also of great scientific and technological interest. The numerical simulation of 2-D and –D inverse (or even direct) problems involves a considerable amount of computation. Therefore, the investigation and exploitation of parallel properties of such algorithms are equally becoming very important. Domain decomposition (DD) methods are widely used to solve large scale engineering problems and to exploit their inherent ability for the solution of such problems.

A Distributed algorithm for 1-D non-linear heat conduction with an unknown point source

Abstract not available

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.

Explicit finite volume modeling of aircraft anti-icing and de-icing

In this paper, a runback water and ice prediction model is extended to anti-icing and thermal de-icing situations. The resulting coupled equations that govern thin-film flow, ice accretion, and heat conduction in the multilayered system substrate-ice-water are solved using an explicit finite volume approach. The procedure is implemented in the three-dimensional icing code ICECREMO2, and both structured and unstructured grids can be considered. Numerical results are presented to compare the present code simulations to some data provided by other ice prediction codes and to show the capabilities of the present numerical tool.

PHYSICA: A multiphysics computational framework and its application to casting simulations

Metal 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 other phenomena, such as porosity formation, requires modelling the interaction of the fluid flow, heat transfer, solidification and the development of stressdeformation in the solidified part of the casting. This paper will describe a modelling framework called PHYSICA[1] which has the capability to stimulate such multiphysical phenomena.

Investigation into the performance of turbulence models for fluid flow and heat transfer phenomena in electronic applications

Heat is extracted away from an electronic package by convection, conduction, and/or radiation. The amount of heat extracted by forced convection using air is highly dependent on the characteristics of the airflow around the package which includes its velocity and direction. Turbulence in the air is also important and is required to be modeled accurately in thermal design codes that use computational fluid dynamics (CFD). During air cooling the flow can be classified as laminar, transitional, or turbulent. In electronics systems, the flow around the packages is usually in the transition region, which lies between laminar and turbulent flow. This requires a low-Reynolds number numerical model to fully capture the impact of turbulence on the fluid flow calculations. This paper provides comparisons between a number of turbulence models with experimental data. These models included the distance from the nearest wall and the local velocity (LVEL), Wolfshtein, Norris and Reynolds, k-ε, k-ω, shear-stress transport (SST), and kε/kl models. Results show that in terms of the fluid flow calculations most of the models capture the difficult wake recirculation region behind the package reasonably well, although for packages whose heights cause a high degree of recirculation behind the package the SST model appears to struggle. The paper also demonstrates the sensitivity of the models to changes in the mesh density; this study is aimed specifically at thermal design engineers as mesh independent simulations are rarely conducted in an industrial environment.