Discretisation procedures for multi-physics phenomena

Procedures are described for solving the equations governing a multi-physics process. Finite volume techniques are used to discretise, using the same unstructured mesh, the equations of fluid flow, heat transfer with solidification, and solid deformation. These discretised equations are then solved in an integrated manner. The computational mechanics environment, PHYSICA, which facilitates the building of multi-physics models, is described. Comparisons between model predictions and experimental data are presented for the casting of metal components.

Modelling the nano-scale phenomena in condensed matter physics via computer-based numerical simulations

A review of the atomistic modelling of the behaviour of nano-scale structures and processes via molecular dynamics (MD) simulation method of a canonical ensemble is presented. Three areas of application in condensed matter physics are considered. We focus on the adhesive and indentation properties of the solid surfaces in nano-contacts, the nucleation and growth of nano-phase metallic and semi-conducting atomic and molecular films on supporting substrates, and the nano- and multi-scale crack propagation properties of metallic lattices. A set of simulations selected from these fields are discussed, together with a brief introduction to the methodology of the MD simulation. The pertinent inter-atomic potentials that model the energetics of the metallic and semi-conducting systems are also given.

Surface physics at the nano-scale via scanning probe microscopy and molecular dynamics simulations

Probe-based scanning microscopes, such as the STM and the AFM, are used to obtain the topographical and electronic structure maps of material surfaces, and to modify their morphologies on nanoscopic scales. They have generated new areas of research in condensed matter physics and materials science. We will review some examples from the fields of experimental nano-mechanics, nano-electronics and nano-magnetism. These now form the basis of the emerging field of Nano-technology. A parallel development has been brought about in the field of Computational Nano-science, using quantum-mechanical techniques and computer-based numerical modelling, such as the Molecular Dynamics (MD) simulation method. We will report on the simulation of nucleation and growth of nano-phase films on supporting substrates. Furthermore, a theoretical modelling of the formation of STM images of metallic clusters on metallic substrates will also be discussed within the non-equilibrium Keldysh Green function method to study the effects of coherent tunnelling through different atomic orbitals in a tip-sample geometry.

Parallel performance in multi-physics simulation

A comprehensive simulation of solidification/melting processes requires the simultaneous representation of free surface fluid flow, heat transfer, phase change, non-linear solid mechanics and, possibly, electromagnetics together with their interactions in what is now referred to as "multi-physics" simulation. A 3D computational procedure and software tool, PHYSICA, embedding the above multi-physics models using finite volume methods on unstructured meshes (FV-UM) has been developed. Multi-physics simulations are extremely compute intensive and a strategy to parallelise such codes has, therefore, been developed. This strategy has been applied to PHYSICA and evaluated on a range of challenging multi-physics problems drawn from actual industrial cases.

Multi-physics-multi-scale simulation and optimisation: the next generation

FEA and CFD analysis is becoming ever more complex with an emerging demand for simulation software technologies that can address ranges of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and length scales. Computation modelling of such problems requires software technologies that enable the representation of these complex suites of 'physical' interactions. This functionality requires the structuring of simulation modules for specific physical phemonmena so that the coupling can be effectiely represented. These 'multi-physics' and 'multi-scale' computations are very compute intensive and so the simulation software must operate effectively in parallel if it is to be used in this context. Of course the objective of 'multi-physics' and 'multi-scale' simulation is the optimal design of engineered systems so optimistation is an important feature of such classes of simulation. In this presentation, a multi-disciplinary approach to simulation based optimisation is described with some key examples of application to challenging engineering problems.

Polymer waveguide and VCSEL array multi-physics modelling for OECB based optical backplanes [opto-electrical circuit boards]

The deployment of OECBs (opto-electrical circuit boards) is expected to make a significant impact in the telecomm switches arena within the next five years. This will create optical backplanes with high speed point-to-point optical interconnects. The crucial aspect in the manufacturing process of the optical backplane is the successful coupling between VCSEL (vertical cavity surface emitting laser) device and embedded waveguide in the OECB. The results from a thermo-mechanical analysis are being used in a purely optical model, which solves optical energy and attenuation from the VCSEL aperture into, and then through, the waveguide. Results from the modelling are being investigated using DOE analysis to identify packaging parameters that minimise misalignment. This is achieved via a specialist optimisation software package. Results from the thermomechanical and optical models are discussed as are experimental results from the DOE.

Computational modelling of multi-physics and multi-scale processes in parallel

This paper provides an overview of the developing needs for simulation software technologies for the computational modelling of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and space scales. Computational modelling of such problems requires software tech1nologies that enable the mathematical description of the interacting physical phenomena together with the solution of the resulting suites of equations in a numerically consistent and compatible manner. This functionality requires the structuring of simulation modules for specific physical phenomena so that the coupling can be effectively represented. These multi-physics and multi-scale computations are very compute intensive and the simulation software must operate effectively in parallel if it is to be used in this context. An approach to these classes of multi-disciplinary simulation in parallel is described, with some key examples of application to2 challenging engineering problems.

Multi-physics modelling for microelectronics and microsystems - current capabilities and future challenges

At present the vast majority of Computer-Aided- Engineering (CAE) analysis calculations for microelectronic and microsystems technologies are undertaken using software tools that focus on single aspects of the physics taking place. For example, the design engineer may use one code to predict the airflow and thermal behavior of an electronic package, then another code to predict the stress in solder joints, and then yet another code to predict electromagnetic radiation throughout the system. The reason for this focus of mesh-based codes on separate parts of the governing physics is essentially due to the numerical technologies used to solve the partial differential equations, combined with the subsequent heritage structure in the software codes. Using different software tools, that each requires model build and meshing, leads to a large investment in time, and hence cost, to undertake each of the simulations. During the last ten years there has been significant developments in the modelling community around multi- physics analysis. These developments are being followed by many of the code vendors who are now providing multi-physics capabilities in their software tools. This paper illustrates current capabilities of multi-physics technology and highlights some of the future challenges

Multi-physics modelling for the fabrication, packaging and reliability of micro-systems components

The latest advances in multi-physics modelling both using high fidelity techniques and reduced order and behavioural models will be discussed. Particular focus will be given to the application and validation of these techniques for modelling the fabrication, packaging and subsequent reliability of micro-systems based components. The paper will discuss results from a number of research projects with particular emphasis on the techniques being developed in a major UK Goverment funded project - 3D-MINTEGRATION (www.3d-mintegration.com).

Choosing the appropriate level of coupling in multi-physics modeling of metallurgical processes

A computational model for the interrelated phenomena in the process of vacuum arc remelting is analyzed and adjusted of optimal accuracy and computation time. The decision steps in this case study are offered as an example how the coupling in models of similar processes can be addressed. Results show dominance of the electromagnetic forces over buoyancy and inertia for the investigated process conditions.

Challenges in integrative approaches to modelling the marine ecosystems of the North Atlantic: Physics to fish and coasts to ocean

It has long been recognised that there are strong interactions and feedbacks between climate, upper ocean biogeochemistry and marine food webs, and also that food web structure and phytoplankton community distribution are important determinants of variability in carbon production and export from the euphotic zone. Numerical models provide a vital tool to explore these interactions, given their capability to investigate multiple connected components of the system and the sensitivity to multiple drivers, including potential future conditions. A major driver for ecosystem model development is the demand for quantitative tools to support ecosystem-based management initiatives. The purpose of this paper is to review approaches to the modelling of marine ecosystems with a focus on the North Atlantic Ocean and its adjacent shelf seas, and to highlight the challenges they face and suggest ways forward. We consider the state of the art in simulating oceans and shelf sea physics, planktonic and higher trophic level ecosystems, and look towards building an integrative approach with these existing tools. We note how the different approaches have evolved historically and that many of the previous obstacles to harmonisation may no longer be present. We illustrate this with examples from the on-going and planned modelling effort in the Integrative Modelling Work Package of the EURO-BASIN programme.

Arctic Oceanography - Oceanography: Atmosphere-Ocean Exchange, Biogeochemistry & Physics

The Arctic Ocean is, on average, the shallowest of Earth’s oceans. Its vast continental shelf areas, which account for approximately half of the Arctic Ocean’s total area, are heavily influenced by the surrounding land masses through river run-off and coastal erosion. As a main area of deep water formation, the Arctic is one of the main «engines» of global ocean circulation, due to large freshwater inputs, it is also strongly stratified. The Arctic Ocean’s complex oceanographic configuration is tightly linked to the atmosphere, the land, and the cryosphere. The physical dynamics not only drive important climate and global circulation patterns, but also control biogeochemical cycles and ecosystem dynamics. Current changes in Arctic sea-ice thickness and distribution, air and water temperatures, and water column stability are resulting in measurable shifts in the properties and functioning of the ocean and its ecosystems. The Arctic Ocean is forecast to shift to a seasonally ice-free ocean resulting in changes to physical, chemical, and biological processes. These include the exchange of gases across the atmosphere-ocean interface, the wind-driven ciruclation and mixing regimes, light and nutrient availability for primary production, food web dynamics, and export of material to the deep ocean. In anticipation of these changes, extending our knowledge of the present Arctic oceanography and these complex changes has never been more urgent.

Computational challenges in atomic, molecular and optical physics

Six challenges are discussed. These are the laser-driven helium atom; the laser-driven hydrogen molecule and hydrogen molecular ion: electron scattering (with ionization) from one-electron atoms; the vibrational and rotational structure of molecules such as H-3(+) and water at their dissociation limits; laser- heated clusters; and quantum degeneracy and Bose-Einstein condensation. The first four concern fundamental few-body systems where use of high-performance computing (HPC) is currently making possible accurate modelling from first principles. This leads to reliable predictions and support for laboratory experiment as well as true understanding of the dynamics. Important aspects of these challenges addressable only via a terascale facility are set out. Such a facility makes the last two challenges in the above list meaningfully accessible for the first time, and the scientific interest together with the prospective role for HPC in these is emphasized.