Taking modelling to a different plane

Background

BAE Systems is a global company engaged in the development, delivery and support of advanced defence and aerospace systems in the air, on land and at sea.

They are the largest European defence company with annual sales exceeding £12 billion ($22 billion) and 88,000 employees.

The problem

Computer modelling has become an indispensable tool in modern engineering design. The aerospace industry makes extensive use of computational fluid dynamics (CFD) simulations in the design of new aircraft. BAE SYSTEMS have an in-house CFD code which they use to model the aerodynamics of military aeroplanes. Accurate prediction of the airflows around the whole aircraft is important in determining the heat and noise characteristics in operation, both of which impact on running costs. However, whole aircraft simulations were impossible to achieve using single processor hardware. Ground breaking code development was required to allow this.

The challenge

Solving equations of fluid flow is non-trivial even for simple geometries. Solving them exactly for complicated geometries such as a whole aircraft is impossible. Best approximations are approached by constructing 3D finite element grids around the surface of interest. Grid mesh size varies depending on the rate of change of the property being modelled. Grids of over 10 million nodes are possible; however they can only be run in reasonable timescales using parallel computing techniques. The challenge was to convert the BAE SYSTEMS in-house code to operate in parallel mode in order to enable accurate whole aircraft simulations to be performed in acceptable timescales.

The solution 

The development of parallel computing techniques is based on partitioning the grid into roughly equal sections and then distributing each section to a separate processor. Inter-processor communication is used to update points on the surface of each sub-grid. In practice, a three stage process is used involving coarsening, re-partitioning and refinement. The method developed at Daresbury is self adapting, inserting extra grid points as necessary where the solution varies rapidly. This can lead to load imbalance among the several processors and so a load sharing mechanism is also used. Using a 128 processor distributed memory architecture this approach succeeded in delivering whole aircraft simulation involving over half a million nodes and, in addition, the solution was achieved 80 times faster than it would have been on a single processor of equivalent capacity.

The benefits

The customer has gained an ability to perform computer simulations that were previously not achievable.

Whole aircraft simulations can now be performed in a fraction of the time taken previously, allowing design improvements leading to product optimisation and significant savings in both time and money.

The customer has effected a permanent improvement, keeping it at the forefront of aerospace technology.