A University of Arkansas researcher has created a computer model that may prevent the kind of unexpected and uncontrollable swaying that caused London’s Millennium Bridge to be closed.
His model can be used for both suspension and rigid bridges.
‘It is like being able to put the entire bridge into a wind tunnel to test it,’ explained Panneer Selvam, professor of civil engineering. ‘It is critical to check wind velocity to eliminate flutter, but that is difficult to do in the real world.’
In the past, builders have tested bridge stability by putting a model of the bridge in a wind tunnel. While this provides some information, scaling up to full size can cause discrepancies in the way the bridge actually performs. In addition, a wind tunnel may not accurately represent the airflow at the site where the bridge will be built.
This location-specific type of wind flow was the primary cause of the collapse of the Tacoma Narrows Bridge in 1940. In recent years, scientists have tried to improve the stability of bridges by using computer models. These early models required a lot of computer resources and time, but produced limited results.
‘Other models and wind tunnel studies typically require between one and three months and a lot of computing resources to execute,’ said Selvam. ‘Our model is very robust and can provide more information, but it takes only one or two days on a desktop computer.’
Although wind may be coming straight at a bridge, once it hits the structure it forms eddies and currents around the bridge. These complex wind movements produce the flutter that can damage or destroy a bridge.
Selvam’s approach, fluid-structure interaction (FSI) modelling, uses moving grids that are constantly being refined and unrefined, according to the movement of the wind vortices.
‘Information on the wind currents at a location is available, but modelling it is a highly complex problem,’ said Selvam. ‘Even with modern computers, the amount of computing time required to model a bridge system with these early approaches is immense.’
FSI overcomes these limitations by using new solution techniques that can reduce the computation time by an order of 10. A model that previously required 500 days to execute can now be completed in only five days, Selvam explained.
Use of the moving grid and new computation techniques allows the FSI model to include more parameters and produce a clearer picture of how the actual bridge will perform under different conditions.
Because it includes more detailed information in a much shorter time, the FSI model will allow bridge designers to build safer, more durable structures.