Building More Reliable Models of Materials

Research sponsored by U.S. Office of Naval Research used world-leading capability at the CNBC to observe stresses while applying tension or compression in two directions. These stress measurements provide vital data to improve material modelling capabilities.

Source: Canadian Neutron Beam Centre (CNBC)
Contact: cnbc@cnl.ca
Image: USS Farragut (U.S. Navy)

The United States spends tens of billions of dollars each year in the construction of ships for defense. It is no wonder, then, that the U.S. Office of Naval Research (ONR) funds basic research programs that may one day stretch defense dollars further.

Professor Paul Dawson of Cornell University, who has received ONR funding for about 20 years, aims to create a scientific model that could serve as a foundation for the future design of materials that last longer, perform better, and increase safety margins. Improved alloys, for example, could enhance the ability of ship hulls to withstand pressure or last longer, thereby reducing maintenance costs.

Currently used models sometimes fail to predict a material’s behaviour under stress, because they neglect the properties of microscopic grains in the material. Engineers are frequently forced to compensate for this uncertainty by conservatively overbuilding essential parts in a ship, car or airplane. Overbuilding increases purchase prices as well as fuel costs.

Prof. Dawson’s long-term research program combines advanced simulations and experiments, to understand on a fundamental level how materials change or break when subjected to stress. His model will be more reliable because it will account for microscopic properties that current models neglect.

Over the past 15 years, Prof. Dawson has used the neutron beamlines at the CNBC for numerous measurements of stress in materials under realistic conditions of tension or compression. His recent experiments have used a new world-leading capability at the CNBC to observe stresses while applying tension or compression in two directions. These stress measurements provide vital data for Prof. Dawson to refine his model.

doi:10.1016/j.jmps.2012.01.007