Fatigue Resistance Optimization of Armored Vehicle Structures using Weld Master S-N Curve

This project began in 2018 and was completed in 2020.

To date, fatigue design and life evaluation methods for design evaluation of armored vehicles have been empirical at simple joint level under simple loading conditions, e.g., weld category approach by American Association of State Highway and Transportation Officials (AASHTO) and unable to take advantage of rapid advances in finite element structural modeling methods, resulting in significant uncertainties in structural lives for armored vehicles in operation. The situation will become even more severe for autonomous vehicles for which the dynamic loads are not limited by the presence of occupants (for example safety and comfort). As the Next Generation Combat Vehicle (NGCV) is expected to have manned and unmanned variations of the same vehicle, fatigue of weldments will become critical for avoiding cracks due to the dynamic loads developed under both sets of operating conditions.

With recent rapid advances in mesh-insensitive structural stress method and master S-N curve approach adopted by ASME Codes and Standards, a quantitative evaluation of armored vehicle structural life becomes possible once fatigue behaviors in thick armor plate weldments are understood in the context of relevant material combinations and welding conditions. Then, a relevant master S-N curve using the mesh-insensitive structural stress method can be formulated for implementation in structural optimization algorithms for evaluating design scenarios for achieving both required structural life and lightweighting goals. Such modeling capabilities also represent a significant advancement over the methods used in conventional automotive applications.

Research objectives and contributions of this project are:

• Develop a fundamental understanding of unique fatigue behaviors associated with thick plate joints used in armored vehicle structures through computational modeling and selected laboratory testing.
• Establish a theoretical framework for data transferability of fatigue test data from different joint types, loading modes, thicknesses, and material combinations relevant to applications in armored vehicles, i.e., master S-N curve representation of joint fatigue resistance.
• Develop computational algorithms for incorporating the master S-N curve developed for structural life evaluation and weight optimization for armored vehicle structures. The new algorithms will consider the candidate materials, the panel thicknesses, the layout of the welds, and the type of the welds as design variables. Improvement in performance metrics associated with lightweighting and reducing the manufacturing cost will be pursued, while meeting expectations for the fatigue life, and the survivability to loads from blast and ballistic impact.