Computational Models Aid in Prediction of Material Failure, Fatigue

Adding impurities in a virtual setting makes it easier to test different material combinations

Computational Models Aid in Prediction of Material Failure, Fatigue

Computational Models Aid in Prediction of Material Failure, Fatigue

Reliable performance of aerospace materials is crucial to maintain safe and efficient operations while aircrafts hurtle through the stratosphere. Traditional methods of testing and evaluating materials for life limiting features are cumbersome and time intensive.

A research team led by Michael D. Sangid, the Elmer F. Bruhn Professor of Aeronautics and Astronautics, has developed a computational methodology to execute predictive models to account for the lifespan of materials, including nickel-based superalloys, titanium alloys and structural composites. Four examples are provided in terms of addressing the reliability of materials in an attempt to improve aircraft safety.

As a first example — many times, these life limiting features take the form of intermetallic inclusions, which are impurities in the material. Since these inclusions represent rare events — needles in the haystack — it is difficult to test a sufficient quantity of material to understand their effect on the material's life. Sangid's group uses computational techniques, known as crystal plasticity, to model materials with inclusions as well as experimental techniques using high energy X-rays to characterize the response of the material and the inclusions during loading.

By computationally modeling inclusions in the material, the research team can account for more broad scenarios, thereby developing a richer probabilistic approach to the material's capabilities to complement traditional experiments.

"A lot of the methodology done to date relies on technology that's 70 years old," Sangid said. "Our methodology doesn't rely on large-scale testing campaigns focused on making and breaking of parts. Developing the material in a virtual setting and computationally testing the materials results in time and cost savings when compared to traditional techniques."

Second, Sangid's research group is also applying computational methods to better understand the phenomenon of cold dwell fatigue in titanium alloys, a commonly used material in aircrafts. At lower temperatures, hold times on titanium materials reduce the lifetime of the material and can result in premature aircraft failures. "Once we understand how the material's microstructure is responding under certain conditions, we can develop computational approaches to predict this behavior in an effort to manage titanium cold dwell behaviors, in order to mitigate failure," Sangid said.

Third, "As we start to introduce new materials and manufacturing processes into service, we must have ways of qualifying these materials can operate safely," Sangid said. "There are many operating conditions and environments that we might not fully understand or have experience with, so rigorous testing in our labs that mimic in service flight operation, as well as computational modeling, provide an understanding of the failure mechanisms and the associated lifetime for the material."

Some of the new materials the group is testing include ceramic matrix composites and metallic alloys made through additive manufacturing. They're also evaluating more familiar materials, such as carbon fiber reinforced polymer (CFRP) composites which have been used to build aircrafts for the past two decades.

Service usage and laboratory testing have recently revealed CFRP materials to be susceptible to slow crack growth associated with fatigue. Sangid's team is developing a fatigue criteria using X-ray techniques and computational approaches to identify the remaining lifetime for the aircraft's CFRP components, in order to proactively manage the inspection and replacement of susceptible parts.

Sangid's industrial background, witnessing the effects of material failures in a lab setting and understanding the limitations of testing, drives his passion for improving safety in the aerospace industry through the development of new computational methodologies.

"When it comes to aircraft, we have the smallest margins for risk of nearly any other industrial sector," he said. "At the same time, any overly-conservative design results in excessive fuel consumption and exhaust byproducts."

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