Methods and systems to predict fatigue life in aluminum castings

Abstract

Methods and systems of predicting fatigue life in aluminum castings that combines extreme values of both casting flaws and microstructures with multiscale life models. The multiscale life models account for differing fatigue crack initiation based on the size scale of the defect and microstructure features, including provisions for generally millimeter scale casting flaws, generally micrometer scale second phase particles by cracking or debonding, or submicrometer scale dislocation interactions with precipitates which form persistent slip bands. In the presence of casting flaws, the fatigue initiation life is negligible and the total fatigue life is spent in propagation of a fatigue crack from such flaws. In the absence of casting flaws, however, the total fatigue life is spent in both crack initiation and propagation, except for the case where fatigue cracks initiate from large second phase particles in a coarse microstructure. The extreme values of casting flaws, second phase particles, mean free path through an aluminum matrix or grain sizes are obtained from extreme value statistics when two or three dimensional sizes of casting flaws and microstructure features are provided by either direct measurement or analytical prediction. The upper bound flaw or microstructure feature size is calculated by extreme value statistics.

Description

BACKGROUND OF THE INVENTION[0001]The present invention relates generally to methods and systems of predicting fatigue life in aluminum castings, and more particularly to predicting fatigue life of a cast aluminum object by combining extreme value statistics and multiscale fatigue life models with casting flaw and microstructural constituent types, sizes and shapes.[0002]Improved fuel efficiency is an important goal in automotive design. One way to help achieve this goal is through the use of lightweight materials in the construction of vehicle component parts, including in the powertrain and related componentry. In addition to making such components lighter, it is desirable to keep their cost of production low, through the use of casting and related scalable processes. For example, aluminum based materials and related methods of casting may be employed where heretofore heavy materials (typically, steel or other iron based alloys) have been used.[0003]Nevertheless, care must be taken...

AI Technical Summary

Benefits of technology

[0006]These desires are met by the present invention, wherein improved methods and systems for predicting fatigue life in aluminum castings are disclosed. Such methods and systems combine extreme value statistics (EVS) to predict a maximum casting flaw size, in conjunction with multiscale life (also called multiscale fatigue (MSF)) models, to more accurately estimate fatigue properties of the casting. The present inventors have discovered that fatigue predictions that vary depending on the scale or size regime of the flaw (defect) lead to more accurate forecasts of fatigue properties in cast components than if such different scales are not taken into consideration. In this way, the relatively large scale of the aforementioned flaws...

Problems solved by technology

As stated above, when casting flaws (for example, porosity, voids, oxide films or...

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