journal article·2018-06

Effect of electrical discharge machining on corrosion and corrosion fatigue behavior of aluminum alloys

Saravanan R. Arunachalam, Sarah E. Galyon Dorman, Richard T. Buckley, N. Aidan Conrad, Scott A. Fawaz

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Abstract

Abstract Electrical discharge machining (EDM) is often used in the manufacturing of fatigue test coupons because it allows for the production of complex shapes and sharp starting notches. However, the effect that the machining process has on the corrosion susceptibility due to the surface alterations is unknown. This work focuses on the effect the machining method has on the corrosion and corrosion fatigue behavior of aluminum alloys. The study is aimed at understanding the influence of EDM processes on environmentally assisted cracking evaluations, namely crack growth rate. Conventional milling and electrical discharge machining were the machining process examined in this study; the machining parameters used were best practices for laboratory fatigue sample production. The following aluminum alloys (AA) 2024-T351, 5083-H116, 6061-T6 and 7075-T651 were evaluated in this study. EDM was performed using a 0.152 mm (0.006 in.) hard brass wire. Surface quality evaluations, microstructural analysis, electrochemical tests and corrosion fatigue testing in sodium chloride (NaCl) solution were completed. The study found corrosion rates are affected by the EDM machining in all aluminum alloys. In final testing, crack growth rate tests were completed in sodium chloride solution with starter notches that were traditionally cut and EDM machined for 7xxx and 2xxx series alloys. The testing showed accelerated fatigue crack growth rates for the samples with EDM notches as compared to cut notches.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Machining and Optimization Techniques · Advanced machining processes and optimization · Advanced Surface Polishing Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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