Failure and fatigue life estimate of a pre-stressed Aircraft seat support tube

• Published in: Engineering failure analysis Vol. 54; pp. 120 - 130
• Main Authors: Al-Bahkali, Essam A., Elkenani, Hisham, Souli, Mhamed
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2015; Elsevier
• Subjects: Aircraft; Aircraft components; Aluminum base alloys; Damage ratio; Engineering Sciences; Fatigue; Fatigue failure; Mathematical models; Power spectra density; Random vibration; Seats; Service life; Support tube; Tubes; Power spectra density; Support tube; Fatigue; Damage ratio; Random vibration
• ISSN: 1350-6307; 1873-1961; 1350-6307
• DOI: 10.1016/j.engfailanal.2015.04.001

•A random vibration analysis is conducted.•A contact algorithm is added to transfer the support’s movement to the tube.•Dirlik method is used for the analysis of lifetime.•Numerical analysis are in good agreement with the actual failure location.•The analysis gives cumulative damage ratio calculation and fatigue life prediction. There have been increasing reports of annoyance, fatigue, and even neck and back pain during prolonged operation of troop propeller aircraft, where persistent multi-axis vibration occurs at higher frequencies. A claim from failure of the 2024-T3 aluminum tube used as a seat support tube (SST) for troop seat – wall style – construction. A failure occurs after about 85 flight hours. A numerical static analysis model for the tube with its holders shows that it is safe, even with impact loading. In the present work, a random vibration analysis is conducted to calculate the lifetime of the SST. First, a static analysis is performed using a pressure load on part of the tube that represents the seating location, followed by random vibration analysis. A contact algorithm is added in order to transfer the support’s movement to the tube. Dirlik method is used for the analysis of lifetime as it is proven to provide accurate results for large number of applications, both in automotive and aerospace industry. The predicted service life is in a good agreement with the real actual life.