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Application of Extreme Value Statistics for Predicting Engine Valve Spring Endurance Limit in Presence of Inclusions

Posted on:2009-03-15Degree:D.E.M.SType:Thesis
University:Lawrence Technological UniversityCandidate:Choucair, Hassan AliFull Text:PDF
GTID:2442390005459204Subject:Statistics
Abstract/Summary:
The reliability of engine valve springs is a very important issue from the warranty point of. This thesis presents a combined experimental and statistical analysis for predicting the fatigue limit of high tensile engine valve spring material in the presence of non-metallic inclusions. Experimentally, inclusion size and chemistry will be determined as a result of rotating bending and torsion fatigue testing. Fatigue tests will be performed on wires and valve springs of high strength material at different stress amplitudes. A model developed by Murakami and Endo, which is based on the fracture mechanics approach and on Extreme value statistics (GUMBEL Distribution), will be utilized for predicting the fatigue limit and the maximum inclusion size. Predicting the maximum inclusion size from the model will be verified experimentally. The two approaches, experimental and theoretical, will verify the Murakami Model for developing the S-N curve for latest valve spring material in the presence of non-metallic inclusions.;Upon completion of this research, a new model will be utilized by Associated Spring engineers for designing highly reliable engine valve springs. Besides predicting valve springs performances and warranty costs in the field, predicting the fatigue strength in the presence of inclusions will assist in improving and optimizing the current manufacturing process (specifically the compressive residual stress profile). Also, it will allow the steel makers enhance and implement better inclusion control methods.
Keywords/Search Tags:Engine valve, Valve spring, Inclusion, Predicting, Presence, Limit
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