Evaluation and Prediction of Fatigue Behavior of Carburized Steel under Uniaxial and Torsional Cyclic Loading Eaton India Innovation Center

Format:

Book

Conference/Event

Author/Creator:

Bhadak, Bhalchandra, author.

Contributor:

Carroll, Jason

Roy, Trishita

Wink, Carlos

Conference Name:

International Conference on Automotive Materials and Manufacturing AMM 2023 (2023-06-01 : Pune, India)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2023

Summary:

Improving fatigue resistance is a key factor to design components for advanced vehicle transmissions. The selection of materials and heat treatment plays a crucial role in controlling fatigue performance of power transmission components such as gears and shafts. Traditional, low frequency fatigue testing, used for identifying fatigue limit or generating S-N curve for multiple sets of material parameters is highly time consuming and expensive. Hence, it is necessary to develop the capability to predict fatigue performance of materials at different loading conditions with limited amount of data for instance the hardness and inclusion size. In the present work, we have evaluated behavior of the carburized steel subjected to axial and torsional cyclic loading conditions at low frequencies. The effect of different loading conditions is reflected in fatigue life curves (S-N curves), which provides correlation factor given as τ/σ = 0.841 ± 6%, between cyclic torsional stress and axial stress amplitude. Further, using scanning electron microscope (SEM), fracture morphologies were analyzed. It was revealed that, during axial fatigue testing two types of failure modes were obtained id est, sub-surface and surface failures; while in torsional fatigue testing, failures initiated at the sample surface and exhibited a spiral fractured morphology. Model of Liu is utilized to predict the S-N curve during axial cyclic loading where size of sub-surface defect id est, inclusion and material hardness were provided as input variables. Moreover, with the help of derived correlation factor, the S-N curve during torsional cyclic loading was derived. It is found that the predicted S-N curve, and experimental results are in good agreement. Altogether, this work provides an approach to derive S-N curves using metallurgical properties during two different loading conditions for carburized steel

Notes:

Vendor supplied data

Publisher Number:

2023-28-1330

Access Restriction:

Restricted for use by site license