Papers by Keyword: Wear Modeling

Abstract: The purpose of this work is to evaluate the performance of several wear models, either with different mathematical formulation or different definition of the unknown wear coefficients, on the prediction of the work-roll wear amplitude in Hot Strip Mills (HSM). To achieve this goal, a classical model calibration approach based on inverse optimization has been developed to calibrate these several wear models. A large industrial hot rolling database composed by roll wear amplitude measurements for both later finishing mill stands (F6 and F7) from ArcelorMittal Dofasco HSM was considered and a least-square cost function was applied to minimize the differences between both numerical and experimental results during the optimization process. The averaged roll wear gap between measurements and optimized numerical predictions was then used as a quantitative indicator to compare the performance between the wear models and identify the most suitable one for roll wear prediction. In addition, an Artificial Neural Network (ANN) approach was developed based on the most suitable wear model. Thus, roll wear predictions obtained using the ANN were compared with the ones obtained using Classical calibration to evaluate the performance of both approaches.

Abstract: Wear modeling makes it possible to predict the evolution of wear profile and explain wear mechanism from process variables, such as temperature, pressure and sliding velocity etc. A composite crater wear model considering adhesive and diffusion wear is established by means of experiment and modeling in conventional speed machining. A series of cutting tests are performed to obtain wear profiles and corresponding process variables. The constants in wear model are fitted by regression analysis with crater wear tests. This crater wear model shows a good predictive capability in conventional cutting speed.

Abstract: Virtual life testing is becoming a widely accepted methodology for predicting the life span of products. In this method, reliable models are important to predict different aspects of design performance, one of which is wear. Wear and has been a subject of numerous scientific and empirical investigations. Due to the complex and dynamic nature of the phenomena, there is no general wear model, which can be adopted for all wear problems. A systematic approach to the modelling of dry sliding wear using analytical time domain models is presented in this paper. Given the sliding distance, the model is capable of predicting wear status in transient (running-in) and steady-state operating conditions. The validity of the modelling approach is demonstrated by comparing the predicted results of wear experiments, with that actually measured. For simplicity, the model is based on sliding distance as input variable, while other factors like temperature, load, surface conditions are treated as constant. A simple geometry of sliding polymer-based contacts is used for establishing of wear model.