Sobre a simulação computacional com emprego do método GIWM para predição de desgaste por deslizamento em ensaio pino-disco de materiais roda-trilho ferroviários

• Ano de defesa: 2023
• Autor(a) principal: Silva e Silva, João Vitor Raimundo
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Mestrado em Engenharia Mecânica; Centro Tecnológico; UFES; Programa de Pós-Graduação em Engenharia Mecânica
• Palavras-chave em Português: Tribologia; Roda-trilho; Desgaste por deslizamento; Lei de Archard; Pino-disco; Simulação computacional; GlobaI Incremental Wear Model; subject.br-rjbn; Engenharia Mecânica
• Link de acesso: http://repositorio.ufes.br/handle/10/17136

Tribology encompasses the study of phenomena related to friction, wear, and lubrication of surfaces in contact and under relative motion. Wear due to sliding is a significant concern across various sectors, as seen in situations such as the interaction between a wheel and rail in railway systems, where pure sliding can occur during curves. Laboratory pin-on-disc tests are widely employed to investigate this type of wear; however, they exhibit limitations in terms of time and cost. Computational simulations utilizing the Finite Element Method (FEM) have been explored as an alternative to mitigate the need for these tests, yet they encounter challenges concerning computational expense and simulation duration. In this context, the present study assesses the capability of the semianalytical computational method known as GIWM (Global Incremental Wear Model) to identify the dimensional wear coefficient (m³/N.m) from pin-on-disc tests conducted on materials employed in railway wheels and rails under varying conditions. Additionally, the study employs this coefficient to predict the wear rate of these tribosystems when altering the applied normal load. To achieve this, experimental data drawn from laboratory databases and literature sources were employed both for model calibration (tests under 5 N and 300 N load) and for comparing its predictive capacity (tests under 10 N, 15 N, and 600 N load). It was observed that the GIWM method effectively identified the dimensional wear coefficient in all cases, and its predictions exhibited substantial agreement with a portion of the experimental results. Moreover, the algorithm demonstrated computational efficiency, with simulation times negligible compared to experiments and FEM simulations reported in the literature. Consequently, it was concluded that the GIWM method could diminish the necessity for conducting pin-on-disc tests with varying applied normal loads for materials within the wheelrail system, contingent upon the alteration in the normal load parameter not inducing severe fluctuations in the predominant wear mechanisms and wear intensity throughout the test.