Avaliação da incerteza associada à temperatura de transição dúctil-frágil obtida via ensaios de impacto charpy
Ano de defesa: | 2024 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Uberlândia
Brasil Programa de Pós-graduação em Engenharia Mecânica |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | https://repositorio.ufu.br/handle/123456789/43674 http://doi.org/10.14393/ufu.di.2024.674 |
Resumo: | The Charpy impact test is an efficient method for evaluating the mechanical properties of materials applied in various industries, such as nuclear, naval, and oil and gas. The change in material behavior as a function of temperature, indicated by the ductile-to-brittle transition curve, helps in the proper selection of materials according to the operating temperature. Although the determination of the ductile-to-brittle transition temperature (DBTT) is widely discussed in the literature, it is necessary to understand how sources of error can impact the obtained result. In this context, this study aims to assess the uncertainty associated with DBTT obtained through conventional Charpy testing using the Monte Carlo method. To achieve this, the transition curve was fitted using the asymmetric hyperbolic tangent (AHT) method, and results regarding the behavior of the evaluated materials were obtained. Subsequently, uncertainties associated with both the absorbed energy (KV) and the test temperature (T) were determined using the GUM method for the three thermal conditioning methods employed. The results showed that the expanded uncertainty associated with the ductile-to-brittle transition temperature for AISI 4340-34 HRC steel is 2,85 °C, while for AISI 4340-40 HRC steel, it is 0,63 °C, representing 3,24% and 1,74% of the DBTT value with a 95,45% coverage probability. Analyzing the temperature data revealed that assessments considering only the variability of readings may underestimate the calculated measurement uncertainty, thereby justifying a more detailed evaluation of the equipment used, such as the testing machine and thermal conditioning methods. |