An Investigation Into the Applicability of Charpy Dynamic Fracture Tests for a Digital Twin

Fabian S. Sorce, D. Cogswell, C. Davies
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Abstract

The Charpy impact test has historically been used in a qualitative and comparative manner to infer toughness behaviour and determine the brittle to ductile transition temperature (TBD) of low alloy ferritic steels used in reactor pressure vessels (RPVs). The simple and quick setup makes it an attractive test given the ease of data generation to assess the suitability of a given material; however, the scatter in the data produced is significant and the test does not provide a value of fracture toughness. Quasi-static tests using high-constraint geometries (e.g. single-edge notch bend (SENB) specimens) are used to determine fracture toughness properties, whilst the Charpy impact test (governed by the ASTM E23 and ISO 148 standards) gives insight into the dynamic fracture response of a material. There is significant interest, demonstrated by recent work, in utilising Charpy impact test data to predict fracture toughness properties and material behaviour, which typically require expensive and time-consuming test procedures. The ongoing digital transformation of industry and proposals of digital twins becoming ubiquitous relies intrinsically on high-quality data inputs and fully understanding the underlying mechanistic relationships governing material behaviour. This work examines the relationships between microstructure, temperature, and quasi-static and dynamic fracture behaviour of a low alloy ferritic steel (comparable in composition to SA508). The microstructures are analysed before a Charpy impact pendulum is used to determine the energy absorbed by standard V-notch samples from −196 °C to 200 °C and the fracture surfaces examined. A distinct transition zone is observed and the data is compared to historic fracture data of the material. The results are discussed in light of applicability to a digital twin and the framework for a machine learning model to predict the fracture behaviour and reduce error in transition behaviour is proposed.
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数字孪生体夏比动态断裂试验的适用性研究
Charpy冲击试验历来以定性和比较的方式用于推断反应堆压力容器(rpv)中使用的低合金铁素体钢的韧性行为并确定其脆性到延性转变温度(TBD)。由于易于生成数据以评估给定材料的适用性,简单快速的设置使其成为一种有吸引力的测试;然而,所产生的数据中的散点是显著的,并且测试没有提供断裂韧性的值。使用高约束几何形状(例如单刃缺口弯曲(SENB)试样)的准静态测试用于确定断裂韧性性能,而Charpy冲击测试(由ASTM E23和ISO 148标准管理)可以深入了解材料的动态断裂响应。最近的研究表明,人们对利用Charpy冲击试验数据预测断裂韧性和材料性能非常感兴趣,而这通常需要昂贵且耗时的测试程序。正在进行的工业数字化转型和数字孪生无处不在的建议本质上依赖于高质量的数据输入和对控制材料行为的潜在机制关系的充分理解。本文研究了一种低合金铁素体钢(成分与SA508相当)的显微组织、温度、准静态和动态断裂行为之间的关系。在用夏比冲击摆测定从- 196°C到200°C的标准v形缺口样品吸收的能量和断口表面之前,分析了显微组织。观察到一个明显的过渡区,并将数据与材料的历史断裂数据进行比较。从数字孪生的适用性角度讨论了结果,并提出了预测断裂行为和减少过渡行为误差的机器学习模型框架。
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