No abstract

The rapid development of new infrastructure programmes requires an accelerated deployment of new materials in new environments. Materials 4.0 is crucial to achieve these goals. The application of digital to the field of materials has been at the forefront of research for many years, but there does not exist a unified means to describe a framework for this area creating pockets of development. This is confounded by the broader expectations of a digital twin (DT) as the possible answer to all these problems. The issue being that there is no accepted definition of a component DT, and what information it should contain and how it can be implemented across the product lifecycle exist. Within this position paper, a clear distinction is made between the “manufacturing DT” and the “component DT”; the former being the starting boundary conditions of the latter. In order to achieve this, we also discuss the introduction of a digital thread as a key concept in passing data through manufacturing and into service. The stages of how to define a framework around the development of DTs from a materials perspective is given, which acknowledges the difference between creating new understanding within academia and the application of this knowledge on a per-component basis in industry. A number of challenges are identified to the broad application of a component DT; all lead to uncertainty in properties and locations, resolving these requires judgments to be made in the provision of safety-dependent materials property data.

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.