AMENTUM | ADVERTORIAL FEATURE
Far left: The UK High Temperature Facility at Amentum’s Warrington campus
Left: Graphite blocks in the core of an advanced gas-cooled reactor. Image courtesy of EDF
With many next-generation high-temperature reactors
expected to adopt graphite cores, Amentum’s ability to pair simulation and testing provides confidence in design qualification and long-term safety.
Creep crack growth Developers of new reactors envisage using ever higher operating temperatures to improve efficiency and enable the re-use of spent fuel. Therefore, understanding the high temperature response of the materials used in reactor construction is paramount to safe operation, financial return, and acceptance among regulators and the public. At such high temperatures, the metallic structures are seen to creep – meaning that they stretch or deform under a constant load. The understanding of creep, and how it impacts on reactor design, initiation of defects and subsequent defect growth, is a complex area and receives conservative treatment in design codes. Materials high temperature creep is an area where Amentum has enormous expertise. Our modelling and simulation team uses finite element analysis and assessment procedures to predict – and develop more realistic methods to assess – creep-fatigue initiation and creep crack growth in metallic components under a variety of loading conditions. We have modelled creep crack growth within finite element models that provide good correspondence to measured laboratory test data. Our high temperature testing and associated laboratory testing programmes provide materials data and wider experimental validation. Such tests can be very long-term and are very specialised. Over many years of experience we have acquired a deep fundamental understanding of tests, test conditions and the ability to accurately interpret the results.
Stress corrosion cracking in plant materials At Amentum, we’ve been investigating stress corrosion cracking (SCC) in plant materials for more than 30 years. SCC is caused by numerous mechanisms with complex relations between the material in question, how it was fabricated, the local environments, and stress on the component. SCC can go undetected in nuclear power plants for many years before manifesting as a detectable crack, a leak before break, or even a sudden and unexpected catastrophic failure. It poses a high risk to safety-critical components. Despite many years of targeted research worldwide, there is still an urgent need to improve understanding of
the underlying causes of degradation and to inform a lifetime risk approach for all the materials critical to the integrity of nuclear power plants. Amentum is at the forefront of research investigating
the SCC susceptibility of in-service plant materials, lifetime extensions of operating reactors, qualification of new materials and advanced manufacturing methods such as hot isostatic pressing and additive manufacturing. New methods of fabrication allow components to be produced more quickly and extremely close to their final dimensions, reducing the need for machining or welding. Our research also reaches into alternative plant chemistries, an improved mechanistic understanding of SCC and the data generated, and the development of advanced digital models for prediction purposes.
Lithium testing and tritium breeders Lithium is a critical feature of all tritium breeder systems for a fusion power plant. Pure lithium is a viable material but there are several challenges to deployment, including corrosion, operating conditions, and impurity ingress. To support the industrial deployment of lithium, Amentum developed a liquid lithium test facility to provide robust and reliable data that supports the design of a commercial breeder system. Existing expertise on liquid metal testing was integrated with novel techniques specific to lithium. To maximise the value of the data, digital solutions are being developed, including a digital twin. Combining the practical laboratory testing with engineering expertise, the latest computational methods are being combined to aid in the design of a lithium breeder system, including machine learning, reduced order models, and uncertainty quantification. These optimisation approaches, coupled with uncertainty quantification, allow lithium-breeder designs to operate in windows of high performance whilst highlighting where predictions are uncertain. Knowing uncertainty can prevent overconfidence in design choices, help underpin risk-aware decision making, and target experiments in under-sampled regimes. Integrating practical research and digital analysis is key to accelerating the design and delivery of next generation power plants. ■
Authors: Saurav Sarkar, Nayden Matev, Jennifer Borg, Ryan Morris, Zinnia Parker
Amentum 601 Faraday Street Warrington, WA3 6GN United Kingdom
T: +44 01925 974877 E: mayur.jagatia@global.
amentum.com W:
www.amentum.com L:
www.linkedin.com/ showcase/amentum-uk
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