Design and analysis of a computer experiment for the study of the distortion of an advanced gas-cooled reactor moderator brick

• Published in: Nuclear engineering and design 2020-10, Vol.367, p.110766, Article 110766
• Main Authors: McNally, Kevin, Yates, Tim, Fahad, Muhammad, Marsden, Barry J, Warren, Nick, Hall, Graham N
• Format: Article
• Language: English
• Subjects: Advanced gas-cooled reactor; Calibration; Computer experiment; Construction materials; Distortion; Emulator; Finite element method; Gas cooled reactors; Global sensitivity analysis; Material properties; Mathematical models; Parameter identification; Parameter sensitivity; Parameter uncertainty; Reactors; Sensitivity analysis; Stresses; Variability
• ISSN: 0029-5493; 1872-759X
• DOI: 10.1016/j.nucengdes.2020.110766

•A computer experiment for studying the deformation of an AGR moderator brick was run.•A computationally efficient methodology was used for assessing parameter sensitivity.•A subset of shape metrics for use in future parameter calibration was proposed. Engineering models, resolved using the finite element method, are used to model through-life changes in material properties and the resulting internal brick stresses in graphite moderator bricks within an advanced gas-cooled reactor (AGR). These models require inputs that describe the loading conditions of the moderator brick and coded relationships describing the behaviour of material properties as the brick ages. A highly multivariate spacio-temporal dataset of displacements, stresses and strains is returned as model output. In this work we describe a computer experiment conducted to study the variability in brick distortion resulting from parameter value uncertainty in the inputs to the model. We identify summary measures of brick shape and conduct global sensitivity analyses to identify the key uncertain parameters driving the variability in brick shape. Our results indicate that different measures of brick shape show sensitivities to different groups of model inputs and suggest that data obtained from core monitoring campaigns can be used to calibrate uncertain parameters in the model. Model calibration and the impact of calibration on predictions of internal brick stresses, which cannot be directly validated, are areas of current research.