Mini-symposium S10

S10: Validation: Computing and Communicating Confidence in Simulations

Co-chairs: 

Ksenija Dvurecenska (University of Liverpool)*

Hannah Little (University of Liverpool)

Keywords: Validation; Credibility; Computational solid mechanics; Uncertainty communication

ABSTRACT

The focus of this mini-symposium is on approaches for demonstrating confidence in computational mechanics models to support decision makers. Validation is a core process for providing evidence and establishing confidence in computational models. While verification and calibration approaches confirm that a model is built correctly, validation helps to answer the question whether the model is appropriate for its intended use [1-2]. The validation process involves the application of quantitative statistical methods to compare model predictions and physical measurements, and interpretation of the outcomes to demonstrate the level of confidence in the model predictions. The latter should also take into consideration how validation outcomes are communicated [3], for example reporting within the industry or to the regulator, and how the communication used around validation affects perception and trust in computational models. 

Building on the well-known aphorism ‘All models are wrong, but some are useful’ attributed to George Box, we invite presentations that emphasise methods for comparing data sets and extracting key information in support of the model, rather than presenting ‘correct’ models. To encourage exchange of knowledge and discussion, we invite speakers from academia and industry with expertise on: 

• Model validation techniques,

• Extraction of key features from data to support validation,

• Communication of confidence in simulations.

The mini-symposium will conclude with a keynote, where we will discuss how engineers and scientists communicate about validation process and their confidence in computational models. All submissions to this mini-symposium are asked to accompany their submission with a short lay summary (2 sentences max) of their validation example and explaining their level of confidence in their simulation. The summary should be written to be understood by a non-specialist audience (e.g. a policy maker looking to support a technology). These summaries will be anonymised, and an aggregated analysis of the statements will be presented during the keynote.

REFERENCES

[1] ASME V&V 10-2019. VV10 - Standard for Verification and Validation in Computational Solid Mechanics, American Society of Mechanical Engineers, New York, 2020. 

[2] ASME V&V 20-2009 R(2021), Standard for Verification and Validation in Computational Fluid Dynamics and Heat Transfer. American Society of Mechanical Engineers, New York, 2009. 

[3] A.M. van der Bles, S. van der Linden, A.L.J. Freeman, J. Mitchell, A.B. Galvao, L. Zaval and D.J. Spiegelhalter. Communicating uncertainty about facts, numbers and science, Royal Society Open Science, Vol. 6:5, 2019.