Uncertainty quantification and sensitivity analysis for resilient infrastructure systems

Computational modelling provides a vital tool to support infrastructure investment decisions. Model outputs though are conditional on a range of uncertain assumptions and input data. Overconfidence in model results and insufficient consideration of the breath of possible futures are key obstacles to resilient infrastructure design.

This project, led by Francesca Pianosi of the University of Bristol, will integrate into DAFNI a generic methodology to analyse the propagation of uncertainties and enable better model construction, validation, and use for decision-making under uncertainty.

The methodology will be tested and showcased on pilot applications in the water and energy systems sector. Ultimately the project will contribute to promote best practices for responsible modelling and robust decision-making in the DAFNI user’s community.

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