Bacton Digital Beach Twin: a Digital Twin for natural assets

From Design Computation
(Redirected from DCIO.2022.RELW8964)
Jump to: navigation, search
DCIO2022-Logo.png
DC I/O 2022 Slides by Ruben Borsje. https://doi.org/10.47330/DCIO.2022.RELW8964 | Watch Left | Left


DCIO2022 S4-5 R-Borsje.png


Abstract

The Bacton Digital Beach Twin (DBT) is a virtual mirror of the Bacton Sandscaping scheme. This £20M coastal protection scheme consists of a mega-nourishment that protects a nationally critical gas terminal and buys adaptation time for the surrounding villages. The scheme’s Digital Twin aims to supports the client’s ‘big decision’: when to invest in renourishment or other measures to manage risk to the gas terminal and villages in future. The DBT uses the results of coastline modelling to predict the future state of the beach, determining when a critical state is reached, and thus intervention is needed. The predictive models are regularly recalibrated using the latest monitoring data, reducing the uncertainty in the predictions; a process that is also supported by the DBT. The end users can interact with the DBT through an online user interface, which was developed in close collaboration with the client group and which allows them to make informed decisions around the future investments into the management of this coastline.

Keywords

Digital Twin, Costal Management.

Bibliography

  • VAN HOUDT, J. 2012. Aerial image of the Zandmotor.
  • TAYLOR, C. 2019. The Bacton to Walcott Sandscaping Scheme – Summer 2019.
Retrieved from "http://wiki.designcomputation.org/home/index.php?title=Bacton_Digital_Beach_Twin:_a_Digital_Twin_for_natural_assets&oldid=27427"