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Emulating long-term weather-driven transportation earthworks deterioration models to support asset management

Lookup NU author(s): Dr Peter Helm, Dr Aleksandra Svalova, Professor Mohamed Rouainia, Professor Stephanie Glendinning

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

The deterioration of transport infrastructure earthworks is a global problem, with negative impacts for infrastructure resilience, becoming of increasing significance as existing infrastructure ages. Key mechanisms which affect this deterioration include seasonal pore pressure cycling driven by changing weather and climate, and the long-term dissipation of construction induced excess pore pressures. These complex processes lead to significant uncertainty in rates of deterioration and the current state of existing earthworks assets. The objective in this work was to establish a framework to emulate deterministic numerical models of slope deterioration over time using statistical (Gaussian process) emulation. A validated, physically based, deterministic modeling capability has been developed that can replicate the hydro-mechanically coupled behavior of cut and embankment slopes and their deterioration as driven by weather and climate. In parallel, a statistical (Gaussian process) emulator model was developed, and then trained with data from a deterministic modeling parametric study, using a formal experimental design approach, making use of Latin hypercube sampling. Exemplar forecasting outputs are presented to demonstrate application of the approach for use in decision-making. This information can be used in the design of new earthworks and the management of existing earthwork portfolios


Publication metadata

Author(s): Helm PR, Svalova A, Morsy AM, Rouainia M, Smith A, El-Hamalawi A, Wilkinson DJ, Postill H, Glendinning S

Publication type: Article

Publication status: Published

Journal: Transportation Geotechnics

Year: 2024

Volume: 44

Print publication date: 01/01/2024

Online publication date: 23/11/2023

Acceptance date: 18/11/2023

Date deposited: 25/11/2023

ISSN (electronic): 2214-3912

Publisher: Elsevier BV

URL: https://doi.org/10.1016/j.trgeo.2023.101155

DOI: 10.1016/j.trgeo.2023.101155

Data Access Statement: Data used in the preparation of figures in this publication, along with the emulator code, are available from a data repository with doi numbers listed in the acknowledgments section of the paper. The data used in the preparation of the figures in this publication is available from an institutional data repository with the following doi: 10.25405/data.ncl.22714831. The emulator code and the data used as emulator input is available via the following doi numbers: 10.25405/data.ncl.14447670.v2; 10.25405/data.ncl.14331314.v2


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Funding

Funder referenceFunder name
EP/F063482/1
Engineering and Physical Sciences Research Council (EPSRC)
EP/K027050/1EPSRC
EP/R034575/1EPSRC
GR/R72341/01
GR/S87430/01EPSRC

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