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Summary of Cut Slope Modelling Used for the Derivation of Climate Change Deterioration Factors

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posted on 2024-03-07, 16:38 authored by Peter HelmPeter Helm

This report summarises the deterministic numerical modelling used to compare rates of deterioration of cut slopes subjected to climate change.

In order to assess the effects of climate change on deterioration it was necessary to derive both control (present) and future climate datasets using the UKCP09 weather generator and the UKCP18 regional climate model output respectively. These datasets were then used to produce a discharge boundary flux for a validated geotechnical model (Forecasting the long‐term deterioration of a cut slope in high‐plasticity clay using a numerical model) of a cut slope, excavated in high plasticity overconsolidated clay with properties representative of London Clay.

Slope deterioration was evaluated in terms of a change in the factor of safety (FoS) against ultimate limit state failure over time. This deterioration was caused by the dissipation of excavation induced negative pore water pressures and due to strain softening driven by progressive failure and shrink-swell cycles within the model.

The change in FoS over time, for the differing models, was plotted as a series of deterioration curves and the time to failure of the models subjected to differing climates was recorded. The difference in the times to failure, for the control and future climate models, was in turn used to derive a deterioration factor due to climate change.

The results suggest that on average, for the cut slopes modelled, future climate change based on UKCP18 RCP8.5 (the projected worst-case emissions scenario), will lead to a doubling of the rate of deterioration of the slopes towards ultimate limit state failure.

The modelling summarised in this report informed the work undertaken to develop earthworks deterioration factors for use by UK National highways. See the linked document (National Highways Geotechnical Asset Performance: Deterioration Modelling for Decision Support).

Funding

Assessment, Costing and enHancement of long lIfe, Long Linear assEtS (ACHILLES)

Engineering and Physical Sciences Research Council

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