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Journal articleTaborda DMG, Pedro AMG, Matos Fernandes M, 2026, , Computers and Geotechnics, Vol: 197, ISSN: 0266-352X
Deep braced excavations are widely employed to support urban construction, with the axial stiffness of strut systems playing a crucial role in their structural performance. However, field observations have consistently shown that the effective axial stiffness of struts is often significantly lower than theoretical values, frequently attributed to slack arising from imperfections during assembly, gaps between structural elements, and initial curvatures. This paper presents a nonlinear model that captures the deformation-dependent stiffness behaviour arising from those initial imperfections. The model is governed by a single physically interpretable parameter, which controls the offset between effective and theoretical force–deformation curves and serves as an indicator of construction quality. A consistent unloading–reloading response and pre-stressing capability are incorporated within the same framework. The model is applied to a single-propped embedded wall to demonstrate its performance. The results confirm that the range of effective stiffness values reproduced by the model is consistent with instrumented case studies reported in the literature, and that pre-stressing improves average stiffness and reduces wall displacements. A straightforward calibration procedure based on monitored force–displacement data is proposed, enabling application within the Observational Method to improve predictions and inform installation practice.
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Journal articleKontoe S, Pedone G, Bellumat E, et al., 2026, , Geomechanics for Energy and the Environment, Vol: 45, ISSN: 2352-3808
Open-ended steel piles are commonly driven to support offshore wind energy structures. Their design poses significant challenges in chalk, a very weak brittle limestone found in several regions worldwide. Impact driving causes chalk de-structuration and fracturing around the piles, greatly affecting their lateral load-bearing performance. This was observed in recent field tests undertaken in the UK on piles with different lengths, diameters and thicknesses, exhibiting both geotechnical and structural failures. Most of these lateral loading tests, including those conducted on larger and longer monopiles, were completed recently and were never analysed numerically. This paper presents results of 3D Finite Element analyses conducted on open-ended steel piles with different diameters (up to 1.22鈥痬), embedded lengths (up to 10.16鈥痬) and wall thicknesses (up to 44.5鈥痬m), allowing to explore the marked scale effects observed on site. The newly available field tests also showed that steel yielding can occur before geotechnical failure is reached in chalk when testing piles with practical dimensions. However, steel yielding is usually neglected when modelling soil-pile interaction in geotechnical applications. The paper also aims at covering this gap by introducing a simplified modelling approach to account for elasto-plastic pile behaviour. The analyses delivered generally good matches with field behaviour and allowed to explore the main geotechnical uncertainties affecting accurate pile-chalk interaction predictions, mainly including the extent of the chalk fracturing induced by pile driving and its impact on chalk mechanical properties. The studies provide new and vital guidance for those involved in designing large driven piles for chalk sites.
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Journal articleYang Y, Ruiz Lopez A, Tsiampousi K, et al., 2026, , Data-Centric Engineering, Vol: 7, ISSN: 2632-6736
Surrogate models have gained widespread popularity for their effectiveness in replacing computationally expensive numerical analyses, particularly in scenarios, such as design optimisation procedures, requiring hundreds or thousands of simulations. While one-shot sampling methods – where all samples are generated in a single stage without prior knowledge of the required sample size – are commonly adopted in the creation of surrogate models, these methods face significant limitations. Given that the characteristics of the underlying system are generally unknown prior to training, the adoption of one-shot sampling can lead to suboptimal model performance or unnecessary computational costs, especially in complex or high-dimensional problems. This paper addresses these challenges by proposing a novel, model-independent adaptive sampling approach with batch selection, termed CV-BASHES (Cross-Validation Batch Adaptive Sampling for High Efficiency Surrogates). CV-BASHES is first validated using two analytical functions to explore its flexibility and accuracy under different configurations, confirming its robustness. Comparative studies on the same functions with two state-of-the-art methods, Maxpro and SAS, demonstrate the superior accuracy and robustness of CV-BASHES. Its applicability is further demonstrated through a geotechnical application, where CV-BASHES is used to develop a surrogate model to predict the horizontal deformation of a diaphragm wall supporting a deep excavation. Results show that CV-BASHES efficiently selects training samples, reducing 29 the dataset size while maintaining high surrogate accuracy. By offering more efficient sampling strategies, CV-BASHES streamlines and enhances the process of creating machine learning models as surrogates for tackling complex problems in general engineering disciplines
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Journal articleSheil B, Anagnostopoulos C, Buckley R, et al., 2026, , Computers and Geotechnics, Vol: 189, ISSN: 0266-352X
Our reliance on the underground space to deliver critical civil engineering infrastructure is growing: to accommodate utility and transport infrastructure in urban environments, to provide innovative housing and commercial solutions, and to support proliferating renewable energy infrastructure, particularly offshore. Artificial intelligence (AI) is arguably the most promising enabler to transform geotechnical engineering by extracting knowledge from data to achieve step-change increases in efficiency, sustainability, reliability and safety. This paper seeks to develop a shared understanding of the state of the art of AI in geotechnics and to explore future developments. By way of example, specific popular use cases in geotechnics are considered to highlight current progress in AI applications including intelligent site investigation, predictive modelling for soil behaviour, and optimisation of design and construction processes. The paper then addresses key research challenges, such as data scarcity and interpretability, and discusses the opportunities that lie ahead in the integration of AI with geotechnical engineering. Finally, priority technological enablers are identified for future transformations.
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Journal articleMaddah Sadatieh MS, Tsiampousi A, Paschalis A, 2026, , Geotech Geol Eng (Dordr), Vol: 44
Soil-Plant-Atmosphere Interaction (SPAI) is an essential factor in slope behaviour, affecting water inflow and outflow, and thereby influencing Pore Water Pressures (PWP), soil strength and stiffness, and slope stability and serviceability. Due to its complexity, SPAI and its effect on slope behaviour are best described by hydro-mechanically coupled numerical analysis, rendering the boundary conditions (BC) used to replicate atmospheric conditions critical. Here, different considerations have been made regarding the temporal and spatial variation of these BCs to assess their effect on slope behaviour. Specifically, daily and monthly atmospheric data were contrasted, dynamic vegetation growth was juxtaposed with static vegetation, and water extraction with depth due to transpiration was compared with a simplified approach where evapotranspiration was modelled to occur from the ground surface. A representative cut slope was considered, and fully coupled hydro-mechanical analyses were conducted under different BCs to study its stability and serviceability. The numerical results highlight which modelling choices significantly influence predicted performance, particularly under climate change, and which can be safely simplified. Guidance is provided for balancing computational efficiency with accuracy in geotechnical design.
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Journal articleTantivangphaisal P, Taborda D, Kontoe S, et al., 2025, , Geotechnique: international journal of soil mechanics, Vol: 75, Pages: 1507-1523, ISSN: 0016-8505
The High-Cycle Accumulation framework is modified and coupled with a practice-oriented cyclic sand constitutive model and implemented in a geotechnical finite elementsoftware to test the approach’s ability to predict the outcomes of monotonic and cyclic lateral loading field tests performed in Dunkirk, France, under the Pile-Soil Analysis (PISA) Joint Industry Project. A consistent and rational calibration procedure using only site-specific in-situ investigation and laboratory tests is presented and a single set of calibrated parameters is shown to reproduce Dunkirk sand’s response in monotonic, drained cyclic and undrained cyclic triaxial element tests up to 10,000 cycles, covering awide range of densities and stress conditions. The finite element analyses are shown to match well the monotonic lateral loading responses of fully instrumented 2m and 0.76m diameter open steel driven test piles and the latter’s cyclic lateral response up to 30,000 cycles. New insights into the evolution of the ground state under long-term lateral cyclic loading are gained to inform future research into practical site-specific methods for cyclic loading design over the full lifespan of piled foundations.
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Journal articleStewart M, Ruiz Lopez A, Tsiampousi A, 2025, , Journal of Geotechnical and Geoenvironmental Engineering, Vol: 151, ISSN: 0733-9410
Being able to predict with precision and certainty how existing tunnels respond to new tunnelling works in urban areas is vital for the safety of the existing tunnels and for minimising the cost and environmental impact of the new tunnels. The three-dimensional interaction of tunnels in stiff, overconsolidated clays has mainly been restricted to field studies, with only a few generic numerical studies. Nonetheless, a large part of underground tunnel construction has happened and continues to occur in overconsolidated clays. The paper bridges this gap by using the case study of Waterloo International Terminal, where two new tunnels were excavated beneath two 70 year-old tunnels, to validate a numerical model. The validated numerical results provide new, valuable insights into the differences and similarities of the response of the existing tunnels depending on their typology (running or station tunnels) and on the time after the excavation of the new tunnels. Furthermore, they reveal the significance of the stiffness reduction factors that need to be applied to account for the segmental nature of the tunnel linings, highlighting the need for further research into the operational value of the tunnel stiffness.
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Journal articlePedro AMG, Taborda D, Repsold LM, et al., 2025, , Soils and Rocks, Vol: 48, Pages: 1-15, ISSN: 1980-9743
Shaft excavation is essential in modern cities, allowing for quick and direct access to the underground, where most transportation networks and utilities are being installed to reduce surface congestion. Selecting the appropriate construction methodology is critical to minimize ground movements, while ensuring structural stability and construction efficiency. This study assesses the performance of three typical construction methodologies – Excavation Before Support (EBS), Support Before Excavation (SBE) and Dual-Lined Shafts (DLS) – through a comprehensive numerical study. The validation of the adopted modelling approach for each methodology is performed by simulating three case studies in close proximity to each other. Several aspects of numerical modelling are discussed, such as the simulation of the hardening behavior of the sprayed concrete, the modelling the wall installation and their stiffness anisotropy. For each methodology, the influence of key variables is assessed through parametric studies, highlighting the importance of the excavation step height, the lining thickness and the embedded length of the wall. A final study, where all methodologies are compared for the same ground conditions, is carried out for two shaft diameters. Results indicate that SBE produces the smallest ground movements but induces the highest lining forces. In contrast, EBS originates higher ground movements due to significant soil decompression but smaller lining forces. DLS methodology exhibits an intermediate behavior, although more similar to that observed in EBS. These findings emphasize the importance of selecting an adequate shaft construction methodology and provide valuable information regarding the appropriate numerical simulation of each technique.
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Journal articleMA S, Kontoe S, Taborda D, 2025, , Soil Dynamics and Earthquake Engineering, Vol: 197, ISSN: 0267-7261
Hydraulic conductivity plays a significant role in the evolution of liquefaction phenomena induced by seismic loading, influencing the pore water pressure buildup and dissipation, as well as the associated settlement during and after liquefaction. Experimental evidence indicates that hydraulic conductivity varies significantly during and after seismic excitation. However, most previous studies have focused on experimentally capturing soil hydraulic conductivity variations during the post-shaking phase, primarily based on the results at the stage of excess pore water pressure dissipation and consolidation of sand particles after liquefaction. This paper aims to quantify the variation of hydraulic conductivity during liquefaction, covering both the co-seismic and post-shaking phases. Adopting a fully coupled solid-fluid formulation (u–p), a new back-analysis methodology is introduced which allows the direct estimation of the hydraulic conductivity of a soil deposit during liquefaction based on centrifuge data or field measurements. Data from eight well-documented free-field dynamic centrifuge tests are then analysed, revealing key characteristics of the variation of hydraulic conductivity during liquefaction. The results show that hydraulic conductivity increases rapidly at the onset of seismic shaking but gradually decreases despite high pore pressures persisting. The depicted trends are explained using the Kozeny-Carman equation, which highlights the combined effects of seismic shaking-induced agitation, liquefaction, and solidification on soil hydraulic conductivity during the co-seismic and post-shaking phases.
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Conference paperImansyah MR, Taborda D, Hau KW, et al., 2025,
Numerical investigation of offshore foundation on liquefiable sands
, 20th International Conference: The Jack-up PlatformThis study investigates the seismic response of shallow foundations resting on liquefiable sand deposits, with theaim of providing insights into the expected behaviour of Wind Turbine Installation Vessels (WTIV) when subjected to earthquake loading. A detailed calibration strategy based on commonly available ground information is outlined for Nevada sand, with a detailed characterisation of the model performance being undertaken in termsof CSR, stiffness degradation, and damping ratio curves. Subsequent validation process is also provided bysimulating centrifuge experiments of footings resting on liquefiable deposits. Lastly, three-dimensional finiteelement analyses of a WTIV are performed employing the calibrated UBC3D-PLM parameters. The impact of soilliquefaction on the response of the WTIV is investigated, with particular emphasis given to the additionalsettlements caused by the seismic loading.
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Journal articleMaddah Sadatieh MS, Tsiampousi A, Paschalis A, 2025, , Geomechanics for Energy and the Environment, Vol: 43, ISSN: 2352-3808
Soil-plant-atmosphere interaction (SPAI) plays a significant role on the safety and serviceably of geotechnical infrastructure. The mechanical and hydraulic soil behaviour varies with the soil water content and pore water pressures (PWP), which are in turn affected by vegetation and weather conditions. Focusing on the hydraulic reinforcement that extraction of water through the plant roots offers, this study couples advances in ecohydrological modelling with advances in geotechnical modelling, overcoming previous crude assumptions around the application of climatic effects on the geotechnical analysis. A methodology for incorporating realistic ecohydrological effects in the geotechnical analysis is developed and validated, and applied in the case study of a cut slope in Newbury, UK, for which field monitoring data is available, to demonstrate its successful applicability in boundary value problems. The results demonstrate the positive effect of vegetation on the infrastructure by increasing the Factor of Safety. Finally, the effect of climate change and changes in slope vegetation cover are investigated. The analysis results demonstrate that slope behaviour depends on complex interactions between the climate and the soil hydraulic properties and cannot be solely anticipated based on climate data, but suctions and changes in suction need necessarily to be considered.
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Conference paperMaddah Sadatieh MS, Tsiampousi A, Paschalis A, 2025,
IMPACT OF DEPTH DISTRIBUTED PLANT WATER UPTAKE ON SLOPE SAFETY
, The 9th Internation Symposium for Geotechnical Safety and Risk (ISGSR) in August 2025 -
Conference paperMaddah Sadatieh MS, Tsiampousi A, Paschalis A, 2025, , 5th European Conference on Unsaturated Soils and Biotechnology applied to Geotechnical Engineering (EUNSAT2025 with BGE), Publisher: EDP Sciences, ISSN: 2555-0403
The soil-plant-Atmosphere interaction (SPAI) significantly influences the safety and serviceability of engineering infrastructure by affecting pore water pressure (PWP) distribution. Rainfall and water infiltration increase PWPs, reducing soil strength, while evapotranspirationa "driven by evaporation and plant transpirationa "induces negative pore pressures (suction), enhancing soil strength and safety. However, vegetation can also pose serviceability challenges. During summer, root water uptake causes soil shrinkage, and in wet months, infiltration induces swelling. These cyclic volume changes can disrupt infrastructure, leading to road and track delays or closures. Accurate modelling of SPAI is therefore critical to understanding the effects of climate change and vegetation on soil hydraulic and mechanical behaviour. This study examines how surface and internal flow boundary conditions affect SPAI modelling within a fully coupled flow-deformation framework. While most recent research has focused on surface boundary conditions for hydrological fluxes, this paper evaluates the inclusion of internal boundary conditions to simulate vegetation transpiration. A comparative analysis assesses the safety and serviceability outcomes for models employing only surface boundary conditions versus those incorporating both surface and internal conditions.
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Journal articleTaborda D, Pedro A, Xia H, et al., 2025, , Proceedings of the Institution of Civil Engineers: Geotechnical Engineering, Vol: 178, Pages: 479-493, ISSN: 1353-2618
Shafts are typically employed in urban environments to provide access or ventilation to underground structures such as stations, railways or highways. The choice of design is determined, among other things, by the need to control settlements at the surface, often estimated during early design stages using empirical expressions. These have been shown to have limited accuracy, failing to account appropriately for the effect of shaft diameter on the ground movements associated with shaft excavation. This paper reviews empirical expressions available in the literature in the context of a large database of settlements induced by shaft excavation in London. A comprehensive set of detailed numerical analyses is performed to enable the development of a new set of expressions capable of predicting accurately the computed vertical and horizontal ground movements at the surface. The new expressions are shown to provide better predictions of the observed field data than predictive expressions available in the literature, establishing a new benchmark against which future proposals can be assessed.
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Journal articleSanchez Fernandez J, Ruiz Lopez A, Taborda D, 2025, , Data-Centric Engineering, Vol: 6, ISSN: 2632-6736
Thermal Integrity Profiling (TIP) is a non-destructive testing technique which takes advantage of the concrete heat of hydration (HoH) to detect inclusions during the casting process. This method is becoming more popular due to its ease of application, as it can be used to predict defects in most concrete foundation structures requiring only the monitoring of temperatures. Despite its advantages, challenges remain with regard to data interpretation and analysis, as temperature is only known at discrete points within a given cross-section. This study introduces a novel method for the interpretation of TIP readings using neural networks. Training data is obtained through numerical FE simulation spanning an extensive range of soil, concrete and geometrical parameters. The developed algorithm first classifies concrete piles, establishing the presence or absence of defects. This is followed by a regression algorithm that predicts the defect size and its location within the cross-section. Additionally, the regression model provides reliable estimates for the reinforcement cage misalignment and concrete hydration parameters. To make these predictions, the proposed methodology only requires temperature data in the form standard in TIP, and so it can be seamlessly incorporated within the TIP workflows. This work demonstrates the applicability and robustness of machine learning algorithms in enhancing non-destructive TIP testing of concrete foundations, thereby improving the safety and efficiency of civil engineering projects.
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