Michael graduated in Civil Engineering from the University of Manchester in 1982. He obtained his PhD from the same university in 1990 and was appointed Research Associate in 1986, Lecturer in 1987 and then Senior Lecturer in 1998. Michael joined Delft University of Technology in 2009 as Professor of Soil Mechanics, is head of the Section of Geo-Engineering and was interim head of the Department of Geoscience and Engineering in 2018. He is the TU Delft representative for ALERT Geomaterials.
Michael was Chairman of the Organising Committee for Géotechnique’s 2005 Symposium in Print, “Risk and Variability in Geotechnical Engineering,” and is Editor of a published (2007) Thomas Telford book by the same name. He was Chairman (2006-2010) of the British Geotechnical Association’s Working Group on “Numerical Methods in Design,” was a member of the Board of Directors of ALERT Geomaterials (2000-2017), was Chairman of ALERT’s 2007 Workshop Session on “Inverse and Stochastic Modelling,” Chairman of the International Workshop on “Safety Concepts and Calibration of Partial Factors in European and North American Codes of Practice” (Delft, 2011), Chairman of the International Conference on “Installation Effects in Geotechnical Engineering” (Rotterdam, 2013), Chairman of the 8th European Conference on “Numerical Methods in Geotechnical Engineering” (Delft, 2014), and Chairman of the 4th International Symposium on Cone Penetration Testing (Delft, 2018). He is on the Editorial Panels of the international journals “Acta Geotechnica,” “Georisk” and “Computers and Geotechnics,” and was Coordinator of ALERT’s 2014 Doctoral School on “Stochastic Analysis and Inverse Modelling.” He was awarded the Institution of Civil Engineers’ Geotechnical Research Medal in 1999, for a Géotechnique paper on the static liquefaction of hydraulic sand fills.
- (Random) finite element method
- (Random) material point method
- Reliability analysis
- Soil heterogeneity
- Slope stability
- Constitutive modelling
- Strain localisation
Michael has nearly 40 years’ experience in the constitutive modelling of soil behaviour and numerical modelling of geotechnical problems. He currently supervises a team of 2 postdocs and 12 PhD students, with a particular interest in risk and variability in geotechnical engineering. Contributions within that domain broadly come under 3 main areas:
Stochastic characterization and modelling of soil spatial variability
This is mainly concerned with the characterization of spatial variability within soil layers using cone penetration test (CPT) data, in order to provide point and spatial statistics as input for random field models of spatial variability. Of particular interest has been the determination of scales of fluctuation, especially in the horizontal plane. For example, Lloret-Cabot et al. (2014) proposed a strategy utilizing conditional random fields for determining the vertical and horizontal scales of fluctuation based on CPT data, and demonstrated its performance for a hydraulically placed sand fill (this paper won the Georisk 2014 Best Paper Award and the Georisk 2017 Most Cited Paper Award). More recently, de Gast et al. (2021a) evaluated a large number of very closely spaced CPTs to derive guidelines for the number and spacing of CPTs as a function of required confidence level in the computed horizontal scale of fluctuation. Meanwhile, other research work has investigated the conditioning of random fields using CPT data. For example, Li et al. (2016) demonstrated how uncertainty in the reliability of an embankment slope (modelled in 3D) was reduced when random fields were conditioned to CPTs located at regular intervals along the embankment crest (i.e., along the third dimension); this was shown to lead to more efficient slope designs for a given target reliability. Another series of papers investigated how data assimilation, for example pore pressure monitoring data, can be used to reduce the uncertainty in an embankment’s performance over time (Vardon et al., 2016; Liu et al., 2018).
Stochastic modelling of slope reliability using the random finite method (RFEM)
This is mainly concerned with the stochastic (Monte Carlo) modelling of slope stability, using the finite element method to compute structure response and random fields to model spatial variability of properties within soil layers. The emphasis has been on gaining insight into how soil spatial variability influences the initiation and propagation of failure mechanisms in slopes, and how this in turn influences the computed slope reliability. Hicks & Samy (2002a) investigated the influence of depth trend in the point statistics of shear strength on 2D slope stability, and demonstrated that a depth trend generally leads to a greater range of solutions and also to a decrease in reliability. Meanwhile, Hicks & Onisiphorou (2005) used RFEM, together with a sophisticated constitutive model for sand, to investigate the failure of the Nerlerk underwater berm, which failed during construction due to apparent liquefaction even though CPT data had indicated a predominantly dilative fill (Hicks & Boughrarou, 1998). The RFEM analyses demonstrated that failure of the berm was possible through liquefaction of semi-continuous looser zones arising from deposition-induced anisotropy. Hicks & Spencer (2010) investigated the influence of horizontal scale of fluctuation on the stability of embankment slopes, by carrying out 3D RFEM analyses for slopes that were very long in the third dimension. They demonstrated that 3 categories of failure mode were possible, depending on the horizontal scale of fluctuation relative to the embankment dimensions. This was reinforced by Hicks et al. (2014), who computed the distributions of slide volumes associated with the different failure mode categories. They demonstrated that nearly all failures are 3D, even for problems (such as embankments) which appear 2D from a geometric point of view. Hicks & Spencer (2010) highlighted that such problems require 3D analysis and that the reliability of such structures is problem length dependent; i.e., the longer the embankment, the greater the chance of encountering a zone that is weak enough to trigger failure. However, they also demonstrated that a full 3D analysis was not needed for very long embankments; instead, the results of a detailed 3D RFEM analysis for a representative length of embankment (of around 10 times the embankment height) could be combined with simple probabilistic analysis to accurately compute the reliability of embankments of different length (as verified by comparison with full 3D RFEM analyses of embankments of different length). This strategy was used by Hicks & Li (2018) to benchmark existing simpler 3D and 2.5D semi-analytical methods. Recently, the material point method has been linked with random fields for modelling problems involving large deformations. This so-called random material point method (RMPM) was first introduced by Wang et al. (2016) in a paper published in Géotechnique Letters, and was awarded best paper status by the journal in Q2 of 2016.
Probabilistic assessments of embankment reliability and characteristic values
The influence of soil spatial variability on geotechnical response, as modelled using RFEM, has been used to provide an interpretation of characteristic values as defined in Eurocode 7. Hicks & Samy (2002b) demonstrated that characteristic values should be a function of not only the point statistics of a material property, but also the scales of fluctuation in the coordinate directions and the geotechnical problem under consideration. Hicks (2012) and Hicks & Nuttall (2012) took this further, and explained how Clause 11 of Section 220.127.116.11, “Characteristic Values of Geotechnical Parameters,” in Eurocode 7 could be interpreted through a consideration of the scale of fluctuation relative to the domain of influence of the structure. Recently, this line of research has taken on an increased level of importance in the Netherlands (as outlined below). In brief, climate change, increased external loadings and new design guidelines mean that much of the Dutch flood defense and rail networks (i.e., dykes and embankments, respectively) no longer meet required safety standards. This has prompted research into the use of advanced methods of analysis that explicitly account for uncertainties (Hicks et al., 2019; Varkey et al., 2020).
Michael coordinates and teaches the 2nd year undergraduate course on Soil Mechanics to both Civil Engineering and Applied Earth Science bachelor students, as well as the master track course on Risk and Variability in Geo-Engineering. He also supervises bachelor and master dissertation students, and contributes to the 1st year Civil Engineering course on Introduction to Civil Engineering.
- Hicks, M. A. & Boughrarou, R., Finite element analysis of the Nerlerk underwater berm failures, Géotechnique, 48(2), 169-185, 1998.
- Hicks, M. A. & Samy, K., Influence of heterogeneity on undrained clay slope stability, Quarterly Journal of Engineering Geology and Hydrogeology, 35(1), 41-49, 2002.
- Hicks, M. A. & Onisiphorou, C., Stochastic evaluation of static liquefaction in a predominantly dilative sand fill, Géotechnique, 55(2), 123-133, 2005.
- Hicks, M. A. & Spencer, W. A., Influence of heterogeneity on the reliability and failure of a long 3D slope, Computers and Geotechnics, 37, 948-955, 2010.
- Lloret-Cabot, M., Fenton, G. A. & Hicks, M. A., On the estimation of scale of fluctuation in geostatistics, Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 8(2), 129-140, 2014.
- Li, Y. J., Hicks, M. A. & Vardon, P. J., Uncertainty reduction and sampling efficiency in slope designs using 3D conditional random fields, Computers and Geotechnics, 79, 159-172, 2016.
- Hicks, M. A., Varkey, D., Eijnden, A. P. van den, Gast, T. de & Vardon, P. J., On characteristic values and the reliability-based assessment of dykes, Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 13(4), 313-319, 2019.
- de Gast, T., Hicks, M. A., van den Eijnden, A. P. & Vardon, P. J., On the reliability assessment of a controlled dyke failure, Géotechnique, 71(11), 1028–1043, 2021.
Hicks, M. A. (PI), with Vardon, P. J., Jommi, C., Askarinejad, A., Reliable Dykes: Reliability-based geomechanical assessment tools for dykes and embankments in delta areas; funded by NWO; 1.012 million euros; 3 postdocs and 4 PhDs; 2014-2021.
Hicks, M. A., with multiple partners, All-Risk: Implementation of new risk standards in the Dutch flood protection programme; funded by NWO; 0.220 million euros and 1 PhD for Hicks WP; 2017-2022.
Hicks, M. A. (PI), with Jommi, C., Korff, M., SOFTTOP: Investigating heterogeneous soft top soils for wave propagation, cyclic degradation and liquefaction potential; funded by NWO; 1.043 million euros; 2 postdocs and 2 PhDs; 2019-2024.
Hicks, M. A. (co-PI), with Ghose, R., 3DSOIL: 3D soil variability in Groningen for accurate, local site response analysis; funded by NWO; 0.350 million euros; 1 PhD; 2021-2025.
Hicks, M. A. (co-PI), with Dollevoet, R., Li, Z., Gavin, K., Jommi, C. (and collaboration partners Deltares), RESET: Reliable embankments for safe expansion in rail traffic; funded by ProRail; 5 million euros (TU Delft share); 2 postdocs and 8 PhDs; 2021-2026.
The following gives an overview of some recent and current research projects:
Reliable Dykes (2014-2021)
The aim of this project was to develop reliability-based geomechanical assessment tools for rural dykes. More than 1 million euros was awarded by the research council NWO, which included 300 thousand euros from STOWA, the Foundation for Applied Water Management Research, which is the official body representing the water boards and provinces in the Netherlands. In addition, the flood defense industry fully funded a full-scale failure test on a 400 year-old dyke founded on peat to provide validation data for the numerical and probabilistic tools developed in the project; this test was possible because the dyke was protecting a small polder that was to be “returned to nature” (i.e., flooded) to compensate for the loss of free water surface elsewhere in the Netherlands. The project included a site characterization based on an extensive CPT database (de Gast et al., 2021a), an RFEM analysis of the failure test (de Gast et al., 2021b), laboratory testing and constitutive modelling, and the development of various numerical tools, primarily linked to RFEM, including a subset simulation strategy for analyzing very small failure probability events (van den Eijnden & Hicks, 2017) and an extended 3D semi-analytical model benchmarked against RFEM (Varkey et al., 2019). In parallel to the Reliable Dykes project, further funding was obtained through the NWO research programme All-Risk to investigate the residual resistance of dykes, i.e., the resistance of a dyke to flooding following an initial slope failure. This research used RMPM to demonstrate the influence of soil spatial variability on the potential for an initial slope instability to cause a retrogressive failure mechanism leading to flooding; in particular, it developed a probabilistic framework that differentiated between the probability of a slope failure (which might be easily repaired) and the probability of flooding (with potentially massive consequences) (Remmerswaal et al., 2021).
The probabilistic tools developed in Reliable Dykes were used to assess the stability of the Starnmeer dyke in North Holland for the water board Hoogheemraadschap Hollands Noorderkwartier (HHNK) in 2018, and this resulted in mitigation measures that were far less expensive and far less intrusive than had originally been expected based on traditional methods of analysis; specifically, a stabilising berm of much smaller dimensions, as reported in Hicks et al. (2019) and Varkey et al. (2020). Similar assessments were commissioned by the water board Rijnland in 2019, and by the engineering company RPS (on behalf of HHNK) in 2020. Moreover, at the special request of STOWA, NWO agreed to fund Dr Varkey for an additional year as a postdoc, in order to facilitate further transfer of knowledge to industry. This included an assessment of partial factors used in semi-probabilistic design (Varkey et al, 2020), in collaboration with Deltares, as well as further work for the wider Dutch flood defence industry. Meanwhile, the rail operator ProRail commissioned a similar slope stability assessment for the embankment of the Delft-Schiedam line, which formed the basis for a new industry-funded project, RESET (referred to in a different tab).
The aim of this project is to investigate the influence of the shallow subsurface (up to 30 m depth) on the transfer of energy (due to induced seismicity) to the ground surface; specifically, what is the influence of the cyclic loading of soft deltaic soils (organic clay, peat and sand) on the site response? This is linked with induced earthquakes in Groningen, in the north of the Netherlands, due to shale gas extraction. The influence of the shallow subsurface on the site response is being quantified probabilistically using coupled RFEM analyses accounting for the spatial variability of the soil properties at 3 scales: (a) small scale heterogeneities, for example in the form of laminations in sand and fibres in peat, are being accounted for through the development of constitutive models incorporating soil anisotropy and fabric; (b) medium scale heterogeneity, which is the spatial variation with material layers, is being accounted for by random fields; and (c) large scale heterogeneity, which is the spatial distribution of geologic layers, is being accounted for using a coupled Markov chain model. The stratification of the Groningen area is being determined from a grid of CPTs with approximately 30 m spacing, using Bayesian updating to account for uncertainty in stratification at the CPT locations and coupled Markov Chain Monte Carlo simulation to predict soil stratigraphy between the CPTs. However, a detailed representation of spatial variability between CPTs, both of soil layering and within individual soil layers, is difficult, and this was the motivation for a new project, 3DSOIL (2021-2025). This project is seeking to use high frequency full-wave immersion geophysics, correlated with CPT data, to generate detailed 3D images of the subsurface. In addition, the intention is to use machine learning to develop a model for predicting CPT data based on geophysical measurements conditioned to known CPT data.
This project is funded by Prorail and is in collaboration with Deltares. It is motivated by the need of the Dutch rail network to accommodate (in the future) an increase in rail traffic, both in terms of the magnitude of applied loadings and the frequency of rail traffic, and also by the need to satisfy new safety guidelines and account for climate change. This is a huge project involving numerical and probabilistic modelling, physical modelling, laboratory testing, site investigation and various forms of monitoring, and is worth around 15 million euros over 5 years to all participants (with the possibility of another 15 million euros for years 6-10). The TU Delft share for the first 5 years is around 5 million euros and this will mainly be used to fund 8 PhDs. The main product of the project will be the probability-based framework for quantifying uncertainty and embankment performance: it is expected that 2 PhDs will work on this aspect (under my supervision), while the other 6 PhDs will primarily be involved in obtaining various sources of laboratory, field and numerical model data for calibrating and benchmarking the probabilistic framework. The framework itself will build on developments made in the previous research highlighted above; for example, the stochastic characterisation of sites will utilise multiple data sources, and extend the earlier work on using CPT data in Reliable Dykes and current research on using geophysical measurements and machine learning in 3DSOIL. Meanwhile, the reliability-based framework for embankment performance under train loading will build on the advances made in safety assessments for the flood defence industry in Reliable Dykes, as well as on experience gained in SOFTTOP on the dynamic loading of heterogeneous subsoils.
- Editorial Panel of “Computers and Geotechnics”
- Editorial Board of “Georisk”
- “Géotechnique” Advisory (Editorial) Panel (2019-2021)
- Editorial Panel of “Acta Geotechnica”
- Expert advisor to the EPSRC research Programme ACHILLES
- Member of ISSMGE Technical Committee TC103 on Numerical Methods
- TU Delft representative for ALERT Geomaterials
- Hicks, M. A., (Editor) Risk and variability in geotechnical engineering, Thomas Telford, London, 2007.
- Arnold, P., Fenton, G. A., Hicks, M. A., Schweckendiek, T. & Simpson B., (Editors) Modern geotechnical design codes of practice, IOS Press, Amsterdam, pp 331, 2013.
- Hicks, M. A., Dijkstra, J., Lloret-Cabot, M. & Karstunen, M., (Editors) Proceedings of the International Conference on Installation Effects in Geotechnical Engineering, Rotterdam, The Netherlands, CRC Press, Leiden, pp 271, 2013.
- Hicks, M. A. & Jommi, C., (Editors) Stochastic analysis and inverse modelling, ALERT Geomaterials, pp 280, 2014.
- Hicks, M. A., Brinkgreve, R. B. J. & Rohe, A., (Editors) Proceedings of the 8th European Conference on Numerical Methods in Geotechnical Engineering, Delft, The Netherlands, Taylor and Francis, 2014.
- Hicks, M. A., Pisano, F. & Peuchen, J., (Editors) Proceedings of the 4th International Symposium on Cone Penetration Testing, Delft, The Netherlands, CRC Press, Leiden, 2018.
Professor of Soil Mechanics / Head of the Geo-Engineering Section
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Faculty of Civil Engineering and Geosciences
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