Evan Ricketts
MMath, PhD, FHEA
- Available for postgraduate supervision
Teams and roles for Evan Ricketts
Lecturer
Overview
My current research focuses on the numerical modelling of heterogeneous materials, with particular interest in stochastic methods and random field theory. Interests include
- Numerical methods
- Random field theory
- Plurigaussian simulation
- Soil mechanics
- Stochastics
- Theory of acoustic-gravity waves
- Machine learning
- Multi-level modelling
- Flow in porous media
Publication
2025
- Freeman, B. L. et al. 2025. A probabilistic cut finite element method with random field generator and Bayesian model calibration for flow through rough cracks. International Journal for Numerical and Analytical Methods in Geomechanics nag.70104. (10.1002/nag.70104)
2024
- Farid, A. et al., 2024. A review of the occurrence and causes for wildfires and their impacts on the geoenvironment. Fire 7 (8) 295. (10.3390/fire7080295)
- Ricketts, E. J. 2024. Stochastic periodic microstructures for multiscale modelling of heterogeneous materials. Transport in Porous Media 151 (6), pp.1313-1332. (10.1007/s11242-024-02074-z)
- Ricketts, E. J. et al. 2024. Representation of three-dimensional unsaturated flow in heterogeneous soil through tractable Gaussian random fields. Géotechnique 74 (13), pp.1868-1880. (10.1680/jgeot.22.00316)
- Ricketts, E. J. et al. 2024. The influence of spatially varying boundary conditions based on material heterogeneity. European Journal of Computational Mechanics 33 (03), pp.199-226. (10.13052/ejcm2642-2085.3331)
- Ricketts, E. J. et al. 2024. Microcapsule triggering mechanics in cementitious materials: a modelling and machine learning approach. Materials 17 (3) 764. (10.3390/ma17030764)
2023
- Ricketts, E. 2023. Stochastic representation of material heterogeneity and its effects on flow: applications in soils of mixed wettabilities. PhD Thesis , Cardiff University.
- Ricketts, E. J. et al. 2023. Near-boundary error reduction with an optimized weighted Dirichlet-Neumann boundary condition for stochastic PDE-based Gaussian random field generators. Engineering with Computers 39 , pp.3821-3833. (10.1007/s00366-023-01819-6)
- Ricketts, E. J. et al. 2023. A statistical finite element method integrating a plurigaussian random field generator for multi-scale modelling of solute transport in concrete. Transport in Porous Media (10.1007/s11242-023-01930-8)
- Sayadi, S. et al., 2023. Effect of microstructure heterogeneity shapes on constitutive behaviour of encapsulated self-healing cementitious materials. Presented at: SMARTINCS’23 Conference on Self-Healing, Multifunctional and Advanced Repair Technologies in Cementitious Systems 22-23 May 2023. Vol. 378.EDP Sciences. (10.1051/matecconf/202337809004)
Articles
- Farid, A. et al., 2024. A review of the occurrence and causes for wildfires and their impacts on the geoenvironment. Fire 7 (8) 295. (10.3390/fire7080295)
- Freeman, B. L. et al. 2025. A probabilistic cut finite element method with random field generator and Bayesian model calibration for flow through rough cracks. International Journal for Numerical and Analytical Methods in Geomechanics nag.70104. (10.1002/nag.70104)
- Ricketts, E. J. 2024. Stochastic periodic microstructures for multiscale modelling of heterogeneous materials. Transport in Porous Media 151 (6), pp.1313-1332. (10.1007/s11242-024-02074-z)
- Ricketts, E. J. et al. 2024. Representation of three-dimensional unsaturated flow in heterogeneous soil through tractable Gaussian random fields. Géotechnique 74 (13), pp.1868-1880. (10.1680/jgeot.22.00316)
- Ricketts, E. J. et al. 2024. The influence of spatially varying boundary conditions based on material heterogeneity. European Journal of Computational Mechanics 33 (03), pp.199-226. (10.13052/ejcm2642-2085.3331)
- Ricketts, E. J. et al. 2023. Near-boundary error reduction with an optimized weighted Dirichlet-Neumann boundary condition for stochastic PDE-based Gaussian random field generators. Engineering with Computers 39 , pp.3821-3833. (10.1007/s00366-023-01819-6)
- Ricketts, E. J. et al. 2024. Microcapsule triggering mechanics in cementitious materials: a modelling and machine learning approach. Materials 17 (3) 764. (10.3390/ma17030764)
- Ricketts, E. J. et al. 2023. A statistical finite element method integrating a plurigaussian random field generator for multi-scale modelling of solute transport in concrete. Transport in Porous Media (10.1007/s11242-023-01930-8)
Conferences
- Sayadi, S. et al., 2023. Effect of microstructure heterogeneity shapes on constitutive behaviour of encapsulated self-healing cementitious materials. Presented at: SMARTINCS’23 Conference on Self-Healing, Multifunctional and Advanced Repair Technologies in Cementitious Systems 22-23 May 2023. Vol. 378.EDP Sciences. (10.1051/matecconf/202337809004)
Thesis
- Ricketts, E. 2023. Stochastic representation of material heterogeneity and its effects on flow: applications in soils of mixed wettabilities. PhD Thesis , Cardiff University.
Teaching
I am module lead for:
- EN3301: Digital and Computational Architectural, Civil, and Environmental Engineering
- EN4302/T603: Finite element theory and practice
I also supervise BEng/MSc dissertations and help with the field trip in Year 2
Supervisions
I welcome enquiries from prospective PhD students interested in computational mechanics and scientific machine learning applications to heterogeneous porous media. I am particularly keen to supervise projects addressing:
- Unfitted finite element methods for complex geometries
- Adjoint methods for optimisation problems
- Stochastic characterisation of material heterogeneity
- Stochastic methods for microstructural generation
- Physics-informed machine learning for porous media
- Sustainable geomaterials
Prospective students should have a strong background in computational mechanics, applied mathematics, or related engineering disciplines. Experience with finite element methods, scientific programming (Python/MATLAB), and machine learning frameworks would be advantageous.
Contact Details
Queen's Buildings - South Building, Room 0.20, 5 The Parade, Newport Road, Cardiff, CF24 3AA