A5046959259- Numerical methods in engineering
- Fluid Dynamics Simulations and Interactions
- Geotechnical and Geomechanical Engineering
- Granular flow and fluidized beds
- Advanced Numerical Analysis Techniques
- Advanced Numerical Methods in Computational Mathematics
- Metal Forming Simulation Techniques
- Elasticity and Material Modeling
- Geotechnical Engineering and Soil Mechanics
- Lattice Boltzmann Simulation Studies
- Non-Destructive Testing Techniques
- Model Reduction and Neural Networks
- Fluid Dynamics and Heat Transfer
- Composite Structure Analysis and Optimization
- Machine Learning in Materials Science
- Fluid Dynamics and Turbulent Flows
- Aerodynamics and Fluid Dynamics Research
- Spacecraft and Cryogenic Technologies
- Fatigue and fracture mechanics
- High-Velocity Impact and Material Behavior
- Rheology and Fluid Dynamics Studies
- Infrastructure Maintenance and Monitoring
- Wind Energy Research and Development
- Composite Material Mechanics
- Fire effects on concrete materials
University of Leeds
2017-2022
University of Sheffield
2018-2022
Durham University
2016
University of Ulsan
2012
The material point method is ideally suited to modelling problems involving large deformations where conventional mesh-based methods would struggle. However, total and updated Lagrangian approaches are unsuitable non-ideal, respectively, in terms of formulating equilibrium for the method. This due basis functions, particularly derivatives normally being defined on an unformed, sometimes regular, background mesh. It possible map function spatial using deformation at a but this introduces...
Abstract We present deep learning phase‐field models for brittle fracture. A variety of physics‐informed neural networks (PINNs) techniques, example, original PINNs, variational PINNs (VPINNs), and energy (VE‐PINNs) are utilized to solve problems. The performance the different versions is investigated in detail. Also, ways imposing boundary conditions examined compared with a self‐adaptive approach terms computational cost. Furthermore, data‐driven discovery length scale examined. Finally,...
This paper extends the non-uniform rational basis spline (NURBS) plasticity framework of Coombs et al. (2016) and Ghaffari Motlagh (2017) to include non-associated plastic flow. The NURBS approach allows any smooth isotropic yield envelope be represented by a surface whilst numerical algorithm (and code) remains unchanged. provides full theoretical algorithmic demonstrates predictive capability using both small large deformation problems. Wherever possible errors associated with constitutive...
The material point method (MPM) is a version of the particle-in-cell (PIC) which has substantial advantages over pure Lagrangian or Eulerian methods in numerical simulations problems involving large deformations. MPM helps to avoid mesh distortion and tangling related as well advection errors associated with methods. Despite being promoted for its ability solve deformation suffers from instabilities when points cross between elements. These are due lack smoothness grid basis functions used...
Summary A recently proposed phase‐field model for cohesive fracture is examined. Previous investigations have shown stress oscillations to occur when using unstructured meshes. It now that the use of nonuniform rational B‐splines (NURBS) as basis functions rather than traditional Lagrange polynomials significantly reduces this oscillatory behavior. Moreover, there no effect on global structural behavior, evidenced through load‐displacement curves. The imposes restrictions interpolation order...