Three-dimensional meshfree analysis of interlocking concrete blocks for step seawall structure

This study adapts the flexible characteristic of meshfree method in analyzing three-dimensional (3D) complex geometry structures, which are the interlocking concrete blocks of step seawall. The elastostatic behavior of the block is analysed by solving the Galerkin weak form formulation over local support domain. The 3D moving least square (MLS) approximation is applied to build the interpolation functions of unknowns. The pre-defined number of nodes in an integration domain ranging from 10 to 60 nodes is also investigated for their effect on the studied results. The accuracy and efficiency of the studied method on 3D elastostatic responses are validated through the comparison with the solutions of standard finite element method (FEM) using linear shape functions on tetrahedral elements and the well-known commercial software, ANSYS. The results show that elastostatic responses of studied concrete block obtained by meshfree method converge faster and are more accurate than those of standard FEM. The studied meshfree method is effective in the analysis of static responses of complex geometry structures. The amount of discretised nodes within the integration domain used in building MLS shape functions should be in the range from 30 to 60 nodes and should not be less than 20 nodes

Modelling of advection-dominated transport in fluid-saturated porous media

The modelling of contaminant transport in porous media is an important topic to geosciences and geo-environmental engineering. An accurate assessment of the spatial and temporal distribution of a contaminant is an important step in the environmental decision-making process. Contaminant transport in porous media usually involves complex non-linear processes that result from the interaction of the migrating chemical species with the geological medium. The study of practical problems in contaminant transport therefore usually requires the development of computational procedures that can accurately examine the non-linear coupling processes involved. However, the computational modelling of the advection-dominated transport process is particularly sensitive to situations where the concentration profiles can exhibit high gradients and/or discontinuities. This thesis focuses on the development of an accurate computational methodology that can examine the contaminant transport problem in porous media where the advective process dominates.The development of the computational method for the advection-dominated transport problem is based on a Fourier analysis on stabilized semi-discrete Eulerian finite element methods for the advection equation. The Fourier analysis shows that under the Courant number condition of Cr=1, certain stabilized finite element scheme can give an oscillation-free and non-diffusive solution for the advection equation. Based on this observation, a time-adaptive scheme is developed for the accurate solution of the one-dimensional advection-dominated transport problem with the transient flow velocity. The time-adaptive scheme is validated with an experimental modelling of the advection-dominated transport problem involving the migration of a chemical solution in a porous column. A colour visualization-based image processing method is developed in the experimental modelling to quantitatively determinate the chemical concentration on the porous column in a non-invasive way. A mesh-refining adaptive scheme is developed for the optimal solution of the multi-dimensional advective transport problem with a time- and space-dependent flow field. Such mesh-refining adaptive procedure is quantitative in the sense that the size of the refined mesh is determined by the Courant number criterion. Finally, the thesis also presents a brief study of a numerical model that is capable to capture coupling Hydro-Mechanical-Chemical processes during the advection-dominated transport of a contaminant in a porous medium

Partitioned methods for coupled fluid flow problems

Many flow problems in engineering and technology are coupled in their nature. Plenty of turbulent flows are solved by legacy codes or by ones written by a team of programmers with great complexity. As knowledge of turbulent flows expands and new models are introduced, implementation of modern approaches in legacy codes and increasing their accuracy are of great concern. On the other hand, industrial flow models normally involve multi-physical process or multi-domains. Given the different nature of the physical processes of each subproblem, they may require different meshes, time steps and methods. There is a natural desire to uncouple and solve such systems by solving each subphysics problem, to reduce the technical complexity and allow the use of optimized legacy sub-problems' codes. The objective of this work is the development, analysis and validation of new modular, uncoupling algorithms for some coupled flow models, addressing both of the above problems. Particularly, this thesis studies: i) explicitly uncoupling algorithm for implementation of variational multiscale approach in legacy turbulence codes, ii) partitioned time stepping methods for magnetohydrodynamics flows, and iii) partitioned time stepping methods for groundwater-surface water flows. For each direction, we give comprehensive analysis of stability and derive optimal error estimates of our proposed methods. We discuss the advantages and limitations of uncoupling methods compared with monolithic methods, where the globally coupled problems are assembled and solved in one step. Numerical experiments are performed to verify the theoretical results

Modeling studies and numerical analyses of coupled PDEs system in electrohydrodynamics

Electrohydrodynamics (EHD) is the term used for the hydrodynamics coupled with electrostatics, whose governing equations consist of the electrostatic potential (Poisson) equation, the ionic concentration (Nernst-Planck) equations, and Navier-Stokes equations for an incompressible, viscous dielectric liquid. In this dissertation, we focus on a specic application of EHD - fuel cell dynamics - in the eld of renewable and clean energy, study its traditional model and attempt to develop a new fuel cell model based on the traditional EHD model. Meanwhile, we develop a series of ecient and robust numerical methods for these models, and carry out their numerical analyses on the approximation accuracy. In particular, we analyze the error estimates of nite element method for a simplied 2D isothermal steady state two-phase transport model of Proton Exchange Membrane Fuel Cell (PEMFC) as well as its transient version. On the aspect of hydrodynamics arising in the fuel cell system, the fluid flow through the open channels and porous media at the same time, both Navier-Stokes equations and Darcy\u27s law are involved in the fluid domains, leading to a Navier-Stokes-Darcy coupling problem. In this dissertation, we study a one-continuum model approach, so-called Brinkman model, to overcome this problem in a more ecient way. To develop a new fuel cell model based on EHD theory, in addition to the two-phase transport model of fuel cells, we carry out numerical analyses for Poisson-Nernst-Planck (PNP) equations using both standard FEM and mixed FEM, which are the essential governing equations involved by EHD model. Finally, we are able to further extend the traditional fuel cell model to more general cases in view of EHD characteristics, and develop a new fuel cell model by appropriately combining PNP equations with the traditional fuel cell model. We conduct the error analysis for PNP-Brinkman system in this dissertation

Numerical Computation, Data Analysis and Software in Mathematics and Engineering

The present book contains 14 articles that were accepted for publication in the Special Issue “Numerical Computation, Data Analysis and Software in Mathematics and Engineering” of the MDPI journal Mathematics. The topics of these articles include the aspects of the meshless method, numerical simulation, mathematical models, deep learning and data analysis. Meshless methods, such as the improved element-free Galerkin method, the dimension-splitting, interpolating, moving, least-squares method, the dimension-splitting, generalized, interpolating, element-free Galerkin method and the improved interpolating, complex variable, element-free Galerkin method, are presented. Some complicated problems, such as tge cold roll-forming process, ceramsite compound insulation block, crack propagation and heavy-haul railway tunnel with defects, are numerically analyzed. Mathematical models, such as the lattice hydrodynamic model, extended car-following model and smart helmet-based PLS-BPNN error compensation model, are proposed. The use of the deep learning approach to predict the mechanical properties of single-network hydrogel is presented, and data analysis for land leasing is discussed. This book will be interesting and useful for those working in the meshless method, numerical simulation, mathematical model, deep learning and data analysis fields

On multivariate overlapping grid spectral quasilinearization methods for problems in cavity flow.

Masters Degree. University of KwaZulu-Natal, Pietermaritzburg.We investigate fluid flow in cavities with different boundary conditions. Three cavity flow problems of varying complexity are investigated in this study. In the first problem, a flow filled with a porous medium, and with adiabatic and impermeable walls is considered. The left wall is heated. For the second problem, we investigate free convection in an enclosed square with porous medium and nanofluid. We assume that the side walls have a high fixed temperature and a lower fixed temperature for the horizontal walls. The third problem is more complex, and it involves investigating a square enclosure with porous medium, a top moving wall, and the side walls heated with a sinusoidally varying temperature. We analyze the effect of fluid parameters on the fluid flow characteristics such as the streamline distribution, isoconcentration, isotherms, local Nusselt number, skin friction, and the local Sherwood number. The flow equations are solved using two recent numerical techniques, namely the multivariate overlapping grid spectral quasilinearization method (MOGSQLM) and the multivariate spectral quasilinearization method (MSQLM). The MOGSQLM is an extension of the MSQLM with improved accuracy. Using the two methods we determine the solution, the residual solution errors and the computational time to achieve a converged solution. The MOGSQLM is found to be more accurate, and for this reason, only the MOGSQLM is used to numerically solve the third problem. The MOGSQLM was found to be the better method in terms of convergence, accuracy, and CPU time. The changes in the Rayleigh number alter the flow pattern from circular to elliptic with stronger circulation in the core region

Numerical methods and analysis for continuous data assimilation in fluid models

Modeling fluid flow arises in many applications of science and engineering, including the design of aircrafts, prediction of weather, and oceanography. It is vital that these models are both computationally efficient and accurate. In order to obtain good results from these models, one must have accurate and complete initial and boundary conditions. In many real-world applications, these conditions may be unknown, only partially known, or contain error. In order to overcome the issue of unknown or incomplete initial conditions, mathematicians and scientists have been studying different ways to incorporate data into fluid flow models to improve accuracy and/or speed up convergence to the true solution. In this thesis, we are studying one specific data assimilation technique to apply to finite element discretizations of fluid flow models, known as continuous data assimilation. Continuous data assimilation adds a penalty term to the differential equation to nudge coarse spatial scales of the algorithm solution to coarse spatial scales of the true solution (the data). We apply continuous data assimilation to different algorithms of fluid flow, and perform numerical analysis and tests of the algorithms

Statistical Fluid Dynamics

Modeling micrometric and nanometric suspensions remains a major issue. They help to model the mechanical, thermal, and electrical properties, among others, of the suspensions, and then of the resulting product, in a controlled way, when considered in material formation. In some cases, they can help to improve the energy transport performance. The optimal use of these products is based on an accurate prediction of the flow-induced properties of the suspensions and, consequently, of the resulting products and parts. The final properties of the resulting micro-structured fluid or solid are radically different from the simple mixing rule. In this book, we found numerous works addressing the description of these specific fluid behaviors