pressure.
In Breward et al. [26,27] numerical simulations are presented in one dimension using a FDM scheme on structured meshes. Also, there is some research using the finite difference method, in multiple space dimensions, for simulating tumour growth, for example in [53, 73]. In [84, 85] the finite element method is used on unstructured meshes, which can be designed for a particular geometry.
In [99] a computational model is used to solve three cases of biological relevance. The governing equations are solved by a FEM to predict the growth rate of the mass of tumour as a function of the initial ratio of tumour density to density of healthy cells, mechanical strain, concentration of nutrient, cell adhesion and geometry. This model allows straightforward insertion of additional extra phases and nutrient types.
In [57] the computational approach is a combination of FEM and FVM. In this two di-mensional model, the hyperbolic PDEs of mass balance are discretised through a conservative, upwind, FVM scheme, whereas the momentum balance equations lead to generalised Stokes equations solved using a FEM scheme. Additionally, the discretization of nutrient reaction-diffusion equations is also based upon a finite element method used with a Newton iteration to solve the nonlinear equations. This numerical model demonstrates that the framework can be applied in multiple dimensions. In fact, extensions to more phases and 3D are claimed to be straightforward if the storage and time requirements are sufficient.
4.2 Numerical Schemes for Chosen Model
In this section, the numerical solution schemes are described for the mathematical model intro-duced in Section 2.2. In [57] the computational approach is a combination of FEM and FVM on unstructured triangular meshes. In the following subsections, the numerical schemes for mass balance equations, momentum balance equations and reaction diffusion equation are described.
4.2.1 Mass Balance Equations
Equation (2.2) is a set of hyperbolic mass balance equations which are time dependent PDEs.
These equations are approximated using an explicit solver in time with a standard cell centred finite volume scheme with forward Euler time stepping. The integral form for the mass balance equation is given by The discrete system of equations is designed to update the unknown θi, which are the cell-average values. By using the Gauss divergence theorem for the flux integrals in the previous equation we obtain
Z where ∆ is the control volume, qi represents the source/sink terms, ∂∆ is the boundary of the control volume, and ~n is the outward-pointing unit normal to the boundary. In [57] a cell-centred MUSCL approach is used, which is a conservative, upwind, finite volume scheme. This is used to update θ1, θ2, and θ3 in time, while the no-voids condition (2.3) is used to update θ4. The fluxes θi~ui are approximated by using a standard upwind scheme [71]. So, the discrete equation for each triangle can be written as
θn+1i = θni − ∆t
in which n denotes the time level, ∆t is the time step size, | ∆ | is the control volume area, and ~nk is the outward-pointing unit normal to the edge of the cell opposite the vertex k. The asterisk (*) is used to distinguish the quantities, which have been approximated depending on the variables ¯θi, which is a cell average.
To define the boundary condition, the volume fraction θi is described for each phase on the inflow section Γinf lowi for t ≥ 0. These inflow sections belong to the domain boundary Γ where ~ui.~n < 0, where ~n is the outward-pointing unit normal to Γ. In this model, the boundary condition is only required for the inflow section of the boundary.
4.2.2 Momentum Balance Equations
The momentum balance equations (2.4), do not depend on time, and they are linear in ~ui and p4. The weak form is obtained by applying a Galerkin finite element scheme with Taylor-Hood elements (see Section 3.1.1) as
where ωland ωq are the standard linear and quadratic Lagrange test functions respectively, σi are the stresses in each individual phase
σi= −piI + µi( ~∇~ui+ ( ~∇~ui)T) + λi( ~∇.~ui)I, and ~Fi are the momentum sources
F~i= piI ~∇θi+
4
X
j=1,j6=i
dijθiθj(~uj− ~ui) i = 1, ..., 4
43 4.2. Numerical Schemes for Chosen Model
Using integration by parts for the first equation from (4.4) leads to
I The velocities ~ui and pressures p are approximated by using piecewise polynomials, which are written using the trial function as
~
in which Nq and Nlare, respectively, the numbers of degrees of freedom related to the quadratic and linear Lagrange elements.
There are two possible boundary conditions used for the momentum balance equations, which are Dirichlet condition on ~ui or σi.~n specified. Here, the boundary conditions imposed are zero normal stress σi.~n = 0 for the three phases of healthy cells, tumour cells and blood vessels, and zero velocity for the extracellular phase ~u4= 0.
These choices of boundary conditions for the normal stress lead to the boundary term in (4.5) becoming zero, and so (4.4) may be expressed as:
−R
Applying integration by parts to the continuity equation, which is the second equation in (4.7), and using (4.6) gives:
PNq described in greater detail in Chapter 6.
In [57] the resulting large sparse system of linear equations is solved using the direct solution package MUMPS. The resulting system is nonsymmetric and indefinite and has similarities with the standard arising from a mixed FEM solution of Stokes’ equation for incompressible flow.
One of the contributions of this thesis is the use of a novel preconditioned GMRES method instead of MUMPS in this problem. More details for new solver are shown in Chapter 6
4.2.3 Reaction Diffusion Equation
Equation (2.6) is the quasi/steady state, reaction-diffusion equation. This equation is a time-independent PDE, and nonlinear, and is approximated using a standard Galerkin finite element scheme with linear elements to get:
Z
in which Dcdenotes to the diffusion coefficient, which is assumed to be constant, ωlf is a linear test function defined on the finer mesh, which is used to update the volume fractions of the phases, and qc is a source term, which is a nonlinear function of the nutrient concentration c.
Using integration by parts leads to Z
The nutrient concentration c is written using the trial functions as:
c ≈
Nlf
X
k=1
ckωklf. (4.13)
There are two possible boundary conditions used for the reaction diffusion equation, which are Dirichlet conditions c or Neumann conditions ~∇c.~n. In this work ~∇c.~n = 0 is specified in all cases throughout the boundary.
Here, FEM leads to a nonlinear system of equations with a sparse Jacobian which is solved using a Newton method to linearise it. The MUMPS sparse direct algorithm is again used to solve the linear system of equations at each nonlinear iteration in [57]. In this thesis, AMG