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The Full Discretization Method (often referred to as direct Finite Difference Methods for space-time grids) approaches partial differential equations (PDEs) by discretizing both the spatial and temporal dimensions simultaneously onto a discrete grid.

Unlike the Method of Lines—which retains continuous time to yield an ODE system—full discretization converts the PDE directly into a system of algebraic equations that can be solved step-by-step or via matrix inversion.

How It Works:

The 3-Step Process Consider the 1D transient heat equation:

\frac{\partial u}{\partial t} = \alpha \frac{\partial^2 u}{\partial x^2}

Grid Generation: We partition space into steps of size $\Delta x$ ( $x_i = i \Delta x$ ) and time into steps of size $\Delta t$ ( $t^n = n \Delta t$ ). The discrete approximation to $u(x_i, t^n)$ is denoted as $u_i^n$ .

Algebraic Substitution: Both the time derivative and spatial derivative are replaced with algebraic finite difference approximations. For example, using a forward difference in time and a central difference in space:

\frac{u_i^{n+1} - u_i^n}{\Delta t} \approx \alpha \frac{u_{i+1}^n - 2u_i^n + u_{i-1}^n}{(\Delta x)^2}

Time Marching / Matrix Solution: Re-arranging the algebraic equation allows us to explicitly compute values at the next time level $n+1$ from known values at level $n$ (Explicit Scheme), or solve a linear system $A u^{n+1} = B u^n$ (Implicit Scheme).

## Explicit vs. Implicit Schemes

When discretizing space and time simultaneously, the evaluation point of the spatial derivative defines the nature of the solver: - Explicit Schemes (Forward Euler): Evaluate spatial derivatives entirely at the current time step $n$. Fast per iteration, but strictly bounded by stability constraints. - Implicit Schemes (Backward Euler / Crank-Nicolson): Evaluate spatial derivatives at the future time step $n+1$ (or a weighted blend). Unconditionally stable, but requires solving a system of linear equations at each time step.

Example 1: Explicit Method (FTCS Scheme)

The Forward-Time Central-Space (FTCS) scheme explicitly updates each grid point based on its immediate neighbors at the previous time level:

u_i^{n+1} = u_i^n + r \left(u_{i+1}^n - 2u_i^n + u_{i-1}^n \right), \quad r = \frac{\alpha \Delta t}{(\Delta x)^2}

Stability Warning: The 1D explicit FTCS scheme is stable if and only if $r \le 0.5$ . Exceeding this limit causes catastrophic non-physical oscillations.

Example 1C#

// SOLVE_HEAT_EXPLICIT Solves 1D heat equation using Explicit FTCS scheme
// Equation: du/dt = alpha * d^2u/dx^2
double alpha = 0.5;
double L = 1.0;
double t_final = 0.5;
int Nx = 50;
double dx = L / Nx;
ColVec x = Linspace(0, L, Nx + 1);
// Select dt to satisfy the stability criterion: r = alpha * dt / dx^2 <= 0.5
double CFL = 0.45, r = CFL;
double dt = CFL * (dx * dx) / alpha;
int Nt = (int)(t_final / dt / 5);
// Initial condition: u(x,0) = sin(pi * x)
ColVec Un = Sin(pi * x), Unp1 = Zeros(Nx + 1);
// Plot the initial condition
var TempProfile = Plot(x, Un, Linewidth: 2);
Title("Emplicit Solution"); GridOn();
Xlabel("Position x"); Ylabel("Temperature T");
byte[] Animfun(int n)
{
    for (int m = 0; m < 5; m++)
    {// Internal grid point update
        for (int i = 1; i < Nx; i++)
            Unp1[i] = Un[i] + r * (Un[i + 1] - 2.0 * Un[i] + Un[i - 1]);
        // Dirichlet Boundary Conditions
        Unp1[0] = 0.0; Unp1[Nx] = 0.0;
        Un = Unp1.Duplicate();
        TempProfile.Ydata = Un;
    }
    return GetFrame();
}
AnimationMaker(Animfun, "TemperatureProfile_Explicit.gif", 10, Nt);
CloseFig();

// SOLVE_HEAT_EXPLICIT Solves 1D heat equation using Explicit FTCS scheme
// Equation: du/dt = alpha * d^2u/dx^2
double alpha = 0.5;
double L = 1.0;
double t_final = 0.5;

int Nx = 50;
double dx = L / Nx;
ColVec x = Linspace(0, L, Nx + 1);

// Select dt to satisfy the stability criterion: r = alpha * dt / dx^2 <= 0.5
double CFL = 0.45, r = CFL;
double dt = CFL * (dx * dx) / alpha;
int Nt = (int)(t_final / dt / 5);

// Initial condition: u(x,0) = sin(pi * x)
ColVec Un = Sin(pi * x), Unp1 = Zeros(Nx + 1);

// Plot the initial condition
var TempProfile = Plot(x, Un, Linewidth: 2);
Title("Emplicit Solution"); GridOn();
Xlabel("Position x"); Ylabel("Temperature T");

byte[] Animfun(int n)
{
    for (int m = 0; m < 5; m++)
    {// Internal grid point update
        for (int i = 1; i < Nx; i++)
            Unp1[i] = Un[i] + r * (Un[i + 1] - 2.0 * Un[i] + Un[i - 1]);

// Dirichlet Boundary Conditions
        Unp1[0] = 0.0; Unp1[Nx] = 0.0;
        Un = Unp1.Duplicate();
        TempProfile.Ydata = Un;
    }
    return GetFrame();
}
AnimationMaker(Animfun, "TemperatureProfile_Explicit.gif", 10, Nt);
CloseFig();

Example 2: Implicit Crank-Nicolson Scheme

The Crank-Nicolson scheme is a second-order accurate implicit method formed by averaging the central differences at time steps $n$ and $n+1$ :

-\frac{r}{2} u_{i-1}^{n+1} + (1 + r) u_i^{n+1} -\frac{r}{2} u_{i+1}^{n+1} = \frac{r}{2} u_{i-1}^n + (1 - r) u_i^n + \frac{r}{2} u_{i+1}^n

Expressed in matrix-vector form:

\mathbf{A} \mathbf{u}^{n+1} = \mathbf{B} \mathbf{u}^n

where $\mathbf{A}$ and $\mathbf{B}$ are tridiagonal matrices. This scheme is unconditionally stable for any choice of $\Delta t$ .

Example 2C#

// SOLVE_HEAT_CRANK_NICOLSON Solves 1D heat equation via implicit matrix linear system
double alpha = 0.5;
double L = 1.0;
double t_final = 0.5;
int Nx = 100;
double dx = L / Nx;
double dt = 0.01;                        // Can take much larger time steps safely
double r = alpha * dt / (dx * dx);
ColVec x = Linspace(0, L, Nx + 1);
ColVec Un = Sin(pi * x);
// Plot the initial condition
var TempProfile = Plot(x, Un, Linewidth: 2); GridOn();
Title("Crank-Nicolson Implicit Solution");
Xlabel("Position x"); Ylabel("Temperature T");
// Construct Tridiagonal System A * u^{n+1} = B * u^n
int N = Nx + 1;
Matrix A = Zeros(N, N), B = Zeros(N, N);
// Internal nodes
for (int i = 1; i < Nx; i++)
{
    A[i, i - 1] = -0.5 * r;
    A[i, i] = 1.0 + r;
    A[i, i + 1] = -0.5 * r;
    B[i, i - 1] = 0.5 * r;
    B[i, i] = 1.0 - r;
    B[i, i + 1] = 0.5 * r;
}
// Enforce Dirichlet Boundary Conditions implicitly
A[0, 0] = 1.0; B[0, 0] = 0.0;
A[Nx, Nx] = 1.0; B[Nx, Nx] = 0.0;
int Nt = (int)(t_final / dt);
byte[] Animfun(int n)
{
    // Internal grid point update
    ColVec rhs = B * Un;
    // Linear solve using SepalSolver matrix operator (Mldivide / Thomas Algorithm)
    Un = Mldivide(A, rhs);
    TempProfile.Ydata = Un;
    return GetFrame();
}
AnimationMaker(Animfun, "TemperatureProfile_CrankNicolson.gif", 10, Nt);
CloseFig();

// SOLVE_HEAT_CRANK_NICOLSON Solves 1D heat equation via implicit matrix linear system
double alpha = 0.5;
double L = 1.0;
double t_final = 0.5;

int Nx = 100;
double dx = L / Nx;
double dt = 0.01;                        // Can take much larger time steps safely
double r = alpha * dt / (dx * dx);

ColVec x = Linspace(0, L, Nx + 1);
ColVec Un = Sin(pi * x);

// Plot the initial condition
var TempProfile = Plot(x, Un, Linewidth: 2); GridOn();
Title("Crank-Nicolson Implicit Solution");
Xlabel("Position x"); Ylabel("Temperature T");

// Construct Tridiagonal System A * u^{n+1} = B * u^n
int N = Nx + 1;
Matrix A = Zeros(N, N), B = Zeros(N, N);

// Internal nodes
for (int i = 1; i < Nx; i++)
{
    A[i, i - 1] = -0.5 * r;
    A[i, i] = 1.0 + r;
    A[i, i + 1] = -0.5 * r;

B[i, i - 1] = 0.5 * r;
    B[i, i] = 1.0 - r;
    B[i, i + 1] = 0.5 * r;
}

// Enforce Dirichlet Boundary Conditions implicitly
A[0, 0] = 1.0; B[0, 0] = 0.0;
A[Nx, Nx] = 1.0; B[Nx, Nx] = 0.0;
int Nt = (int)(t_final / dt);

byte[] Animfun(int n)
{
    // Internal grid point update
    ColVec rhs = B * Un;

// Linear solve using SepalSolver matrix operator (Mldivide / Thomas Algorithm)
    Un = Mldivide(A, rhs);
    TempProfile.Ydata = Un;
    return GetFrame();
}
AnimationMaker(Animfun, "TemperatureProfile_CrankNicolson.gif", 10, Nt);
CloseFig();

Example 3: Implicit Scheme, with Finite Element for Spatial derivatives

When applying the Finite Element Method to time-dependent problems such as the 1D heat equation:

\cfrac{\partial u}{\partial t} = \alpha \cfrac{\partial^2 u}{\partial x^2} + f(x,t)

applying the Galerkin spatial discretization yields a system of coupled ODEs in matrix form:

\mathbf{M} \cfrac{d\mathbf{u}}{dt} + \alpha \mathbf{K} \mathbf{u} = \mathbf{F}

where: - $\mathbf{M}$ is the Global Mass Matrix ( $M_{ij} = \int_\Omega \phi_i \phi_j \, dx$ ), representing the temporal inertia/capacity. For 1D linear elements of length $h$ , the local element mass matrix is $\mathbf{m}_e = \cfrac{h}{6} \begin{bmatrix} 2 & 1 \\ 1 & 2 \end{bmatrix}$ . - $\mathbf{K}$ is the Global Stiffness Matrix ( $K_{ij} = \int_\Omega \cfrac{d\phi_i}{dx} \cfrac{d\phi_j}{dx} \, dx$ ), with local element stiffness matrix $\mathbf{k}_e = \cfrac{1}{h} \begin{bmatrix} 1 & -1 \\ -1 & 1 \end{bmatrix}$ . - $\mathbf{u}(t)$ is the vector of nodal temperature values evolving over time.

Using an implicit time-integration scheme (Backward Euler) for stability:

\left( \mathbf{M} + \Delta t \cdot \alpha \mathbf{K} \right) \mathbf{u}^{n+1} = \mathbf{M} \mathbf{u}^n + \Delta t \cdot \mathbf{F}^{n+1}

Example 3C#

double alpha = 0.5, L = 1.0, t_final = 0.5;
int numElements = 50, numNodes = numElements + 1;
double h = L / numElements, dt = 0.01;
int Nt = (int)(t_final / dt);
ColVec x = Linspace(0, L, numNodes);
// Global Stiffness Matrix K and Mass Matrix M
Matrix K = Zeros(numNodes, numNodes);
Matrix M = Zeros(numNodes, numNodes);
// Local element stiffness matrix: (1/h) * [1, -1; -1, 1]
Matrix ke = new double[,] { { 1, -1 }, { -1, 1 } }; ke /= h;
// Local element mass matrix: (h/6) * [2, 1; 1, 2]
Matrix me = new double[,] { { 2, 1 }, { 1, 2 } }; me *= h / 6;
// Global assembly over elements
for (int e = 0; e < numElements; e++)
{
    int[] nodes = [e, e + 1];
    K[nodes, nodes] += ke;
    M[nodes, nodes] += me;
}
// Initial Condition: u(x,0) = sin(pi * x)
ColVec U = Sin(pi * x);
var TempProfile = Plot(x, U, Linewidth: 2); GridOn();
Title("1D FEM Transient Heat Equation Solution");
Xlabel("Position x"); Ylabel("Temperature T");
// Construct System Matrix A = M + dt * alpha * K for Implicit Time Stepping
Matrix A = M + dt * alpha * K;
// Apply Dirichlet Boundary Conditions to System Matrix A
A[0, ..] = 0.0; A[0, 0] = 1.0;
A[numNodes - 1, ..] = 0.0; A[numNodes - 1, numNodes - 1] = 1.0;
// Time-stepping Loop
byte[] Animfun(int n)
{
    // Right-hand side vector: B = M * u^n
    ColVec rhs = M * U;
    // Apply Dirichlet Boundary Conditions to RHS
    rhs[0] = 0.0; rhs[numNodes - 1] = 0.0;
    // Solve linear system A * u^{n+1} = rhs
    U = Mldivide(A, rhs);
    TempProfile.Ydata = U;
    return GetFrame();
}
AnimationMaker(Animfun, "FEM_1D_Heat_Solution.gif", 10, Nt);
CloseFig();

double alpha = 0.5, L = 1.0, t_final = 0.5;

int numElements = 50, numNodes = numElements + 1;
double h = L / numElements, dt = 0.01;
int Nt = (int)(t_final / dt);

ColVec x = Linspace(0, L, numNodes);

// Global Stiffness Matrix K and Mass Matrix M
Matrix K = Zeros(numNodes, numNodes);
Matrix M = Zeros(numNodes, numNodes);

// Local element stiffness matrix: (1/h) * [1, -1; -1, 1]
Matrix ke = new double[,] { { 1, -1 }, { -1, 1 } }; ke /= h;

// Local element mass matrix: (h/6) * [2, 1; 1, 2]
Matrix me = new double[,] { { 2, 1 }, { 1, 2 } }; me *= h / 6;

// Global assembly over elements
for (int e = 0; e < numElements; e++)
{
    int[] nodes = [e, e + 1];
    K[nodes, nodes] += ke;
    M[nodes, nodes] += me;
}

// Initial Condition: u(x,0) = sin(pi * x)
ColVec U = Sin(pi * x);
var TempProfile = Plot(x, U, Linewidth: 2); GridOn();
Title("1D FEM Transient Heat Equation Solution");
Xlabel("Position x"); Ylabel("Temperature T");

// Construct System Matrix A = M + dt * alpha * K for Implicit Time Stepping
Matrix A = M + dt * alpha * K;

// Apply Dirichlet Boundary Conditions to System Matrix A
A[0, ..] = 0.0; A[0, 0] = 1.0;
A[numNodes - 1, ..] = 0.0; A[numNodes - 1, numNodes - 1] = 1.0;

// Time-stepping Loop
byte[] Animfun(int n)
{
    // Right-hand side vector: B = M * u^n
    ColVec rhs = M * U;

// Apply Dirichlet Boundary Conditions to RHS
    rhs[0] = 0.0; rhs[numNodes - 1] = 0.0;

// Solve linear system A * u^{n+1} = rhs
    U = Mldivide(A, rhs);
    TempProfile.Ydata = U;
    return GetFrame();
}
AnimationMaker(Animfun, "FEM_1D_Heat_Solution.gif", 10, Nt);
CloseFig();

Example 2: Implicit Scheme with Chebyshev Spectral Differentiation for Spatial Derivative

Constructing a Chebyshev differentiation matrix $\mathbf{D}_N$ to compute high-accuracy spatial derivatives on Gauss-Lobatto collocation points $x_k = \cos\left(\frac{k\pi}{N}\right)$ :

Example 4C#

// CHEBYSHEV_SPECTRAL_DERIVATIVE High-accuracy spectral spatial derivative
double alpha = 0.5;
double t_final = 0.5;
int N = 20; // Only 20 spectral nodes yield machine-precision spatial derivative
// Chebyshev Gauss-Lobatto nodes on [-1, 1]
ColVec k = Linspace(0, N, N + 1);
ColVec x = Cos(k * pi / N);
// 1. Construct Chebyshev Differentiation Matrix D
Matrix D = Zeros(N + 1, N + 1);
ColVec c = Ones(N + 1);
c[[0, N]] = 2.0;
for (int i = 0; i <= N; i++)
{
    for (int j = 0; j <= N; j++)
    {
        if (i != j)
        {
            D[i, j] = (c[i] / c[j]) * (Pow(-1.0, i + j) / (x[i] - x[j]));
        }
    }
}
// Enforce negative row-sum identity on diagonals
for (int i = 0; i <= N; i++)
{
    double sum = 0.0;
    for (int j = 0; j <= N; j++)
    {
        if (i != j) sum += D[i, j];
    }
    D[i, i] = -sum;
}
// 2. Second Derivative Matrix D2 = D * D
Matrix D2 = D * D;
// Time-stepping setup (Implicit Backward Euler)
double dt = 0.005;
int Nt = (int)(t_final / dt);
// Initial Condition: u(x,0) = cos(pi * x / 2)
ColVec U = Cos(pi * x / 2.0);
var TempProfile = Plot(x, U, Linewidth: 2); GridOn();
Title("1D Chebyshev Spectral Transient Heat Equation Solution");
Xlabel("Position x"); Ylabel("Temperature T");
// System Matrix: A = I - dt * alpha * D2
Matrix I = Eye(N + 1);
Matrix A = I - dt * alpha * D2;
// Enforce Dirichlet Boundary Conditions implicitly at x = 1 (row 0) and x = -1 (row N)
A[0, ..] = 0.0; A[0, 0] = 1.0;
A[N, ..] = 0.0; A[N, N] = 1.0;
// Time-stepping Loop
byte[] Animfun(int n)
{
    // Right-hand side vector: B = M * u^n
    ColVec rhs = U.Duplicate();
    // Apply Dirichlet Boundary Conditions to RHS
    rhs[0] = 0.0; rhs[N] = 0.0;
    // Solve linear system A * u^{n+1} = rhs
    U = Mldivide(A, rhs);
    TempProfile.Ydata = U;
    return GetFrame();
}
AnimationMaker(Animfun, "Spectral_1D_Heat_Solution.gif", 10, Nt);
CloseFig();

// CHEBYSHEV_SPECTRAL_DERIVATIVE High-accuracy spectral spatial derivative

double alpha = 0.5;
double t_final = 0.5;
int N = 20; // Only 20 spectral nodes yield machine-precision spatial derivative

// Chebyshev Gauss-Lobatto nodes on [-1, 1]
ColVec k = Linspace(0, N, N + 1);
ColVec x = Cos(k * pi / N);

// 1. Construct Chebyshev Differentiation Matrix D
Matrix D = Zeros(N + 1, N + 1);
ColVec c = Ones(N + 1);
c[[0, N]] = 2.0;

for (int i = 0; i <= N; i++)
{
    for (int j = 0; j <= N; j++)
    {
        if (i != j)
        {
            D[i, j] = (c[i] / c[j]) * (Pow(-1.0, i + j) / (x[i] - x[j]));
        }
    }
}

// Enforce negative row-sum identity on diagonals
for (int i = 0; i <= N; i++)
{
    double sum = 0.0;
    for (int j = 0; j <= N; j++)
    {
        if (i != j) sum += D[i, j];
    }
    D[i, i] = -sum;
}

// 2. Second Derivative Matrix D2 = D * D
Matrix D2 = D * D;

// Time-stepping setup (Implicit Backward Euler)
double dt = 0.005;
int Nt = (int)(t_final / dt);

// Initial Condition: u(x,0) = cos(pi * x / 2)
ColVec U = Cos(pi * x / 2.0);
var TempProfile = Plot(x, U, Linewidth: 2); GridOn();
Title("1D Chebyshev Spectral Transient Heat Equation Solution");
Xlabel("Position x"); Ylabel("Temperature T");

// System Matrix: A = I - dt * alpha * D2
Matrix I = Eye(N + 1);
Matrix A = I - dt * alpha * D2;

// Enforce Dirichlet Boundary Conditions implicitly at x = 1 (row 0) and x = -1 (row N)
A[0, ..] = 0.0; A[0, 0] = 1.0;
A[N, ..] = 0.0; A[N, N] = 1.0;

// Time-stepping Loop
byte[] Animfun(int n)
{
    // Right-hand side vector: B = M * u^n
    ColVec rhs = U.Duplicate();

// Apply Dirichlet Boundary Conditions to RHS
    rhs[0] = 0.0; rhs[N] = 0.0;

// Solve linear system A * u^{n+1} = rhs
    U = Mldivide(A, rhs);
    TempProfile.Ydata = U;
    return GetFrame();
}
AnimationMaker(Animfun, "Spectral_1D_Heat_Solution.gif", 10, Nt);
CloseFig();

Takes a free account.

Solution Of PDE by Full Descretization

How It Works:

Example 1: Explicit Method (FTCS Scheme)

Example 2: Implicit Crank-Nicolson Scheme

Example 3: Implicit Scheme, with Finite Element for Spatial derivatives

Example 2: Implicit Scheme with Chebyshev Spectral Differentiation for Spatial Derivative