 # Contents of /trunk/doc/cookbook/example02.tex

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Cookbook modifications Review -> Not quite finished yet.
New figure.

 1 2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 3 % 4 % Copyright (c) 2003-2010 by University of Queensland 5 % Earth Systems Science Computational Center (ESSCC) 6 7 % 8 % Primary Business: Queensland, Australia 9 % Licensed under the Open Software License version 3.0 10 11 % 12 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 13 14 15 \section{Example 2: One Dimensional Heat Diffusion in an Iron Rod} 16 \sslist{example02.py} 17 18 \label{Sec:1DHDv0} 19 \begin{figure}[ht] 20 \centerline{\includegraphics[width=4.in]{figures/onedheatdiff002}} 21 \caption{Example 2: One dimensional model of an Iron bar.} 22 \label{fig:onedhdmodel} 23 \end{figure} 24 25 Our second example is of a cold iron bar at a constant temperature of $T\hackscore{ref}=20^{\circ} C$, see \reffig{fig:onedhdmodel}. The bar is perfectly insulated on all sides with a heating element at one end keeping the the temperature at a constant level $T\hackscore0=100^{\circ} C$. As heat is applied; energy will disperse along the bar via conduction. With time the bar will reach a constant temperature equivalent to that of the heat source. 26 27 This problem is very similar to the example of temperature diffusion in granite blocks presented in the previous section~\ref{Sec:1DHDv00}. Thus, it is possible to modify the script we have already developed for the granite blocks to suit the iron bar problem. 28 The obvious difference between the two problems are the dimensions of the domain and different materials involved. This will change the time scale of the model from years to hours. 29 The new settings are; 30 \begin{python} 31 #Domain related. 32 mx = 1*m #meters - model length 33 my = .1*m #meters - model width 34 ndx = 100 # mesh steps in x direction 35 ndy = 1 # mesh steps in y direction - one dimension means one element 36 #PDE related 37 rho = 7874. *kg/m**3 #kg/m^{3} density of iron 38 cp = 449.*J/(kg*K) # J/Kg.K thermal capacity 39 rhocp = rho*cp 40 kappa = 80.*W/m/K # watts/m.Kthermal conductivity 41 qH = 0 * J/(sec*m**3) # J/(sec.m^{3}) no heat source 42 Tref = 20 * Celsius # base temperature of the rod 43 T0 = 100 * Celsius # temperature at heating element 44 tend= 0.5 * day # - time to end simulation 45 \end{python} 46 We also need to alter the initial value for the temperature. Now we need to set the 47 temperature to $T\hackscore{0}$ at the left end of the rod where we have $x\hackscore{0}=0$ and 48 $T\hackscore{ref}$ elsewhere. Instead of \verb|whereNegative| function we use now the 49 \verb|whereZero| which returns the value one for those sample points where 50 the argument (almost) equals zero and the value zero elsewhere. The initial 51 temperature is set to; 52 \begin{python} 53 # ... set initial temperature .... 54 T= T0*whereZero(x)+Tref*(1-whereZero(x)) 55 \end{python} 56 57 \subsection{Dirichlet Boundary Conditions} 58 In the iron rod model we want to keep the initial temperature $T\hackscore0$ on the left side of the domain constant with time. 59 This implies that when we solve the PDE~\refEq{eqn:hddisc}, the solution must have the value $T\hackscore0$ on the left hand 60 side of the domain. As mentioned already in Section~\ref{SEC BOUNDARY COND} where we discussed 61 boundary conditions, this kind of scenario can be expressed using a \textbf{Dirichlet boundary condition}. Some people also 62 use the term \textbf{constraint} for the PDE. 63 64 To define a Dirichlet boundary condition we need to identify where to apply the condition and determine what value the 65 solution should have at these locations. In \esc we use $q$ and $r$ to define the Dirichlet boundary conditions 66 for a PDE. The solution $u$ of the PDE is set to $r$ for all sample points where $q$ has a positive value. 67 Mathematically this is expressed in the form; 68 \begin{equation} 69 u(x) = r(x) \mbox{ for any } x \mbox{ with } q(x) > 0 70 \end{equation} 71 In the case of the iron rod 72 we can set; 73 \begin{python} 74 q=whereZero(x) 75 r=T0 76 \end{python} 77 to prescribe the value $T\hackscore{0}$ for the temperature at the left end of the rod where $x\hackscore{0}=0$. 78 Here we use the \verb|whereZero| function again which we have already used to set the initial value. 79 Notice that $r$ is set to the constant value $T\hackscore{0}$ for all sample points. In fact, 80 values of $r$ are used only where $q$ is positive. Where $q$ is non-positive, 81 $r$ may have any value as these values are not used by the PDE solver. 82 83 To set the Dirichlet boundary conditions for the PDE to be solved in each time step we need 84 to add some statements; 85 \begin{python} 86 mypde=LinearPDE(rod) 87 A=zeros((2,2))) 88 A[0,0]=kappa 89 q=whereZero(x) 90 mypde.setValue(A=A, D=rhocp/h, q=q, r=T0) 91 \end{python} 92 It is important to remark here that the Dirichlet condition \textbf{overwrites} any Neuman boundary 93 condition \esc sets by default (or those defined by the user). 94 95 \begin{figure} 96 \begin{center} 97 \includegraphics[width=4in]{figures/ttrodpyplot150} 98 \caption{Example 2: Total Energy in the Iron Rod over Time (in seconds).} 99 \label{fig:onedheatout1 002} 100 \end{center} 101 \end{figure} 102 103 \begin{figure} 104 \begin{center} 105 \includegraphics[width=4in]{figures/rodpyplot001} 106 \includegraphics[width=4in]{figures/rodpyplot050} 107 \includegraphics[width=4in]{figures/rodpyplot200} 108 \caption{Example 2: Temperature ($T$) distribution in the iron rod at time steps $1$, $50$ and $200$.} 109 \label{fig:onedheatout 002} 110 \end{center} 111 \end{figure} 112 113 Besides some cosmetic modification this all we need to change. The total energy over time is shown in \reffig{fig:onedheatout1 002}. As heat 114 is transfered into the rod by the heater the total energy is growing over time but reaches a plateau 115 when the temperature is constant is the rod, see \reffig{fig:onedheatout 002}. 116 You will notice that the time scale of this model is several order of magnitudes faster than 117 for the granite rock problem due to the different length scale and material parameters. 118 In practice it can take a few models run before the right time scale has been chosen\footnote{An estimate of the 119 time scale for a diffusion problem is given by the formula $\frac{\rho c\hackscore{p} L\hackscore{0}^2}{4 \kappa}$, see 120 \url{http://en.wikipedia.org/wiki/Fick\%27s_laws_of_diffusion}}. 121 122 123 124 125 126 127 \section{For the Reader} 128 \begin{enumerate} 129 \item Move the boundary line between the two granite blocks to another part of the domain. 130 \item Split the domain into multiple granite blocks with varying temperatures. 131 \item Vary the mesh step size. Do you see a difference in the answers? What does happen with the compute time? 132 \item Insert an internal heat source (Hint: The internal heat source is given by $q\hackscore{H}$.) 133 \item Change the boundary condition for iron rod example such that the temperature 134 at the right end is kept at a constant level $T\hackscore{ref}$, which corresponds to the installation of a cooling element (Hint: Modify $q$ and $r$). 135 \end{enumerate} 136