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@ -47,6 +47,17 @@ f(1,0,0) & = & 1\\
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\text{otherwise }f(\_,\_,\_) & = & 0
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\end{eqnarray*}
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\begin{figure}[H]
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\includegraphics[scale=0.55]{plots}
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\centering
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\captionsetup{width=0.80\textwidth}
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\caption{Plots of the execution of the cellular automata with the different
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updating methods. From top-left to top-right: Synchronous, Random
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Independent, Random Order. From bottom-left to bottom-right: Clocked,
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Cyclic, Self-Synchronous}
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\label{fig:plot}
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\end{figure}
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\subsection*{Why do different patterns appear with different update
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rules?}\label{why-do-different-patterns-appear-with-different-update-rules}
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@ -83,7 +94,7 @@ Independent method allows any cell to be updated at any time
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models is to scan through an array updating each cell in turn, based on
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the current values of its neighbours. Which of the update schemes
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demonstrated corresponds to
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this?}\label{a-common-mistake-in-writing-programs-to-run-simulation-models-is-to-scan-through-an-array-updating-each-cell-in-turn-based-on-the-current-values-of-its-neighbours.-which-of-the-update-schemes-demonstrated-corresponds-to-this}
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this?}
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The cycle option corresponds to updating each cell based on the current
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state of its neighbours. This can be verified by looking at the pattern
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@ -98,11 +109,16 @@ possible rules being active i.e.
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\subsection*{Suggest cases where the clock scheme or random asynchronous
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updating might bean appropriate way to model a system in the real
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world?}\label{suggest-cases-where-the-clock-scheme-or-random-asynchronous-updating-might-bean-appropriate-way-to-model-a-system-in-the-real-world}
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world?}
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In cases where we are modelling systems over continuous time, then the
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clock scheme or random asynchronous updating would be appropriate to
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use. These might be systems like
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use. An advantage of these schemes compared to the other schemes is
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that they allow for more complex agents as not all agents are updated
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at every step. This means that many multi-agent systems would probably
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use such a scheme. A well known example of this would be ``Boids'', a
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simulation of flocking birds where every bird is evaluated as a separate
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agent.
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\section{Sensitivity analysis - critical mass in a
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nuclear}\label{sensitivity-analysis---critical-mass-in-a-nuclear}
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@ -115,12 +131,20 @@ simulate the system at varying densities between 0\% and 20\% and use
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the graphs showing the energy released from the system over time to
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gauge how where the runaway reaction occurs.
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\begin{figure}[H]
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\includegraphics[scale=0.70]{plots2}
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\centering
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\captionsetup{width=0.80\textwidth}
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\caption{Plots of energy released over time. Each plot corresponds a
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different density: 0\%, 5\%, 8\%, 10\%, 11\%, 12\%, 13\%, 15\%, 17\% and 20\%}
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\label{fig:plot2}
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\end{figure}
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We take measurements of the energy released at densities of 0\%, 5\%,
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8\%, 10\%, 11\%, 12\%, 13\%, 15\%, 17\% and 20\%, sampling at shorter
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intervals of density closer to the density at which the maximum reading
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of the energy released exceeds 10 .
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of the energy released exceeds 10.
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This breakout first happens at 12, and so we deem this to be the
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critical density of the system.
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\\
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We found that the hightest desity for which no breakouts occur is at
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10\%. We thus deem this to be the critical density of the system.
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\end{document}
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