From 204397f16ad5012245411d65783607f1a83f1a32 Mon Sep 17 00:00:00 2001 From: Lukas Winkler Date: Thu, 19 Sep 2019 16:51:10 +0200 Subject: [PATCH] abstract --- 10_introduction.tex | 8 ++------ 20_simulations.tex | 2 +- 41_griddata.tex | 2 +- template.tex | 2 +- 4 files changed, 5 insertions(+), 9 deletions(-) diff --git a/10_introduction.tex b/10_introduction.tex index 2c4ebd5..164ed28 100644 --- a/10_introduction.tex +++ b/10_introduction.tex @@ -2,15 +2,11 @@ \addchap{Abstract} - -Quos est voluptatem officiis animi et aliquid natus deserunt ad omnis perspiciatis voluptatum quas non natus sint molestiae minima officiis porro dolorem temporibus est non porro aut velit corrupti nostrum numquam facilis cupiditate esse sit quibusdam autem eum non dolores eum at in necessitatibus aliquid rerum voluptatum necessitatibus aut officia voluptates consequatur voluptatem nobis corporis quod nostrum et tempore placeat minima corrupti. - -Autem animi consequatur delectus mollitia. Earum nesciunt distinctio et quam nam libero. Illum deserunt non voluptatem. Dolores quas qui aspernatur maxime reprehenderit repellat porro aliquam.% +To get a closer estimate on how much water remains after the collision of two protoplanets or asteroids covered in water, a total of 1375 SPH simulations have been conducted. Six parameters like impact velocity, angle and mass have been varied between the simulations to give estimations for many possible collision scenarios. To interpolate the resulting water retention fraction for collisions in between the simulations, the three methods gridbased linear interpolations, Radial Basis Functions and Artificial Neural Networks have been used. This allows to predict the remaining water for arbitrary collisions within the simulated parameter range. {\let\clearpage\relax \chapter{Introduction}\label{introduction}} -One important question for planet formation is, how water got to the earth. The part of the protoplanetary disk closest to the sun was too hot to make it possible that water can condense on Earth during formation. And while there are theories that the region where ice is possible inside the snow-line moved during Earth's formation\footcite{snowline}, the most popular theory is that water moved inwards in the solar system through collisions of water-rich proto-planets.% -\todo{citation needed} +One important question for planet formation is, how water got to the earth. The part of the protoplanetary disk closest to the sun was too hot to make it possible that water can condense on Earth during formation. And while there are theories that the region where ice is possible inside the snow-line moved during Earth's formation\footcite{snowline}, the most popular theory is that water moved inwards in the solar system through collisions of water-rich proto-planets. %\section{The perfect merging assumption} diff --git a/20_simulations.tex b/20_simulations.tex index ebc3b14..169be52 100644 --- a/20_simulations.tex +++ b/20_simulations.tex @@ -48,7 +48,7 @@ The last two parameters are the mass fraction of the ice to the total mass of ea \label{tab:first_simulation_parameters} \end{table} -\section{Execution}\todo{think of a better title} +\section{Execution} In the first simulation run for every parameter combination from Table \ref{tab:first_simulation_parameters} a separate simulation has been started. First, the parameters and other configuration options are written in a \mbox{\texttt{simulation.input}} text file. Afterwards the relaxation program described in \cite[24\psqq]{Burger2018} generates relaxed initial conditions for all 20k particles and saves their state to \texttt{impact.0000}. Finally, \texttt{miluphcuda} can be executed with the following arguments to simulate starting from this initial condition for 300 timesteps which each will be saved in a \texttt{impact.XXXX} file. diff --git a/41_griddata.tex b/41_griddata.tex index 58bb83f..27a0c33 100644 --- a/41_griddata.tex +++ b/41_griddata.tex @@ -60,7 +60,7 @@ For doing the actual interpolations, the \texttt{scipy.interpolate.griddata} fun \subsection{Results} -Most notable about the results of the griddata interpolation (see Figure \ref{fig:griddataresults}\todo{text}) are the many fine details that can be seen. This is mostly caused by the fact that this method only uses the closest values for interpolations and therefore there is no smoothing. These details might just be random derivations of the simulation and not a higher resolution of the data. Another thing that can be seen in the bottom right corner of Figure \ref{fig:griddata1} is that griddata can't extrapolate data. +Most notable about the results of the griddata interpolation (see Figure \ref{fig:griddataresults}) are the many fine details that can be seen. This is mostly caused by the fact that this method only uses the closest values for interpolations and therefore there is no smoothing. These details might just be random derivations of the simulation and not a higher resolution of the data. Another thing that can be seen in the bottom right corner of Figure \ref{fig:griddata1} is that griddata can't extrapolate data. \begin{figure}[h!] % also temporary \centering diff --git a/template.tex b/template.tex index a73796a..9699a68 100644 --- a/template.tex +++ b/template.tex @@ -59,7 +59,7 @@ american, % language of the document \usepackage{subcaption} % allows to nicely put two images next to each other \usepackage{tabularx} \usepackage{booktabs} % nicer table seperations -\usepackage{todonotes} +%\usepackage{todonotes} \usepackage{pgf}