DOI: 10.18419/darus-4143
title: Replication Data for: Rayleigh invariance allows the estimation of effective CO2 fluxes due to convective dissolution into water-filled fractures

description: This dataset features both data and code related to the research article titled "Rayleigh Invariance Enables Estimation of Effective CO2 Fluxes Resulting from Convective Dissolution in Water-Filled Fractures." It includes raw data packaged in tarball format, including Python scripts used to derive the results presented in the publication. High-resolution raw data for contour plots is available upon request.&lt;br&gt;
&lt;div class="box"&gt;
 &lt;div class="number"&gt;1&lt;/div&gt;
 &lt;strong&gt;Download the Dataset:&lt;/strong&gt;
 &lt;ul&gt;
 &lt;li&gt;Download the dataset file using Access Dataset.&lt;/li&gt;
 &lt;li&gt;Ensure you have sufficient disk space available for storing and processing the dataset.&lt;/li&gt;
 &lt;/ul&gt;
&lt;/div&gt;
&lt;div class="box"&gt;
 &lt;div class="number"&gt;2&lt;/div&gt;
 &lt;strong&gt;Extract the Dataset:&lt;/strong&gt;
 &lt;ul&gt;
 &lt;li&gt;Once the dataset file is downloaded, extract its contents.&lt;/li&gt;
 &lt;li&gt;The dataset is compressed in a tar.xz format. Use appropriate tools to extract it. For example, in Linux, you can use the following command:
 &lt;pre&gt;&lt;code&gt;tar -xf Publication_CCS.tar.xz&lt;/code&gt;&lt;/pre&gt;
 &lt;pre&gt;&lt;code&gt;tar -xf Publication_Karst.tar.xz&lt;/code&gt;&lt;/pre&gt;
 &lt;pre&gt;&lt;code&gt;tar -xf Validation_Sim.tar.xz&lt;/code&gt;&lt;/pre&gt;
 &lt;/li&gt;
 &lt;li&gt;This will create a directory containing the dataset files.&lt;/li&gt;
 &lt;/ul&gt;
&lt;/div&gt;

&lt;div class="box"&gt;
 &lt;div class="number"&gt;3&lt;/div&gt;
 &lt;strong&gt;Install Required Python Packages:&lt;/strong&gt;
 &lt;ul&gt;
 &lt;li&gt;Before running any code, ensure you have the necessary Python (version 3.10 tested) packages installed. The required packages and their versions are listed in the &lt;code&gt;requirements.txt&lt;/code&gt; file.&lt;/li&gt;
 &lt;li&gt;You can install the required packages using pip:
 &lt;pre&gt;&lt;code&gt;pip install -r requirements.txt&lt;/code&gt;&lt;/pre&gt;
 &lt;/li&gt;
 &lt;/ul&gt;
&lt;/div&gt;

&lt;div class="box"&gt;
 &lt;div class="number"&gt;4&lt;/div&gt;
 &lt;strong&gt;Run the Post Processing Script:&lt;/strong&gt;
 &lt;ul&gt;
 &lt;li&gt;After extracting the dataset and installing the required Python packages, you can run the provided post processing script.&lt;/li&gt;
 &lt;li&gt;The post processing script (&lt;code&gt;post_process.py&lt;/code&gt;) is designed to replicate all the plots from a publication based on the dataset.&lt;/li&gt;
 &lt;li&gt;Execute the script using Python:
 &lt;pre&gt;&lt;code&gt;python3 post_process.py&lt;/code&gt;&lt;/pre&gt;
 &lt;/li&gt;
 &lt;li&gt;This script will generate the plots and output them to the specified directory.&lt;/li&gt;
 &lt;/ul&gt;
&lt;/div&gt;

&lt;div class="box"&gt;
 &lt;div class="number"&gt;5&lt;/div&gt;
 &lt;strong&gt;Explore and Analyze:&lt;/strong&gt;
 &lt;ul&gt;
 &lt;li&gt;Once the script has completed running, you can explore the generated plots to gain insights from the dataset.&lt;/li&gt;
 &lt;li&gt;Feel free to modify the script or use the dataset in your own analysis and experiments.&lt;/li&gt;
&lt;li&gt;High-resolution data, such as the vtu's for contour plots is available upon request; please feel free to reach out if needed.&lt;/li&gt;
 &lt;/ul&gt;
&lt;/div&gt;

&lt;div class="box"&gt;
 &lt;div class="number"&gt;6&lt;/div&gt;
 &lt;strong&gt;Small Grid Study:&lt;/strong&gt;
 &lt;ul&gt;
 &lt;li&gt;There is a tarball for the data that was generated to study the grid used in the related publication.&lt;/li&gt;
&lt;pre&gt;&lt;code&gt;tar -xf Publication_CCS.tar.xz&lt;/code&gt;&lt;/pre&gt;
 &lt;li&gt;If you unpack the tarball and have the requirements from above installed, you can use the python script to generate the plots.&lt;/li&gt;
 &lt;/ul&gt;
&lt;/div&gt;

&lt;div class="box"&gt;
 &lt;div class="number"&gt;7&lt;/div&gt;
 &lt;strong&gt;Citation:&lt;/strong&gt;
 &lt;ul&gt;
 &lt;li&gt;If you use this dataset in your research or publication, please cite the original source appropriately to give credit to the authors and contributors.&lt;/li&gt;
 &lt;/ul&gt;
&lt;/div&gt;