Dataset: Two Heat Pumps Simulation - Raw, 1000 Data Points (doi:10.18419/darus-3652)

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Part 2: Study Description
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Document Description

Citation

Title:

Dataset: Two Heat Pumps Simulation - Raw, 1000 Data Points

Identification Number:

doi:10.18419/darus-3652

Distributor:

DaRUS

Date of Distribution:

2023-09-06

Version:

1

Bibliographic Citation:

Pelzer, Julia, 2023, "Dataset: Two Heat Pumps Simulation - Raw, 1000 Data Points", https://doi.org/10.18419/darus-3652, DaRUS, V1

Study Description

Citation

Title:

Dataset: Two Heat Pumps Simulation - Raw, 1000 Data Points

Identification Number:

doi:10.18419/darus-3652

Authoring Entity:

Pelzer, Julia (Universität Stuttgart)

Grant Number:

EXC 2075 - 390740016

Distributor:

DaRUS

Access Authority:

Pelzer, Julia

Access Authority:

Schulte, Miriam

Depositor:

Pelzer, Julia

Date of Deposit:

2023-07-31

Holdings Information:

https://doi.org/10.18419/darus-3652

Study Scope

Keywords:

Computer and Information Science, Earth and Environmental Sciences, Open Loop, Groundwater, Heat Pump

Abstract:

This data set serves as training data for modelling the temperature field emanating from two groundwater heat pumps (one fixed, one randomly placed). It is simulated with Pflotran and saved in h5 format. It contains 1000 data points, each consisting of one simulation run until a near steady state is reached. Each datapoint measures 1250 m x 2560 m with 250 x 512 cells. The varying parameters of the data set are pressure and permeability. Both are constant within a data point, but vary across the data set. Other parameters that define the data set, such as porosity, are chosen to be as close as possible to reality. <br> Source: "Die hydraulischen Grundwasserverhältnisse des quartären und des oberflächennahen tertiären Grundwasserleiters im Großraum München", Geologica Bavarica Volume 122. <br> Generated with scripts from <a href="https://github.com/JuliaPelzer/Dataset-generation-with-Pflotran">Dataset generation with Pflotran</a> (commit 94daf52) with arguments given in inputs/args.yaml.

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

Related Publications

Citation

Title:

Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788.

Identification Number:

10.1016/j.geoen.2024.212788

Bibliographic Citation:

Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788.

Other Study-Related Materials

Label:

args.yaml

Notes:

application/x-yaml

Other Study-Related Materials

Label:

dataset_2hps_1fixed_1000dp.zip

Notes:

application/zip