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International Journal of Refrigeration

ISSN: 0140-7007

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Datasets associated with articles published in International Journal of Refrigeration

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1970
2025
1970 2025
16 results
  • Data for: Density and viscosity of a polyol ester lubricant: Measurement and molecular dynamics simulation
    Density and viscosity of pentaerythritol tetrahexanoate (PEC6) for 258 K to 373 K.
    • Dataset
  • Data for: Influence of the refrigerant charge in an R407C liquid-to-water heat pump for space heating and domestic hot water production
    The Excel file contains raw experimental data of 75 experiments. Measured parameters include: temperatures (T), gauge pressures (P), volumetric flow rates (V), compressor electric power (Welec) and atmopheric pressure. See Figure 1 of the paper for the numbering and position of the different sensors. See Table 1 of the paper for the types of sensors used and their accuracies.
    • Dataset
  • Data for: Computing Thermodynamic Properties of Ammonia-water Mixtures using Artificial Neural Networks
    Artificial Neural Network based MATLAB functions for computing thermodynamic properties of ammonia-water mixtures
    • Dataset
  • Data for: Application of the group contribution volume translated Peng-Robinson equation of state to new commercial refrigerant mixtures
    Supporting Information, including additional figures
    • Dataset
  • Data for: Performance analysis of a R407C liquid-to-water heat pump: effect of a liquid-vapor heat exchanger and domestic hot water production
    The Excel file contains raw experimental data of 64 experiments. Measure parameters include: temperatures (T), gauge pressures (P), volumetric flow rates (V), compressor electric power (Welec) and atmopheric pressure. See Figure 1 of the paper for the numbering and position of the different sensors. See Table 1 of the paper for the types of sensors used and their accuracies.
    • Dataset
  • Data for: An Empirical Model for Refrigerant Flammability Based on Molecular Structure and Thermodynamics
    The data files are: ASHRAE34_applications.csv ASHRAE Standard 34 existing agents, test data for refrigerant flammability FlameAngles.csv ASHRAE Standard 34 applications for new refrigerants, flammability data cantera_flammability.py A python script to run the calculations for Taft, F-ratio, and PI_bar outlined in the paper hfcmech_v13all.cti Thermodynamic database necessary to run the above calculations.
    • Dataset
  • Data set on "1D models of an active magnetic regeneration cycle for cryogenic applications"
    The is the data set for the paper [Diamantopoulos, T., Matteuzzi, T., & Bjørk, R., 1D models of an active magnetic regeneration cycle for cryogenic applications, International Journal of Refrigeration, 167, 246-256, 2024]. The DOI for the publication is 10.1016/j.ijrefrig.2024.08.011The data set consists of two zip-folders, each containing a folder structure, and a README file. The scripts to produce the figures in the paper are for Matlab, as is the data file format.`scripts` folder contains all the scripts that generate the plots that are shown in the publication. The respective directories path where the data are located are also mentioned. Namely: 1. `plot_figure_1_density_ratio.m` plots Fig.1 2. `plot_figure_3_material_properties.m` plots Fig.3 1. Parses the MFT generated files located at `data/validation/mft-properties` directory. 3. `plot_figures_4_5_validation.m` generates Fig. 4 and Fig. 5. 1. Parses the data located at `data/validation/results` directory generated by the solvers. 2. Parses the reference data (experimental and numerical) located at `data/validation/validation_data` directory. 3. Plots the mass flow rate and magnetization profiles using a MATLAB function located at the end of the plotting script. 4. `plot_figures_6_to_8_Gauss_19T.m` generates Figs. 6-8. 1. Parses the data located at `data/19T-profile/` directory generated by the solvers. 2. Plots the total magnetization field as well as the magnetization at various positions of the AMR using a MATLAB function located at the end of the plotting script. `data` folder contains all the pertinent data to the publication: 1. `/data/validation` folder contains all the files relevant to Section 5 of the paper 1. `/data/validation/mft-properties/` contains the files with the properties of the magnetocaloric materials used for the validation. 2. `/data/validation/validation_data/` contains the files which has the data stored from the experimental study of Park et al and Zheng et al shown in Figure 5 of the publication. 3. `/data/validation/results` contains the results of the simulations shown in Figure 5, namely the cooling power as a function of the temperature span for the two given mass flow rates reported in the publication. 1. `/data/validation/results/IMEX` results from the IMEX solver for two constant mass flow rates as reported in the paper and various temperature spans. 2. `/data/validation/results/LMN` results from the IMEX solver for two constant mass flow rates as reported in the paper and various temperature spans. 2. `/data/19T-profile` folder contains all the results pertinent to Section 6 of the publication: 1. `/data/19T-profile/density-profiles/` includes the data for generating Figure 8, namely density of the fluid as a function of location and time. 2. `/data/19T-profile/IMEX` includes the cooling power and COP and the mass flow rate for the IMEX solver used in Figure 7. 3. `/data/19T-profile/LMN` includes the cooling power and COP and the mass flow rate for the LMN solver used in Figure 7. 4. `/data/19T-profile/incompressible` includes the cooling power and COP and the mass flow rate for the incompressible solver used in Figure 7.
    • Dataset
  • Data set on "1D models of an active magnetic regeneration cycle for cryogenic applications"
    The is the data set for the paper [Diamantopoulos, T., Matteuzzi, T., & Bjørk, R., 1D models of an active magnetic regeneration cycle for cryogenic applications, International Journal of Refrigeration, 167, 246-256, 2024]. The DOI for the publication is 10.1016/j.ijrefrig.2024.08.011The data set consists of two zip-folders, each containing a folder structure, and a README file. The scripts to produce the figures in the paper are for Matlab, as is the data file format.`scripts` folder contains all the scripts that generate the plots that are shown in the publication. The respective directories path where the data are located are also mentioned. Namely: 1. `plot_figure_1_density_ratio.m` plots Fig.1 2. `plot_figure_3_material_properties.m` plots Fig.3 1. Parses the MFT generated files located at `data/validation/mft-properties` directory. 3. `plot_figures_4_5_validation.m` generates Fig. 4 and Fig. 5. 1. Parses the data located at `data/validation/results` directory generated by the solvers. 2. Parses the reference data (experimental and numerical) located at `data/validation/validation_data` directory. 3. Plots the mass flow rate and magnetization profiles using a MATLAB function located at the end of the plotting script. 4. `plot_figures_6_to_8_Gauss_19T.m` generates Figs. 6-8. 1. Parses the data located at `data/19T-profile/` directory generated by the solvers. 2. Plots the total magnetization field as well as the magnetization at various positions of the AMR using a MATLAB function located at the end of the plotting script. `data` folder contains all the pertinent data to the publication: 1. `/data/validation` folder contains all the files relevant to Section 5 of the paper 1. `/data/validation/mft-properties/` contains the files with the properties of the magnetocaloric materials used for the validation. 2. `/data/validation/validation_data/` contains the files which has the data stored from the experimental study of Park et al and Zheng et al shown in Figure 5 of the publication. 3. `/data/validation/results` contains the results of the simulations shown in Figure 5, namely the cooling power as a function of the temperature span for the two given mass flow rates reported in the publication. 1. `/data/validation/results/IMEX` results from the IMEX solver for two constant mass flow rates as reported in the paper and various temperature spans. 2. `/data/validation/results/LMN` results from the IMEX solver for two constant mass flow rates as reported in the paper and various temperature spans. 2. `/data/19T-profile` folder contains all the results pertinent to Section 6 of the publication: 1. `/data/19T-profile/density-profiles/` includes the data for generating Figure 8, namely density of the fluid as a function of location and time. 2. `/data/19T-profile/IMEX` includes the cooling power and COP and the mass flow rate for the IMEX solver used in Figure 7. 3. `/data/19T-profile/LMN` includes the cooling power and COP and the mass flow rate for the LMN solver used in Figure 7. 4. `/data/19T-profile/incompressible` includes the cooling power and COP and the mass flow rate for the incompressible solver used in Figure 7.
    • Dataset
  • Supporting data - Novel design of a high efficiency multi-bed active magnetic regenerator heat pump
    Supporting data for publication 'Novel design of a high efficiency multi-bed active magnetic regenerator heat pump" submitted to the International Journal of Refrigeration (DOI 10.1016/j.ijrefrig.2021.09.007) The videos show the operation of the novel magnetocaloric heat pump called the MagQueen, which has been developed by DTU Energy. The Excel sheet summarizes the experimental output parameters for the performance data presented in the publication. All data were measured continuously after reaching steady-state conditions, and the data were averaged over a time span of 600 s.
    • Video
  • Supporting data - Novel design of a high efficiency multi-bed active magnetic regenerator heat pump
    Supporting data for publication 'Novel design of a high efficiency multi-bed active magnetic regenerator heat pump" submitted to the International Journal of Refrigeration (DOI 10.1016/j.ijrefrig.2021.09.007) The videos show the operation of the novel magnetocaloric heat pump called the MagQueen, which has been developed by DTU Energy. The Excel sheet summarizes the experimental output parameters for the performance data presented in the publication. All data were measured continuously after reaching steady-state conditions, and the data were averaged over a time span of 600 s.
    • Video
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