SoftwareApplication
name: Data and code underlying Chapter 4 of the PhD thesis "Advanced Magnetocaloric Regenerators for Heat Pump Applications"
description: Data and code underlying Chapter 4 of the PhD thesis "Advanced Magnetocaloric Regenerators for Heat Pump Applications"
description: This dataset contains the results of numerical simulations performed to estimate the seasonal coefficient of performance (SCOP) of a magnetocaloric heat pump for the built environment. The SCOP is estimated based on the heating demand of a well-insulated house in the Netherlands. These results were published in the International Journal of Refrigeration 164 (2024) 38-48. The simulations were performed using a one-dimensional numerical model of an AMR implemented in Python.
code repository: https://data.4tu.nl/v3/datasets/042da9ba-6fe8-414f-9c40-1a152e831867.git
author: https://orcid.org/0009-0000-2848-8923
author: Person
  given name: Beatriz
  family name: Fonseca Lima
  name: Beatriz Fonseca Lima
author: Person
  given name: Carlos A.
  family name: Infante Ferreira
  name: Carlos A. Infante Ferreira
author: Person
  given name: Ekkes
  family name: Brück
  name: Ekkes Brück
keywords: numerical simulation
keywords: active magnetocaloric regenerator
keywords: layered AMR
keywords: python
keywords: seasonal COP
keywords: MnFePSi
keywords: one-dimensional AMR model
keywords: magnetocaloric heat pump
programming language: Other
programming language: Python
license:
  creative work: creativeWork
    name: CC-BY-4.0
reference publication: j.ijrefrig.2024.04.014

https://orcid.org/0009-0000-2848-8923
type: Person
given name: Diego
family name: Pineda Quijano
name: Diego Pineda Quijano

j.ijrefrig.2024.04.014
type: ScholarlyArticle
name: Seasonal COP of a residential magnetocaloric heat pump based on MnFePSi
pagination: 38-48
url: https://doi.org/10.1016%2Fj.ijrefrig.2024.04.014