Replication Data for: Exploring the Predictive Potential of Sequential Data in Concrete Manufacturing

DOI

Addendum to the corresponding paper. The paper explores the predictive potential of sequential data of a mixing plant regarding fresh concrete characteristics.

The data was synthetically generated and takes into account the specific concrete mix proportions and their effect on the mixing power consumption as well as the slump flow value. The set contain 500 samples.

The data set includes: torque_x: A series of 90 time-steps reflecting the mixing power consumption from start until end of mixing. One value per time-step. water, cement, filler, gravel: (content of given mix constituents) slump flow value: The slump flow value based on the mix proportion as well as the power consumption in mixing stage VI

Identifier
DOI https://doi.org/10.18419/DARUS-4780
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-4780
Provenance
Creator Teichmann, Alexander ORCID logo
Publisher DaRUS
Contributor Teichmann, Alexander; IntCDC RDM
Publication Year 2025
Funding Reference DFG EXC 2120/1 - 390831618
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Teichmann, Alexander (University of Stuttgart); IntCDC RDM (University of Stuttgart)
Representation
Resource Type Dataset
Format text/tab-separated-values
Size 852444
Version 1.0
Discipline Construction Engineering and Architecture; Engineering; Engineering Sciences