The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/fa8a2ec4-7022-492c-852a-20a6bee61bcd

Tan, Michael; Ibarra-Gonzalez, Paola; Nikolic, Igor; Ramirez Ramirez, Andrea (2024): Petrochemical cluster analysis tool. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/fa8a2ec4-7022-492c-852a-20a6bee61bcd.v1

Software

• Environmental Engineering
• Chemical Engineering
• Engineering

Complex networks, Industrial cluster, Industrial ecology, Key performance indicators, Petrochemical cluster

BSD-3-Clause

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Michael Tan , Paola Ibarra-Gonzalez , Igor Nikolic , Andrea Ramirez Ramirez

Petcluster Python module combines complex network and key performance indicators to assess petrochemical clusters.

• 2024-09-03 first online, published, posted

4TU.ResearchData

.py

Understanding the Level of Integration in Existing Chemical Clusters: Case Study in the Port of Rotterdam

• http://www.tudelft.nl/innovatie-impact/project-cases/unravelling-the-impact-of-using-alternative-raw-materials-in-industrial-clusters

• NWO VICI Grant (grant code VI.C.183.010) [more info...] NWO

TU Delft, Faculty of Technology, Policy and Management, Department of Engineering, Systems and Services, Section of Energy and Industry
TU Delft, Faculty of Technology, Policy and Management, Department of Multi Actor Systems, Section of System Engineering
TU Delft, Faculty of Applied Sciences, Department of Chemical Engineering