Data underlying the paper: "Interactive Multi-Constrained System-to-Compartment Allocation to Support Real-Time Collaborative Complex Ship Layout Design Decision-Making"
Datacite citation style:
le Poole, Joan; Hopman, Hans; Kana, Austin; Duchateau, Etienne (2022): Data underlying the paper: "Interactive Multi-Constrained System-to-Compartment Allocation to Support Real-Time Collaborative Complex Ship Layout Design Decision-Making". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/20141636.v1
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Dataset
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version 2 - 2023-05-08 (latest)
version 1 - 2022-06-24
This data set comprises the data underlying the case study in the paper "Interactive Multi-Constrained System-to-Compartment Allocation to Support Real-Time Collaborative Complex Ship Layout Design Decision-Making", to be presented at the International Naval Engineering Conference and Exhibition (INEC 2022) .
Specifically, the data underlying the case studies is provided. For each case study, the Input is provided, consisting of a set of Systems, System Properties, Interactions, and Compartments. Also, the satisfaction of all design parameters for each developed concept design is provided.
history
- 2022-06-24 first online, published, posted
publisher
4TU.ResearchData
format
.csv, .txt
associated peer-reviewed publication
Interactive Multi-Constrained System-To-Compartment Allocation To Support Real-Time Collaborative Complex Ship Layout Design Decision-Making
organizations
TU Delft, Faculty Mechanical, Maritime and Materials Engineering 3mE, Department of Marine and Transport TechnologyDefence Materiel Organisation, Netherlands
DATA
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1ed53ae2aad3108da832858c2a98a1fa
Data_lePoole_INEC2022_v1.zip -
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