Extending the Capabilities of the Mooring Analysis Program: A Survey of Dynamic Mooring Line Theories for Integration into FAST

Marco Masciola, Jason Jonkman, Amy Robertson

Research output: Contribution to conferencePaperpeer-review

24 Scopus Citations

Abstract

Techniques to model dynamic mooring lines take various forms. The most widely used models include a heuristic representation of the physics (such as a lumped-mass system), a finite-element analysis discretization of the lines (discretized in space), or a finite-difference model (which is discretized in both space and time). In this paper, the authors explore the features of the various models, weigh the advantages of each, and propose a plan for implementing one dynamic mooring line model into the open-source Mooring Analysis Program (MAP). MAP is currently used as a module for the FAST offshore wind turbine computer-aided engineering (CAE) tool to model mooring systems quasi-statically, although dynamic mooring capabilities are desired. Based on the exploration in this paper, the lumped-mass representation is selected for implementation in MAP based on its simplicity, low computational cost, and ability to provide physics similar to those captured by higher-order models. To begin, the underlying theories defining the three classes of dynamic mooring line models are identified and explored. This leads to insight into the capabilities of each representation. These capabilities are weighed against the current needs of the FAST wind turbine CAE tool, to which MAP will be coupled. Based on the assessment, a plan for integrating the dynamic mooring line theory into the current MAP structure is developed. Common problems arising from the determination of the model static equilibrium and known issues with numerical stability are addressed. Because MAP is a module that FAST can call, a plan consistent with the FAST modularization framework principles is described. Adding dynamic mooring line capabilities extends the features in MAP and also allows uncoupled analysis to be performed through MAP's native Python bindings.

Original languageAmerican English
Number of pages13
DOIs
StatePublished - 2014
EventASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2014 - San Francisco, United States
Duration: 8 Jun 201413 Jun 2014

Conference

ConferenceASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2014
Country/TerritoryUnited States
CitySan Francisco
Period8/06/1413/06/14

Bibliographical note

See NREL/CP-5000-61159 for preprint

NREL Publication Number

  • NREL/CP-5000-63514

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