A parametric decision model for navigational lock components
With the Prinses Marijkesluizen as case study
B. Dudink (TU Delft - Civil Engineering & Geosciences)
Bas Jonkman – Mentor
M.Z. Voorendt – Mentor
E.J. Houwing – Mentor
R. Abspoel – Mentor
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Abstract
More than 50 locks owned by Rijkswaterstaat need replacement or renovation in the coming 40 years. Due to this fact an opportunity for changing the traditional way of building and maintaining navigational locks has arisen. Because of the replacement/renovation of locks in the coming time, implementing a new owning and building strategy is relatively easy. Rijkswaterstaat is interested in how standardization could be applied to (some) lock components to save costs, and increase reliability and availability.
The lock gates are the lock components with the highest potential for standardization. A parametric model for several lock gates is made in order to compare these gate types for a range of boundary conditions. The comparison of several gate types which can be made by the parametric model, could lead to a prescription of a standard gate type for specific boundary conditions. With this prescription, standardization could be implemented in the design process for navigational lock gates. The parametric model can also be used to assess the impact of design choices on the standard design. A parametric model is made to assess rolling gates and mitre gates (with and without clearance at the pivots) made in steel. The model has led to a way of optimising one design (in terms of steel volume used) per gate type for these gates for a range of boundary conditions. The model is able to prescribe a gate type for the case study used, the Prinses Marijkesluizen. The model is unable to prescribe a gate type for bilateral retaining gates, since the results of the design are too close to each other to prescribe one variant as the best variant. It is recommended to record more data, since costs can be added as optimisation criteria (instead of material volume) when this data is known.