Data for integrated offshore driveability and noise prediction modelling (COAX)

Publieke samenvatting / Public summary

Aanleiding
The objective of the COAX project is to collect advanced offshore pile driving data together with the associated data on underwater noise emission and seabed vibrations with the aim to assist in the further reduction of the uncertainties in the prediction of driveability and the relation between vibratory driving (vibro-piling) performance and offshore underwater noise levels and frequency spectrum.

Doelstelling
The objective of COAX is to accelerate the introduction of the Vibratory Pile driving method. To achieve this goal we need to better understand the driveability and extraction of the monopile, the noise emission mechanisms, and the correlation between pile driving parameters, pile, and soil response, and underwater noise. The vibratory installation method produces much lower peak noise levels in typical Dutch North Sea conditions and should be able to install piles faster compared to the traditional impact hammer method.

Korte omschrijving
- Design and build of near field vertical hydrophone array for detailed near source noise measurements; - Design, supply and build of advanced pile, vibro, and crane instrumentation for measuring stress and deformations; - Execution of actual pile driving tests offshore; - Execution of acoustic measurements and measurements of pile stress and deformations; - Data handling, analysis, and interpretation.

Resultaat
- A high-quality time domain coupled data set enabling correlation between pile driving parameters, pile response, seabed vibrations, and underwater noise emission; - Measurements of underwater noise generated during pile extraction - Enable the validation of integrated models for underwater noise prediction that account for pile driving parameters (e.g. type of vibration tool, frequency, amplitude, etc.), soil properties and stratigraphy, water depth, etc. This work will be done in Work Packages 3B, 3C, and 3E of the SIMOX project and the data will be available for any future result to further improve these models as required.