Trans RINA, Vol 152, Part B1, Intl J Small Craft Tech, 2010 Jan-Jun discrete planes through the flow domain. By its very


nature a CFD simulation predicts quantities at each point in the flow domain and therefore avoids the need for plane traversing or multiple experiments. Additionally CFD can provide flow predictions within enclosed regions


where access to permit experimental


measurements may be impractical. 3.2 (c) Elimination of Scale Effects


Compared to the wind tunnel environment, the CFD model may consider the performance of the superstructure at full scale. Therefore, the complexities and challenges of scaling flow speeds and thermal effects in the wind tunnel are removed. Additionally, there is negligible difference between the mesh resolution required to model at either full scale or model scale.


3.2 (d) Prediction of Multiple Variables


Finally, with little additional effort a CFD model can readily be configured to simultaneously predict velocity fluctuations, exhaust


use of tracer gases to examine dispersion


performance. 3.2 (e) Turbulence Modelling


One of the key challenges to CFD modelling is the representation of turbulence. The most common approach for capturing turbulence with CFD simulations is to separate


each flow quantity into mean and


fluctuating components and to solve the Navier-Stokes equations for the mean components. This is termed the Reynolds Averaged Navier Stokes approach (RANS).


An artefact of the decomposition of flow variables into mean and fluctuating components is that


unknown terms are introduced into the system of equations to be solved. equations


unknown terms based on the mean flow conditions. There are a number


is it necessary of


different turbulence models


available, which have been developed and validated for a range of different flow scenarios.


Whilst no one turbulence model has been developed which covers


every conceivable flow scenario, the


experience and expertise of the CFD analyst is used to determine which model is most appropriate for the modelling of super yacht airwake based on features of the yacht and the physics to be considered.


The result of the simulation is a direct steady-state solution of the flow field, including a prediction of local turbulence levels which may be manipulated to derive the standard deviation of vertical velocity as required by both CAP437 and LY2.


Compared to experimental


In order to close the system of to model the additional


additional gas dispersion and plume


behaviour. This alleviates the requirement for multiple individual experiments tailored for each assessment and the


testing, there is no requirement to capture a sufficient number of velocity measurements at each location to derive meaningful


statistics in relation to local


fluctuations. 3.2 (f) Data Storage


An often forgotten but important benefit of CFD analysis is that the models and associated data are permanently stored in electronic format. This readily permits the simulation of new scenarios from old model files and/or the re-interrogation of results to examine new flow variables.


3.3 RELATIVE MERITS OF MODELLING AND EXPERIMENT


The discussion presented in Sections 3.1 and 3.2 has indicated the testing


challenges of external presented by aerodynamics and the


experimental potential


benefits offered by computer methods of prediction.


Given the differences between these two routes of assessment, one question commonly asked is which is the best method for airwake analysis.


In terms of timescales


and cost effectiveness, CFD modelling is favoured over testing as analyses are quick to run and modifications to superstructure design and ventilation location can be assessed with relative ease.


In terms of the accuracy there is an argument that experimental testing assumptions


representative results. However, it is noted that experimental


and therefore should testing is


does not require modelling provide more


itself prone to scale induced


uncertainties, measurement error and the invasive nature of some techniques.


The decision to use experimental testing or computer modelling is largely informed by the stage of the design process. At the bid stage the relatively quick turnaround of CFD modelling affords substantial risk reduction in design by allowing the comparison of different concepts and iteration towards an optimum design. Whilst in theory such a design study could be conducted within the wind tunnel environment, the requirement to construct multiple test pieces would be prohibitively expensive and time consuming.


4. EXAMPLE CFD ASSESSMENT 4.1


YACHT GEOMETRY


This section presents the results of an example CFD calculation for a generic 93m super yacht. Whilst the geometry is not based on a specific yacht


it exhibits


many of the characteristic features typical of modern design. e.g.. multiple decks and a mast. The helideck is situated on the upper most deck, aft of the bridge and mast, and has a width of approximately 12m, which


B-26


©2010: The Royal Institution of Naval Architects


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