Investigating Surfboard Design with CFD and Design of Experiments

The development of surfboards is a traditional and artisan process. Slowly throughout history surfboard designers have lent on technical engineering advancement to iteratively improve the performance capabilities of the crafts. Within the modern surfboard industry, differences in surfboard designs can be very small, and the impact these slight differences have on the behaviour of the board is mostly based on empirical knowledge and practical trail-and-error testing. However, for a small industry trail-and-error development is a costly endeavour, not to mentions it’s impact on the natural environment. CFD presents the opportunity for this industry to assess these minute adjustment and unconventional concepts through a consistent and quantitative platform which allows for unique insights into surfboard design. In this article the intricacies of some of the major surfboard design elements are evaluated. The main goal is to assess the potential of augmenting the current surfboard development process with even simplified simulation setups. For a detailed report of the project, an extended discussion is include within the PhD thesis by Sam Crameri

Investigating Surfboard Design Elements using Computational Fluid Dynamics and Design of Experiments

Introduction to planing phenomenon and airfoil equivalencies

When simplified to its most basic form, a surfboard is what is known as a “planning” body. The most basic definition of planning a thin, flat plate moving along a fluid surface at speed and pitch angle which results in the lift force fully supporting the weight of the plate.

A representation of a planning flat plate cross-section.

Naval hydrodynamicists have been investigating planing phenomena for many years, well before access to computational support. Planning is an extremely complicated behaviour to analyse and there have been several obstacles in solving these problems. One of the key problems is the wash or wake which is pushed in front of the plate as it introduces instability with the flow which reaches the object. This creates what is known as “porpoising” of planing craft, when the object appears to bounce on the bow wave it creates. For further details of planning complexities see Mancini’s comprehensive validation study in their thesis [1]. To overcome these challenges, some research concludes the approximation of planing behaviour through airfoil analysis is suitable for engineering applications where theoretical or experimental analysis has yet to be conducted. The pressure distribution of a planing surface is similar to that of an equivalent fully immersed airfoil, with the comparison most similar at low pitch angle. Because the surfboard shape is comparable to that of a flat plate, surfboard comparative analysis can be completed using NablaFlow’s AeroCloud platform.

Understanding fluid dynamics and its relation to surfing performance analysis

Surfboard motion is largely governed by force equilibriums. In simplified terms, the surfers weight force, is in balance with the lift and drag forces acting on the surfboard. To understand the fundamentals of this relationship, a look at the sequential events which cause rudimentary surfboard motion is needed.

1. The initial stage is a stable central position. This position is surfing is called “trimming”. The surfer stands in a single spot and moves along with the wave at a consistent speed and pitch angle. For a balance position the forces either side of the board origin (BO) axes create moments acting on the axis which are equal and opposite, maintaining the equilibrium.

A surfer in a stable position, and the indicative pressure distribution for a given pitch angle.

2. As the surfer shifts their mass, they initiate board rotation by creating an imbalance in the moment equilibrium. The board force act as a counter moment to this shift, naturally felt by the surfer as the limit to how far they can move before the equilibrium collapse. Should the surfer shift rapidly or too far the board cannot produce the necessary counterbalance and they fall. This is an example as to how a board can be designed based on simulation data.

3. In this example, we will only consider a shift forward along the x-axis. Shifting COG forward decreases the pitch angle, which in turn lessens the displaced water and reduces the lift and drag forces acting on the board. This case is shown below.

A surfer moving forward and the pressure distribution on the board for a lowered pitch angle.

4. If this occurs at the top of the wave, the reduced drag allows the surfer to fall from the top of the wave, accelerating from gravity and the steepness of the wave. As the board accelerates the forces increases, allowing the surfer improved control over the board. Higher forces are utilised to initiate turns as these counter moments allow for wider shifts in COG.
5. However, there is a trade-off to consider. As the surfer drops from the wave and reaches flat water the acceleration from gravity finishes and the board drag decelerates the surfer. As the surfer slows the balancing moments from the board also drop. With a lack of counter-moments the board becomes increasingly unstable. This is an explanation of why beginners often struggle when surfing on flat water. Without sufficient velocity, the board lacks the resisting force necessary to support their balance.

Even investigating a single simplified surfing scenario, it becomes apparent the lift and drag a board induces has significant performance implications. As the understanding of surfing physics improves, supporting surfboard prototyping via section analysis of forces is a viable approach. Allowing for simple interpretation of results, and the ability to highlight areas of interest on board designs for deeper comparison for both board designers and surfers who may not have familiarity with CFD outputs. In the following analysis the board is sectioned into quarter length spans (Nose, Front-Core, Back-Core and Tail), however for more fidelity a greater number of sections can be analysed.

The design elements of a surfboard.

The rapidly expanding intricacies of surfboard design has led to the adaption of various specifications and dimensions for the shape of a surfboard. Those included in this analysis are in the table below.

Element	Code	Factor	Low Level (-)	Centre (0)	High Level (+)
Tail Rocker	TR	A	20mm	40mm	60mm
Tail Shape	TS	B	Square	n/a	Rounded
Single Concave	SC	C	0mm	3mm	6mm
Rail Shape	RS	D	Hard	n/a	Boxy
Wide Point	WP	E	- 100 mm	0 mm	+ 100 mm
Width	W	F	440mm	470mm	500mm

These variables are not the only design elements for surfboards. However, they are referenced the most when shapers describe a surfboard’s on-wave performance. For some parameters included in this study, there are other categorical design options that are more complex in shape (i.e., for concave: single, double, channels, v-hull). As screening designs are applied best with numerical variables, a single concave was chosen because it is the simplest variation for CAD modelling. Surfboard design is likely limited only to what is possible to manufacture; therefore, the ranges for the numerical parameters were selected through a review of high-performance shortboard surfboards on the market. The levels of the categorical variables were chosen to reflect two of the common options that are said to have opposite performance benefits.

The advantages of Design of Experiments (DOE)

Design of Experiments (DOE) is a statistical tool for analysing problems with multiple factors. DOE methods design systematic experiments for the factors defined and identifies the factor with the most significant impacts on the outputs and identifies whether the combination effects of the main factors are also significant. A combination effect is if factor A is at the high or low level does the significance of factor B change. In this analysis 36 different surfboard designs with a mix of the high and low level of the factors were simulated under the same condition. With many simulations required the benefits of using the Aerocloud platform was shown. The easy uploading of .stl models and storage of data meant each design was able to be tracked throughout process. It also provided us with the confidence that each simulation had a consistent meshing and initialisation procedures, minimising the error across each run. Furthermore, access to cloud-based computational resources allowed the 36 simulations to be completed within a day of uploading, a dramatic reduction in the delay of the project. Lastly, the ability to download a summary of results as well as the simulation files was surprisingly handy. Of course, the simulation files are important for deeper analysis and custom post processing, but the summary allows for a quick assessment of the results. For this project the summaries allowed us to identify a modelling error on the fins for one of the CAD models uploaded. This instant feedback meant we could fix the issue, reupload and finish the simulation, all while continuing the post processing of the successful results.

A comparison of the two extremes of the board designs simulations, top: Board 1 – all low level factors, bottom: Board 32 – all high level factors.

Main effects and implications on performance.

The key results from the screening study are the Pareto charts and main effect plots shown below. These charts display the hierarchy of importance and the nature of the main effect of each factor in the surfboard section. One of these is given for each force (lift and drag) and each section of the board, resulting in 8 graphs for each (16 total), for this short summary only a selection is shown to showcase the advantages of DOE analysis.

From these plots the comparisons of note are highlighted. Of the main effects for both lift and drag, Tail Rocker was always among the 3 most significant factors, being the most significant factor for lift in every section. This result supports the conclusion found in initial case studies from Oggiano and Pierella [2], as well as the current knowledge developed by industry shapers formed from many years of design trials with professional surfers [3]. Below is a comparison of two board with variations in tail rocker.

Visualisation of differences in Tail Rocker, where: a. Top: high TR and Bottom: low TR. b. Right: high TR and Left low TR.

Both high- and low-tail rockers provide effects that can be desirable for specific surfing situations, with a low-tail rocker indicating greater acceleration (as drag is decreased) and a high-tail rocker improving stability (high lift negative lift values). Other significant main effects were the effect of width and wide point on the core sections of the board and tail shape on the tail. A comparison of width effect on trailing vortices is shown below.

Visualisation of differences in Width, where: a. Top: Low Width and Bottom: High Width. b. Right: Low Width and Left High Width.

Conclusion There are many more results to discuss from this project. Although, overall CFD and DOE is an effective and efficient research tool for surfboard design, as the results aligned with the current empirical understanding of surf design elements and preliminary CFD studies on the topic. The use of AeroCloud provided so many benefits to the project in both confidence in the results and rapid turn around for results. Further development is needed to integrate these tools within the shaping design process. But already the result able to be acquired in these simplified simulations, clearly showcases the complexity of surfboard design and the potential for CFD to reduce the number of board iterations required to develop models, improving sustainability of the design process both economically and environmentally.

1. Crameri, S. The Three F’s of Surfboards: Flex, Form and Feel. Deakin University; School of Engineering: Australia, 2025.
2. Mancini, S. The problem of verification and validation processes of CFD simulations of planing hulls. In Department of Industrial Engineering; University of Naples “Federico II”: Napoli, 2015.
3. Oggiano, L. Numerical comparison between a modern surfboard and an Alaia board using computational fluid dynamics (CFD). In Proceedings of the 5th International Congress on Sport Sciences Research and Technology Support; SCITEPRESS - Science and Technology Publications, 2017; pp. 75–82. DOI: 10.5220/0006488400750082.
4. McCagh, S. The surfboard book: how design drives performance. 2013: McCagh O’Neill Pty Ltd.