AirShaper

CORRECTION (0:57 to 1:30) for the picture on the right-hand side: 'laminar boundary layer' should be 'turbulent boundary layer'.

For more information:
- Boundary layers: https://youtu.be/TwOxa9rAOfE
- Flow separation: https://youtu.be/HfICmKv9SzE
- soccer ball aerodynamics: https://youtu.be/AWKuRLJl25Ig

In this video, we look at the aerodynamics of golf ball dimples and how to apply (or not apply) them to your design!

Aerodynamics of a sphere
A golf ball without dimples, a simple sphere, features attached, laminar flow at the front: as the air moves over the surface,  a boundary layer of slower moving air grows thicker as it sticks to this surface. As soon as the flow goes beyond the halfway point and needs to contract, it becomes more & more difficult for the flow to stay attached to the surface and eventually. Separates, resulting in a detached flow. This creates a large wake behind the golf ball, which increases drag and slows it down.

Aerodynamics of a golf ball with dimples
When you apply dimples to the surface, the boundary layer becomes turbulent. It will mix with the surrounding air and retain more kinetic energy. This energy allows the airflow to stay attached further down the back of the golf ball, moving the separation location further downstream to reduce the size of the wake. These dimples may increase the friction drag a little but reduce the pressure drag so much that the golf flies roughly twice as far!

Golf ball dimples on cars, golf ball dimples on planes, ...
So does this mean we should cover every surface on every car or plane with dimples to make it more aerodynamic? No, not quite. It only makes sense to create a turbulent boundary layer just ahead of a separation location. Modern day cars for example, have such a sleek profile that they have attached flow all the way to the back of the car. And even at the back of the car, a turbulent boundary layer would still not be enough to make it follow the negative curvature at the end of the trunk.

Golf ball dimples in sports
Another example is to reduce drag around cylinders. There it does make sense, depending on the Reynolds number, to add roughness or dimples or what so ever, to move the separation location further downstream. But on a golf ball you have dimples everywhere because you don’t know the direction of the golf ball. On a cylinder, if the flow is coming always from the same direction, it makes sense to only add roughness just ahead of the separation location, so not at the rear of the cylinder where the flow is already detached. A practical example of this are the arms of an athlete or cyclist, where the wind always comes from the front or a slight angle of attack, so it makes sense to only add roughness just ahead of the separation location on the arms. This is something you already see on some outfits of the riders.

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The AirShaper videos cover the basics of aerodynamics (aerodynamic drag, drag & lift coefficients, boundary layer theory, flow separation, reynolds number...), simulation aspects (computational fluid dynamics, CFD meshing, ...) and aerodynamic testing (wind tunnel testing, flow visualization, ...).

We then use those basics to explain the aerodynamics of (race) cars (aerodynamic efficiency of electric vehicles, aerodynamic drag, downforce, aero maps, formula one aerodynamics, ...), drones and airplanes (propellers, airfoils, electric aviation, eVTOLS, ...), motorcycles (wind buffeting, motogp aerodynamics, ...) and more!

For more information, visit www.airshaper.com

Golf Ball Dimples Aerodynamics - How do they work and are they relevant for your design?

Golf balls have dimples applied to their surface to manipulate the behaviour of the boundary layer to reduce the wake and overall drag. However, it only makes sense to use dimples just ahead of the separation point.

Why do golf balls have dimples?

For more information on adjoint shape optimization: https://youtu.be/cZAhPQFINZ8

In this video, we look at how machine learning / deep learning / neural networks can be applied to aerodynamic CFD simulations.

Neural Concept
We interviewed Pierre Baqué, CEO of Neural Concept, a Swiss startup developing & offering Deep Learning software. They have developed algorithms to connect 3D shape morphing, deep learning and aerodynamics.

senseFly
senseFly is a Swiss drone company that wanted to improve the flight time of their fixed-wing drones. senseFly, Neural Concept, EPFL (the technical University of Lausanne - École polytechnique fédérale de Lausanne) and AirShaper teamed up to apply Deep Learning to drone design to improve the aerodynamics, as improvements to the lift/drag ratio directly extend the range / increase flight time.

Deep Learning setup
The Neural Concept software can create & explore new 3D shapes to train its network, but it needs an aerodynamics component to give feedback on the lift/drag performance (and other aerodynamic parameters) of each design. For that, the Neural Concept software connected to the AirShaper cloud via an API interface.

Network Training
The training of the network was done in multiple phases with increasing accuracy. The initial warm-up of the network was done using older, in-house simulations from other projects. In the second phase, medium accuracy AirShaper simulations were applied. And in the final phase, high-accuracy AirShaper simulations were used for final tweaking of the network.

Output
Without any design input, the network came up with special drone shapes that partially matched what engineers had been applying for years in practice (anhedral/dihedral setup, ...). The lift/drag ratio was improved by more than 4%. Because the Reynolds number is quite different compared to large aircraft, so were the suggested design solutions.

AIRBUS
Neural Concept worked on the prediction of shock waves (transonic simulations). These results were presented at NEURIPS.

Future of Deep Learning for Aerodynamics
- Today
For industry specific, repetitive tasks, it pays off to train a network so that new designs can be analysed using the predictive model
- Short term
In the short term, machine learning can be used to make existing CFD codes faster and more accurate
- Long term
It's uncertain if it will ever work, but it might be possible to create generic Neural Networks that cover various industry segments, without needing to train the network.

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Full Research Paper: https://www.airshaper.com/research
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The AirShaper videos cover the basics of aerodynamics (aerodynamic drag, drag & lift coefficients, boundary layer theory, flow separation, reynolds number...), simulation aspects (computational fluid dynamics, CFD meshing, ...) and aerodynamic testing (wind tunnel testing, flow visualization, ...).

We then use those basics to explain the aerodynamics of (race) cars (aerodynamic efficiency of electric vehicles, aerodynamic drag, downforce, aero maps, formula one aerodynamics, ...), drones and airplanes (propellers, airfoils, electric aviation, eVTOLS, ...), motorcycles (wind buffeting, motogp aerodynamics, ...) and more!

For more information, visit www.airshaper.com

Machine Learning for Aerodynamics - Deep Learning & Neural Networks applied to CFD simulations

For more information on sports car aerodynamics:
- Lotus Evija: https://youtu.be/WaLxG9CT3RI
- 300 MPH custom Lamborghini: https://youtu.be/N9kMQBBMUdM
- Porsche Taycan - part 1: https://youtu.be/K2jgsgihZ_w
- Porsche Taycan - part 2: https://youtu.be/kyHjWGnrByQ


Cars by Gordon Murray
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Brabham BT46
Inspired by the ground-effect Lotus Type 78 featuring side skirts and the Chaparral 2J “sucker car”, featuring 2 fans at the rear, Gordon Murray and the team installed a massive fan at the rear of the Brabham Formula One car. Because ‘moveable aerodynamic devices’ were not allowed, its official purpose was actually to improve cooling, which it did. What it unofficially also did, was to draw air from underneath the car. With side skirts around the car closing off the underfloor area from the outside air, the fan was able to maintain a low pressure underneath the car. This led to high amounts of downforce, enabling crazy cornering speeds.

McLaren F1
On sports cars, you’ll often see a diffuser, the upward sloped rear part of the underfloor. It’s there to increase the airspeed underneath the car, which will help to create suction because of the Bernoulli effect. If the upward angle is too aggressive, the air will not be able to follow the curvature and will continue on its own, more horizontal path. This is what we call a “stalled” diffuser. To activate it and make the air follow the curvature, the fans draw air away at the beginning of the diffuser step. This helps to remove the boundary layer and makes the airflow stick to the underfloor surface. It increased downforce by 5% and reduced drag by 2%.

Aerodynamic analysis of the Gordon Murray T50
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Fan
The fan has an 8.5kW electric motor and can spin up to 7.000 rpm. It will eject the air into the wake behind the car, helping to reduce drag by virtually creating a long-tail car. And the 15kg of thrust it produces is around 2.5% of the total drag on the car, so that effect is actually significant as well. Even more so – from what we understand from various interviews, it’s actually more efficient to provide 8.5kW to the fan and not to the drive shafts to increase top speed. Now let’s see how the fan works together with other parts of the car in different aero modes. 

Downforce mode
In down force mode, the fan will source air from the diffuser channels. The car has 2 very pronounced diffuser channels which fit between the engine bay and the rear wheels. Without fan assistance, the air is not able to follow this profile and the diffuser stalls, creating just a mild diffuser effect. But in downforce mode, the fan draws its air from the beginning of the diffuser, at the steep part of the step. This helps to remove the boundary layer and to make the air to stick to the profile. This not only creates downforce at the rear, it also helps to accelerate the air underneath the entire car, creating down force at the center and front of the car as well.  In total, down force mode will generate 50% more overall downforce on the car.

Streamline mode
The rear spoilers drop by 10° to reduce base suction, which is the pressure just behind the car, holding it back. And the fan will now source its air from the top air inlets. This again helps to remove the boundary layer which will help to reduce drag on the parts downstream of these inlets. Together with the virtual long-tail effect, drag is reduced by an impressive 12.5% in streamline mode.

Vmax mode
This is basically the same as streamline mode, but the fan is now powered by the battery instead of the engine, to free up engine power.

Brake mode
The flaps rise even further to their maximum angle of 45°. This mode provides a 100% increase in downforce, which provides more grip for braking. And because the flaps are positioned relatively high on the car, the drag on them creates a backward tilting moment, counteracting the forward tilt caused by the deceleration. This greatly improves the balance of the car under braking. All this reduces the braking distance from 150mph to standstill by 10 meters.


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The AirShaper videos cover the basics of aerodynamics (aerodynamic drag, drag & lift coefficients, boundary layer theory, flow separation, reynolds number...), simulation aspects (computational fluid dynamics, CFD meshing, ...) and aerodynamic testing (wind tunnel testing, flow visualization, ...).

We then use those basics to explain the aerodynamics of (race) cars (aerodynamic efficiency of electric vehicles, aerodynamic drag, downforce, aero maps, formula one aerodynamics, ...), drones and airplanes (propellers, airfoils, electric aviation, eVTOLS, ...), motorcycles (wind buffeting, motogp aerodynamics, ...) and more!

For more information, visit www.airshaper.com

Gordon Murray T50 Aerodynamics - Successor to the McLaren F1 supercar

For more information on how to interpret CFD results: https://youtu.be/XntO27S5Urc


In this video we explain how to use Paraview to analyze CFD data:

Installing paraview
Visit https://www.paraview.org/download and select the release & operating system that you need.

Loading data
How to load the mesh & field data in Paraview.

Surface Methods
- Surface pressure map
- Surface friction map
- Surface velocity map
- Surface streamlines using SurfaceLIC

Volume Methods
- 2D slices (sections)
- 2D streamlines
- 3D Isosurfaces

State files
Saving & loading your project setup using paraview state files


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The AirShaper videos cover the basics of aerodynamics (aerodynamic drag, drag & lift coefficients, boundary layer theory, flow separation, reynolds number...), simulation aspects (computational fluid dynamics, CFD meshing, ...) and aerodynamic testing (wind tunnel testing, flow visualization, ...).

We then use those basics to explain the aerodynamics of (race) cars (aerodynamic efficiency of electric vehicles, aerodynamic drag, downforce, aero maps, formula one aerodynamics, ...), drones and airplanes (propellers, airfoils, electric aviation, eVTOLS, ...), motorcycles (wind buffeting, motogp aerodynamics, ...) and more!

For more information, visit www.airshaper.com

CFD Results - How to analyse OpenFOAM data with ParaView - 25-minute Tutorial

How to run an AirShaper simulation

Hi, and welcome to AirShaper, the cloud-based simulation platform for external aerodynamics.
In just three easy steps you can obtain all the data & insights you need to understand and improve the aerodynamics of your design.

Fixed wing drone

Step 1 - The Set Up

Start a new project and select the required accuracy. If you’re just exploring initial concepts or simple shapes, a concept simulation will do. If you’re working on the final details or a very complex 3D model, our ultimate simulation is the best choice.

Give the project a name and simply drag & drop your 3D file into AirShaper. By the way, AirShaper is capable of working directly with open surface models. So there is no need to spend weeks to make your 3D model watertight.

On the setup page, first, choose your simulation type. This drone, for example, is above the ground and moving. Fill in the velocity and rotate the model if needed. Finally, let us know the units of your 3D model and if needed, add a scale factor. That’s all there is to it for the setup!

Simply fill in your details on the payment page and submit the simulation.


STEP 2 – The Cloud Simulations

Our automated algorithms will now automatically build a virtual wind tunnel around your 3D model and analyze the aerodynamics. And because it’s a cloud platform, you don’t need any software or hardware and we can use high-performance computing to deliver fast and accurate results.

STEP 3 - The Results

Once the simulation is finished, a full simulation report will be in your mailbox.

You can also view the 3D flow results directly in your browser. Look at pressure, for example, to find sources of drag, analyze streamlines to understand vortex structures and even get insights into which areas are generating wind noise!

And it that is not enough, you can download the full flow results to perform your own post-processing.

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The AirShaper videos cover the basics of aerodynamics (aerodynamic drag, drag & lift coefficients, boundary layer theory, flow separation, reynolds number...), simulation aspects (computational fluid dynamics, CFD meshing, ...) and aerodynamic testing (wind tunnel testing, flow visualization, ...).

We then use those basics to explain the aerodynamics of (race) cars (aerodynamic efficiency of electric vehicles, aerodynamic drag, downforce, aero maps, formula one aerodynamics, ...), drones and airplanes (propellers, airfoils, electric aviation, eVTOLS, ...), motorcycles (wind buffeting, motogp aerodynamics, ...) and more!

For more information, visit www.airshaper.com

How to run an Aerodynamic Simulation

For more information on how to process CFD data in paraview (free software):
https://youtu.be/kczZPc4M-ms

In this video, we explain how to interpret a typical CFD simulation report. The topic is a car and we will learn how to:
- Understand the different forces & moments
We analyze the drag force, lift force, lateral force as well as the pitch roll and yaw moments. The forces are then used together with the frontal surface area to calculate the drag coefficient of the car.

- Detect sources of drag
The iso-surface of the total pressure for a value of 0 is a good 3D representation of where you are 'losing energy', or dragging air along, or creating a wake. Typically this happens around the wheels, A-pillar, front splitter, door handles, etc.

- Read surface pressure & friction maps
The aerodynamic pressure map provides useful information on where the air is impacting the object, and where it is speeding up to go around curvatures. This can be useful to determine suitable locations for radiator inlet and outlet, to analyze the performance of aerodynamic elements such as rear wings, front splitters, etc.

The friction map can be used to spot areas of flow separation, as low friction usually indicates detached flow (unless it's an area of flow stagnation). The surface streamlines also help to understand the local flow direction.

- Analyse 3D streamlines
Aerodynamic streamlines around the object help to visualize vortex structures, the scope of impact on the surrounding air etc.

- Interpret sections of velocity & pressure
Looking at sections of velocity & pressure helps to understand how the air curves around local parts of the geometry (suspension parts etc), how much it accelerates, what the wake looks like etc.

- Localize sources of wind noise
The results shown are not based on a full acoustic simulation but on an acoustic analogy, which is a mathematical translation of turbulent kinetic energy into noise energy. It doesn't provide the user with any frequency or absolute sound level results, it simply serves as a rough indication of the biggest wind noise sources.


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The AirShaper videos cover the basics of aerodynamics (aerodynamic drag, drag & lift coefficients, boundary layer theory, flow separation, reynolds number...), simulation aspects (computational fluid dynamics, CFD meshing, ...) and aerodynamic testing (wind tunnel testing, flow visualization, ...).

We then use those basics to explain the aerodynamics of (race) cars (aerodynamic efficiency of electric vehicles, aerodynamic drag, downforce, aero maps, formula one aerodynamics, ...), drones and airplanes (propellers, airfoils, electric aviation, eVTOLS, ...), motorcycles (wind buffeting, motogp aerodynamics, ...) and more!

For more information, visit www.airshaper.com

CFD Results - How to Interpret an Aerodynamic Analysis

For more video interviews on car design:
- Part 1 - Ferrari 458 to Lightyear One: https://youtu.be/o4Yv5hynV1Q
- Part 2 - Lightyear One Solar Car: https://youtu.be/TKHjyC_L0OM
- Part 3 - Autonomous Vehicle Design: https://youtu.be/xw-B_yTU4mY
- Part 4 - The Dallara Stradale: https://youtu.be/c7NyvCluYVc


Henrik Fisker has designed the BMW Z8, Aston Martin DB9, Fisker Karma and many more iconic cars. He's now set the target even higher:
to create the World's Most Sustainable Vehicle

History in the Car Design Business
I love designing cars, I would do it even if I didn't get paid for it - I would still be sketching cars in my spare time. It feels like my calling.

Sustainable Vehicles
Over the past 10 years, I've been inspired by people trying to create a better environment and I wanted to do something myself, on a bigger level. So I decided to create sustainable vehicles that are still beautiful, still desirable.

Sustainable vehicles will be there one day, but it will not happen over night - this industry is like an oil tanker that needs 7-10 years to take a dramatic turn. Part of the reason for this is that the lifetime of a new automotive platform, with all the development, crashtesting, investment, ... is about 7 years. Scrapping that after 2 years doesn't make financial sense.

So we'll see dramatic changes over the next 7 years, but even then, we'll need more time to ultimately manufacture truly sustainable cars.

But we cannot sit around and wait, just because they're not perfect yet, and go drive diesel cars again. That's what we are trying to do at Fisker Inc.

Aerodynamics
One key advantage of having an electric car is the flat floor [note: which helps to smoothen the flow underneath the car]. The roof shape was also tuned to help aerodynamics. And the lower front & rear end were also optimized to make sure the air goes around & leaves the vehicle without too much turbulence. Over the years, as a designer, I've learned what things you need to do to optimize this.

But honestly, the goal was not just to design the most aerodynamic car, because then it just ends up looking like most other very aerodynamic cars, which ultimately is a hatchback-style teardrop shape.


Range
The range argument is really only happening right now because we still feel there is a long distance between charging stations and we'll not sure if we'll get there [range anxiety] and have time to fill up the car with electricity.

In my view, over the next 3-4 years, we will see a dramatic increase in charging infrastructure in the US, Europe and China. We'll also get much better at assessing how long we need to stay at a charging station and in the future, we will not necessarily have to wait there for hours. Once people get used to all this, the total range will become irrelevant.


Scale
If all-electric car manufacturers/manufacturers that make electric cars today were using the same battery cell, set of modular electric motors, you would already have scale.

The only way to get scale is to partner up and create some sort of consortium. That is what we are working on and that is how we'll get our price down.

UPDATE:
this interview has also been featured on Clean Fleet Report:
https://cleanfleetreport.com/interview-henrik-fisker-talks-about-the-worlds-most-sustainable-vehicle/


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The AirShaper videos cover the basics of aerodynamics (aerodynamic drag, drag & lift coefficients, boundary layer theory, flow separation, reynolds number...), simulation aspects (computational fluid dynamics, CFD meshing, ...) and aerodynamic testing (wind tunnel testing, flow visualization, ...).

We then use those basics to explain the aerodynamics of (race) cars (aerodynamic efficiency of electric vehicles, aerodynamic drag, downforce, aero maps, formula one aerodynamics, ...), drones and airplanes (propellers, airfoils, electric aviation, eVTOLS, ...), motorcycles (wind buffeting, motogp aerodynamics, ...) and more!

For more information, visit www.airshaper.com

Henrik Fisker Talks -  World's Most Sustainable Vehicle

Part 1 of this interview: https://youtu.be/BUkaejkHRn8

For more videos on motorbike aerodynamics:
- Motorbike wheelies: https://youtu.be/M2Z_GuLHmHs
- AMA superbikes: https://youtu.be/qrH_QBOrqbw
- Damon motorcycles - electric motorbikes: https://youtu.be/asYdvFfzHTs


MV Agusta is one of the teams competing in the MOTO GP - moto2 race class. In this interview, technical director Brian Gillen reveals how they blend physical & virtual wind tunnel testing to improve the aerodynamics of their moto2 race bike.

Wind tunnel testing process
Wind tunnel testing is great: you get a lot of empirical data. But there are a number of steps involved before you get there:
- Test definition: set up the goals & methods of the test plan, which sensors to use, which loads to expect, ...
- CAD design: design the parts for the prototype in a 3D CAD package
- Component prototyping: manufacture the components using 3D printing, carbon fiber, CNC machining, ...
- Mounting on a test bike: mount all the components on a frame (which can be the frame of an existing bike)
- Transportation: move all the required people, equipment and the prototype to the wind tunnel.
- Wind tunnel test: execute the wind tunnel test, monitor the forces, log the data, apply different visualization techniques, set different angles of attack, test at multiple speeds, apply tufts, ...
- Post-processing: process the data into a comprehensive report and draw conclusions

Wind tunnel testing advantages and disadvantages
+ Accurate force & moment data
+ Live feedback
- Indirect visualization
- Challenging to find causality

Wind tunnel simulations
- Traditional CFD programs: the time required to prepare a CAD model (close all gaps & holes) and manually set up a simulation is too long compared to the rapid steps of evolution of the bike in the development process. By the time simulation results were in, they were already 3 steps past with the real prototype.
- AirShaper: take a non-closed model and very quickly put it through the CFD algorithms to get back data. This allowed for very fast iterations to understand where they were in terms of fluid dynamics around the bike.

Data validation
For them, as engineers, data means nothing if it is not validated.
They were able to validate the AirShaper data versus data from the wind tunnel test and found an almost complete convergence in terms of forces & moments on the vehicle.

Virtual iterations
That allowed them to build a virtual avatar around the bike as a mirror image of the physical world. From there on, they could dive into the virtual world for an iterative process before going back to the real world, where testing costs a lot of money. Designing, constructing, testing & scrapping prototypes when they do not work is very expensive.

Track testing
On the track, the drivers can test the real performance of the bike and give qualitative & quantitative feedback to the development team (vibrations at certain speeds, wind buffeting affecting visibility, aerodynamic stability, ...). 
Here too, like in the wind tunnel, you need to be able to correlate numbers to sensation. For this to be possible, the rider has to be very lucid & clear in his description of what he's experiencing on the track (what & where is he experiencing an issue) so that this can be matched to data to find a mathematical reason.

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The AirShaper videos cover the basics of aerodynamics (aerodynamic drag, drag & lift coefficients, boundary layer theory, flow separation, reynolds number...), simulation aspects (computational fluid dynamics, CFD meshing, ...) and aerodynamic testing (wind tunnel testing, flow visualization, ...).
We then use those basics to explain the aerodynamics of (race) cars (aerodynamic efficiency of electric vehicles, aerodynamic drag, downforce, aero maps, formula one aerodynamics, ...), drones and airplanes (propellers, airfoils, electric aviation, eVTOLS, ...), motorcycles (wind buffeting, motogp aerodynamics, ...) and more!

For more information, visit www.airshaper.com

Race Talk with MV Agusta - How to Improve Moto GP Aerodynamics

Part 2 of this interview: https://youtu.be/fGNdMaVft_w

For more videos on motorbike aerodynamics:
- Motorbike wheelies: https://youtu.be/M2Z_GuLHmHs
- AMA superbikes: https://youtu.be/qrH_QBOrqbw
- Damon motorcycles - electric motorbikes: https://youtu.be/asYdvFfzHTs


MV Agusta is one of the teams competing in the MOTO GP - moto2 race class. In this interview, technical director Brian Gillen reveals the top priorities when it comes to race bike/motorbike aerodynamics.

Brian Gillen
Brian is originally from Buffalo, New York, America. He grew up in a family that had a multi-line motorcycle dealership for over 40 years, selling Italian motorcycle brands (Ducatti, MV Agusta, ...), Swedish brands (Husqvarna), German brands (Maico), ...
He's now technical director of the R&D group at MV Agusta: engine design/testing, vehicle design/testing, homologation, styling.

Moto 2
MV Agusta joined the moto2 championship in 2019 with an official team with their technical partner FORWARD RACING (www.forward-racing.com). In 9 months time, they designed a completely new bike from the ground up.

MV Agusta had been following the moto2 series and when the new 3-cylinder engine was introduced, this was a good time for them to get on board: they had been competing with a 3-cylinder racebike in the world championship world supersport. They had a good understanding of what makes a motorbike powered by a 3-cylinder engine perform well.

Aerodynamics
To make the difference within the tightly regulated race class (standard electronics, tires, ...) they looked for areas where they could make a difference and aerodynamics was one of them. Main aspects:
- Coefficient of drag: most want to reduce the coefficient of drag to increase the top speed. But the amount of time you spend over an entire lap at top speed, with wide-open throttle and high rpm, is very limited. Even big gains in top speed advantage result in a limited overall lap time advantage.
- How not to benefit your competitor: on a straight line, people try to get in behind you to go faster by drafting.
- Rider comfort: the engine dissipates a lot of heat and in ambient temperature conditions (like in Thailand) this decreases the mental performance of the rider. Keeping the rider cool is very important to keep his/her mental performance high. A better thermal comfort, relative to the competition, is a strong advantage for the rider.
- Wind buffeting: the air coming off the wind screen can be highly turbulent with frequencies around 20Hz for example which can shake the head of the rider. This reduces the focus, reducing the capability to detect the correct braking point. With just hundreds of seconds to decide on when to brake, this is very crucial.


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The AirShaper videos cover the basics of aerodynamics (aerodynamic drag, drag & lift coefficients, boundary layer theory, flow separation, reynolds number...), simulation aspects (computational fluid dynamics, CFD meshing, ...) and aerodynamic testing (wind tunnel testing, flow visualization, ...).

We then use those basics to explain the aerodynamics of (race) cars (aerodynamic efficiency of electric vehicles, aerodynamic drag, downforce, aero maps, formula one aerodynamics, ...), drones and airplanes (propellers, airfoils, electric aviation, eVTOLS, ...), motorcycles (wind buffeting, motogp aerodynamics, ...) and more!

For more information, visit www.airshaper.com

Our Latest Videos Gain aerodynamic insight by watching our videos

Golf Ball Dimples Aerodynamics - How do they work and are they relevant for your design?

Machine Learning for Aerodynamics - Deep Learning & Neural Networks applied to CFD simulations

Gordon Murray T50 Aerodynamics - Successor to the McLaren F1 supercar

CFD Results - How to analyse OpenFOAM data with ParaView - 25-minute Tutorial

How to run an Aerodynamic Simulation

CFD Results - How to Interpret an Aerodynamic Analysis

Henrik Fisker Talks - World's Most Sustainable Vehicle

Race Talk with MV Agusta - How to Improve Moto GP Aerodynamics

Race Talk with MV Agusta - Top Aerodynamic Priorities for moto GP bikes

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