AirShaper

For more information on sports car aerodynamics:
- 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

In this video, we’re analyzing how aerodynamics impact the performance of rally cars.

Surprisingly enough, in many ways the aerodynamics of rally cars are far more complex than in Formula One, where the cars enjoy some of the world’s smoothest and grippiest bits of tarmac. That’s quite a big contrast to rally cars, where driving in a straight line without wheel spin, drifting or jumping is a rare occasion.
So, where do you start if you want to optimize the aerodynamic performance? The hard reality is that you’ll have to look at multiple scenario's and strike a delicate balance between aerodynamic performance in each of those.

Let's take this 2016 Skoda Rally car in normal setup (regular ride height) and straight-line driving at 40 m/s as the reference. As shown by these red clouds, which indicate where a drag-increasing wake is created, this clearly isn’t the most streamlined car out there:

The rooftop air intake disturbs the air to such an extent that in its wake the center of the rear wing loses pressure and performance. And those wheel arches cause a lot of separation of the airflow at the sides of the car.

But enough on theoretical straight-line driving – it almost never happens, it’s time to start jumping & drifting!

If we increase the car's ride height by 15cm, which is not uncommon just before or during a jump, then the drag on the car increases by 16% and the downforce is cut in half! As you can imagine, losing downforce and grip just before take-off can be quite tricky for the launch. And once you’re flying, you’re slowing down quite a lot because of the drag!

Massive changes in ride height like this are one of the main reasons it’s difficult to boost rally car performance by using underfloor aerodynamics, diffusers and so on: the downforce they generate is extremely sensitive to changes in ride height. And perhaps even more important, that change of downforce can be more pronounced at the front or the rear, changing the aerodynamic balance and thus the handling & stability of the car.

Next, let's look at drifting. Obviously, there's enough debate going on already as to whether you'll be faster or not when drifting. When it comes to aerodynamics, the drag on this car increased by 43% at a moderate drift angle of 15°! That would slow you down quite a lot. But there's good news as well:

The entire car starts acting like a giant wind shield, with the wind hitting the outer side flank. This generates around 100kg of lateral force pushing the car back into the corner.

And, interestingly, the wake of the rooftop air intake is no longer affecting the rear wing, which is now happily creating downforce, so it seems that this car really comes together in the corners.



Note: the 3D model of the rally car used in this video was a public one from hum3D.com and is not an official model from Skoda: it serves mainly to highlight general rally car challenges and not to make official claims to the performance of this car in question.

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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

Rally Car Aerodynamics - Side Slipping through the Air

For more information on sports car aerodynamics:
- Gordon Murray T50: https://youtu.be/FSaI6STYIQA
- 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

In this video, we’ll cover the advanced aerodynamic features of the upcoming Lotus Evija electric hypercar.

From a distance, the Lotus looks relatively normal, at least for a hypercar. But the closer you get, the more hidden channels you discover. At the front, underneath the hood, the air is guided between the wheels and the center of the car, to exit a bit further downstream at the sides of the car. The air that has chosen to go on top of the hood, tumbles down to the flanks to enter the air intakes on the side of the car to exit at the back.

We didn’t yet obtain a 3D model of the Evija, but we have something that comes quite close. The Aquilo is a concept car I designed 10 years ago, featuring roughly the same channels. Let’s have a look at how they help to improve aerodynamic performance.

In this concept, the air enters the car in the middle and then splits left & right to exit on the sides. This helps to reduce the virtual frontal area of the car, something Lotus refers to as aerodynamic porosity. This same porosity can be seen at the back, where large channels take the air in on the sides and spit it back out at the rear. This air helps to fill the low-pressure bubble at the back of the car, greatly reducing the wake it leaves behind, as shown by these red pressure clouds. This helps a great deal to reduce the drag of the car and thus increases range and top speed.

Beyond reducing drag, the channels in the Aquilo are meant to split the air left & right in an asymmetric way. This generates lateral forces to help the car corner faster. The concept was patented and later on referenced to in patents of Ferrari and Toyota. So perhaps the Lotus Evija hasn’t revealed it’s full potential yet, let’s see what the future brings!

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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

Hypercar Aerodynamics - 2000hp Lotus Evija

For more videos on motorbike aerodynamics:
- Motorbike wheelies: https://youtu.be/M2Z_GuLHmHs
- MV Agusta - MotoGP - part 1: https://youtu.be/BUkaejkHRn8
- MV Agusta - MotoGP - part 2: https://youtu.be/fGNdMaVft_w
- Damon motorcycles - electric motorbikes: https://youtu.be/asYdvFfzHTs

In this video, we’ll discuss the motorbike aerodynamics with together with Joseph Katz, author of the famous book “race car aerodynamics”, professor at the San Diego State University and passionate motorbike rider.
Before we move on to the interview, let’s summarize some basic aspects of motorbike aerodynamics and how they differ from cars:

First of all, the drag: the frontal area, which is the area when looking at an object from the front, is much smaller for a motorbike. But to get the total drag on an object, you need to multiply this frontal area by the drag coefficient, which is much, much larger for a motorbike, offsetting the benefit of the smaller frontal area: it is filled with exposed bits of geometry like the wheels, brakes, and so on, and the surface the air needs to follow is hardly a smooth one: it’s full of abrupt changes like the end of the wind shield causing the flow to detach. And then there’s the rider, a massive disturbance to the air. So, the drag coefficient of a motorbike is easily double or more than that of a modern-day car.
Second of all, the centre of pressure, which is the point where the total sum of the pressure is acting, is quite high above the ground. With respect to the contact point of the rear wheel on the ground, this tends to push the motorbike backwards, lowering contact pressure on the front wheel, which reduces steering control. As the aerodynamic drag force increases with the square of velocity, this can become problematic at high speeds. So, trying to get the center of pressure as low as possible is crucial for motorbikes. A low rider position is a good start. Another way to balance things is to create down force on the front wheel to counteract this back-flipping moment on the bike.

In the interview, we cover the following topics:
- Effects of leaning on aerodynamics
- Engine performance
- AMA superbikes
- Rider position
- Rear tire wear
- Active aerodynamics
- Wind tunnel testing
- Centre of pressure
- Ducati wings
- Lateral forces
- Helmet vibration
- Better engine performance via RAM air


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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

Motorbike Aerodynamics - 10 mph faster with Joseph Katz

Open wheels, exposed components and a constantly moving rider makes optimising motorcycle aerodynamics a huge challenge. But there are many techniques engineers use to refine the designs of motorbikes, helmets and suits and the rider has an important role to play too.

How to improve Motorcycle aerodynamics

For more information about race car aerodynamics:
- Porsche GT4 racing: https://youtu.be/JkdoXKfc2hU
- Race car aerodynamics: https://youtu.be/GApwSjKYUpQ

In this video we’ll explain how you can build aero maps for your own race car.

What are aero maps?
In general, a map is a tool to visualize or store the relationship between different variables. Like the altitude of a terrain in function of longitude and latitude. Or, in case of a race car, the aerodynamic drag, lift and balance in function of the setup of the car, like the ride height at the front and the rear, the angle of a wing, and so on. So in general, aero mapping can be described as the “mapping” of the relationship between geometric parameters of the car on one hand, and the effect on aerodynamic properties on the other hand.

What do you use them for?
When the time has come to race, every second matters: not only for lap times, but also for setting up the car prior to and during the race. Aerodynamics are crucial for the dynamic behavior & performance of the car. For example, the aero balance describes how the down force is distributed between the front and rear axle. Shifting this balance can help mitigate oversteer for example. Another aspect is the cornering performance: when the circuit is filled with high-speed corners, you need more down force. But on circuits with long straights, the drag penalty associated with high-down force settings will slow you down over the course of a lap. Having a clearly mapped relationship available between the setup parameters of the car and the aerodynamics is essential to setup or modify the car on race day – when there is no room for trial & error.

Where can you get these aero maps?
“Ok, you have me convinced, I need aero maps. Where do I buy one?” Unfortunately, it’s not that easy, for a number of reasons:
a. You could ask the manufacturer, but quite often the aero maps are not shared, or the ones that are shared are not always accurate or useful.
b. You could also consider building your own aero maps in a wind tunnel: it can result in highly accurate maps, but requires large budgets as a proper tunnel with moving floor costs thousands of euros per hour, not even taking the cost of preparation & data processing into account.
An interesting budget-friendly way of building aero maps is to run CFD, or computational fluid dynamics simulations on the different setups of your car. Let’s have a look at how this can be done.


Building an aero map through simulations
To illustrate the process of aero mapping we’ll be using this public 3D model of the 2016 Audi R8 LMS. We changed the ride height of this car by 20mm in two steps and then mapped two important aerodynamic properties.

First, the drag and down force. As you can see, increasing the ride height of the car doesn’t impact the aerodynamic drag much but it significantly reduces the down force. This is because you reduce the speed up of the air underneath the car, helped by the splitter at the front and the diffuser at the back. So lowering the car would actually be a better idea in terms of aerodynamics, giving you extra down force at hardly any drag penalty, so why didn’t we?
Well, in most race classes there is a lower limit to the ride height of the car, so you wouldn’t be allowed. And, if you lower the car too much, you can actually block or choke the flow underneath the car, losing that precious down force.

But down force is more complicated than just a single number. As mentioned before, the aero balance describes the distribution of down force between the front and rear axle. Too much on the front will make the front wheels grip nicely but allows the back to lose grip easily, resulting in oversteer. So, it’s important to tweak the balance properly and amongst many things, align it with the weight distribution of the car itself. In this example, we can see that increasing the ride height of the car, also shifts the aerodynamic balance backwards. To counter this, you may need to play with the front splitter or the angle of attack of the rear wing, or the rake of the car, if allowed by regulations.

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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 car aerodynamics #3 - Aero mapping

Aero maps visualise the relationship between downforce, drag and ride height. Engineers use aero maps to tune the set-up of a race car to achieve maximum downforce and optimum aero balance in the corners where the most lap time can be found.

How aero maps can improve race car performance

To learn more about the Tesla Semi Aerodynamics: https://youtu.be/Km1NHe0ZsVo

---What is Vecto---
Within the quest to limit climate change, the pressure on heavy duty transport has been rising, and with good reason: trucks, buses and coaches together produce around a quarter of all CO2 emissions from road transport in the European Union. To ensure that the most fuel-efficient vehicle combinations are brought onto the market, the European Union developed the “Vehicle Energy Consumption calculation Tool”, or VECTO in short, a mandatory tool since January 2019 for new trucks & buses in a number of categories. Based on input parameters like rolling resistance, air drag, masses and inertias, gearbox friction, auxiliary power and engine performance, it simulates fuel consumption and CO2 emissions based on standardised driving cycles. So how do you obtain all these parameters?


---What is Vecto AirDrag---
Based on constant speed track tests and a massive set of measurement data, Vecto AirDrag allows you to calculate the air drag Cd*A, based based on force measurements:
- Constant forces, that do not change with velocity (rolling resistance, bearing losses, and so on)
- Air drag force, which scales with the square of the velocity
To obtain the split between these forces, you can measure the force at 2 different velocities. If you then fit a curve through both low-speed and high-speed tests, including a constant and a quadratic term, you can isolate both components.
***The Track***
Tests are executed on a proving ground test track, with two straight parts running in opposite direction. Data is logged throughout the entire test, but it’s only the data captured on these straights that counts.
 
***Measurements***
- On the vehicle
High-accuracy DGPS data
Front axle rpm & torque (left and right)
Wind speed & direction above the truck measured using an anemometer mounted on a pole
Ambient temperature on the truck
- At the fixed weather station on the proving ground
Ground temperature and
Air pressure & humidity are measured.

 
***Data evaluation***
Once all the tests have been performed and the data has been gathered, the constant speed tests are processed in 8 steps:
1: the instantaneous velocity readings are corrected using the average velocity over a test section.
2: the forces acting on the truck are calculated, based on the torque readings from the shafts and the engine or cardan speed. These are then corrected:
- the force for climbing or descending is compensated for based on the road gradient & vehicle mass.
- the correct air density is calculated using the temperature at the vehicle and pressure & humidity at the fixed weather station
3: validity criteria are applied to each constant speed test (speed & temperature ranges, ...)
4: CdA(beta) is calculated for each test by fitting a curve through the data.
5: result averaging per heading and then across headings.
6: extra checks (on rolling resistance, ...).
7: CdA(beta) conversion to CdA(0°) based on empirical data / vehicle type.
8: anemometer drag correction

---Optimizing for efficiency--
As you can imagine, running these tests requires large budgets & a lot of preparation effort, so you want to get it right the first time around. To know up front how changes in aerodynamics will impact vehicle efficiency, you can run aerodynamic simulations: 12--these allow you to calculate the CdA for each design concept and quantify the effects of replacing mirrors by camera’s, shielding the wheels, reducing the gap between tractor and trailer, and so on.
You can then use the engineering mode of Vecto to assess the effect of these differences in aerodynamic coefficient on total vehicle efficiency. Once you’re comfortable enough with the predicted efficiency gains, you can move on to real physical testing, using the declaration mode of Vecto for the final analysis.

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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

Cutting truck & bus emissions - The Vecto AirDrag Tool

In this video, we’ll guide you on how to select the right simulation for your project.

In theory, the advice is simple: go for the one with the highest resolution, as it results in the highest accuracy & the most useful data. But in practice, this is also the most expensive & time-consuming solution, so the real question is:
“Within a given budget & timeframe, how can I improve the aerodynamics the most?”

For example, should I run 10 simulations at low resolution or one at high resolution? The answer is to select the right resolution for the right purpose. 

But first, let’s explain what exactly resolution means for aerodynamic simulations:
Very similar to the pixels of a digital photograph, which form a 2D grid or mesh, a flow simulation uses a 3D mesh, featuring small blocks around your 3D model to calculate the aerodynamics. For more details on this, watch our separate video on computational fluid dynamics using the link in the description below or at the end of this video. Most important aspect: the higher the resolution, the smaller these 3D blocks become and the more accurate the flow simulation will be. That brings us to the first guideline on how to select the right resolution, the 3D model you’re analyzing.

3D model
Let’s compare the effect of low, medium and high resolution on the same object, in this case, a Formula E car. At low resolution, the global mesh looks quite ok but in areas, with small details like the wheels the mesh is quite rough. Depending on how accurately you want to capture the flow around these details, the mesh resolution needs to increase accordingly.
So if you’re interested in the global flow around a smooth object, a low resolution might be enough for a first idea. But if you’re interested in the flow around small details on a large 3D model, you may want to go for a high resolution.

Accuracy
Next up is the accuracy. Your shape may be simple, like an airfoil, but to accurately analyze lift & drag forces, you still need a high resolution. So if you’re simply interested in learning about the order of magnitude of forces, like the difference between 1 or 10 Newtons of lift, a low resolution might do. But if you’re looking to make more accurate force estimations, to know whether the lift on your airfoil is 6 or 6.5 Newtons, you’ll need a high resolution.

Design phase
Finally, it also depends on the design phase of your project. If you’re in the very initial phase, you first want to gain basic insights and not spend all your budget on simulations just yet. So a low resolution might be enough to provide you with those first valuable learnings and relative ranking between concepts. But as you progress towards more detailed models with smaller differences, the resolution needs to evolve accordingly.

This means you could for example run 10 simulations at low resolution to determine the main design direction during the concept phase, run 5 simulations at medium resolution when you’re detailing a selected number of designs and finish off with 3 simulations at high resolution to tweak the last bits of performance before releasing the design for physical wind tunnel testing or production. 

So in conclusion, a low resolution might be enough if you’re working on simple, early-stage 3D models and just need a ball-park estimate on the forces and the flow field. But if you’re looking to make accurate force predictions on complex 3D model towards the end of your design process, you’re better off with a high resolution.

Last but not least: talk about it. If you’re not sure how to approach things, just get in touch and we’ll see how we can help!

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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

Choosing your Simulation - Accuracy vs Speed vs Cost

To learn more about adjoint shape optimization: https://youtu.be/cZAhPQFINZ8

In this video, we’ll explain the basic principles of CFD or computational fluid dynamics.


Modeling involves the continuous mathematical functions that you use to describe the real flow. In reality, that flow is the result of many different laws of physics working together. To limit computational effort, it’s a matter of selecting only the ones that have a substantial impact on your flow topic: if you’re calculating the aerodynamic force on a wing, for example, there’s little use in taking the gravitational pull of the moon into account, as the effect is negligible. So, defining correct & relevant models is important to limit the modeling errors:

In case of fluid mechanics, the most important model is a set of partial differential equations called the “Navier Stokes” equations. These basically apply the laws of Newton for every small bit of the fluid, stating the dynamic balance between the forces acting on it and the change in its momentum. This conservation of momentum, together with the conservation of mass, allows you to describe the flow field.

For some very simple cases, like laminar flow through a pipe, there are analytical solutions: the entire flow field can be described using continuous mathematical functions. These allow you to calculate the exact velocity & pressure for any given location in the flow field at an infinite resolution.

But for anything more complex than these very simple cases, we don’t have such an analytical solution. That means we need to break down reality into small blocks for which we do have a solution. These blocks can be finite elements or finite volumes, also called cells. Think of it as the difference between analog and digital photography, where a complex image is described by simple pixels, each having just one color.

This process of breaking down a large continuous flow field into small cells is called meshing. For each of these cells, we can approximate the continuous Navier-Stokes equations by discrete algebraic equations. These allow us to calculate the pressure & velocity at the center of each cell, which is called the node, based on the values of velocity & pressure of the surrounding nodes.

The higher the order of these discrete approximations, the more surrounding nodes are included. This “reach” is called the computational molecule, resulting in a set of algebraic equations for each node. As the value of one node depends on the value of neighboring nodes and vice versa, the equations are connected. This means you need to solve them simultaneously by putting them together in a big matrix.

But before we discuss how to solve this matrix, we need to talk about the discretization error: “The difference between the exact solution of the governing equations and the exact solution of the discrete approximation”. The more cells you apply, the smaller this error. But this also increases the number of equations you need to solve, and with meshes typically containing millions of cells, this quickly becomes very expensive. So you’re best off applying small cells to locations where the flow is complex, and large cells where the flow is less curvy, typically further away from the object.

Once you have defined your mesh and your matrix of equations, it’s time to solve them. It’s possible to find the exact solution of this matrix problem through a direct method like Gauss elimination or LU decomposition. But this is very costly in terms of computational power and why bother solving the equations down to computer accuracy level, when your discretization error is much bigger anyway?

This is where faster iterative methods come in: they start by “guessing” an initial solution, which could even just be a standstill flow field, or “zero velocity” for every point. Then they linearize the equations around that point and improve the solution through iteration. If you iterate long enough, the flow field will converge to a stable solution, reducing the iteration error. The difference between this solution and the direct solution of the equations is called the iteration error.


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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

Computational Fluid Dynamics Explained

Computational Fluid Dynamics is used in many industries to model and optimise the behaviour of fluids. Based on the Navier Stokes equations, there are three steps to computing flow, modelling, discretisation and linearisation.

Computational Fluid Dynamics (CFD) explained

For more on cycling aerodynamics:
- Iron man: https://youtu.be/DqlDpUFcScc
- Custom aerodynamic clothing: https://youtu.be/A0Gx-lBzSFA

Aerodynamic backpack ventilation – Vaude has your back

Why do we sweat when we exercise?
Well, we like to keep our body temperature constant and when doing sports, that temperature increases. To counter that, we sweat. The sweat evaporates into the air around your body and the energy needed to do so is drawn from your body, cooling it down.

But what if you’re blocking the air? Then the sweat piles up and you’ll need to sweat even more in other places to get enough cooling. It leaves commuters with a soaked T-shirt on the back and athletes with decreased performance.

So Vaude turned up the technology level on their newest backpack to come up with a solution for this. In a first step, they ran several airflow simulations on a digital mountain biker without a backpack, simply to understand how the air moves around the body and find sources of cooling. They saw that the airflow around neck & shoulders re-joins at the higher part of the back, to then channel down at relatively high speed before letting go somewhere lower down the back.

At some point, the air going around the torso was also considered to help drive air underneath the backpack. But with the air being too turbulent after going around the torso and the backpack hidden in the wake of the rider’s back, this turned out to be less efficient.

So together, we figured it would be quite nice to use the central airstream at neck & shoulders to help cool down the rider’s back in the locations where it matters most: the central part of the lower back. Multiple concepts were thought of, all with the aim to capture this airstream and channel it between the rider’s back, and the backpack itself.

Aerodynamically optimized channels were carved out of the padding between rider and backpack and after numerous checks via simulation, we ended up with a design that outperforms anything that is currently out there in the market.

And that’s not just us talking: Vaude performed multiple wind tunnel tests, with riders going at it in well-controlled conditions, like the temperature, seating position, produced power and so on. They even went to the Sports Tech Research Centre, who operate a specialized wind tunnel, to put their new backpack design to the test.

Read more in this research paper:
https://airshaper.com/research/cycling-backpack-thermal-comfort-cfd-analysis

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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

Sports Aerodynamics #3 - Aerodynamic backpack ventilation

For information on tidal turbine hydrodynamics check this link: https://youtu.be/c3VaPgTJh88


Let’s focus on these flat roof systems. 
Penetrating the waterproof coverage for anchoring purposes isn’t always an option, many operators just put ballast of weight on the mounting system to keep things down. That avoids a possible leakage problem but adds a new one: extra weight. 

A decade ago, when no norms were available yet to determine the right amount of ballast to keep the panels down, some applied more safety than others. And with the financial crisis in full force back then, there was yet another incentive to get the total weight below the capacity limit of the roof to get projects approved and profitable. So sadly, some panels flew away.

Nowadays though, through extensive wind tunnel testing & simulations, norms have been formed and it’s clear & simple: follow the norm. Still, those norms allow for optimization, as they often take the aerodynamic behavior of the system into account. So prior to final wind tunnel testing & certification of a system, it makes a lot of sense to integrate aerodynamic simulations into the R&D phase to optimize the mounting systems.

To illustrate this, we’ve analyzed a single free-standing panel in an airflow of 40 m/s, a pretty decent storm. Under headwind, the vertical lift on the panel is around 240 kg, so the weight of the panel itself, around 20kg, is not nearly enough to keep it down.

This happens because the panel behaves like a wing with ground effect: the air hits the bottom of the panel, creating a high pressure pushing it upwards. At the top, the air separates as it jumps over the panel, creating a large suction effect again pulling the panel upwards. Even when the wind hits the panel under a large angle, the lift force can still be as high as 100kg.

If we look at the same panel receiving headwind, but now surrounded by neighbors in an array, the vertical lift force increases even further. Why? The free-standing panel had an escape route for the air on both sides. But when flanked by two neighboring panels, the only way for the air is up, increasing the pressure build up. The panels on the second, third and fourth-row feature much lower lift values, and sometimes even downforce. That is why very often the ballast for the outer panels of the array is much higher than the ballast for the inner ones.

Now if we rotate the entire array by 45°, we see some other interesting effects. As expected, the panel at the corner feels the highest vertical pull, but it’s lower than the headwind case. As we move away from the corner, the lift on the front row panels decreases significantly. Nevertheless, values are still very high and too much ballast would be needed to keep them down. So to reduce wind loading, plates are usually installed to prevent the air from entering underneath the panel, which reduces the high pressure build up at the bottom side.

We’ve added such a plate to the isolated panel. The air now hits this backplate, pushing the plate itself downwards as the air jumps up. The lift on the total system has been reduced drastically for all angles and even features downforce at some angles. The solar panel itself, however, can still feel the suction effect in the wake of the plate.

To counter that, there are some innovative systems that feature an intended opening at the top of the backplate. The suction effect, which is the largest just at the top of the backplate, will now draw air from underneath the panel. This helps to both reduce the pressure below the panel and to reduce the suction effect at the top. The effect on the vertical forces is quite clear!

Studying the behavior of a system in clean airflow is just the beginning though. In real life, complex wind flow patterns around the building itself, influenced by the surrounding terrain and featuring wind guests, add multiple layers of complexity to the problem. So complementing simulations with wind tunnel testing and adding the right safety factors is key to keep your panels from flying.

Wind tunnel image courtesy of Peutz

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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, ...).

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