AirShaper

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, ...).

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

Renewable Energy - Solar Panels Can... Fly?

For more Porsche videos:
- Porsche Taycan - part 1: https://youtu.be/K2jgsgihZ_w
- Porsche Taycan - part 2: https://youtu.be/kyHjWGnrByQ
- Porsche Taycan - adjoint shape optimization: https://youtu.be/cZAhPQFINZ8
- Porsche Taycan - rear wing optimization: https://youtu.be/-fBXwx_n10I

For more information on race car aerodynamics:
- Aero maps: https://youtu.be/u-GyTRblNmc
- Race car aerodynamics: https://youtu.be/GApwSjKYUpQ

In this video, we’ll be playing with the aerodynamics of the Porsche GT4 race car.

Some people are satisfied with buying a standard Porsche GT4 to go racing. And to be honest, I’d be quite ok with that as well, if I had the budget. But others get creative and start modifying their car to gain that extra bit of performance.

Volker Wawer is one of those people: he wanted to fit wider tires on his GT4 and that meant he needed to shield those tires using wider fenders. But these impact the airflow around the car, possibly blocking the air going into the side air intakes further downstream. As reduced pressure & airflow rate at the inlets translates into a loss of power, Volker wanted to check this using aerodynamic simulations.

There was one problem though: getting a 3D model from Porsche is not so trivial. As an alternative, there are near-exact 3D models made by skilled 3D drafters, which are available for purchase online. As these models are built for visualization purposes, they’re usually built using surfaces and feature quite a lot of gaps & holes. This causes aerodynamic software packages to crash, so we put a lot of effort into it at AirShaper to make our algorithms able to work directly with these so-called open surface models.

So we purchased a Porsche GT4 model and had the wider fenders modeled onto it. We launched 2 Detailed Simulations: the normal GT4 and the one with modified fenders, to clearly see the difference. And we found some interesting results.

To understand how the air flows around the side of the car, we released particles just upstream of the car’s front left fender and traced their path. This showed us that the air that eventually ends up at the side air intakes, doesn’t just come from air going around the side of the car. Part of the breathing air for the engine first rises on top of the front hood of the car, to then tumble down to the side flank of the car after the front wheel arch.

Interestingly, the new front fenders are able to sustain this high airflow on the front hood over a longer distance, reducing the amount of air that passes via the sides, where it loses momentum and gains turbulence at it passes over the front wheels. We measured the pressure at the air intakes for both cars and actually found a higher pressure for the car with the modified fenders.

It doesn’t happen too often, but in this case, Volker got both the wider fenders and a power boost for the engine. In racing, it’s impossible to fully isolate driver & car performance, but both must have been pretty good as he won his next race at the Nürbürgring.
That was it for this video on Porsche GT4 aerodynamics, thanks for watching and see you soon!

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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 #2 - Improving the Porsche GT4

In this video, we’ll show you how aerodynamics can impact the performance, safety & environmental impact of your design!

Let’s start with aviation.
The most obvious field in aerodynamics.
Now the pinnacle of airplane performance is the Red Bull Air Race. Apart from big engines and big balls, aerodynamics determine who wins and who loses. Australian team Matt Hall Racing used AirShaper to optimize the airflow around key components of their plane. They won several races that season and nearly took the overall win!

Drones are another hot aviation topic 
Getting the aerodynamics right is crucial to fly as long and as far as possible on a single battery charge. For their latest model, the eBee X, senseFly ran several AirShaper simulations to optimize the vortex, or the corkscrew motion, of the air at the tip of the wings. By tweaking the vertical winglets together, we increased the aerodynamic efficiency by 30%! 

Aerodynamics also play a key role in performance sports, like cycling or skiing. We used a 3D scan of a speed skier to improve the aerodynamics of his stance & equipment. We helped him take his personal record from 198 km/h to a whopping 214km/h! At those speeds, aerodynamic forces dominate anything else!

But what about safety? 
Let’s have a look at the Sunfold, a free-standing container equipped with solar panels at the top to capture and store energy! Tiger Power uploaded a 3D model of their entire system into AirShaper and analyzed the forces and the moments caused by the wind to see if would tip over. 

Luckily, it didn’t!

The next step is to put all that renewable energy to good use, like efficient road transport. We benchmarked the Tesla Semi versus an optimistic generic truck and found a reduction in aerodynamic drag of around 20%! That’s over 5.000$ of fuel savings each year for a conventional truck, not to mention the reduction in emissions!

So whether you’re cycling at 30 km/h, transporting cargo at a 100 km/h or racing at 300 km/h, aerodynamics matter big time.

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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

Why aerodynamics matter! - Performance, Safety, Environment

In this video, we will analyze the aerodynamic features of the Tesla Semi truck.

Emissions
First, some context. Lately, heavy-duty transport has been facing increasing pressure: in Europe, trucks, buses, and coaches together produce around a quarter of all road transport CO2 emissions.

On the power consumption side, efforts are made to reduce aerodynamic drag, as it is responsible for more than half of the power required to drive a truck at highway speeds.
Truck aerodynamics

But improving truck aerodynamics is not easy: typically, trucks and trailers are bulky objects that have been stretched to make use of every cubic centimeter that is allowed by road regulations, such as maximum length, height & width. It’s not hard to see that trucks are not exactly super streamlined, but exactly how bad is it?

Aerodynamic efficiency is expressed via the drag coefficient Cd. If you want to learn more about the drag coefficient, just watch our separate movie on this. In short, lower is better with the Tesla model 3 at 0.23 and a conventional truck between 0.5 to 1. So when Tesla claimed 0.36 for their Tesla Semi truck, we jumped up and wanted to know more.

3D model
We called Elon Musk and asked him to send us a 3D model of the truck within 2 weeks. But he’s not too good with deadlines and we didn’t want to wait, so we asked our partner engineering agency Voxdale to build a 3D model for us instead.

Results
And believe it or not, we got a drag coefficient of 0.35 for the Tesla Semi truck! You can argue that we didn’t use the exact geometry for example, but even compared to our optimistic conventional truck it featured a 20% drop in aerodynamic resistance! That’s over 10% reduction in fuel consumption or 5000 liters of fuel per year!

Let’s start at the front: the vertical frontal face of the boxy conventional truck causes a huge pressure build-up on this entire surface, as the air needs to take a 90° turn to get around the cabin, either over the top or around the sides.
To provide smoother escape routes for the air, the Tesla Semi’s cabin features a strong backward inclination angle and large smooth corners around the sides of the cabin. This allows for a much more gradual evacuation of incoming air and thus a lower pressure buildup.

On road cars, the mirrors make up 2 to 5 % of total drag. On trucks, they are much bigger and Tesla decided to simply replace them with tiny camera’s mounted on aerodynamic wing-shaped beams! It’s quite easy to spot this difference by looking at the wake caused by both mirror setups!

If the roof spoiler is too wide or too high, this can leave a large wake and create unnecessary drag, as we can see at the top of our conventional truck. If it’s too low or narrow, the air will hit the square front of the trailer, causing local pressure to build up and separation downstream. Tesla made sure the Semi cabin fits nicely with its trailer: they were able to do so by extending the side spoilers all the way to the trailer and by leaving just enough space in top view for the trailer to rotate.

The wheels. Covering the front wheels is quite difficult, as they need room to turn in corners, but the rear wheels of the Tesla Semi have been shielded to create a smoother airflow.
Should they stop there? Of course not! The trailer itself can be optimized a lot as well, with side skirts and flaps at the rear for example. There’s plenty of after-market equipment already out there. 

You can argue that in the end, it’s the CO2 emission per unit of cargo that matters and that the Semi’s longer cabin reduces the available cargo space in its wake. But then again, this depends on local regulations and it’s not a coincidence that the European Union is increasing the allowable length.
 
They have already triggered others to come up with innovative concepts, like the Ford F-Vision, for example.

Credits: 
Tesla: https://www.tesla.com/
Mercedes: https://www.mercedes-benz.com/en/
Ford: https://www.ford.com/

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