
#### Different approaches

The aerodynamic design of small aeroplanes involves two main methods (prior to wind tunnel testing & flight testing). The first uses the theory of 2D airfoils, while the second focuses on 3D <Link href="/videos/computational-fluid-dynamics-explained/dyiREvdc4Gg">Computational Fluid Dynamics (CFD)</Link> simulations.

<ImageWithCaption
  src="/assets/images/cessna_210j-centurion.jpeg"
  alt="A Cessna 210J Centurion. CREDIT: Arpingstone"
  width="700"
  height="470"
  positionCenter={true}
/>

#### 2D airfoil theory

Since 1915, when the <ExternalLink href="https://history.nasa.gov/SP-4406/chap1.html">Advisory Commission for Aeronautics</ExternalLink> was formed, 2D airfoils have been extensively researched and developed. This commission later became the National Advisory Commission for Aeronautics (NACA) and any airfoils created under this program were called NACA airfoils. Still today, aeroplane wings are often 3D extrusion elements based on 2D airfoils from the NACA database. Check out our guide to the <Link href="/blog/best-aerodynamic-resources">best aerodynamic resources</Link> where you can find databases of airfoils, such as Airfoiltools.

#### 3D CFD simulations

At the other end of the spectrum is 3D CFD. These are essentially simulations that capture the behaviour of airflow as it interacts with complex 3D objects. They are an excellent method of learning how much the flow deviates from the predicted 2D flow along a selected airfoil. These simulations can also be utilised to understand the intricate flow around other elements of an aeroplane such as the landing gear, cockpit and wing fuselage.

#### Lift off

An important aspect of determining the lift capacity of a wing based on 2D airfoils is the wing span. The 2D lift and drag properties of an airfoil are often provided for a section of an ‘infinitely wide’ wing. This means that end effects, such as <Link href="/videos/how-do-winglets-improve-aerodynamics/ubvr1w1hH80">wing tip vortices</Link>, where air crosses from high to low pressure via the side edge of the wing, are not taken into account. Therefore, the lift generated per unit length by a finite wing is much smaller than an infinite one, as the wing loading near the tips and even further away can be significantly reduced.

To counter this loss of lift, winglets can be implemented which, in their simplest form, are vertical flanges preventing the air from crossing and curling around the wing tip. This is relevant for all types and sizes of wing, even for fixed wing drones.

<Link href="/cases/sense-fly-increasing-drone-flight-time">
    Increasing the flight time of a fixed wing drone case study
  </Link>

#### Optimization

To demonstrate that a small airplane can also benefit from optimized winglets, we used AirShaper’s <Link href="/blog/aerodynamic-shape-optimization">Aerodynamic Shape Optimization</Link> software to optimize the winglets of a Cessna 210J Centurion.

We asked the software to morph the wing tip to improve the amount of lift generated by the wing and the results are shown below. The software designed a new 3D shape for the winglet which improved the lift of this section of wing by almost 60% with a minimal increase in drag.

<Optimization
  objectiveValues={[1, 1.033949, 1.108846, 1.224037, 1.381086503, 1.570511887]}
  title="Normalized Lift Coefficient [+]"
  project={'cessna/wingtip'}
  views={['left', 'front', 'top']}
/ >

--


<LazyIframe src="https://app.airshaper.com/simulations/cessna-public-3d-model-design-advice-for-lower-drag/embed" width="100%" height="650" title="Test" />

As always with CFD simulations, the results need to be validated with wind tunnel or real world testing and at different angles of attack. There are also other factors such as manufacturing constraints and aesthetics that need to be evaluated before a design can be put into production. However, the software was able to optimize the complex 3D shape of a winglet quickly and robustly; providing an incredible tool that allows designers the freedom to create new, innovative and exciting shapes.


AirShaper Aerodynamics Shape Optimization software was used to optimize the shape of a winglet of a Cessna 210J Centurion

Optimizing the shape of a winglet

Cessna winglet


Superfast Matt is the YouTube channel of Matt Brown, an Automotive Engineer who has spent the last decade working at Tesla, Apple and NASCAR. Today, he spends his time designing and building some seriously whacky, but innovative, vehicles. He has made a <ExternalLink href="https://www.youtube.com/watch?v=IU98_D2sE1U&ab_channel=SuperfastMatt">motorcycle-powered car</ExternalLink>, integrated a <ExternalLink href="https://www.youtube.com/watch?v=DxxaHYlCuN8&list=PLoTU9_iCGa6i_C38pwQyg0pBGoov76NNv&ab_channel=SuperfastMatt">Tesla Model 3 powertrain into a 1950 Jaguar</ExternalLink> and now he is building a land speed record car, by himself.

<YouTubeEmbed videoId="6ebYRigOu1g" />

#### The challenge

The faster a vehicle moves, the more air it has to push through and the higher it’s drag. In fact, the aerodynamic drag forces acting on a body increases with the square of velocity.

To overcome this aerodynamic resistance, you need more power. However, the power required to accelerate a vehicle through air is equal to the product of this drag force _and_ the velocity. So, the power you need scales with the cube of velocity. In other words, to travel twice as fast, you need eight times more power.

<Link href="/videos/what-is-aerodynamic-drag/DbIIw-WryHY">
    What is aerodynamic drag?
  </Link>

This is why land speed record cars look like cigars on wheels. Minimizing the frontal surface area and making the vehicle as streamlined as possible is the only way to achieve the high speeds in land speed competition.

#### AirShaper optimization

To help Matt optimize the aerodynamic efficiency of his land speed car, we introduced him to AirShaper and the capabilities of our <Link href="/blog/aerodynamic-shape-optimization">Shape Optimization algorithm</Link>.

In land speed competition, the regulations define several areas where the shape of the car can be modified. This includes the front of the nose, the top of the nose and the area ahead of the front wheels. After defining a few parameters, the AirShaper Aerodynamic Shape Optimization algorithm automatically morphed the shape of these areas to reduce the overall drag of the car.

#### Optimizing the front of the nose

At the nose, the original design features a fairly short nose with a relatively "flat" front. When the air hits this flat front, the pressure builds up (all the way to the stagnation pressure).
As shown below, the software suggested increasing the length of the nose to create more of a teardrop shape. This reduces the size of the high pressure area and provides a smoother "piercing" of the air, resulting in a drag reduction of 1.7%.

<Optimization
  objectiveValues={[
    0.17926594759, 0.179257476645, 0.178558485887, 0.177903294026,
    0.177276012223, 0.177225713226, 0.178564960447, 0.176923972965,
    0.176885035508, 0.176778591969,
  ]}
  title="Drag Coefficient [-])"
  project={'sfmatt/nose'}
  views={['left', 'front', 'top']}
></Optimization>

#### Optimizing the top of the nose

At the top of the nose, the air passes in between the wheel arches. Along this trajectory, the air will accelerate and decellerate. This also leads to variations in pressure, as pressure and velocity are linked to each other via the Bernoulli equation.
The algorithm has altered the height of the area in between the wheels long the length of the car. As a result, the pressure pattern is now smoother. This reduction in variation for pressure and velocity leads to lower energy losses, reducing the drag by 0.3%.

<Optimization
  objectiveValues={[
    0.148654374585, 0.148478425871, 0.148394019205, 0.148310484031,
    0.148345862206, 0.148354582471, 0.148322805987, 0.148263656876,
    0.148184384884, 0.148370077895,
  ]}
  title="Drag Coefficient [-])"
  project={'sfmatt/between_wheels'}
  views={['front', 'top']}
></Optimization>

#### Optimizing the area in front of the wheels

At the front, the air hits the exposed part of the wheels, which causes the air to 'splash out' around the wheels. Production cars manage this affect by using air deflectors. These are miniature bumps that help to push the air out of the way before it hits the tire.

This is exactly what the shape optimization suggested. Without any external input, the algorithm identified that this was a potentially disastrous area for drag and so morphed the shape to act like a deflector and minimise drag.

<Optimization
  objectiveValues={[
    0.16358104147014013, 0.16354635312964472, 0.16350143817513574,
    0.1634757895167319, 0.16347201849739743, 0.16347699390327175,
    0.16348450830131656, 0.16348751902587672, 0.1634874397000019,
    0.1634871752986611,
  ]}
  title="Drag Coefficient [-])"
  project={'sfmatt/wheels_bottom'}
  views={['left', 'front', 'bottom']}
></Optimization>

Within just a few days of simulation time, Matt had a fully optimized 3D model, which he could then import into his own CAD software. This allowed him to iterate the design, taking into account other constraints such as manufacturing and packaging.

Overall, AirShaper's Aerodynamic Shape Optimization software reduced the drag of Matt's land speed car by over 2%. This will help him develop an aerodynamically efficient car that is capable of achieving higher top speeds and hopefully, beating his competition.


Superfast Matt is the YouTube channel of Matt Brown, an Automotive Engineer who has spent the last decade working at places like Tesla, Apple, and NASCAR

Optimizing a land speed record car

Superfast Matt


#### The challenge

Climate change is slowly moving to the top of the agenda for most businesses and governments, with countless regulations and incentives now in place to reduce our impact on the planet. One sector that is making the most substantial changes is transport, with cars seemingly the main focus in the media. However, there is small mention of the efforts to improve the sustainability of truck, buses and coaches which make up around 27% of all road transport emissions in Europe. Therefore, reducing the emissions of this large group of vehicles through aerodynamic optimization and improved fuel efficiency could be the key to helping the transport sector in its mission to combat climate change.

<ExternalLink href="https://www.youtube.com/watch?v=s2QyP6n4Zxs&ab_channel=AirShaper">
    How the Vecto AirDrag tool can help cut truck and bus emissions
  </ExternalLink>

---

#### The status

For decades trucks have been designed to move cargo as efficiently as possible within a regulated design space, resulting in large box shapes that maximise the cargo area. However, these box shapes are not aerodynamically efficient which is why the drag coefficients of trucks range from 0.7 to 0.9. That’s significantly higher than most production cars, with some of the latest models such as the <Link href="/blog/tesla-model-y-aerodynamic-benchmarking">Tesla Model S</Link> achieving drag coefficients as low as 0.2.

---

#### Futuristic designs

With future regulation changes in the dimensions of trucks, increased packaging freedom and the reduced cooling needs of electric drivetrains, engineers now have much more freedom to try and minimise drag. For example, the <Link href="/videos/truck-aerodynamics-tesla-semi-explained/Km1NHe0ZsVo">Tesla Semi</Link> features a smooth transition from the truck to the trailer as well as covered wheels which help achieve a drag coefficient of just 0.35. Taking aerodynamic optimization a step further, the <Link href="/blog/beyond-tesla-semi-with-the-future-truck-2032">Betterflow Future Truck</Link> improved the underfloor aerodynamics to feed fresh air into the wake, further reducing drag. Initial Computational Fluid Dynamics (CFD) simulations suggest that the resulting drag coefficient of the Betterflow Future Truck is approximately 30% lower than the Tesla Semi.

<ImageWithCaption
  src="/assets/images/air-channel.jpg"
  alt="The Betterflow Future Truck features a channel below the truck and trailer to feed fresh air into the wake"
  width="800"
  height="388"
  positionCenter={true}
/>

---

#### Realistic changes today

However, the Tesla Semi is not yet in production and the Betterflow concept is even further away from driving on our roads. Therefore, to reduce emissions now we need to optimize the aerodynamics and improve fuel consumption of existing fleets. This is precisely what manufacturers like Wabco and Transtex are doing. By integrating features such as <ExternalLink href="https://wabco-solutioncentre.com/optiflow-sidewings/">side wings</ExternalLink> and modifying the tail of the trailer to close the wake, manufacturers claim they can achieve over 10% fuel savings.

<ExternalLink href="https://transtex-llc.com/edge-elite-aero-system/">
    How the Edge Elite Aero System achieves 10% fuel savings
  </ExternalLink>

---

#### Further improvements

In most cases reducing the wake behind a trailer involves geometries that provide an “inward” momentum to the air so that it fills the wake. One method of doing this involves adding a tail to the end of the trailer. If done properly, this tail will guide air inwards and remain attached.

When the regulations don’t allow for such extensions, another technique is to add a small bump ahead of the trailing edge of the trailer. This pushes the air outwards initially and as the flow makes its way back inwards, it builds up “inward momentum” by the time it hits the end of the trailer. Such features are very sensitive to small changes in geometry. If the angle is too shallow it has a limited effect, whereas if the inward angle is too high, the flow could separate.

---

#### Automated optimization

AirShaper's <Link href="/blog/aerodynamic-shape-optimization">Aerodynamic Shape Optimization</Link> is a vital tool for creating geometries that result in maximum aerodynamic performance. The example below shows how the algorithm is optimizing the shape of the end of the trailer, with the results similar to what is currently being used today, such as the bump ahead of the trailing edge. A fascinating aspect of the software is that no previous information about such concepts was inputted into the algorithm, yet it still produced the same features.

This proves that optimization software can really inspire designers and engineers to create new and innovate shapes - which is going to be essential for developing trucks with less drag, lower fuel consumption and reduced emissions.

<Optimization
  objectiveValues={[
    0.343249792504, 0.342837444517, 0.343695721009, 0.343546545307,
    0.342336632606, 0.340953837021, 0.340815056272, 0.338991857199,
    0.335689107614,
  ]}
  title="Drag Coefficient [-])"
  project={'semi'}
  views={['left', 'rear', 'top']}
/ >

---


AirShaper Aerodynamic Shape Optimization software has automatically modified the shape of the Tesla Semi trailer to improve its aerodynamic performance and therefore reduce fuel consumption and emissions

A taste of the possibilities

Compare simulations to real-world data for accuracy and reliability

Cessna winglet

Superfast Matt

Tesla Semi Trailer

Unlock High-Performance Designs with Our Cloud-Based Aerodynamic Simulation Tool