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Luglio 21 2020

Optimising a Formula 1 aerodynamic wing by simulation

Metal additive manufacturing (AM) is widely used in Formula One, motorsport and racing to manufacturing complex parts in a short time. Powder Bed Fusion – PBF technologies, such as selective laser melting – SLM (also known as direct metal laser sintering – DMLS), are currently used to manufacture parts (e.g. exhaust systems, aerodynamic inserts and wings, pipes, roll hoops, etc.) in aluminium, titanium, Inconel and other high-performance Alloys. The main success factors driving the increased use of metal AM in motorsport are the maximum freedom assured during the design phase; and the possibilities of manufacturing lightweight parts, using complex geometries, and using lattice structures with controlled variable densities. Nevertheless, metal AM is not synonymous with perfection; it has its own limits and constraints. One of its critical issues is the distortions that occur to the part during the laser melting process. In particular, this happens with thin-walled titanium components, which frequently deviate from the nominal 3D CAD geometry despite stress-relieving treatments. The use of simulation tools to limit and compensate for the distortions can dramatically reduce the risk of scraps and delays in delivery, and the related costs.

This paper presents a joint project between ADDITIVA and a prestigious F1 Manufacturer for the production and optimisation of an aerodynamic insert in titanium Ti6Al4V. Production was optimised by identifying the best orientation for the parts and the best positioning for the support structures in the melting chamber, in addition to using the ANSYS Additive Print module, a simulation software useful for predicting the distortion of a part and for developing a new 3D compensated model that guarantees the best “as-built” quality.

 

The role of Simulation in DfAM

The Design for Additive Manufacturing (DfAM) guidelines support designers in achieving this objective, enabling them to understand the real strengths and weakness of the technology to maximise the first and limit the second. One aspect addressed by DfAM concerns the simulation of laser melting to predict and correct the distortions that can occur in parts during melting. The high energy density and, most importantly, the rapid solidification rates cause residual stress whose intensity depends on: the building strategy; the part’s orientation in the melting chamber; the presence/absence of support structures; the geometry, density, mass and distribution of the supports; and the thermal conditions. Residual stress induces distortions in the as-built part, even before the supports are removed, resulting in differences between the nominal dimensions of the 3D CAD model and the real shape and dimensions of the AM part. Manufacturers usually manage this critical issue with a “trial and error method”, or by taking decisions based on their own experience. However, if they are not correctly engineered, parts can be out of tolerance at the end of the process, meaning they are discarded, resulting in higher costs and longer delivery times. As a result, the prediction of and compensation for distortions is a fundamental objective. Knowledge of material properties is essential to understanding how the powder changes in the melt pool and how it creates the part, layer by layer. The first aspect occurs at a microscopic scale, while the latter occurs at a much larger scale. Hence, a multi-scale approach is required to predict the possible results of the AM process.

Modern CAE simulation tools offer new opportunities to add value and diversify a company’s services in this area by providing the ability to re-design the product from the beginning using advanced simulation tools that can accompany the entire product development process. Once the shape of the part has been defined, the designer and the manufacturer can shift their focus to the AM production process, to predict possible defects or non-conformities, and to better manage the parameters of the 3D printers. Simulation plays a decisive role thanks to modern techniques that can virtually reproduce the printing phase, analysing the complex multi-scale and multi-physical (thermo-structural) phenomena in a transitory manner. This phase becomes even more appealing when performed via a direct interface between the 3D printers and the simulation software, allowing the file in the print format to be read and the metallurgical quality (porosity, residual stress, anisotropy, etc.) of the material to be forecast.

 

Formula 1 aerodynamic wing challenges

The main factors driving the increased use of metal AM in motorsport and racing are weight reduction; maximum design freedom; the use of high-performance materials; and short lead times. One of the most important applications for AM in Formula One concerns aerodynamic inserts and wings, with their complex geometries, internal cavities, and thin walls. Thanks to its strength and stiffness, Titanium Ti6Al4V is the best material to use for heavily loaded aerodynamic structures like the one shown below.

Picture 1 – Aerodynamic wing for Formula 1 application

For a part like that, the most critical requirements concern:

  • Surface roughness (SLM/DMLS guarantees “as-built” surface roughness within the range of 5.6÷2μm Ra, meaning that several finishing processes are required to achieve at least 1.6÷2.4μm Ra)
  • Tolerances of 0.6 mm
  • Part weight (the component must be positioned to allow the support structures to be perfectly removed during post-processing so that no residue will alter the weight. It is vital to establish the correct position for the part inside the melting chamber to avoid generating non-removable supports, particularly inside cavities that may be not accessible after printing is complete).

Motorsport and racing impose short lead times; this means that parts must be printed properly at the first attempt without distortions that generate scraps. This is the core challenge for both the manufacturer and for the simulation software, which must be able to model the melting process without excessive computing time.

 

Optimisation of the AM process

The process to evaluate the best configuration for the part to be printed was developed as follows:

  1. Printing a reference shape and measuring the distortion to calibrate the model
  2. Executing a set of rapid simulations to identify the best orientation/positioning for the part inside the build platform
  3. Analysing the distortion tendency (maximum and average displacement)
  4. Analysing the processing time

1.Model Calibration

In order to configure the 3D printing machine set-up and the laser parameters identified to melt the aerodynamic wing part, a cross-shaped sample was printed using a CONCEPT LASER M2 system. This sample was measured to establish its deviations from the nominal ones used by the software to calibrate the model’s response. This approach is used in the preliminary stages of modelling to accelerate computing time while ensuring that the model suitably represents the process.

2. Orientation and positioning

Four positions were developed for the part, as shown in Picture 2. Two of them (2 and 3) were selected to minimise the printing time (minimum job height), while the other two (1 and 4) were expected to result in a minimum mass for the supports in the critical areas of the part. The software enables the maximum displacement of the part to be estimated, and the areas where that distortion is expected to be identified. Table I summarises the results of this screening phase (the qualitative levels of distortion and the workload necessary to remove the supports was assessed by the manufacturer based on experience).

Picture 2 – Comparison of different orientations

 

Orientation no. 2 had the maximum expected displacement, while Orientation no. 3 had the minimum one. Orientation no. 3, however, would require a high mass of support structures that would be difficult, or even impossible, to remove. While the internal support structures could be left inside the cavities, this would unacceptably increase the weight of the part. Consequently, Orientations no. 2 and 3 were discarded and not investigated further.

Orientation no. 1 showed a maximum displacement that was higher than the one of Orientation no. 4, yet, Orientation no. 4 had the maximum height in the Z-axis, leading to greater printing time and cost. This simplified model showed that neither Orientation no. 1 nor no. 4 fulfil the design requirement of a maximum distortion less than 0.6 mm.

When considering both the manufacturing times and the distortion tendency, however, Orientation no. 4 was the most promising candidate for printing: the increased printing time did not cause consistent variations in the total production cost, and the primary purpose of the project was to reduce the number of deformations.

 

3. Analysis of the distortion tendency

The third step consisted of developing a compensated geometry. ANSYS Additive Suite simulates the laser melting process, predicts distortions, and develops a new compensated geometry by reversing the distortion effects. The melting of this new compensated geometry should significantly reduce the distortions, resulting in a part as close as possible to the original 3D model.

Picture 3 shows the new compensated geometry. The maximum displacement of 0.70 mm was observed on the red surface. The slight difference from the analysis described in (B) was due to the simulation assumptions: in this case, to obtain a better estimate of the distortion, a finer mesh was used in addition to the actual scan pattern.

Picture 3 – Simulation results: (right) simulated distortion in printing orientation 4 and (left) automatic compensated geometry generation

 

The part was printed both using the uncompensated geometry and the compensated geometry for Orientation no. 4.

3D optical scanning was used to measure the surface of the part in three scenarios: after the melting process (with parts and support structures still attached to the build platform); after stress reduction; and after removal of the supports. The results of the dimensional measurements, shown in Picture 4, are in agreement with the simulation result in terms of position, maximum and minimum deviation from the nominal values, as well as the tendency towards improvement by moving the solution from four different orientations. The comparison between the simulation results and the 3D scans of the printed parts clearly shows how it is possible to obtain an accurate output through simulation, which can predict the location of the maximum distortions in the upper part of the component. Just from the preliminary simulations, it was possible to keep the maximum distortion below 0.59 mm. Compensation further improved the quality of the part, with a maximum displacement of 0.48 mm and a lower average and standard deviation of the absolute value of the distortions. These results were achieved with a single simulation iteration; better results could be achieved with more iterations in order to better estimate the effects of distortion, and thus generate a more effective compensated geometry.

 

Picture 4 – Distortion comparison between non-compensated vs compensated parts

 

Conclusions

Metal AM allows new complex parts to be designed and produced in a very short time. This is particularly true in demanding fields like motorsport and racing, where mechanical properties (elastic modulus and strength) are mandatory, with minimum manufacturing times to rapidly introduce new solutions for each race. This project has shown that it is possible to print complex parts that conform to design specifications through a correct understanding of the SLM/DMLS process and the use of simulation tools. Through rapid simulations on simplified models, it is possible to study the effects of different part orientations and to identify the most promising one in terms of the distortion tendency. This also makes it possible to identify areas affected by high displacements and, if necessary, to locally modify the support structures. Using a more accurate model, it is possible to predict the distortion range and generate a compensated geometry that allows parts closer to the nominal geometry to be manufactured. This approach has the potential to further extend the DfAM field, including not only classical topological optimisation, but also the design of parts and processes that minimise residual stress or distortion.

 

Antonio Vellata

antonio.vellata@additivalab.com, mobile: +39 388 326 9227