Crash-test and image correlation: how to measure seat deformations and follow the dummy’s movements

  • By Alex Chang, Project engineer
  • Feasibility study: application of EikoTwin tools for a crash-test
  • Virtual test – DIC measurement – comparison test calculation
Alexx Illustration Minimalist Of A Dummy On A Seat Being Flung C308c7d2 E736 4198 8ed0 E2aeece1339e

Crash-tests are a crucial step in the development and certification of products, especially for the automotive, aeronautical and railway industries. These tests simulate collision or impact scenarios in order to evaluate the resistance and safety of products. Among the equipment used to perform these tests is the reverse catapult, which is a device that projects an object, in this case the dummy and its seat, at high speed, creating a force pulse that simulates a high-intensity impact. To measure the deformations of a seat during an crash-test, localized strain gauges have long been used. However, these gauges do not allow to measure the whole deformation field of the seat. Therefore, image correlation has been proposed to measure the seat deformations. This measurement also allows to follow the displacements of the dummy from targets strategically positioned on some parts of its body. The interest is to use the same camera system to measure the seat deformations and the mannequin displacements by tracking markers. Image stereo-correlation is used to measure the deformations at various places of the seat, in particular to control a possible weakness detected by calculation, to adjust the dimensions of the components according to the measured constraints, or to provide data for the calculation in the complex zones to be modelled or simulated.

In this crash-test case study, we used EikoTwin Virtual software to create a virtual crash-test environment, position the stereo camera system, and record images of the test. Then, we processed the images with EikoTwin DIC software to calculate the displacements of the dummy and the deformations of the seat.


Creation of a virtual crash-test with EikoTwin Virtual for image correlation

Virtual test principle

In the context of the creation of virtual tests, the use of modeling and 3D rendering software is essential. From this point of view, the Blender software, initially developed for the animation film industry, proved to be a particularly interesting tool for our use. It allows to create cameras with all the necessary characteristics, to position them, to photograph and to export images with a realistic rendering of materials and lights. Although Blender was originally intended for the animation industry, we have used this software to convert it into a tool suitable for image correlation and the creation of virtual tests.
EikoTwin Virtual consists of the ModelConverter tool and the BlenDIC add-on. ModelConverter allows converting a model and simulation results created in a finite element software such as Abaqus or Hyperworks into VTK format that can be imported into Blender. The BlenDIC add-on integrates the necessary tools in Blender for the creation of virtual tests.

Crash-test image correlation
Figure 1: Aesthetic synthetic image on the right created in Blender from the scene on the left.

We created a simplified model of a mannequin on a seat using Abaqus, to which we applied stresses to simulate displacements similar to those of an crash-test. Then we imported this simulation into EikoTwin Virtual.

Crash-test image correlation
Figure 2: Simulation of a shock test on Abaqus

EikoTwin Virtual: speckles & Markers

First, we applied a speckle on the seat in order to allow deformation measurements by image correlation. Markers were also placed on certain areas of the mannequin (head, shoulder, hip, knees, ankle) to follow their movements during the test.

Crash-test image correlation
Figure 3: Application of speckles and targets

EikoTwin Virtual: camera positioning

The two cameras are positioned in the space taking care to cover the entire area of interest. A specific angle of 30┬░ is respected between these cameras and the zone of sharpness is identified.

Crash-test image correlation
Figure 4: Positioning of the cameras
Crash-test image correlation
Figure 5: Positioning of the cameras

EikoTwin Virtual: camera views

The images captured by the two cameras are rendered in real time on Blender.

Figure 6: Blender rendering of the two cameras

Blendic: speckles: size & resolution

Taking into account the resolution and the field of view of the cameras, the optimal size of the speckles can be determined (here 2,5 mm). It is important to have several spots per mesh element as well as several pixels per spot to allow convergence in image correlation, as can be seen in the images.

Crash-test image correlation
Figure 7: The characteristic size of the speckles

EikoTwin Virtual: generation of virtual images of crash-test for image correlation

Crash-test image correlation
Figure 8: Images of the virtual impact test generated by EikoTwin Virtual

The last step in the creation of the virtual trial on EikoTwin Virtual is to generate the virtual images and export them.

Validation of the feasibility of the measurement with the EikoTwin DIC software
EikoTwin DIC: post-processing of the virtual images

After obtaining the test images, the next step is to use the EikoTwin DIC software to evaluate the convergence of the image correlation calculations. This step is critical to verify that the resulting images are able to accurately measure the deformations and displacements of the part. After importing the images and mesh into EikoTwin DIC, a crucial step is to perform the camera calibration. This step calculates the projection matrix of both cameras from the images. 

Once this step is completed, the simulation mesh can be projected onto the images to allow the measurement of displacements and deformations on the part.

Figure 9: Calibration and reprojection of the simulation mesh

Measurement results by image correlation of the crash-test
EikoTwin DIC: displacement calculation | results

Once the calibration was completed, the displacement calculations were performed and here are the results obtained:

Figure 10: A projection of the displacement field on the camera images
Figure 11 Evolution of the displacement field of the seat and the displacement of the markers as a function of time
Figure 12 Evolution of the seat displacement field as a function of time
Figure 13 Evolution of the seat deformation field as a function of time

EikoTwin DIC: comparison test / calculation | displacements

With the EikoTwin DIC software, it is possible to directly visualize the displacement difference field between the test and the simulation. Since the virtual test is created from the simulation, theoretically the differences should be zero. This difference therefore informs us about the accuracy of our measurement and the minimum uncertainties that could be encountered in a real test.

Figure 14 Evolution of the field of differences in seat displacements as a function of time (video)

Figure 14 Evolution of the field of differences in seat displacements as a function of time
Figure 15: Evolution of the seat deformation difference field as a function of time

EikoTwin DIC: tracking of markers

Another interesting feature of the EikoTwin DIC software is the tracking of markers. In the first step, we placed markers on the mannequin to measure its movements. By importing the images into EikoTwin DIC, it is possible to indicate the position of the markers in each image and to measure their displacement over time.

In the software interface, the calculated point for the marker and the result curve can be seen in the 3D view. The results for the head marker are plotted for the displacements along the X and Z axes as a function of time, as well as the trajectory of the head by plotting the Z displacements as a function of the X displacements. It is possible to compare the results between the tests and the calculations on the graphs. 

EikoTwin DIC Suivi De Marqueurs
Figure 16: Marker tracking

Hyperworks export

The last step in EikoTwin DIC, exporting the results. It is possible to export the results in different formats to suit different modeling software. The results can then be imported into HyperWorks, as shown here. 

Screenshot 2023 05 04 Alle 13.06.22
Figure 17 Import of DIC measured fields into HyperWorks


In the context of a shock test, we have written this timeline which presents the dialogue between test and calculation.
The timeline has two stakeholders: the Design Office and the Test Laboratory. The Design Office has performed the simulation of the crash-test and wants to verify and improve the results of their model They therefore need the laboratory to carry out a real crash test. The measurements are carried out with several cameras. To avoid difficulties in positioning these cameras during the real test, the design office and the laboratory carry out a pre-study together with EikoTwin Virtual. This one-time step allows to specify the test campaign and to reduce the risks, and should only be done once.  On the day of the test, an additional step is added to the process: the application of a speckle to perform the image correlation.
The laboratory then sends the images to the design office for post-processing of the data and comparison between the real test and the simulation with EikoTwin DIC. Finally, the design office can use the test results to check and, if necessary, update the simulation with EikoTwin DigitalTwin.

Figure 18: Timeline Dialogue Test Calculation


In summary, this paper presents a feasibility study on the use of EikoTwin tools for crash-testing. The use of digital image stereo-correlation allows for the measurement of the entire seat deformation field and the tracking of the dummy’s displacements from targets strategically positioned on certain parts of its body. The virtual test created with EikoTwin Virtual was used to simulate images of displacements similar to those of an crash-test, and these images imported into the EikoTwin DIC software were used to measure seat deformations and dummy displacements with high accuracy.
The results obtained are promising and show the potential of EikoTwin tools to improve the efficiency and accuracy of crash tests in the automotive, aerospace and railway industries. The use of these tools could lead to a better understanding of product deformation and failure mechanisms, reduce development costs and time.
In sum, this feasibility study is a step towards the wider use of EikoTwin tools in industry, and opens up new opportunities for innovation in crash testing.


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