Wheel Loader Simulation with romAI
Altair EmployeeOverview
System simulation can support the design process by estimating the loads and stresses on critical components ensuring the desired performance. Can Artificial Intelligence (AI) help us to speed-up the study by replacing the DEM system with a more time efficient but still accurate Reduced-Order Model?
In this demo problem, romAI is used to create a reduced order model of more expensive EDEM model. Once the ROM is available, MotionSolve simulations run faster, thus enabling users to run multiple iterations within a short time.
Pre-Requisite
The files used for this particular example is found in the attachments (Wheel_Loader_MS_EDEM_romAI_2024.zip).
Usage/Installation Instructions
Step 1: Create the EDEM model
Export the geometries interacting with the bulk material from MotionView, and import into EDEM. You can also do this by enabling the 'Coupling Server' on EDEM and adding the 'EDEM' subsystem in MotionView and selecting required graphics.
Generate the particles in EDEM and setup the motions.
If you are new to EDEM, check out EDEM Tutorials to learn more about how to setup an EDEM simulation.
Extract the data required from the simulation. Also make sure to extract the forces and the positions of the bucket. These data will be required for the romAI coupling. An example is shown here:
Step 2: Run multiple simulations for training data
Run multiple EDEM simulations with different velocities and rotation speeds at various times. This will be used as the training data for your reduced-order model in romAI.
In this example, 10 cases were run. You need to make sure that the cases cover a wide range of scenarios.
Extract all the required data for all the simulations run.
Merge all the data into one csv file with the same one title row and all the data written one below the other without any spaces. You can use an Altair Compose script to achieve this.
Step 3: Create the Reduced Order Model
Altair TwinActivate is the tool used for creating the reduced order model. Go to Modeling->romAI Director.
Import the merged data file for training. Choose appropriate inputs for your reduced order model which will replace EDEM in an EDEM-MotionSolve coupled simulation, and instead use a romAI-MotionSolve coupling. Since the romAI model is replacing EDEM, it needs inputs like the positions and velocities of the equipments, and the romAI model will give the forces and torques as outputs. An example is shown here:
Choose appropriate number of hidden layers and the neurons in each layer along with the epochs for your reduced order model training. (This is not an easy choice, and trial-and-error is involved, or you can use the Auto-Exploration option for romAI to explore the right neural network parameters.)
Save your Reduced order Model.
Step 4: Create a ROM subsystem in MotionView
Create a ROM susbsystem, so that it can be used in TwinActivate. Make sure to have the outputs in this subsystem as the outputs from your reduced order model created in the above step.
To know more about creating ROM susbsystems in MotionView, please refer here: https://help.altair.com/hwsolvers/ms/topics/solvers/ms/couple_motionsolve_with_activate_r.htm
Step 5: Create a romAI MotionSolve coupled block in TwinActivate
In the palette browser of TwinActivate, go to Palettes->Activate->CoSimulation->MotionSolveSignals, and import the MotionView model created in Step 4.
Next, go to Palettes->romAI and import the romAI model created in Step 3.
Connect the two models in the appropriate manner. An example is shown here:
Run the coupled simulation in TwinActivate by clicking Simulation->Run Simulation.
Step 6: Review Results
In the case of the wheel loader, the boom joint forces are of importance, and a comparison is drawn between the romAI-MotionSolve model and the EDEM-MotionSolve model. The difference observed in the maximum force was less than 7.4%.
The VonMises stresses were also plotted for certain critical elements and compared between the two simulations. The difference in the maximum stress observed here was less than 1.3%.
Post-Requisite
You can also find a detailed YouTube video on the workflow here: https://www.youtube.com/watch?v=aic1GX1YX-4