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Backward deformation optimization method

Can use Simufact forming to perform backward deformation optimization method for preform shape optimization in hot forging? 

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  • This is unfortunately not directly possible. We have "backward deformation" for predicting the initial blank of sheet forming operations in FTI Forming Suite. But there is nothing similar for bulk forming in Simufact Forming.

    But you can use Post Particles to do some thing at least a bit similar. The idea is to mark the desired final shape of the workpiece in the simulation result with particles and to track them backward to the initial preform. The marked area will be close to the optimized preform - as long as you do not need burrs or similar to control the material flow.

    Steps to do:

    1. Guess an initial shape and conduct a forward simulation. Better guess too big to avoid underfills, but not not too big either not to get to serve folds.
    2. Create an empty dummy process and assign the imported CAD geometry of the desired forged workpiece. Take care that the position matches the position of resp. in the simulation result of 1). Define surface particles on this ideal forged workpiece.
    3. Export the defined particles as CVS file without running a simulation before. Modify this in a 3rd party application of your choice to remove the first 4 columns and the header lines leaving only the 3 coordinate columns in the file.
    4. Open the simulation result of 1), go to the last result increment, create post-particles of the type "single points" and import the CVS file from 3).
    5. Wait until the backward tracking is done. If needed push the backward tracking to the pre-stages, too.
    6. Now you have the material that goes into the ideal forged workpiece marked in your preform. Theoretically you can omit all not marked material from the preform.

    You will have to repeat these steps a couple of time as the preform influences the material flow and a smaller preform will behave different. And your initial guess will have a huge influence. Try "long and thin" and "short and thick".

    I hope this helps,

    CB

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