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Error: Data source, file not found ERROR Hyperstudy-FluxMotor

User: "Roberto_"
Altair Community Member
Updated by Roberto_

Hello,


I am doing Hyperstudy simulations of FluxMotor cases and I get many errors from “Error: Data source ((ds_)) file not found” (see image)

 

I would like to know how to improve this. If it is due to PC requirements problems, not enough memory,  or another cause. ( I have 16Gb, Intel Core i7-3720  procesator 2.6 GHz, running 200 simulations at time)


Please if you could give me a hint, since I am getting only 30% of the simulations Success, and it is time that I am losing.

 

Another question: There are cases where there is an Failture in 'Execute', but in 'Extract' is shown as 'Success' (see image). How is that possible?

 

Thank you very much in advance.

 

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    User: "Roberto_"
    Altair Community Member
    OP
    Updated by Roberto_

    The cause of the error is that when the software is trying to find the file hst_output.hstp
    of the simulation, it does not appear  because tere was not created (not in the folder ie: \ run__00092)

    and it gives an error message in that folder inside a file task__exe_err.txt:

     

    ie:

    ' The test Performance mapping, Sine wave, Motor, Efficiency map failed due to the following problem:

     

    Cause : Unknown error

     

    Type : Unknown#100.18.39'

    User: "RECEP YETİM"
    Altair Community Member
    Updated by RECEP YETİM

    hello roberto;

    What's the solution

    User: "Diana_38240"
    Altair Employee
    Updated by Diana_38240

    Hi Roberto,

    As per the question of some failed runs, I think these are all unfeasible geometries in FluxMotor. Indeed, depending on the design variables bounds there may be "conflicts" in the geometry model leading to unfeasible design and so failed analysis. You can see more details about the error in the task_exe_stderr file available in the run folder.

    - If you are running a DOE (screening type), I'd suggest you to change the bounds so that you are able to collect more successful runs.

    - If you are running an optimization, you can keep your bounds. I'd suggest you to duplicate the optimization in order to add more runs and continue the optimization. Note that you can filter and reuse the successful runs from another approach.

    Hope it helps.

    Regards