@ Gayatri Bajpai.. Thanks for your efforts and making these suppurb illustrative videos. I have one question, you just used half equation of that used in paper , What about the remaining part? Thanks in anticipation
amazing, thank you. Would it be possible to get any information for the determination of Johnson Holmquist Ceramic parameters? I am finding it difficult to find references of the breakdown.
Thank you for watching my video. Ofcourse you can find all the parameters for unknown materials means you don't know the name of the material. But you are having the material sample. You can do the experiment and find the stress strain graph at different strain rates. Then, C and P values can be find through stress - strain graph at different strain rate.
What is the material MAT 003? If you are doing test at high strain rate and at different temperatures other than room temperature then it's required to put the C and P values.
There are number of material models. Cowper Symonds is having bilinear constant while JC is having non linear curve. Generally, most of the analysis softwares are having both material model.
Actually parameters estimation problem boils down to an optimisation problem where one have to search for a minima in all the possible parameters domain. Machine learning algorithms can be easily deployed to search these minima as error function of varying parameters are continuous in nature. Gradient descent could be a first candidate one can approach but genetic algorithm might give faster convergence due to its inherent parallelism.
great explanation...
Thank you
Clear, thanks for sharing ji
Thank you
Thank you very much for such a clear explanation. Can you please share the referred journal paper?
Thank you for watching my video. It's given in description box.
@ Gayatri Bajpai.. Thanks for your efforts and making these suppurb illustrative videos. I have one question, you just used half equation of that used in paper , What about the remaining part? Thanks in anticipation
Half equation means
amazing, thank you. Would it be possible to get any information for the determination of Johnson Holmquist Ceramic parameters? I am finding it difficult to find references of the breakdown.
Thank you for watching my video. I am currently working on that. When I gain confidence, I will created a video regarding JH parameters evaluation.
How to get C& P value for unknown material . Where only know item is tested engg stress and strain
Thank you for watching my video. Ofcourse you can find all the parameters for unknown materials means you don't know the name of the material. But you are having the material sample. You can do the experiment and find the stress strain graph at different strain rates. Then, C and P values can be find through stress - strain graph at different strain rate.
how to do a isotropic hardness diagram from stress strain result using excel/matlab?
hey can you please share which paper are you using as ref.... i will be grateful
I have given the paper link in the discription box
Thank u madam....👍
Hello madam, is it compulsory to mention P and C values in Ls dyna MAT 003?
What is the material MAT 003? If you are doing test at high strain rate and at different temperatures other than room temperature then it's required to put the C and P values.
Very nice👍👍
Thank you
Upload video on regular basis
sure.
Very nice and informative. May you tell difference between cowper symonds material model and j c model.
There are number of material models. Cowper Symonds is having bilinear constant while JC is having non linear curve. Generally, most of the analysis softwares are having both material model.
@@scienceandtechnologybygaya3535 Thanks a lot.
Can you explain how parameter estimation done using matlab by genetic algorithm
Actually parameters estimation problem boils down to an optimisation problem where one have to search for a minima in all the possible parameters domain. Machine learning algorithms can be easily deployed to search these minima as error function of varying parameters are continuous in nature. Gradient descent could be a first candidate one can approach but genetic algorithm might give faster convergence due to its inherent parallelism.