Rheological identification of jetted fluid using machine learning g. maîtrejean, a. samson, d. roux, and n. el-kissi univ. grenoble alpes, cnrs, grenoble inp*, lrp 38000 grenoble,

HIGHLIGHTS

• who: G. Mau00eetrejean and colleagues from the CNRS France have published the article: Rheological identification of jetted fluid using machine learning G. Mau00eetrejean, A. Samson, D. Roux, and N. El-Kissi Univ. Grenoble Alpes, CNRS, Grenoble INP*, LRP 38000 Grenoble,, in the Journal: (JOURNAL)
• what: The aim of this paper is to identify the rheological properties of a fluid jetted using Continuous Inject Printing (CIJ) process by comparing the morphology of the aforementioned jetted fluid to a dataset of known (rheologically-speaking) fluid jets morphologies. properties of a fluid by the viscosity the surface tension . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.