Creat membership Creat membership
Sign in

Forgot password?

Confirm
  • Forgot password?
    Sign Up
  • Confirm
    Sign In
Creat membership Creat membership
Sign in

Forgot password?

Confirm
  • Forgot password?
    Sign Up
  • Confirm
    Sign In
Collection

toTop

If you have any feedback, Please follow the official account to submit feedback.

Turn on your phone and scan

home > search >

Clustering of Self Powered Neutron Detectors: Combining Prompt and Slow Dynamics

Author:
Razak, Rihab A.   Bhushan, Mani   Belur, Madhu N.   Tiwari, Akhilanand P.   Kelkar, Mahendra G.   Pramanik, Mahitosh  


Journal:
IEEE Transactions on Nuclear Science


Issue Date:
2014


Abstract(summary):

The focus of this work is on clustering Self Powered Neutron Detectors (SPNDs) with different dynamic characteristics into smaller groups, with each group containing highly correlated SPNDs. In order to cluster the SPNDs correctly, we propose novel ways to compensate for the effect of different dynamic response characteristics. In particular, two types of SPNDs: (i) cobalt, which give a prompt response, and (ii) vanadium, which give a delayed response, are considered. We propose and compare three compensation methods to cluster both types of SPNDs together using their measurement data: (i) pure delay applied to cobalt SPND data, (ii) cobalt SPND data 'slowed down' to match the vanadium SPND dynamics by passing it through vanadium SPND transfer function, and (iii) vanadium SPND data 'speeded up' to match the cobalt SPND dynamics by passing it through the inverse of vanadium SPND transfer function. Based on extensive simulations, it is found that slowing down cobalt SPND measurements to match the vanadium SPND dynamics yields the best results. This method is then used to obtain clusters from data obtained from a nuclear reactor in India for both vanadium and cobalt SPNDs and the resulting clusters appear reasonable.


Page:
3635-3643


Similar Literature

Submit Feedback

This function is a member function, members do not limit the number of downloads