Based on a logistic regression approach, a model was developed using the explanatory variables log([NO3-]), log([NO2-]), and temperature to estimate the probability of pitting in a carbon steel exposed to high-level radioactive waste. Pitting susceptibility data obtained by the two techniques of cyclic potentiodynamic polarization and coupon immersion were separately and jointly analyzed with the model. Similar predictive ability is seen for equations based on both electrochemical and coupon immersion data. Using the theory associated with the determination of confidence intervals for the estimated probability, a methodology was developed to provide a lower bound for the nitrite concentration which inhibits pitting, i. e., which holds the estimated probability of pitting to a reasonably low level of 0.05.

Subject
Pits, Immersion tests, Inhibitor performance, Slurry, Nitrites, Probability, Nitrates, Corrosion inhibitors, Pitting, Carbon steel, Immersion, Corrosion coupons, Coupons
Keywords:
Nitrite, pitting, logistic regression
© 1994 Association for Materials Protection and Performance (AMPP). All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means (electronic, mechanical, photocopying, recording, or otherwise) without the prior written permission of AMPP. Positions and opinions advanced in this work are those of the author(s) and not necessarily those of AMPP. Responsibility for the content of the work lies solely with the author(s).
1994
Association for Materials Protection and Performance (AMPP)
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