Menu
Search
Filters
Close
Menu

Save 20% on select titles with code HIDDEN24 - Shop The Sale Now

09337 Evaluation of Prediction Tool for Sour Water Corrosion Quantification and Management in Refineries

Picture for 09337 Evaluation of Prediction Tool for Sour Water Corrosion Quantification and Management in Refine
Available for download
Product Number: 51300-09337-SG
ISBN: 09337 2009 CP
Author: Vishal Lagad, Russell D. Kane and Sridhar Srinivasan
Publication Date: 2009
Industry: Materials Selection and Design
$0.00
$20.00
$20.00
The Sour Water Joint Industry Program (JIP) has led to the development of new data and insights related to corrosion in H2S-dominated Ammonium bisulfide sour water systems, commonly found in a number of refinery processes. The JIP, termed as Sour Water Phase I, provided a new methodology and software prediction tool targeted towards predicting and quantifying corrosion in hydro-processing units, specifically reactor effluent air cooler (REAC) equipment and associated piping.

Based on comprehensive laboratory data, multiphase flow-modeling and numerical data interpolation, the Sour Water Corrosion Prediction Software (prediction tool) facilitates corrosion prediction, failure prevention, optimized material selection and safe operational practice as a basis for compelling cost saving and improved maintenance planning in refinery operations. This paper evaluates the efficacy of the JIP-based Prediction System when applied to real plant evaluation situations in a variety of refinery conditions. The paper also details appropriate methods of utilizing the data and functionality within the software tool to ensure optimized prediction accuracy. Case studies identifying pitfalls to avoid while using the software model are also provided along side comparison of predicted corrosion rates with measured rates from inspection. The case studies and trends presented demonstrate the importance of rigorous flow modeling and need for accurate characterization of effects of Ammonium Bisulfide NH4HS concentration and environmental parametric data variables in assessment of corrosivity of alkaline sour water systems.

Keywords: Reactor effluent air cooler, REAC, sour water corrosion, NH4HS, ammonium bisulfide, H2S, hydroprocessing, prediction model, refining, materials selection
The Sour Water Joint Industry Program (JIP) has led to the development of new data and insights related to corrosion in H2S-dominated Ammonium bisulfide sour water systems, commonly found in a number of refinery processes. The JIP, termed as Sour Water Phase I, provided a new methodology and software prediction tool targeted towards predicting and quantifying corrosion in hydro-processing units, specifically reactor effluent air cooler (REAC) equipment and associated piping.

Based on comprehensive laboratory data, multiphase flow-modeling and numerical data interpolation, the Sour Water Corrosion Prediction Software (prediction tool) facilitates corrosion prediction, failure prevention, optimized material selection and safe operational practice as a basis for compelling cost saving and improved maintenance planning in refinery operations. This paper evaluates the efficacy of the JIP-based Prediction System when applied to real plant evaluation situations in a variety of refinery conditions. The paper also details appropriate methods of utilizing the data and functionality within the software tool to ensure optimized prediction accuracy. Case studies identifying pitfalls to avoid while using the software model are also provided along side comparison of predicted corrosion rates with measured rates from inspection. The case studies and trends presented demonstrate the importance of rigorous flow modeling and need for accurate characterization of effects of Ammonium Bisulfide NH4HS concentration and environmental parametric data variables in assessment of corrosivity of alkaline sour water systems.

Keywords: Reactor effluent air cooler, REAC, sour water corrosion, NH4HS, ammonium bisulfide, H2S, hydroprocessing, prediction model, refining, materials selection
Product tags
Also Purchased
Picture for 10349 Prediction and Assessment of Ammonium Bisulfide Corrosion Under Refinery Sour Water
Available for download

10349 Prediction and Assessment of Ammonium Bisulfide Corrosion Under Refinery Sour Water Service Conditions-Part 2

Product Number: 51300-10349-SG
ISBN: 10349 2010 CP
Author: Richard J. Horvath, Vishal V. Lagad, Sridhar Srinivasan and Russell D. Kane
Publication Date: 2010
$20.00

This Phase II work in NH3-dominated sour waters studied the impact of several process variables including NH4HS concentration, NH3 partial pressure, H2S partial pressure, temperature, cyanide concentration, and velocity (wall shear stress).
Picture for 06576 PREDICTION AND ASSESSMENT OF AMMONIUM
Available for download

06576 PREDICTION AND ASSESSMENT OF AMMONIUM BISULFIDE CORROSION UNDER REFINERY SOUR WATER SERVICE CONDITIONS

Product Number: 51300-06576-SG
ISBN: 06576 2006 CP
Author: Richard J. Horvath, Michael S. Cayard, Russell D. Kane
Publication Date: 2006
$20.00

This paper summarizes results of a joint industry program (JIP) to address ammonium bisulfide (NH 4 HS) corrosion in H 2 S-dominated alkaline sour waters typically found in refinery services such as the reactor effluent air cooler (REAC) systems of hydroprocessing units.
Picture for Prediction and Assessment of Ammonium Bisulfide Corrosion Under Refinery Service Conditions - Part 3
Available for download

Prediction and Assessment of Ammonium Bisulfide Corrosion Under Refinery Service Conditions - Part 3

Product Number: 51317--8929-SG
ISBN: 8929 2017 CP
Author: Richard Horvath
Publication Date: 2017
$20.00

Summarizes results from Phase III of the joint industry program (JIP) on refinery alkaline sour water (ammonium bisulfide) corrosion. Phase III included a comprehensive engineering analysis of data from all three phases of the Sour Water JIP.
Categories
Industry
Recently viewed
Popular tags
View all

Association for Materials Protection and Performance

© AMPP All Rights Reserved.
Membership Terms of Content Use
Contact Customer Support