Welding Journal - April 2012 - (Page 113-s)

Predictive and Measurement Methods for Delta Ferrite Determination in Stainless Steels A chronological review from the first predictive diagram in 1920 up to the latest mathematical model is presented BY M. ASUNCIÓN VALIENTE BERMEJO ing during solidification. However, for specific applications or service conditions, it is necessary to impose a maximum δ-ferrite content; for example, for hightemperature conditions or thermal cycles (350°–900°C) when δ-ferrite can suffer from spinodal decomposition or be transformed into (σ) sigma-phase, causing embrittlement and a decrease in corrosion resistance. Chromium and molybdenum segregation enriches σ (sigma)-phase formed at the austenite/ferrite (γ/δ) grain boundaries, causing a depletion of these elements in the matrix and raising the material’s vulnerability to corrosion. It is also necessary to establish a maximum δ-ferrite content in the case of stainless steels used under cryogenic conditions, as it influences the material’s ductility and the lowtemperature toughness. Some authors such as Brouwer (Ref. 1), and especially Lefebvre (Ref. 2), present detailed guides of the appropriate δ-ferrite contents according to the application for which the stainless steel is intended. In practical terms, the welding specifications included in fabrication contracts demand a level of δ-ferrite for welded assemblies. Therefore, the level of ferrite is a parameter to be measured by the quality assurance staff and its value should be set according to the risk that the welded material could experience a decrease in its properties. The relationship between the δ-ferrite content, and the mechanical and corrosion-resisting properties in stainless steels, has encouraged researchers to discover predictive tools and measurement methods since the early part of the 20th century. Predictive methods are essential during the design stage of a project in order to have a good approach to the δ-ferrite level that will be achieved, when a weld deposit or pad is not available, or when different options of welding consumables are being considered. When an experimental determination of δ-ferrite content is carried out, the literature (Refs. 1, 3–8) recognizes that within the same weld pad, local variations of δ-ferrite could be shown, due to compositional microsegregation related to variations in cooling conditions or also due to a loss of elements during the welding process. It is also recognized that for the same combination of base material and consumable, differences in the experimental values can also be found related to the specific welding procedure and parameters used. Therefore, whatever FN value is allocated to a weld metal should be derived from an average obtained from several measurements taken, as stated in the standard DIN 32514 (Ref. 5). Presented below is a chronology of the different methods that researchers have proposed. It includes predictive and measurement methods. The advantages and drawbacks of the currently used methods are also considered. ABSTRACT Controlling the δ-ferrite content in stainless steels is of utmost importance as its content will influence the material properties and its on-site behavior in terms of weldability, corrosion resistance, toughness, and thermal stability. The δ-ferrite content can be determined by taking real measurements using magnetic or quantitative metallographic determination, or alternatively can be approached by using well-recognized predictive methods like the WRC-1992 diagram or the FNN-1999 artificial neural network, which are fed by the chemical composition of the weld deposit. This paper presents a chronological review from the first predictive diagram in 1920 up to the latest mathematical model, including also an overview of the different measurement methods available. The advantages, drawbacks, scope, and limitations of predictive and measurement methods are also outlined. Introduction The residual δ-ferrite that remains at room temperature once a stainless steel has been welded, that is, after it has experienced the process of melting followed by solidification, will determine the material’s properties and behavior during its service lifetime. It is well known that primary ferritic solidification avoids the hot cracking phenomenon in austenitic stainless steels, but the determination of the solidification mode requires a metallographic analysis, which is a destructive test. Therefore, in practical terms, a minimum δ-ferrite content of 3–4 FN (Ferrite Number) is considered an acceptable indicator to ensure the absence of hot crackM. ASUNCIÓN VALIENTE BERMEJO (valiente.asun@gmail.com) is an independent researcher and consultant, Barcelona, Spain. Chronology of Predictive and Measurement Methods KEYWORDS Stainless Steels δ-ferrite Schaeffler Diagram DeLong Diagram WRC-1988 Diagram WRC-1992 Diagram Artificial Neural Network FNN-1999 ORFN Historically, authors have contributed to the literature with revisions and collections of the different methods used for the forecast and measurement of δ-ferrite in stainless steels. Worthy of notice is the revision carried out in 1986 by Stalmasek (Ref. 7), showing 25 documented ways to determine δ-ferrite, or the revisions written by Kotecki (Ref. 9) in 1997 and Lundin (Ref. 10) in 1999. In 1985, Olson (Ref. 11) presented a comprehensive review on methodology, starting at 1920 with Strauss WELDING JOURNAL 113-s WELDING RESEARCH

Table of Contents for the Digital Edition of Welding Journal - April 2012

April 2012 - TOC Listing
Unlocking Your Gas Metal Arc Welding Potential - A study sponsored by the National Shipbuilding Research Program investigated low-cost modifications to equipment or parameters that improved welding performance - P. A. Blomquist
Community College Welding Program Update - Many community colleges around the country are equipping future workers with the skills manufacturers need D. Postlethwaite
Modern Power Source Technology Drives Process Improvement - New technology in weld monitoring is making it easier to access the data by all the appropriate personnel and understand how it should be applied to benefit weld quality - T. McEllis
Building a Welding Career from the Ground Up - A thirty-two-year career welder shares her passion for the profession with others in hopes of inspiring them to expand their skills and knowledge
How Today’s Power Sources Aid Pulsed GMAW - The advanced welding machines of today can deliver power to the arc in almost any form and can react with split-second timing to avoid adverse arc phenomena - L. Barley
Fiber Lasers Perform Precision Cutting for Medical Devices - There are many methods to cut thin tubular structures often used in medical devices, but fiber lasers are emerging as the precision machines of choice
Arc Characteristics in Pulsed-GMA Welding with Acute - Groove Angles The characteristics of a joint tracking sensor were monitored under conditions of different groove angles and root openings - R-H. Kim et al.
Design of Experiment and Goal Programming Application for the GMAW Process - This study was conducted to determine critical gas metal arc welding variables and ways to optimize them - Y. T. Iç et al.
Predictive and Measurement Methods for Delta Ferrite Determination in Stainless Steels - The advantages and limitations of predictive measurement methods for δ ferrite are outlined - M. A. Valiente Bermejo
Susceptibility of IN740 to HAZ Liquation Cracking and Ductility-Dip Cracking - Conditions that lead to cracking susceptibility of nickel-based IN740 were simulated to determine an action for its prevention - J. E. Ramirez
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Welding Journal - April 2012