Type 410 steels are typically welded by using consumables with matching composition. However, this type of steel has shown to have poor weldability which is related to formation of hard and brittle martensite in the weld zone, hydrogen-included cracking or retention of δ-ferrite which affects the toughness. One theory that explains the inconsistent toughness is that the wide composition ranges of the base metal results in wide variations of the A1-temperature. In the paper, this theory was investigated with the design of experiment (DoE) approach using Thermo-Calc to perform thermodynamic simulations. Thermo-Calc together with the TCFE8 database was used to predict A1 and A3 temperatures for various compositions.
An A1 temperature predictive diagram was plotted based on the A1 temperature predictive formula and chromium and nickel equivalent equations. The diagram was validated by comparison to published data and through phase transformation analysis of alloy within the AWS and ASTM compositional specification ranges. The predictive accuracy of the A1 temperature formula, calculated by Thermo-Calc, proved to be within the error of experimental temperature measurement (±3°C).
The paper is written by D. J. Stone, B. T. Alexandrov and J. A. Penso at the Ohio state university.
The design of experiment (DoE) approach using thermodynamic simulations with ThermoCalc™ was applied to evaluate the effect of alloy composition on the critical temperatures in Type 410 steels and welding consumables. A predictive equation and predictive diagram for the A1 temperature were developed and verified through experimentation and comparison with published data. This was also complemented with the development of a predictive equation for the A3 temperature.
The results of this study show that the combined ASTM and American Welding Society (AWS) compositional specifications for Type 410 materials provide a range of A1 temperatures that is significantly wider than the postweld heat treatment (PWHT) temperature range specified by the American Society of Mechanical Engineers (ASME). This creates a potential risk of exceeding the A1 temperature during PWHT, resulting in formation of fresh martensite, and can be related to difficulties meeting hardness and toughness requirements for Type 410 welds experienced in industry. Narrowing the ASTM and AWS compositional specifications by introduction of lower limits for all alloying elements, including nitrogen and copper, was identified as a potential solution to this problem.
The predictive tools developed in this study can be applied for selection of welding consumables and base metals, postweld heat treatment (PWHT) temperature selection, and compositional optimization of Type 410 steels and welding consumables.
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
HubSpot sets this cookie to keep track of sessions and to determine if HubSpot should increment the session number and timestamps in the __hstc cookie.
This cookie is set by Hubspot whenever it changes the session cookie. The __hssrc cookie set to 1 indicates that the user has restarted the browser, and if the cookie does not exist, it is assumed to be a new session.
5 months 27 days
This is the main cookie set by Hubspot, for tracking visitors. It contains the domain, initial timestamp (first visit), last timestamp (last visit), current timestamp (this visit), and session number (increments for each subsequent session).
The _ga cookie, installed by Google Analytics, calculates visitor, session and campaign data and also keeps track of site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognize unique visitors.
This cookie is installed by Google Analytics.
A variation of the _gat cookie set by Google Analytics and Google Tag Manager to allow website owners to track visitor behaviour and measure site performance. The pattern element in the name contains the unique identity number of the account or website it relates to.
Installed by Google Analytics, _gid cookie stores information on how visitors use a website, while also creating an analytics report of the website's performance. Some of the data that are collected include the number of visitors, their source, and the pages they visit anonymously.
Linkedin set this cookie to store information about the time a sync took place with the lms_analytics cookie.
YouTube sets this cookie via embedded youtube-videos and registers anonymous statistical data.
5 months 27 days
HubSpot sets this cookie to keep track of the visitors to the website. This cookie is passed to HubSpot on form submission and used when deduplicating contacts.
Wistia sets this cookie to collect data on visitor interaction with the website's video-content, to make the website's video-content more relevant for the visitor.