| People | Locations | Statistics |
|---|---|---|
| Naji, M. |
| |
| Motta, Antonella |
| |
| Aletan, Dirar |
| |
| Mohamed, Tarek |
| |
| Ertürk, Emre |
| |
| Taccardi, Nicola |
| |
| Kononenko, Denys |
| |
| Petrov, R. H. | Madrid |
|
| Alshaaer, Mazen | Brussels |
|
| Bih, L. |
| |
| Casati, R. |
| |
| Muller, Hermance |
| |
| Kočí, Jan | Prague |
|
| Šuljagić, Marija |
| |
| Kalteremidou, Kalliopi-Artemi | Brussels |
|
| Azam, Siraj |
| |
| Ospanova, Alyiya |
| |
| Blanpain, Bart |
| |
| Ali, M. A. |
| |
| Popa, V. |
| |
| Rančić, M. |
| |
| Ollier, Nadège |
| |
| Azevedo, Nuno Monteiro |
| |
| Landes, Michael |
| |
| Rignanese, Gian-Marco |
|
Society, American Welding
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (10/10 displayed)
- 2024Multiphysics Simulation of In-Service Welding and Induction Preheating: Part 2citations
- 2023Corrosion Resistance of Dissimilar GTA Welds for Offshore Applicationscitations
- 2023Application of Machine Learning to Regression Analysis of a Large SMA Weld Metal Databasecitations
- 2023Application of Digital Image Correlation in Cross Weld Tensile Testing: Test Method Validationcitations
- 2022The Toughness of High-Strength Steel Weld Metalscitations
- 2022Metallurgical Design Rules for High-Strength Steel Weld Metalscitations
- 2021Analysis of a High-Strength Steel SMAW Databasecitations
- 2020Steel-Reinforced Polyethylene Pipe: Extrusion Welding, Investigation, and Mechanical Testingcitations
- 2020Metal Transfer Mechanisms in Hot-Wire Gas Metal Arc Weldingcitations
- 2020Effect of PWHT on Laser-Welded Duplex Stainless Steelcitations
Places of action
| Organizations | Location | People |
|---|
article
Analysis of a High-Strength Steel SMAW Database
Abstract
<jats:p>Recently, Dr. Glyn M. Evans posted a large shielded metal arc (SMA) weld metal (WM) database on the ResearchGate website (researchgate.net). This database contains more than 950 WM compositions, along with their respective WM tensile and Charpy V-notch (CVN) impact properties. In particular, the CVN impact properties list the test temperatures that achieved 28 and 100 J impact energy for each WM composition. While the availability of this SMA WM database is a valuable and rare gift to the welding community, how could the welding community analyze this database to gain valuable insights? This paper utilizes a constraints-based model (CBM) as a simple and effective framework to organize and analyze this very large Fe-C-Mn SMA WM database. A CBM is built on the metallurgical principle that one needs to lower relevant solid-state phase transformation (i.e., austenite decomposition) temperatures to improve WM strength and fracture toughness while simultaneously reducing carbon content and Yurioka’s carbon equivalent number (CEN) to improve the weldability of high-strength steels. To this end, a CBM identifies and simultaneously solves several statistical (regression) equations that relate the chemical composition of high-strength steel WM with Yurioka’s CEN and selected solid-state phase transformation temperatures related to austenite decomposition. The results of the current effort demonstrate that the analysis of Evans’s shielded metal arc welding database using a CBM as a framework reaffirms that controlling carbon content, the value of the CEN, and calculated solid-state phase transformation temperatures, particularly the difference between the calculated Bs (bainite-start) and Ms (martensite-start) temperatures, is critical to developing and identifying high-performance, high-strength steel welding electrodes. A dual approach that manipulates the contents of principal alloy elements such as C, Mn, Ni, Cr, Mo, and Cu, and adds controlled amounts of Ti, B, Al, O, and N, appears to offer the best means to lower relevant solid-state phase transformation temperatures to produce high-strength and high-toughness WMs.</jats:p>