The influence of dilution on dissimilar weld joints with high-alloy TRIP/TWIP steels

Halbauer, Lars; Buchwalder, Anja; Zenker, Rolf; Biermann, Horst

doi:10.1007/s40194-016-0324-x

Cited by 19 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For a specific combination of welding consumables and base metals, the degree of chemical heterogeneity within the weld is influenced by the dilution, which significantly affects the metallurgical microstructure and mechanical properties of steel welds [50][51][52][53][54].…”

Section: Dilution and Yield Strength Of Stainless Steel-based Weld Me...mentioning

confidence: 99%

Artificial Neural Network-Based Modelling for Yield Strength Prediction of Austenitic Stainless-Steel Welds

Park,

Kim,

Kang

2024

Applied Sciences

View full text Add to dashboard Cite

This study aimed to develop an artificial neural network (ANN) model for predicting the yield strength of a weld metal composed of austenitic stainless steel and compare its performance with that of conventional multiple regression and machine learning models. The input parameters included the chemical composition of the nine effective elements (C, Si, Mn, P, S, Ni, Cr, Mo, and Cu) and the heat input per unit length. The ANN model (comprising five nodes in one hidden layer), which was constructed and trained using 60 data points, yielded an R2 value of 0.94 and a mean average percent error (MAPE) of 2.29%. During model verification, the ANN model exhibited superior prediction performance compared with the multiple regression and machine learning models, achieving an R2 value of 0.8644 and a MAPE of 3.06%. Consequently, the ANN model effectively predicted the variation in the yield strength and microstructure resulting from the thermal history and dilution during the welding of 3.5–9% Ni steels with stainless steel-based welding consumables. Furthermore, the application of the prediction model was demonstrated in the design of welding consumables and heat input for 9% Ni steel.

show abstract

Section: Dilution and Yield Strength Of Stainless Steel-based Weld Me...mentioning

confidence: 99%

Artificial Neural Network-Based Modelling for Yield Strength Prediction of Austenitic Stainless-Steel Welds

Park,

Kim,

Kang

2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Dilution is commonly defined as the ratio of the cross-sectional area of melted base material to the total area of the fusion zone [8], hence representing the contribution of base material to the weld metal. Therefore, for a given combination of filler and base materials, the extent of chemical heterogeneity within a weld is influenced by dilution, which can have significant effects on the metallurgical and mechanical behaviour of steel weldments [9][10][11][12]. Despite the important role that dilution plays in welding, dilution has not been considered in most published research on multipass weld modelling [13][14][15].…”

Section: Accepted Manuscript N O T C O P Y E D I T E Dmentioning

confidence: 99%

Prediction of Dilution and Its Impact on the Metallurgical and Mechanical Behavior of a Multipass Steel Weldment

Sun

Hamelin

Flint

et al. 2019

Journal of Pressure Vessel Technology

View full text Add to dashboard Cite

A three-pass groove weld made by gas-tungsten arc welding in a 20-mm thick SA508 steel plate is modeled to predict the thermal, metallurgical, and mechanical behavior. The dilution for each pass is estimated as the proportion of base material in the weld metal, based on the predicted cross-sectional areas for the fusion zone (FZ) associated with each individual pass. The temperature predictions are consistent with the thermocouple measurement data and cross-weld macrographs. The predicted microstructures are qualitatively compared with the observed microstructures in cross-weld optical micrographs. The measured hardness is then used to quantitatively validate the predictions for postweld microconstituents (e.g., the ferrite, bainite, and martensite fractions), based on a hardness-microstructure correlation. The predicted residual stresses are compared with those measured by neutron diffraction. The results show that the dilution significantly affects the metallurgical and mechanical properties of weld metal (either as-deposited or reheated), and its consideration notably improves the predictions for microstructure and residual stress in the multipass steel weldment. Furthermore, the increase in dilution promotes the formation of martensite, which enhances the hardness, and leads to lower tensile stresses (or higher compressive stresses) in the weld metal. Such behavior arises due to the higher hardenability of the base material employed in this study, coupled with delayed austenite decomposition on cooling.

show abstract

“…There are studies in the literature reporting the weldability and post-weld strength values of DP steels and TRIP steels with welding methods such as gas metal arc welding (GMAW) [13,14], laser beam welding (LBW) [15,16] and resistance spot welding (RSW) [17,18]. There is some studies about advanced high strength steels are used at automotive industry welded by EBW [19][20][21]. However, no studies regarding the welding of DP or TRIP steels by using EBW were found in the literature.…”

Section: Introductionmentioning

confidence: 99%

The Microstructure and Mechanical Behavior of TRIP 800 and DP 1000 Steels Welded by Electron Beam Welding Method

Sezgin

Hayat

2020

Soldag. insp.

View full text Add to dashboard Cite

TRIP 800 steel and DP 1000 steel welded by using the electron beam welding (EBW) method were investigated in this study. Martensite was a dominant phase at the fusion zone (FZ) of both steels. In addition, bainite and austenite were observed in the FZ of TRIP 800. The hardness of FZ and heat affected zone (HAZ) of both steels were higher than their base metals. The hardness of FZ of the TRIP 800 joinings was higher than the FZ of DP 1000. Ductility and tensile strength decreased at both of the joinings. However, this decrease became higher at the DP 1000 steel joinings compared to the TRIP 800 joinings. It was observed that the TRIP 800 joining absorbed more energy than the DP 1000 joining at impact notch test for each temperature.

show abstract

The influence of dilution on dissimilar weld joints with high-alloy TRIP/TWIP steels

Cited by 19 publications

References 13 publications

Artificial Neural Network-Based Modelling for Yield Strength Prediction of Austenitic Stainless-Steel Welds

Artificial Neural Network-Based Modelling for Yield Strength Prediction of Austenitic Stainless-Steel Welds

Prediction of Dilution and Its Impact on the Metallurgical and Mechanical Behavior of a Multipass Steel Weldment

The Microstructure and Mechanical Behavior of TRIP 800 and DP 1000 Steels Welded by Electron Beam Welding Method

Contact Info

Product

Resources

About