Effect of microstructure heterogeneity on the mechanical properties of friction stir welded reduced activation ferritic/martensitic steel

Li, Shengli; Vajragupta, Napat; Biswas, Abhishek; Tang, Wenshen; Wang, Hao; Kostka, Aleksander; Hartmaier, Alexander

doi:10.1016/j.scriptamat.2021.114306

Cited by 17 publications

(4 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…26 According to equation (2), the effect of GNDs on the hardness of the material is much greater than that of SSDs, so the SSDs is negligible (ρ ≅ ρ GNDs ). 27 For grain boundary strengthening, the smaller the grain size, the better the strengthening effect. The degree of CDRX is the lower, so the hardness of this parameter is the higher.…”

Section: Analysis Of Hardness and Conductivity Test Results Under Dif...mentioning

confidence: 99%

Effect of continuous dynamic-recrystallisation on high-property multilayer Cu foils joint by friction-stir-welding

Li,

Deng,

Zeng

et al. 2024

Materials Science and Technology

View full text Add to dashboard Cite

In this experiment, friction-stir-welding was proposed to research the flexible connection of multilayer Cu foils. It studies the correlation between hardness, conductivity, and continuous dynamic-recrystallisation. New grains of continuous dynamic-recrystallisation have a correlation between the dislocation density and the grain size, such that a lower dislocation density corresponds to a higher grain size and vice versa. It is shown that after friction-stir-welding of multilayer Cu foils, the hardness increases and the conductivity decreases due to the combined effect of fine grain strengthening and dislocation strengthening for new grains of continuous dynamic-recrystallisation of the weld zone. However, the hardness gradually decreases and conductivity gradually increases within the weld zone with continuous dynamic-recrystallisation degree.

show abstract

Section: Analysis Of Hardness and Conductivity Test Results Under Dif...mentioning

confidence: 99%

Effect of continuous dynamic-recrystallisation on high-property multilayer Cu foils joint by friction-stir-welding

Li,

Deng,

Zeng

et al. 2024

Materials Science and Technology

View full text Add to dashboard Cite

show abstract

“…In Equation (12), d(ρ ci (a),ρ mi ) was defined as the mean square root error (MSRE) between the measured and the calculated average dislocation density in the ith experiment:…”

Section: Identification and Validation Of The Modelmentioning

confidence: 99%

“…A similar hypothesis, which combines improved local fracture resistance with smooth gradients of properties, was put forward in [ 9 ]. Although the successful control or application of chemical or microstructural heterogeneity to achieve the desired properties was achieved by some researchers (e.g., for pipeline [ 10 ], multiphase [ 11 ] and ferritic/martensitic steels [ 12 ], as well as for other fields in engineering [ 13 ]), it seems that numerical modelling can still be useful support for the design of these materials. Advanced numerical models with the capability to predict distributions of various microstructural features are needed to reach this goal.…”

Section: Introductionmentioning

confidence: 99%

Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of Steels

et al. 2022

View full text Add to dashboard Cite

The design of modern construction materials with heterogeneous microstructures requires a numerical model that can predict the distribution of microstructural features instead of average values. The accuracy and reliability of such models depend on the proper identification of the coefficients for a particular material. This work was motivated by the need for advanced experimental data to identify stochastic material models. Extensive experiments were performed to supply data to identify a model of austenite microstructure evolution in steels during hot deformation and during the interpass times between deformations. Two sets of tests were performed. The first set involved hot compressions with a nominal strain of 1. The second set involved hot compressions with lower nominal strains, followed by holding at the deformation temperature for different times. Histograms of austenite grain size after each test were measured and used in the identification procedure. The stochastic model, which was developed elsewhere, was identified. Inverse analysis with the objective function based on the distance between the measured and calculated histograms was applied. Validation of the model was performed for the experiments, which were not used in the identification. The distance between the measured and calculated histograms was determined for each test using the Bhattacharyya metric and very low values were obtained. As a case study, the model with the optimal coefficients was applied to the simulation of the selected industrial hot-forming process.

show abstract

“…Exceptional properties of metals and alloys with heterogeneous microstructures are discussed in many publications. As far as steels are concerned, recent papers on complex phase [6], multiphase [7], ferritic/martensitic [8], pipeline [9], and bainitic steels [10] should be mentioned. Modern bainitic steels are used for manufacturing rails [11] and rods [12]; the latter mainly has further application as stock for cold heading processes [13].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Deterministic and Stochastic Models of Microstructure Evolution during Multi-Step Hot Deformation of Steels

et al. 2023

View full text Add to dashboard Cite

Modern construction materials, including steels, have to combine strength with good formability. In metallic materials, these features are obtained for heterogeneous multiphase microstructures. Design of such microstructures requires advanced numerical models. It has been shown in our earlier works that models based on stochastic internal variables meet this requirement. The focus of the present paper is on deterministic and stochastic approaches to modelling hot deformation of multiphase steels. The main aim was to survey recent advances in describing the evolution of dislocations and grain size accounting for the stochastic character of the recrystallization. To present a path leading to this objective, we reviewed several papers dedicated to the application of internal variables and statistical approaches to modelling recrystallization. Following this, the idea of the model with dislocation density and grain size being the stochastic internal variables is described. Experiments composed of hot compression of cylindrical samples are also included for better presentation of the utility of this approach. Firstly, an empirical data describing the loads as a function of time during compression and data needed to create histograms of the austenite grain size after the tests were collected. Using the measured data, identification and validation of the models were performed. To present possible applications of the model, it was used to produce a simulation imitating industrial hot-forming processes. Finally, calculations of the dislocation density and the grain size distribution were utilized as inputs in simulations of phase transformations during cooling. Distributions of the ferrite volume fraction and the ferrite grain size after cooling recapitulate the paper. This should give readers good overview on the application of collected equations in practice.

show abstract

Effect of microstructure heterogeneity on the mechanical properties of friction stir welded reduced activation ferritic/martensitic steel

Cited by 17 publications

References 33 publications

Effect of continuous dynamic-recrystallisation on high-property multilayer Cu foils joint by friction-stir-welding

Effect of continuous dynamic-recrystallisation on high-property multilayer Cu foils joint by friction-stir-welding

Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of Steels

A Comparative Study of Deterministic and Stochastic Models of Microstructure Evolution during Multi-Step Hot Deformation of Steels

Contact Info

Product

Resources

About