A review on the fatigue behaviour of AlSi10Mg alloy fabricated using laser powder bed fusion technique

Raja, A.; Cheethirala, Srinivasa Rakesh; Gupta, Pallavi; Vasa, Nilesh J.; Jayaganthan, R.

doi:10.1016/j.jmrt.2022.01.028

Cited by 42 publications

(13 citation statements)

References 102 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The applicability of data-driven algorithms in different conditions was introduced, providing technical support for the investigation of fatigue behavior based on data-driven algorithms. [23,[131][132][133][134] After the establishment of the database and the analysis of the IFs, different data-driven algorithms were used to predict the fatigue performance. Specifically, several effectively approaches (Bayesian model, [135][136][137] ANN, [67,129,[138][139][140][141] particle swarm optimization (PSO)-BPNN, [75,142] Ant colony optimization-BPNN, [39,55] Figure 12.…”

Section: Progress In Prediction Approachesmentioning

confidence: 99%

“…The applicability of data‐driven algorithms in different conditions was introduced, providing technical support for the investigation of fatigue behavior based on data‐driven algorithms. [ 23,131–134 ] After the establishment of the database and the analysis of the IFs, different data‐driven algorithms were used to predict the fatigue performance. Specifically, several effectively approaches (Bayesian model, [ 135–137 ] ANN, [ 67,129,138–141 ] particle swarm optimization (PSO)‐BPNN, [ 75,142 ] Ant colony optimization‐BPNN, [ 39,55 ] SVM, [ 56,143–145 ] GA‐ANN, [ 146 ] GA‐BPNN, [ 146,147 ] RF, [ 89,137,148,149 ] DNN, [ 112,150–152 ] convolution neural network (CNN), [ 153–155 ] long short‐term memory (LSTM), [ 156–158 ] radial basis function neural network (RBFNN), [ 53,88,159,160 ] etc.)…”

Section: Progress In Prediction Approachesmentioning

confidence: 99%

See 1 more Smart Citation

A State‐of‐Art Review on Prediction Model for Fatigue Performance of Welded Joints via Data‐Driven Method

Feng

Zhao

et al. 2023

Adv Eng Mater

View full text Add to dashboard Cite

Fatigue fracture of welded joints is an important cause for engineering accidents. Due to the coexistence of so many influencing factors, the current prediction model of fatigue behavior cannot be used for all service conditions. The progress of each module (database establishment, data processing, data augmentation, dimension reduction, and comprehensive consideration of influencing factors) during the process of constructing a prediction model is summarized herein. Specifically, the state‐of‐art prediction models of fatigue strength, fatigue crack growth rate, fatigue life, and fatigue reliability are introduced. Moreover, suggestions for future work are given at the end of each section. Finally, according to the influential prediction methods, the establishment of fatigue performance prediction methods of welded joints via data‐driven method is summarized.

show abstract

Section: Progress In Prediction Approachesmentioning

confidence: 99%

Section: Progress In Prediction Approachesmentioning

confidence: 99%

A State‐of‐Art Review on Prediction Model for Fatigue Performance of Welded Joints via Data‐Driven Method

Feng

Zhao

et al. 2023

Adv Eng Mater

View full text Add to dashboard Cite

show abstract

“…6 Oxidation, which can lead to the formation of oxide inclusions, is also one of the common issues associated with aluminum. 7 LS-printed AlSi10Mg has comparable or superior mechanical properties as cast metal. The reason is related to fine microstructure that resulted from high cooling rates during the LS process.…”

Section: Introductionmentioning

confidence: 95%

Mechanical properties of additively manufactured AlSi10Mg under quasi‐static and cyclic loading

Yankin,

Seisekulova,

Perveen

et al. 2024

Fatigue Fract Eng Mat Struct

View full text Add to dashboard Cite

This study examines the effects of minor variations in the building angle of 3D‐printed AlSi10Mg components on mechanical properties under different processing and postprocessing conditions (as‐built [AB], stress relief [SR], and platform heating [HP]). Beginning with tensile tests to determine stress ranges for subsequent fatigue experiments, findings indicate that the building angle significantly impacts tensile strength, yield strength, and ultimate strain, rising with inclining angles. However, Young's modulus remains unaffected. High‐cycle fatigue testing at stress amplitudes below yield strength values reveals differences in S‐N fatigue curves among AB, SR, and HP conditions. While the building angle's influence is not statistically significant, AB samples exhibit lower fatigue resistance than SR and HP counterparts. HP samples perform similarly to SR at high stress levels but notably worse at low stress values. The developed multiple linear regression model shows reasonable accuracy, with 84% of predictions within ±2‐factor and 97.2% within ±3‐factor.

show abstract

“…Despite some improvements in tensile properties, the as‐solidified fine dendritic microstructure may make the material more sensitive to surface notches and volumetric defects under cyclic loading 12,13 . As such, the fatigue performance of this material is not only often negatively impacted by the AM induced defects, including gas‐entrapped pores and lack‐of‐fusion defects, 14,15 but it may also be inferior in the non‐heat treated (NHT) and stress relieved (SR) condition compared to the aged condition 7,15–18 . However, discrepancies still exist in literature regarding the beneficial effect of standardized HTs, such as T6, on additively manufactured (AM) AlSi10Mg parts.…”

Section: Introductionmentioning

confidence: 99%

“…12,13 As such, the fatigue performance of this material is not only often negatively impacted by the AM induced defects, including gasentrapped pores and lack-of-fusion defects, 14,15 but it may also be inferior in the non-heat treated (NHT) and stress relieved (SR) condition compared to the aged condition. 7,[15][16][17][18] However, discrepancies still exist in literature regarding the beneficial effect of standardized HTs, such as T6, on additively manufactured (AM) AlSi10Mg parts. For instance, Zhang et al 19 performed stress relief (300 C for 2 h), solution treatment (530 C for 1 h), and artificial aging (170 C for 12 h) on L-PBF specimens and concluded that all HTs, including T6, diminish fatigue properties when compared with the NHT condition.…”

mentioning

confidence: 99%

Tensile and fatigue behaviors of additively manufactured AlSi10Mg: Effect of solutionizing and aging heat treatments

Baig

Ghiaasiaan

Shao

et al. 2023

Fatigue Fract Eng Mat Struct

View full text Add to dashboard Cite

The effects of various heat treatments on the microstructure and mechanical properties of laser beam powder bed fused AlSi10Mg were investigated. Specimens were solutionized at three different temperatures of 425 C, 475 C, and 525 C followed by natural aging (T4) prior to microstructural and mechanical characterization. In addition, the effect of aging was studied by artificially aging (i.e., T7) some of the solutionized specimens at 165 C. Solutionizing at all temperatures was observed to fully dissolve the additive manufacturing (AM) induced dendritic microstructure, leaving bulky Si and needle-shaped β-AlFeSi precipitates in the grain interiors and boundaries. Tensile results revealed that T4 specimens exhibited more ductility, while T7 specimens showed substantially higher strengths with slightly reduced ductility. Interestingly, no significant effect of heat treatment on strain-life fatigue behavior was observed. Fractography found the Si particles to be responsible for tensile fracture, while AM volumetric defects were the main initiators of fatigue cracks.aluminum, fatigue, laser beam powder bed fusion (LB-PBF/L-PBF), microstructure, tensile Highlights• Effect of heat treatments on tensile and fatigue behavior of L-PBF AlSi10Mg studied.• T7 treatment led to higher tensile strengths than T4, but similar fatigue lives.• Tensile failure initiated from Si-particle fracture or debonding from matrix.• Fatigue life was affected by the size of crack initiators, that is, volumetric defects. | INTRODUCTIONAluminum alloys are commonly used in various industries because of their superior strength/stiffness to weight ratio compared to other alloys. 1,2 Among various Al alloys, AlSi10Mg as a cast alloy 2 has historically been used to fabricate complex/thin-walled geometries. Recently, processing AlSi10Mg through additive manufacturing (AM) has shown to be very promising as intricate, lightweight parts can be manufactured without

show abstract

A review on the fatigue behaviour of AlSi10Mg alloy fabricated using laser powder bed fusion technique

Cited by 42 publications

References 102 publications

A State‐of‐Art Review on Prediction Model for Fatigue Performance of Welded Joints via Data‐Driven Method

A State‐of‐Art Review on Prediction Model for Fatigue Performance of Welded Joints via Data‐Driven Method

Mechanical properties of additively manufactured AlSi10Mg under quasi‐static and cyclic loading

Tensile and fatigue behaviors of additively manufactured AlSi10Mg: Effect of solutionizing and aging heat treatments

Contact Info

Product

Resources

About