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Journal Articles
FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
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Publisher: ASME
Article Type: Research Papers
J. Eng. Mater. Technol. October 2025, 147(4): 041004.
Paper No: MATS-24-1240
Published Online: May 13, 2025
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Methodology and overview of the current work
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in FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
> Journal of Engineering Materials and Technology
Published Online: May 13, 2025
Fig. 1 Methodology and overview of the current work More about this image found in Methodology and overview of the current work
Image
Architecture of FCGR-Net
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in FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
> Journal of Engineering Materials and Technology
Published Online: May 13, 2025
Fig. 2 Architecture of FCGR-Net More about this image found in Architecture of FCGR-Net
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Loss curves across all fourfold
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in FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
> Journal of Engineering Materials and Technology
Published Online: May 13, 2025
Fig. 3 Loss curves across all fourfold More about this image found in Loss curves across all fourfold
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KDE plot indicating the error distribution
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in FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
> Journal of Engineering Materials and Technology
Published Online: May 13, 2025
Fig. 4 KDE plot indicating the error distribution More about this image found in KDE plot indicating the error distribution
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Parameter correlation using pair plots
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in FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
> Journal of Engineering Materials and Technology
Published Online: May 13, 2025
Fig. 5 Parameter correlation using pair plots More about this image found in Parameter correlation using pair plots
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Parameter correlation using heatmap
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in FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
> Journal of Engineering Materials and Technology
Published Online: May 13, 2025
Fig. 6 Parameter correlation using heatmap More about this image found in Parameter correlation using heatmap
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FCGR prediction for different alloys. ( a ) Ni-based superalloy—GTM 720...
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in FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
> Journal of Engineering Materials and Technology
Published Online: May 13, 2025
Fig. 7 FCGR prediction for different alloys. ( a ) Ni-based superalloy—GTM 720, equivalent to In 720 [ 5 ]. ( b ) 300M low-alloy steel [ 48 ]. ( c ) Al alloy—Al 2048-T31 [ 56 ]. ( d ) Al 7010-T6 and RRA compared with prediction [ 75 ]. E in the plot represents experimental curves a... More about this image found in FCGR prediction for different alloys. ( a ) Ni-based superalloy—GTM 720...
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Predictions depicting the effect of stress ratio. E in the plot represents ...
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in FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
> Journal of Engineering Materials and Technology
Published Online: May 13, 2025
Fig. 8 Predictions depicting the effect of stress ratio. E in the plot represents experimental curves [ 5 ] and P represents FCGR-Net predictions. More about this image found in Predictions depicting the effect of stress ratio. E in the plot represents ...
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FCGR prediction for Ni-based superalloys at elevated temperature. ( a )...
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in FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
> Journal of Engineering Materials and Technology
Published Online: May 13, 2025
Fig. 9 FCGR prediction for Ni-based superalloys at elevated temperature. ( a ) Hastelloy X-280 [ 66 ]. ( b ) Inconel 625 [ 9 ]. More about this image found in FCGR prediction for Ni-based superalloys at elevated temperature. ( a )...
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Plot indicating the average sensitivity of input parameters
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in FCGR-Net: A Novel Approach to Predict Fatigue Crack Growth Rate Behavior in Metals Using Machine Learning
> Journal of Engineering Materials and Technology
Published Online: May 13, 2025
Fig. 10 Plot indicating the average sensitivity of input parameters More about this image found in Plot indicating the average sensitivity of input parameters
Journal Articles
Numerical Analysis of Welding Deformation in Double T-Joints of 304 Stainless Steel Sheet
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Publisher: ASME
Article Type: Research Papers
J. Eng. Mater. Technol. October 2025, 147(4): 041003.
Paper No: MATS-25-1012
Published Online: May 12, 2025
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304 stainless steel soil loosening shovel model
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in Numerical Analysis of Welding Deformation in Double T-Joints of 304 Stainless Steel Sheet
> Journal of Engineering Materials and Technology
Published Online: May 12, 2025
Fig. 1 304 stainless steel soil loosening shovel model More about this image found in 304 stainless steel soil loosening shovel model
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304 stainless steel welding specimen model
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in Numerical Analysis of Welding Deformation in Double T-Joints of 304 Stainless Steel Sheet
> Journal of Engineering Materials and Technology
Published Online: May 12, 2025
Fig. 2 304 stainless steel welding specimen model More about this image found in 304 stainless steel welding specimen model
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Welding sequence schemes design
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in Numerical Analysis of Welding Deformation in Double T-Joints of 304 Stainless Steel Sheet
> Journal of Engineering Materials and Technology
Published Online: May 12, 2025
Fig. 3 Welding sequence schemes design More about this image found in Welding sequence schemes design
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Finite element model of 304 stainless steel double T-joints
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in Numerical Analysis of Welding Deformation in Double T-Joints of 304 Stainless Steel Sheet
> Journal of Engineering Materials and Technology
Published Online: May 12, 2025
Fig. 4 Finite element model of 304 stainless steel double T-joints More about this image found in Finite element model of 304 stainless steel double T-joints
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Partial view of the T-joint in the finite element model
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in Numerical Analysis of Welding Deformation in Double T-Joints of 304 Stainless Steel Sheet
> Journal of Engineering Materials and Technology
Published Online: May 12, 2025
Fig. 5 Partial view of the T-joint in the finite element model More about this image found in Partial view of the T-joint in the finite element model
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Double ellipsoidal heat source model
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in Numerical Analysis of Welding Deformation in Double T-Joints of 304 Stainless Steel Sheet
> Journal of Engineering Materials and Technology
Published Online: May 12, 2025
Fig. 6 Double ellipsoidal heat source model More about this image found in Double ellipsoidal heat source model
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Finite element model boundary fixation diagram
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in Numerical Analysis of Welding Deformation in Double T-Joints of 304 Stainless Steel Sheet
> Journal of Engineering Materials and Technology
Published Online: May 12, 2025
Fig. 7 Finite element model boundary fixation diagram More about this image found in Finite element model boundary fixation diagram
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Schematic illustration of equivalent deformation direction and pre- and pos...
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in Numerical Analysis of Welding Deformation in Double T-Joints of 304 Stainless Steel Sheet
> Journal of Engineering Materials and Technology
Published Online: May 12, 2025
Fig. 8 Schematic illustration of equivalent deformation direction and pre- and post-deformation comparison (Arrows are utilized to indicate the direction of strain at various points. The progressive increase in the length of these arrows corresponds to a gradual increase in the magnitude of strain... More about this image found in Schematic illustration of equivalent deformation direction and pre- and pos...
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