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Residual Stresses in Dissimilar Friction Stir Welding of AA2024 and AZ31: Experimental and Numerical Study

Source: Journal of Manufacturing Science and Engineering:;2018:;volume( 140 ):;issue: 005:;page 51015

Author(s): Hou, Z.; Sheikh-Ahmad, J.; Jarrar, F.; Ozturk, F.

Publisher: The American Society of Mechanical Engineers (ASME)

Abstract: Residual Stresses in Dissimilar Friction Stir Welding of AA2024 and AZ31: Experimental and Numerical Study;Thermal history and residual stresses in dissimilar friction stir welding (FSW) of AA2024 and AZ31 were studied ...

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Uncertainty Quantification in Climate Modeling and Projection

Source: Bulletin of the American Meteorological Society:;2016:;volume( 097 ):;issue: 005:;page 821

Author(s): Qian, Yun; Jackson, Charles; Giorgi, Filippo; Booth, Ben; Duan, Qingyun; Forest, Chris; Higdon, Dave; Hou, Z. Jason; Huerta, Gabriel

Publisher: American Meteorological Society

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Neural Networks to Find the Optimal Forcing for Offsetting the Anthropogenic Climate Change Effects

Source: Artificial Intelligence for the Earth Systems:;2024:;volume( 003 ):;issue: 003

Author(s): Ren, Huiying; Lu, Jian; Hou, Z. Jason; Chen, Tse-Chun; Leung, L. Ruby; Liu, Fukai

Publisher: American Meteorological Society

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Residual Stresses in Dissimilar Friction Stir Welding of AA2024 and AZ31: Experimental and Numerical Study

Uncertainty Quantification in Climate Modeling and Projection

Neural Networks to Find the Optimal Forcing for Offsetting the Anthropogenic Climate Change Effects

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Residual Stresses in Dissimilar Friction Stir Welding of AA2024 and AZ31: Experimental and Numerical Study

Uncertainty Quantification in Climate Modeling and Projection

Neural Networks to Find the Optimal Forcing for Offsetting the Anthropogenic Climate Change Effects