Www.msm.cam.ac.uk/phase-trans Neural Networks in Design and Manufacture.

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Presentation transcript:

Neural Networks in Design and Manufacture

0.5 µm

NF °C 1e-031e+001e M 2 X M 3 C Laves Time / h M 23 C 6

Empirical Equations  y = a + b (%C) +c (%Mn) + d (%Ni)....  y = a + b (%C) +c (%Mn) + d (%Ni)

 y = a + b (%C) +c (%Mn) + d(%C x %Mn)  y = a + b (%C) +c (%Mn) + d(%C x %Mn)

 y = a + b (%C) +c (%Mn) + d(%C x %Mn)  y = sin (%C) + tanh (%Mn)  y = a + b (%C) +c (%Mn) + d(%C x %Mn)  y = sin (%C) + tanh (%Mn)

Hyperbolic Tangents

y x A B

Predict what the next two numbers are likely to be: 2, 4, 6, 8, …….

Brun, Robson, Narayan, MacKay & Bhadeshia, 1998

precipitates solid solution iron + microstructure 550 °C 600 °C Murugananth & Bhadeshia, 2001 Components of Creep Strength, 2.25Cr1Mo

Cole & Bhadeshia, 1999

Life / hours GTA weld at 823 K (data from Nippon Steel) Cole & Bhadeshia, 1999

Cool, 1996

As-welded 600 °C 650 °C 700 °C Cool, 1996

Siemens Mitsui Babcock Nippon Steel ABB

Nickel base alloy FT750dc wt%

Temperature / °C Yield stress / MPa Tancret & Bhadeshia, 2002