Evaluation of Property Scatter of Nickel Base Alloy IN 738 LC

Stefan Linn; Alfred Scholz; Christina Berger

doi:10.4028/www.scientific.net/AMR.278.387

Paper Titles

A Mathematical Framework for Cyclic Life Prediction of Directionally Solidified Nickel Superalloys
p.363

Time and Temperature Dependent Cyclic Plasticity and Fatigue Crack Growth of the Nickel-Base Alloy617B – Experiments and Models
p.369

Degradation in Fatigue Crack Propagation Resistance of a Gas Turbine Vane after Long Term Service
p.375

Evaluation of Mechanical Properties of a Superalloy Disk with a Dual Microstructure
p.381

Evaluation of Property Scatter of Nickel Base Alloy IN 738 LC
p.387

Analysis of the Effective and Internal Cyclic Stress Components in the Inconel Superalloy Fatigued at Elevated Temperature
p.393

A1-L1₂ Structures in the Al-Co-Ni-Ti Quaternary Phase System
p.399

Development of New C&W Superalloys for High Temperature Disk Applications
p.405

Hot Deformation Behaviors and Microstructure Evolution in a New PM Nickel-Base Superalloy
p.411

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 278Evaluation of Property Scatter of Nickel Base...

Evaluation of Property Scatter of Nickel Base Alloy IN 738 LC

Abstract:

The nickel base alloy IN 738 LC is in use for gas turbine blades since more than 25 years. In high temperature creep testing the conventionally cast alloy exhibits a comparably large property scatter which requires high safety margins in design and dimensioning and subsequently causes an incomplete exploitation of the materials potential. The reasons for this property scatter were investigated and traced back to different influencing factors. Parallel to investigations on the microstructure of post-exposure material and conventional scatter band analysis, artificial neural networks were successfully applied to discover relations between the chemical composition of the individual melt and the position of the corresponding test results within the global scatter band. Recommendations for a lifting of the lower scatter band boundary and the mean curve are derived.

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Periodical:

Advanced Materials Research (Volume 278)

Pages:

387-392

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.278.387

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Online since:

July 2011

Authors:

Stefan Linn, Alfred Scholz, Christina Berger

Keywords:

Creep Behaviour, Neural Network (NN), Nickel Base Alloy, Scatter Band Assessment

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References

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