Thermomechanical Modeling of Additive Manufacturing Large Parts

By E. R. Denlinger, Jeff Irwin, P. Michaleris. 2014

307 citations recorded by the source corpus.

Subfields: Automotive Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/862c20051a93fba7cb6185ab7fbfa202a97c818a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. T. Mukherjee
2. T. DebRoy
3. H. Wei
4. Amitava De
5. Wei Zhang
6. J. Elmer
7. J. Zuback
8. J. Milewski

In Mechanical Engineering

1. T. DebRoy
2. T. Mukherjee
3. H. Wei
4. Amitava De
5. J. Elmer
6. Wei Zhang
7. J. Zuback
8. J. Milewski

Citations in the corpus

• Prediction of microstructure, residual stress, and deformation in laser powder bed fusion process (2018, background): “[19] developed a layerby-layer coarsening strategy in which the lower layers of the finite elements were merged to maintain a low number of degrees of freedom in themodel for the entire simulation.”
• Metal additive-manufacturing process and residual stress modeling (2016, methodology): “Conductivity, density, and specific heat are temperature dependent and are assumed constant above 800 °C for most materials (IN718 [58], Ti-6Al-4V [63]) or are obtained from a library such as JMatPro® for the metallurgical composition (X4CrNiCuNb 16-4 hardening stainless steel [64] or 316L stainless”
• Additive manufacturing of metallic components – Process, structure and properties (2018, methodology): “Ti-6Al-4V EBAM 3D sequential thermal and elastic-plastic analysis in CUBIC, stress relaxation temperature of 690 C to improve prediction [241,244]”