Multi-scale computational modeling of residual stress in selective laser melting with uncertainty quantification
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Univ. of Texas, Austin, TX (United States)
- Univ. of California, Los Angeles, CA (United States)
Selective laser melting (SLM) is a powder-based additive manufacturing technique which creates parts by fusing together successive layers of powder with a laser. The quality of produced parts is highly dependent on the proper selection of processing parameters, requiring significant testing and experimentation to determine parameters for a given machine and material. Computational modeling could potentially be used to shorten this process by identifying parameters through simulation. However, simulating complete SLM builds is challenging due to the difference in scale between the size of the particles and laser used in the build and the size of the part produced. Often, continuum models are employed which approximate the powder as a continuous medium to avoid the need to model powder particles individually. While computationally expedient, continuum models require as inputs effective material properties for the powder which are often difficult to obtain experimentally. Building on previous works which have developed methods for estimating these effective properties along with their uncertainties through the use of detailed models, this work presents a part scale continuum model capable of predicting residual thermal stresses in an SLM build with uncertainty estimates. Model predictions are compared to experimental measurements from the literature.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- Grant/Contract Number:
- AC04-94AL85000; NA0003525
- OSTI ID:
- 1697993
- Alternate ID(s):
- OSTI ID: 2325066
- Report Number(s):
- SAND--2018-13677J; 685589
- Journal Information:
- Additive Manufacturing, Journal Name: Additive Manufacturing Vol. 29; ISSN 2214-8604
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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