An adaptive integration scheme for heat conduction in additive manufacturing

B. Stump; A. Plotkowski

doi:10.1016/j.apm.2019.07.008

An adaptive integration scheme for heat conduction in additive manufacturing

B. Stump, A. Plotkowski

Computational Coupled Physics

Research output: Contribution to journal › Article › peer-review

42 Scopus citations

Abstract

Solidification dynamics are important for determining final microstructure in additively manufactured parts. Recently, researchers have adopted semi-analytical approaches for predicting heat conduction effects at length and time scales not accessible to complex multi-physics numerical models. The present work focuses on improving a semi-analytical heat conduction model for additive manufacturing by designing an adaptive integration technique. The proposed scheme considers material properties, process conditions, and the inherent physical behavior of the transient heat conduction around both stationary and moving heat sources. Both the adaptive integration scheme and a technique for calculating only the points within the melt pools are described in detail. The full algorithm is then implemented and compared against a simple Riemann sum integration scheme for a variety of cases that highlight process and material variations relevant to additive manufacturing. The new scheme is shown to have significant improvements in computational efficiency, solution accuracy, and usability.

Original language	English
Pages (from-to)	787-805
Number of pages	19
Journal	Applied Mathematical Modelling
Volume	75
DOIs	https://doi.org/10.1016/j.apm.2019.07.008
State	Published - Nov 2019

Funding

The authors would like to acknowledge Matt Bement and Luke Scime for helpful feedback in the preparation of this manuscript. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. Research was co-sponsored the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Advanced Manufacturing Office and the Office of Electricity Delivery and Energy Reliability (OE) – Transformer Resilience and Advanced Components (TRAC) Program, The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (<http://energy.gov/downloads/doe-public-access-plan>).

Keywords

Additive manufacturing
Heat conduction
Numerical integration
Solidification

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.apm.2019.07.008

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AB - Solidification dynamics are important for determining final microstructure in additively manufactured parts. Recently, researchers have adopted semi-analytical approaches for predicting heat conduction effects at length and time scales not accessible to complex multi-physics numerical models. The present work focuses on improving a semi-analytical heat conduction model for additive manufacturing by designing an adaptive integration technique. The proposed scheme considers material properties, process conditions, and the inherent physical behavior of the transient heat conduction around both stationary and moving heat sources. Both the adaptive integration scheme and a technique for calculating only the points within the melt pools are described in detail. The full algorithm is then implemented and compared against a simple Riemann sum integration scheme for a variety of cases that highlight process and material variations relevant to additive manufacturing. The new scheme is shown to have significant improvements in computational efficiency, solution accuracy, and usability.

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An adaptive integration scheme for heat conduction in additive manufacturing

Abstract

Funding

Keywords

UN SDGs

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