The goal of this work is to predict the effect of part geometry and process parameters on the instantaneous spatial distribution of heat, called the heat flux or thermal history, in metal parts as they are being built layerbylayer using additive manufacturing (AM) processes. In pursuit of this goal, the objective of this work is to develop and verify a graph theorybased approach for predicting the heat flux in metal AM parts. This objective is consequential to overcome the current poor process consistency and part quality in AM. One of the main reasons for poor part quality in metal AM processes is ascribed to the heat flux in the part. For instance, constrained heat flux because of illconsidered part design leads to defects, such as warping and thermal stressinduced cracking. Existing nonproprietary approaches to predict the heat flux in AM at the partlevel predominantly use meshbased finite element analyses that are computationally tortuous — the simulation of a few layers typically requires several hours, if not days. Hence, to alleviate these challenges in metal AM processes, there is a need for efficient computational thermal models to predict the heat flux, and thereby guide part design and selection of processmore »
 Award ID(s):
 1752069
 Publication Date:
 NSFPAR ID:
 10140513
 Journal Name:
 Journal of Manufacturing Science and Engineering
 Volume:
 141
 Issue:
 7
 ISSN:
 10871357
 Sponsoring Org:
 National Science Foundation
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Abstract 
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