journal article·2026-02-23

Vector characterization approach for inherent strain modeling of laser powder bed fusion manufacturing

Lucas M. Morand, Garrett J. Pataky

Rapid Prototyping Journal· Volume 32· Issue 3
Publisher page

Abstract

Purpose The inherent strain method for laser powder bed fusion additive manufacturing (AM) allows for rapidly simulating process-induced distortion while still retaining the influence of thermomechanical physics. However, previous implementation of a single vector taken from a global average does not fully capture the known AM process results. This study aims to increase predicted accuracy in simulations by modifying the inherent strain method to better reflect experimentally defined print behavior. Design/methodology/approach This study analyzed the thermomechanical response of a small-scale AM part and applied the findings to a part-scale simulation, validated against experimental measurements of a benchmark geometry. This included the effects of the compressive core and the rapidly cooled tensile shell of an AM part and the differing in-plane and build-direction environments, captured with two strain vectors in the inherent strain method. Findings When compared to experimental X-ray diffraction strain measurements in the in-plane and build directions, simulation accuracy was improved from the traditional single-vector approach, reaching errors as low as 1% and lowering part median error from 82% to 17%. Originality/value This vector assignment approach better captures the process physics to improve AM simulation accuracy without sacrificing the lightweight computational cost advantage of inherent strain modeling. Part residual strain distribution was characterized, leading to a better understanding of post-print effects in AM parts.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Additive Manufacturing Materials and Processes · Additive Manufacturing and 3D Printing Technologies · Cellular and Composite Structures

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Clemson University Department of Mechanical Engineering, , Clemson, ,

Funding

Division of Graduate Education · Federal Student Aid · Division of Computer and Network Systems

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