# Heat Source Model Development for Thermal Analysis of Laser Powder Bed Fusion Using Bayesian Optimization and Machine Learning

https://mdr.nims.go.jp/datasets/39a88805-137a-4c35-9715-91c14e4fbf0b

## File

- [s40192-023-00334-2.pdf](https://mdr.nims.go.jp/filesets/4ff985eb-b70b-4ece-be4f-3efe850cd480/download) ([Detail](https://mdr.nims.go.jp/filesets/4ff985eb-b70b-4ece-be4f-3efe850cd480.md))

## Id

39a88805-137a-4c35-9715-91c14e4fbf0b

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-04-08T07:51:28.184539Z

## Updated at

2024-04-09T03:30:20.353738Z

## Published at

2024-04-09T03:30:20.749850Z

## Doi



## First published url

https://doi.org/10.1007/s40192-023-00334-2

## Date published

2024-01-19

## Recorded date published

2024-3

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Heat Source Model Development for Thermal Analysis of Laser Powder Bed Fusion
    Using Bayesian Optimization and Machine Learning
  title_type: original
  lang: en

## Description

- description: To understand the correlation between process, structures, and properties
    in laser powder bed fusion (L-PBF), it is essential to use numerical analysis
    as well as experimental approaches. A finite element thermal analysis uses a moving
    heat source model represented as a volumetric heat flux to simulate heat input
    by laser. Because of its computational efficiency, finite element thermal analysis
    is suitable for iterative procedures such as parametric study and process optimization.
    However, to obtain valid simulated results, the heat source model must be calibrated
    by comparison with experimental results for each laser scanning condition. The
    need for re-calibration limits the applicable window of laser scanning conditions
    in the thermal analysis. Thus, the current study developed a novel heat source
    model that is valid and precise under any laser scanning condition within a wide
    process window. As a secondary objective in the development, we quantitively evaluated
    and compared the four heat source models proposed to date. It was found that the
    most suitable heat source model for the L-PBF are conical one among them. Then,
    a multiple linear regression analysis was performed to represent the heat source
    model as a function of laser power and scanning velocity. Consequently, the thermal
    analysis with the novel model is valid and precise within the wide process window
    of L-PBF.
  description_type: abstract
  lang: und

## Creator

- name: Masahiro Kusano
  role: author
  orcid: https://orcid.org/0000-0002-5061-0195
  organization: National Institute for Materials Science
- name: Makoto Watanabe
  role: author
  orcid: https://orcid.org/0000-0002-5064-9583
  organization: National Institute for Materials Science

## Contact agent



## Publisher

organization: Springer Science and Business Media LLC

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## Keyword

- subject: Laser powder bed fusion
  schema: not_defined
- subject: Thermal analysis
  schema: not_defined
- subject: Heat source model
  schema: not_defined
- subject: Laser scanning conditions
  schema: not_defined
- subject: Bayesian optimization
  schema: not_defined
- subject: Multiple linear regression
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: Integrating Materials and Manufacturing Innovation
  issn: '21939764'
  volume: '13'
  start_page: 288
  end_page: 304

## Conference



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## Funding

- funder_name: Japan Science and Technology Agency
- identifier: 23K13583
  funder_name: JSPS KAKENHI

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## Fileset

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  filename: s40192-023-00334-2.pdf
  content_type: application/pdf
  size: 7023529
  md5: c9bdfc63c8656c83d9a568c34b906582

## Thumbnail

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filename: s40192-023-00334-2.pdf