Jinqiang Ning

Dr. Jinqiang Ning

Georgia Institute of Technology
orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2020 in International Journal of Mechanical Sciences
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Journal Article
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Jinqiang NingJinqiang Ning
Jinqiang Ning
DSDaniel E. Sievers
Daniel E. Sievers
HGHamid Garmestani
Hamid Garmestani
SLSteven Y. Liang
Steven Y. Liang

8 March 2019 in Materials
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Jinqiang NingJinqiang Ning
Jinqiang Ning
DSDaniel Sievers
Daniel Sievers
Hamid GarmestaniHamid Garmestani
Hamid Garmestani
Steven Yuehsan LiangSteven Yuehsan Liang
Steven Yuehsan Liang
Temperature distribution gradient in metal powder bed additive manufacturing (MPBAM) directly controls the mechanical properties and dimensional accuracy of the build part. Experimental approach and numerical modeling approach for temperature in MPBAM are limited by the restricted accessibility and high computational cost, respectively. Analytical models were reported with high computational efficiency, but the developed models employed a moving coordinate and semi-infinite medium assumption, which neglected the part dimensions, and thus reduced their usefulness in real applications. This paper investigates the in-process temperature in MPBAM through analytical modeling using a stationary coordinate with an origin at the part boundary (absolute coordinate). Analytical solutions are developed for temperature prediction of single-track scan and multi-track scans considering scanning strategy. Inconel 625 is chosen to test the proposed model. Laser power absorption is inversely identified with the prediction of molten pool dimensions. Latent heat is considered using the heat integration method. The molten pool evolution is investigated with respect to scanning time. The stabilized temperatures in the single-track scan and bidirectional scans are predicted under various process conditions. Close agreements are observed upon validation to the experimental values in the literature. Furthermore, a positive relationship between molten pool dimensions and powder packing porosity was observed through sensitivity analysis. With benefits of the absolute coordinate, and high computational efficiency, the presented model can predict the temperature for a dimensional part during MPBAM, which can be used to further investigate residual stress and distortion in real applications.

16 August 2018 in The International Journal of Advanced Manufacturing Technology
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Jinqiang NingJinqiang Ning
Jinqiang Ning
VNVinh Nguyen
Vinh Nguyen
YHYong Huang
Yong Huang
KHKarl T. Hartwig
Karl T. Hartwig
Steven Yuehsan LiangSteven Yuehsan Liang
Steven Yuehsan Liang

1 August 2019 in Journal of Manufacturing Processes
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Journal Article
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Jinqiang NingJinqiang Ning
Jinqiang Ning
EMElham Mirkoohi
Elham Mirkoohi
YDYuanzhe Dong
Yuanzhe Dong
ESElliott Sievers
Elliott Sievers
Hamid GarmestaniHamid Garmestani
Hamid Garmestani
Steven Yuehsan LiangSteven Yuehsan Liang
Steven Yuehsan Liang

1 November 2019 in Applied Physics A
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Jinqiang NingJinqiang Ning
Jinqiang Ning
WWWenjia Wang
Wenjia Wang
BZBruno Zamorano
Bruno Zamorano
Steven Yuehsan LiangSteven Yuehsan Liang
Steven Yuehsan Liang

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EMElham Mirkoohi
Elham Mirkoohi
Jinqiang NingJinqiang Ning
Jinqiang Ning
PBPeter Bocchini
Peter Bocchini
Omar FerganiOmar Fergani
Omar Fergani
KCKuo-Ning Chiang
Kuo-Ning Chiang
Steven Yuehsan LiangSteven Yuehsan Liang
Steven Yuehsan Liang
A physics-based analytical model is proposed in order to predict the temperature profile during metal additive manufacturing (AM) processes, by considering the effects of temperature history in each layer, temperature-sensitivity of material properties and latent heat. The moving heat source analysis is used in order to predict the temperature distribution inside a semi-infinite solid material. The laser thermal energy deposited into a control volume is absorbed by the material thermodynamic latent heat and conducted through the contacting solid boundaries. The analytical model takes in to account the typical multi-layer aspect of additive manufacturing processes for the first time. The modeling of the problem involving multiple layers is of great importance because the thermal interactions of successive layers affect the temperature gradients, which govern the heat transfer and thermal stress development mechanisms. The temperature profile is calculated for isotropic and homogeneous material. The proposed model can be used to predict the temperature in laser-based metal additive manufacturing configurations of either direct metal deposition or selective laser melting. A numerical analysis is also conducted to simulate the temperature profile in metal AM. These two models are compared with experimental results. The proposed model also well captured the melt pool geometry as it is compared to experimental values. In order to emphasize the importance of solving the problem considering multiple layers, the peak temperature considering the layer addition and peak temperature not considering the layer addition are compared. The results show that considering the layer addition aspect of metal additive manufacturing can help to better predict the surface temperature and melt pool geometry. An analysis is conducted to show the importance of considering the temperature sensitivity of material properties in predicting temperature. A comparison of the computational time is also provided for analytical and numerical modeling. Based on the obtained results, it appears that the proposed analytical method provides an effective and accurate method to predict the temperature in metal AM.