Experimental measurement of thermal diffusivity, conductivity and specific heat capacity of metallic powders at room and high temperatures

Ahsan, Faiyaz; Razmi, Jafar; Ladani, Leila

doi:10.1016/j.powtec.2020.07.043

Cited by 27 publications

(6 citation statements)

References 33 publications

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“…However, it is known that the thermal diffusivity of the solid tungsten can be approximated by the constant value κ W = 50 mm 2 /s in a wide temperature range [56,57]. For the powder material the value of thermal diffusivity can be less than those one of the solid material in about 20 times [58]. Thus, for the rough assessment, in the calculations we used the value κ = κ W /2 = 25 mm 2 /s.…”

Section: Resultsmentioning

confidence: 99%

Gradient models of moving heat sources for powder bed fusion applications

Solyaev¹,

Lurie²

2022

Preprint

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In this paper, we derive closed form solutions for the quasi-stationary problems of moving heat sources within the gradient theory of heat transfer. This theory can be formally deduced from the two-temperature model and it can be treated as a generalized variant of the Guyer-Krumhansl model with the fourth order governing equation. We show that considered variant of the gradient theory allows to obtain a useful singularity-free solutions for the moving point and line heat sources that can be used for the refined analysis of the melt pool shape in the laser powder bed fusion processes. Derived solutions contain single additional length scale parameter that can be related to the mean particles size of the powder bed. Namely, we show that developed gradient models allow to describe the decrease of the melt pool depth with the increase of the powder's particles size that was observed previously in the experiments. We also derive the dimensionless relations that can be used for the experimental identification of the model's length scale parameter for different materials. Semi-analytical solution for the Gaussian laser beam is also derived and studied based on the Green function method within the considered theory.

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Section: Resultsmentioning

confidence: 99%

Gradient models of moving heat sources for powder bed fusion applications

Solyaev¹,

Lurie²

2022

Preprint

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“…The same conclusion can be The thermal diffusivity values of the IN718 powder are on the order of 4 × 10 −4 cm 2 /s when the Clark and Taylor model is applied. According to references [26,39], the average thermal diffusivity of IN718 powder over temperature ranges from 26.85 • C to 526.85 • C and from 100.4 • C to 550.2 • C is 1.5 × 10 −3 cm 2 /s and 1.6 × 10 −3 cm 2 /s, respectively. The strong deviation between the literature results and the Clark and Taylor analysis of an assumed pseudo homogeneous tri-layer system shows that a more refined approach is necessary to analyze the raw data, i.e., the temperature or voltage vs. time curves than the Clark and Taylor model.…”

Section: Powder Sample Special Sample Holdermentioning

confidence: 99%

“…Zhang et al [25] investigated the thermal conductivity of metal powder in LPBF AM for IN625 and Ti64 powders using a TA Instruments DLF 1200 laser flash instrument, and finite element (FE) heat transfer modeling. Ahsan et al [26] determined the thermal diffusivity of IN718, Ti-6Al-4V and SS 304L metallic powders using the laser flash technique with a DXF 900 instrument. For their measurements, they used encapsulated powder samples in a holder with a lid.…”

Section: Introductionmentioning

confidence: 99%

Powder Bed Thermal Diffusivity Using Laser Flash Three Layer Analysis

Habiba,

Hebert

2023

Materials

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The thermal diffusivity of powder bed plays a crucial role in laser powder bed fusion (LPBF) additive manufacturing. The mechanical properties of the parts built by LPBF are immensely influenced by the thermal properties of the powder bed. This study aims to measure the thermal diffusivity of metallic powder, nickel-based super alloy Inconel718 (IN718), in LPBF using laser flash three-layered analysis in a DLF1600 instrument, which incorporates a special powder cell to encapsulate the powdered sample. Measurements were performed at different temperatures. The thermal diffusivity of several reference samples was measured for the purpose of validating the test results, and it was compared to published data for identical measures. It was observed that experimental results for powder samples were smaller than the actual thermal diffusivity of the sample. R software analysis was used to analyze test data in order to obtain powder thermal diffusivity values that were close to the actual values.

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“…In particular, nickel is a ferromagnetic material having a Curie point, i.e. a certain temperature above which the conductivity and heat capacity both increase (Ahsan et al, 2020).…”

Section: Materials Propertiesmentioning

confidence: 99%

“…The keyhole region is non-desirable in AM processes, as it is associated with built parts with higher porosity and poorer mechanical properties. Thus, in determining the optimal process parameters, those parameter combinations which fall within the keyhole region (as identified by equation (2.6) in (Ahsan et al, 2020)) can be immediately discounted and the search for the optimal process conditions focused on the remaining areas of the input design space instead.…”

Section: Powder Bed Absorptionmentioning

confidence: 99%

Optimization of built-part distortion in laser powder bed fusion processing of Inconel 718

Chang

Tran

2021

RPJ

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Purpose Laser powder bed fusion (LPBF) provides the means to produce unique components with almost no restriction on geometry in an extremely short time. However, the high-temperature gradient and high cooling rate produced during the fabrication process result in residual stress, which may prompt part warpage, cracks or even baseplate separation. Accordingly, an appropriate selection of the LPBF processing parameters is essential to ensure the quality of the built part. This study, thus, aims to develop an integrated simulation framework consisting of a single-track heat transfer model and a modified inherent shrinkage method model for predicting the curvature of an Inconel 718 cantilever beam produced using the LPBF process. Design/methodology/approach The simulation results for the curvature of the cantilever beam are calibrated via a comparison with the experimental observations. It is shown that the calibration factor required to drive the simulation results toward the experimental measurements has the same value for all settings of the laser power and scanning speed. Representative combinations of the laser power and scanning speed are, thus, chosen using the circle packing design method and supplied as inputs to the validated simulation framework to predict the corresponding cantilever beam curvature and density. The simulation results are then used to train artificial neural network models to predict the curvature and solid cooling rate of the cantilever beam for any combination of the laser power and scanning speed within the input design space. The resulting processing maps are screened in accordance with three quality criteria, namely, the part density, the radius of curvature and the solid cooling rate, to determine the optimal processing parameters for the LPBF process. Findings It is shown that the parameters lying within the optimal region of the processing map reduce the curvature of the cantilever beam by 17.9% and improve the density by as much as 99.97%. Originality/value The present study proposes a computational framework, which could find the parameters that not only yield the lowest distortion but also produce fully dense components in the LPBF process.

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Experimental measurement of thermal diffusivity, conductivity and specific heat capacity of metallic powders at room and high temperatures

Cited by 27 publications

References 33 publications

Gradient models of moving heat sources for powder bed fusion applications

Gradient models of moving heat sources for powder bed fusion applications

Powder Bed Thermal Diffusivity Using Laser Flash Three Layer Analysis

Optimization of built-part distortion in laser powder bed fusion processing of Inconel 718

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