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Dataset of in-situ coaxial monitoring and print's cross-section images by Direct Energy Deposition fabrication.

ABSTRACT: Coaxial monitoring of the Direct Energy Deposition (DED) machines enables a real-time material deposition study. Coaxial-images contain substantial melt-pool information and incorporate situational information including the sparks' intensity, numbers, etc. Recent studies have shown that melt-pool observations correlate directly with machine parameters and artifact properties. Therefore, the melt-pool information not only can assist in measuring the machine's working condition and determining machine operation parameters' reliability but also facilitates the deposition characteristics studies like print's regime and dimensions. This information is gathered during the fabrication and can be expanded to perform various process studies and fault registration. This paper utilizes the Optomec DED machine to fabricate single-track prints with multiple process parameters, while a coaxial camera records the deposition. Each deposited track is then cut perpendicular to the print's direction to facilitate process parameters correlation study with actual geometrical deposition measured using a microscope. The coaxial images taken during fabrication, along with their process parameters, cross-cut measurements, and a developed image-processing toolbox, are presented alongside this paper to empower future research directions.

SUBMITTER: Akhavan J

PROVIDER: S-EPMC10630360 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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Dataset of in-situ coaxial monitoring and print's cross-section images by Direct Energy Deposition fabrication.

Akhavan Javid J Lyu Jiaqi J Mahmoud Youmna Y Xu Ke K Vallabh Chaitanya Krishna Prasad CKP Manoochehri Souran S

Scientific data 20231107 1

Coaxial monitoring of the Direct Energy Deposition (DED) machines enables a real-time material deposition study. Coaxial-images contain substantial melt-pool information and incorporate situational information including the sparks' intensity, numbers, etc. Recent studies have shown that melt-pool observations correlate directly with machine parameters and artifact properties. Therefore, the melt-pool information not only can assist in measuring the machine's working condition and determining mac ...[more]

PMID: 37935696

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Project description:The presence of defects, such as pores, in materials processed using additive manufacturing represents a challenge during the manufacturing of many engineering components. Recently, ultrasonic vibration-assisted (UV-A) directed energy deposition (DED) has been shown to reduce porosity, promote grain refinement, and enhance mechanical performance in metal components. Whereas it is evident that the formation of such microstructural features is affected by the melt pool behavior, the specific mechanisms by which ultrasonic vibration (UV) influences the melt pool remain elusive. In the present investigation, UV was applied in situ to DED of 316L stainless steel single tracks and bulk parts. For the first time, high-speed video imaging and thermal imaging were implemented in situ to quantitatively correlate the application of UV to melt pool evolution in DED. Extensive imaging data were coupled with in-depth microstructural characterization to develop a statistically robust dataset describing the observed phenomena. Our findings show that UV increases the melt pool peak temperature and dimensions, while improving the wettability of injected particles with the melt pool surface and reducing particle residence time. Near the substrate, we observe that UV results in a 92% decrease in porosity, and a 54% decrease in dendritic arm spacing. The effect of UV on the melt pool is caused by the combined mechanisms of acoustic cavitation, ultrasound absorption, and acoustic streaming. Through in situ imaging we demonstrate quantitatively that these phenomena, acting simultaneously, effectively diminish with increasing build height and size due to acoustic attenuation, consequently decreasing the positive effect of implementing UV-A DED. Thus, this research provides valuable insight into the value of in situ imaging, as well as the effects of UV on DED melt pool dynamics, the stochastic interactions between the melt pool and incoming powder particles, and the limitations of build geometry on the UV-A DED technique.

Project description:This dataset corresponds to a data series produced from automated data loggers during the MESOLAC experimental project. Nine pelagic mesocosms (about 3000 L, 3 m depth) were deployed in July 2019 in Lake Geneva near the shore of Thonon les Bains (France), simulating predicted climate scenarios (i.e. intense weather events) by applying a combination of forcing. The design consisted of three treatments each replicated three times: a control treatment (named C - no treatment applied) and two different treatments simulating different intensities of weather events. The high intensity treatment (named H) aimed to reproduce short and intense weather events such as violent storms. It consisted of a short-term stress applied during the first week, with high pulse of dissolved organic carbon (5x increased concentration, i.e. total DOC ∼ 6 mg L-1), transmitted light reduced to 15% and water column manual mixing. The medium intensity treatment (named M) simulated less intense and more prolonged exposures such as during flood events. It was maintained during the 4 weeks of the experiment and consisted of 1.5x increased concentration of dissolved organic carbon (i.e. total DOC ∼ 2 mg L-1), 70% transmitted light and water column manual mixing. Automated data loggers were placed for the entire period of the experiment in the mesocosms and in the lake for comparison with natural conditions. Temperature, conductivity, dissolved oxygen and CO2 were monitored every 15 min at different depths (0.15, 0.25, 1 and 2 m). This data set aims to contribute our understanding of the effect of environmental forcing on lake ecosystem processes (such as production, respiration and CO2 exchange) under simulated intense weather events and the ability of the planktonic community to recover after perturbation. To a broader extent, the presented data can be used for a wide variety of applications, including monitoring of lake community functioning during a period of high productivity on a large peri-alpine lake and being included in further meta-analysis aiming at generalising the effect of climate change on large lakes.

Dataset Information

Dataset of in-situ coaxial monitoring and print's cross-section images by Direct Energy Deposition fabrication.

Publications

Dataset of in-situ coaxial monitoring and print's cross-section images by Direct Energy Deposition fabrication.

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