3D tracking velocimetry of L-PBF spatter particles using a single high-speed plenoptic camera

Fischer, Ralf; Moaven, Mahyar; Kelly, Dustin; Morris, Sarah; Thurow, Brian S.; Prorok, Barton C.

doi:10.1016/j.addlet.2022.100083

Cited by 10 publications

(4 citation statements)

References 32 publications

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“…Finally, the relationship between splash area and splash number and laser energy density was analyzed; the paraxial shooting system built for LPBF and the extraction results are shown in Figure 25 . Ralf D. Fischer et al [ 128 ] built a high-speed all-optical camera to obtain the three-dimensional sputtering particle trajectories generated by the laser and powder interaction in LPBF and also calculated the sputtering particle velocities, which are important for predicting the sputtering particle’s landing point location on the powder bed and provides a new perspective for the subsequent analysis of the forming quality. The schematic diagram of the built light field camera and the three-dimensional sputtering and particle trajectories are shown in Figure 26 .…”

Section: Visual Measurement Methods Of the Molten Metal Evaporation P...mentioning

confidence: 99%

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Review of Visual Measurement Methods for Metal Vaporization Processes in Laser Powder Bed Fusion

et al. 2023

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Laser powder bed fusion (LPBF) is of great importance for the visual measurement and analysis of the metallization process, which is the process of solid, liquid, and gas phase transformations of metal powders under high-energy laser irradiation due to the low boiling point/high saturated vapor pressure. Since the evaporation of metals involves the interaction of driving forces such as vapor back pressure, surface tension, and gravity, the movement of the melt pool is not stable. At the same time, it also produces vaporization products such as vapor plumes and sprays, which cause defects such as bubbles, porosity, lack of fusion, inclusions, etc., during the manufacturing process of the parts, affecting the performance and manufacturing quality of the parts. More and more researchers are using imaging technologies, such as high-speed X-ray, high-speed visible light cameras, and high-speed schlieren imaging, to perform noncontact visual measurements and analyses of the melt pool, vapor plume, and spatter during the metal evaporation process, and the results show that the metal evaporation process can be suppressed by optimizing the process parameters and changing the processing atmosphere, thereby reducing part defects and improving part performance and built part quality. This paper reviews the research on metal evaporation mechanisms and visual measurement methods of metal evaporation, then discusses the measures of metal evaporation, and finally summarizes and prospects the future research hotspots of LPBF technology, according to the existing scholars’ research on numerical simulation analysis and visual measurement methods of the metal evaporation process.

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Section: Visual Measurement Methods Of the Molten Metal Evaporation P...mentioning

confidence: 99%

“… ( a ) Isometric view; ( b ) X-Y plane of particle tracks from the turnaround experiment (showing one in every three tracks for clarity, with different colors corresponding to different particles) [ 128 ]. …”

Section: Figurementioning

confidence: 99%

Review of Visual Measurement Methods for Metal Vaporization Processes in Laser Powder Bed Fusion

et al. 2023

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“…This provided a compact way to encode 4D information onto a 2D sensor, which leads to the ability of computational refocusing and generating different perspectives. 5 The Advanced Flow Diagnostic Laboratory (AFDL) at Auburn University has demonstrated the ability to perform 3D reconstructions with a reduced number of cameras for particle image velocimetry (PIV), 2 particle tracking velocimetry (PTV), 6,7 and tomographic background oriented schlieren (Tomo-BOS). 8 Combustion processes are very complex with multiple reactions, oscillations, and potentially turbulent flow fields with multiscale features throughout the flow.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous tomographic multi-component reconstructions using multispectral plenoptic cameras

Kelly,

George,

Page

et al. 2023

Applied Optical Metrology V

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This paper introduces a methodology for simultaneously conducting multi-component 3D measurements in highspeed turbulent afterburning flames using several spectral plenoptic cameras. Traditionally, plenoptic imaging techniques capture the 3D scene using a single camera, where the camera is modified to include a microlens array that is located between the primary lens and the sensor. Each pixel behind a microlens encodes angular information onto the sensor by sampling a point on the main lens. A multispectral plenoptic camera is a combination of a plenoptic camera with a spectral filter array at the primary lens aperture plane. Thus, spectral information is encoded onto angular information, such that the camera captures spatial, angular, and spectral information of a light-field in a single-snapshot, which enables multiple measurements to be performed using discrete spectral bands from a single camera. Additional cameras provide improved performance by extending the overall range of angular information captured. Experiments were conducted using three spectral plenoptic cameras to capture subsets of the following measurement within a sonic hydrogen flame and subsonic ethylene flame: tomographic particle image velocimetry; dual-wavelength pyrometry of particle-laden flow; and 3D measurement the chemiluminescence of CH*. This work demonstrates the ability to simultaneously capture multiple 3D measurements with views from as few as three multispectral plenoptic cameras, whereas traditional cameras could require an order of magnitude more sensors.

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“…Other data, e.g. plenoptic images of Mie scattered light from a particle field, can also be processed with a triangulation algorithm to locate particles[16].…”

mentioning

confidence: 99%

Stochastic particle advection velocimetry (SPAV): theory, simulations, and proof-of-concept experiments

Zhou

Hong

et al. 2023

Meas. Sci. Technol.

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Particle tracking velocimetry (PTV) is widely used to measure time-resolved, three-dimensional velocity and pressure fields in fluid dynamics research. Inaccurate localization and tracking of particles is a key source of error in PTV, especially for single camera defocusing, plenoptic imaging, and digital in-line holography (DIH) measurements. To address this, we developed stochastic particle advection velocimetry (SPAV): a statistical data loss that improves the accuracy of PTV. SPAV is based on an explicit particle advection model that predicts particle positions over time as a function of the estimated velocity field. The model can account for non-ideal effects like drag on inertial particles. A statistical data loss that compares the tracked and advected particle positions, accounting for arbitrary localization and tracking uncertainties, is derived and approximated. We implement our approach using a physics-informed neural network, which simultaneously minimizes the SPAV data loss, a Navier–Stokes physics loss, and a wall boundary loss, where appropriate. Results are reported for simulated and experimental DIH-PTV measurements of laminar and turbulent flows. Our statistical approach significantly improves the accuracy of PTV reconstructions compared to a conventional data loss, resulting in an average reduction of error close to 50%. Furthermore, our framework can be readily adapted to work with other data assimilation techniques like state observer, Kalman filter, and adjoint–variational methods.

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3D tracking velocimetry of L-PBF spatter particles using a single high-speed plenoptic camera

Cited by 10 publications

References 32 publications

Review of Visual Measurement Methods for Metal Vaporization Processes in Laser Powder Bed Fusion

Review of Visual Measurement Methods for Metal Vaporization Processes in Laser Powder Bed Fusion

Simultaneous tomographic multi-component reconstructions using multispectral plenoptic cameras

Stochastic particle advection velocimetry (SPAV): theory, simulations, and proof-of-concept experiments

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