A new method for fluid-structure interaction (FSI) diagnostics to simultaneously capture time-resolved three-dimensional, three-component (3D3C) velocity fields and structural deformations using a single light field camera is presented. A light field camera encodes both spatial and angular information of light rays collected by a conventional imaging lens that allows for the 3D reconstruction of a scene from a single image. Building upon this capability, a light field fluid-structure interaction (LF FSI) methodology is developed with a focus on experimental scenarios with low optical access. Proper orthogonal decomposition (POD) is used to separate particle and surface information contained in the same image. A correlation-based depth estimation technique is introduced to reconstruct instantaneous surface positions from the disparity between angular perspectives and conventional particle image velocimetry (PIV) is used for flow field reconstruction. Validation of the methodology is achieved using synthetic images of simultaneously moving flat plates and a vortex ring with a small increase in uncertainty under similar to 0.5 microlenses observed in both flow and structure measurement compared to independent measurements. The method is experimentally verified using a flat plate translating along the camera's optical axis in a flow field with varying particle concentrations. Finally, simultaneous reconstructions of the flow field and surface shape around a flexible membrane are presented, with the surface reconstruction further validated using simultaneously captured stereo images. The findings indicate that the LF FSI methodology provides a new capability to simultaneously measure large-scale flow characteristics and structural deformations using a single camera.

Supersonic plume impinging on a granular surface during a Moon/Mars landing causes erosion, resulting in crater formation and ejecta flow. The multiphysics processes involved in the plume-surface interaction (PSI) under rarefied conditions make it challenging to predict and model the cratering and ejecta dynamics. The crater geometries formed during such interactions can provide insights into the underlying erosion mechanisms, aiding the development of predictive models and scaling laws for PSI in lunar/martian environments. A set of experiments called the Physics Focused Ground Test (PFGT) was conducted at NASA Marshall to investigate the PSI in rarefied conditions. This study develops an automated algorithm for extracting and classifying crater geometries from high-speed PFGT videos. The experiments span various mass flow rates, nozzle heights, ambient pressures, and regolith materials. We create a labeled dataset for training edge-based and segmentation-based deep neural networks (DNNs) to identify crater geometry. The segmentation-based DNN (which determines the crater region instead of just the edge) performs much better than the edge-based network. The extracted geometry from the trained network is then used as an input to a convolutional neural network to classify the crater shape. The trained classifier network can automatically categorize video frames into crater shapes: parabolic, annular, conical-parabolic, conical-annular, and conical-deep.

This work describes the development of a particle tracking velocimetry (PTV) algorithm designed to improve three-dimensional (3D), three-component velocity field measurements using a single plenoptic camera. Particular focus is on mitigating the longstanding depth uncertainty issues that have traditionally plagued plenoptic particle image velocimetry (PIV) experiments by leveraging the camera’s ability to generate multiple perspective views of a scene in order to assist both particle triangulation and tracking. 3D positions are first estimated via light field ray bundling (LFRB) whereby particle rays are projected into the measurement volume using image-to-object space mapping. Tracking is subsequently performed independently within each perspective view, providing a statistical amalgamation of each particle’s predicted motion through time in order to help guide 3D trajectory estimation while simultaneously protecting the tracking algorithm from physically unreasonable fluctuations in particle depth positions. A synthetic performance assessment revealed a reduction in the average depth errors obtained by LFRB as compared to the conventional multiplicative algebraic reconstruction technique when estimating particle locations. Further analysis using a synthetic vortex ring at a magnification of − 0.6 demonstrated plenoptic-PIV capable of maintaining the equivalent of 0.1–0.15 voxel accuracy in the depth domain at a spacing to displacement ratio of 5.3–10.5, an improvement of 84–89% compared to plenoptic-PIV. Experiments were conducted at a spacing to displacement ratio of approximately 5.8 to capture the 3D flow field around a rotor within the rotating reference frame. The resulting plenoptic-PIV/PTV vector fields were evaluated with reference to a fixed frame stereoscopic-PIV (stereo-PIV) validation experiment. A systematic depth-wise (radial) component of velocity directed toward the wingtip, consistent with observations from prior literature and stereo-PIV experiments, was captured by plenoptic-PTV at magnitudes similar to the validation data. In contrast, the plenoptic-PIV did not discern any coherent indication of radial motion. Our algorithm constitutes a significant advancement in enhancing the functionality and versatility of single-plenoptic camera flow diagnostics by directly addressing the primary limitation associated with plenoptic imaging. Graphical abstract

In this work, a new gridless approach to tomographic reconstruction of 3D flow fields is introduced and investigated. The approach, termed here as FluidNeRF, is based on the concept of volume representation through Neural Radiance Fields (NeRF). NeRF represents a 3D volume as a continuous function using a deep neural network. In FluidNeRF, the neural network is a function of 3D spatial coordinates in the volume and produces an intensity of light per unit volume at that position. The network is trained using the loss between measured and rendered 2D projections similar to other multi-camera tomography techniques. Projections are rendered using an emission-based integrated line-of-sight method where light rays are traced through the volume; the network is used to determine intensity values along the ray. This paper investigates the influence of the NeRF hyperparameters, camera layout and spacing, and image noise on the reconstruction quality as well as the computational cost. A DNS-generated synthetic turbulent jet is used as a ground-truth representative flow field. Results obtained with FluidNeRF are compared to an adaptive simultaneous algebraic reconstruction technique (ASART), which is representative of a conventional reconstruction technique. Results show that FluidNeRF matches or outperforms ASART in reconstruction quality, is more robust to noise, and offers several advantages that make it more flexible and thus suitable for extension to other flow measurement techniques and scaling to larger-scale problems.

In this work, a Neural Radiance Field approach (TR-FluidNeRF) is investigated as a novel time-resolved tomographic reconstruction technique for 3D flow diagnostics. Neural Radiance Fields (NeRF) is a machine learning concept that a 3D scene can be represented as a continuous function of 3D location, where the continuous function is approximated by a neural network. TR-FluidNeRF extends NeRF to represent a 4D scene using a continuous function of spatial-temporal coordinates to approximate the radiance field. For this work, the neural network determines the radiance field per unit volume. Image projections are rendered using emission-based line-of-sight integration using ray tracing through the scene for each time step. The neural network is updated by the loss between measured and rendered projections, similar to other multi-camera tomography techniques. Compared to traditional tomography techniques, the advantage of FluidNeRF is the continuous approximation of the radiance field in both space and time that i) removes the inherent topology limitation of voxel-based methods, ii) compresses data memory costs for the volume by orders of magnitude, and iii) the reconstruction processes simultaneously considers space and time for the radiance field as compared to traditional tomography methods. TR-FluidNeRF was investigated using a time-resolved DNS simulation of a turbulent, low speed jet, where the perspectives were generated using an in-house code. The results show the importance of hyperparameters on the reconstruction quality, where the biggest improvement was from increasing the network depth. Additionally temporal encoding improved the temporal approximation of the reconstruction. Lastly, time-resolved FluidNeRF was compared to reconstructing each time step independently with the original FluidNeRF model. TR-FluidNeRF produced similar results to the time-independent version but sacrificed some of the finer details in the jet. Overall, TR-FluidNeRF appears as a viable option for time-resolved flow diagnostics.

This study investigates the differences in plume-surface interaction (PSI) cratering behavior between Earth atmospheric (101,325 Pa) and subatmospheric (33 Pa) ambient pressures. A stereo-photogrammetry technique was used to nonintrusively obtain 3D, time-resolved measurements of the full-domain crater geometry. Tests were conducted inside an optically accessible vacuum chamber where the PSI process was simulated using a sonic jet impinging on a bed of regolith simulant. Crater geometry measurements were taken at nozzle heights of 4.6 to 55.6 nozzle diameters above the simulant surface. Results show that the highly underexpanded plume under subatmospheric conditions resulted in broad and shallow craters compared to craters formed under Earth atmosphere. Some craters under subatmospheric conditions exhibited lobed geometry characterized by azimuthal depth variations. In these same cases, the deepest portion of the crater was located radially away from the center, and particles were observed moving toward the center resulting in fountain-like particle movement. Craters formed under Earth atmospheric conditions had an axisymmetric parabolic geometry with the location of maximum depth at the center. In general, subatmospheric crater growth was slower than Earth atmospheric. However, subatmospheric crater formation at nozzle heights of 9.3D and below was characteristically like Earth atmospheric crater formation at large nozzle heights.

Plume surface interaction experiments were conducted in a 4.27m tall drop tower facility to achieve 0g conditions. A stereo photogrammetry technique was used during 1g and 0g tests to capture crater formation, allowing for the quantification of crater depth and volume evolution. Three nozzle heights, non-dimensionalized by nozzle diameter, of 25D, 40D, and 50D and three nozzle pressures of 5, 10, and 15 psig were investigated at both 0g and 1g. Results from the 0g experiments were compared to the results obtained using the same nozzle conditions under 1g conditions. The results indicated that crater evolution occurred more rapidly during 0g conditions, resulting in deeper and wider craters compared to those formed under 1g.

Plume-surface interactions (PSI) occur during the take-off and landing of interplanetary vehicles, leading to particle ejection and the formation of craters. This can be detrimental to the vehicle and any structures or infrastructure near the landing site. A major challenge in developing a comprehensive understanding of this three-dimensional phenomenon is the need to characterize the ejecta and cratering dynamics simultaneously. Here, experiments are conducted in a vacuum chamber at different nozzle heights and ambient pressure conditions using high-speed stereo-photogrammetry and planar particle tracking velocimetry to quantify the cratering and ejecta dynamics. Predictably, it was observed that the trajectory of ejecta with a large Stokes number was mostly unaffected by the nozzle flow after leaving the crater. Under rarefied conditions, the ejecta kinematics (velocity, ejection angle, range, and height) were significantly different compared to continuum conditions. Finally, the findings demonstrate a dependency between ejecta kinematics and crater topology for the current test cases, providing critical insights into particle ejection’s initial characteristics.

Plume-Surface Interactions during landing missions on planetary bodies are known to be associated with several challenges. Fast-moving particles that are eroded from the surface because of this interaction pose a hazard to structures and instrumentation in the vicinity. Characterizing the evolution of these ejecta immediately after the initiation of the jet is important because of a sharp rise in particle velocity within this time span. This study focuses on the development of methodology to study the kinematic properties of the ejecta particles and the geometric features of the ejecta sheet generated by the impulse of a plume. A shadowgraph-based imaging technique was devised to capture the images of shadow cast by ejecta particles and sheet. The operating conditions that included nozzle pressure, pulse duration, and nozzle height from undisturbed granular bed, were tested. The response to plume interaction was measured for three different ejecta particles sizes d(p) = 212-300 mu m, 90-150 mu m, 45-90 mu m. Properties such as emergence time, emergence radius, geometry of the ejecta sheet, and ejecta particle velocities were extracted. The accuracy of the techniques employed was tested, and the techniques were found to be robust to the parameter set.

In this work, a Neural Radiance Field approach (FluidNeRF) is investigated as a novel tomographic reconstruction technique for 3D flow diagnostics. Neural Radiance Fields (NeRF) is a machine learning concept that represents a 3D scene using a continuous function of 3D location, where the continuous function is approximated by a neural network. The neural network outputs the intensity of light per unit volume at a point in the volume. Image projections are rendered using emission-based line-of-sight integration by querying the neural network at sampling points along camera rays. The NeRF is updated using the loss between captured and rendered projections similar to other multi-camera tomography techniques. FluidNeRF is compared to the adaptive simultaneous algebraic reconstruction technique (ASART) for a CFD-generated volume of turbulent mixing jet. Image and volume based metrics are presented comparing both ASART and FluidNeRF to ground truth data. Preliminary results show that FluidNeRF outperforms ASART in most scenarios albeit with increased computational time. Potential benefits of FluidNeRF over ASART are discussed including improvements in fidelity, adaptability and scalability.

This work discusses the implementation of a novel technique for simultaneous 3D particle tracking velocimetry and dual-wavelength pyrometry of spatter particles ejected during the Laser-Powder Bed Fusion (L-PBF) process using a single high-speed spectral plenoptic camera. In this methodology, particle tracking uses the Light-Field Ray Bundling algorithm paired with a four-frame best estimate track initiation with 3D Kalman filter for tracking to generate high-resolution, time-resolved 3D tracks of spatter particles. Utilizing the same light-field image data, spatter particle temperature is measured using dual-wavelength pyrometry that calculates temperature from the ratio of two narrow-band wavelength intensities. Preliminary results demonstrate the viability and potential of this technique for the L-PBF processes on the example of a turnaround laser scan. The temperature measurements indicate that the detected particles are in the liquid phase, with temperatures greater than 1950 & DEG;C. The simultaneous measurements demonstrate an overall deceleration and cooling of particles during their flight.

Plume surface interactions (PSIs) have been identified as a significant challenge in returning humans safely to the Moon. The PSI process encompasses the interaction of the exhaust plume of a landing spacecraft with the surface of a planetary body. This process results in crater formation and ejecta blowing, especially in the case of loose rocky surfaces such as that of the Moon. The crater and ejecta pose a threat to both the landing craft and to equipment and persons already on the surface. This investigation focuses on obtaining 3-D, time-resolved measurements of crater formation during the PSI process under sub-atmospheric conditions using a non-intrusive stereo-photogrammetry measurement technique. An experimental apparatus was constructed inside of a 1.2 m cube vacuum chamber to simulate the PSI process using a supersonic jet impinging on a bed of regolith simulant. Crater geometry measurements were taken at an ambient pressure of 33 Pa (0.25 Torr) and nozzle heights of 37.1, 23.2, 13.9, 9.3, and 4.6 nozzle diameters above the simulant surface. Qualitative analysis of sub-atmospheric versus atmospheric crater formation is provided. Quantitative analysis of the crater formation is provided by extracting the time evolution of maximum depth, center depth, radius, and volume from the 3-D crater measurements.

Plenoptic particle image velocimetry and surface pressure measurements were used to analyse the early development of leading-edge vortices (LEVs) created by a flat-plate wing of aspect ratio 2 rolling in a uniform flow parallel to the roll axis. Four cases were constructed by considering two advance coefficients, $J=0.54$ and 1.36, and two wing radii of gyration, $R_g/c=2.5$ and 3.25. In each case, the wing pitch angle was articulated such as to achieve an angle of attack of $33^{\circ }$ at the radius of gyration of the wing. The sources and sinks of vorticity were quantified for a chordwise rectangular control region, using a vorticity transport framework in a non-inertial coordinate system attached to the wing. Within this framework, terms associated with Coriolis acceleration provide a correction to tilting and spanwise convective fluxes measured in the rotating frame and, for the present case, have insignificant values. For the baseline case ( $J=0.54, R_g/c=3.25$ ), three distinct spanwise regions were observed within the LEV, with distinct patterns of vortex evolution and vorticity transport mechanisms in each region. Reducing the radius of gyration to $R_g/c=2.5$ resulted in a more stable vortex with the inboard region extending over a broader spanwise range. Increasing advance ratio eliminated the conical vortex, resulting in transport processes resembling the mid-span region of the baseline case. Although the circulation of the LEV system was generally stronger at the larger advance coefficient, the shear-layer contribution was diminished.

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.

View Video Presentation: https://doi.org/10.2514/6.2023-2256.vid An improved version of a previously developed camera system has been implemented in a production-scale wind tunnel environment to demonstrate use of the system for a full wind tunnel test campaign. A 226 frame per second (fps) imager was embedded in a planar Busemann inlet model for tests in the UTSI TALon Mach 4 Ludwieg Tube. Illumination was introduced via a ring-light system of micro-LEDs embedded around the camera lens aperture. The entire system was integrated using low-profile, high-speed cables and FPGAs. Using this system, pressure sensitive paint and UV oil flow visualization experiments were performed to visualize the cowl shock impingement at the throat of the inlet. Based on this work, it was found that the shock impingement at the on-design case occurred upstream of the expected location. It was also found that upstream geometric changes heavily influenced the size and shape of the shock foot produced by the cowl shock impingement.

Particle spatter is an unavoidable by-product of the Laser-Powder Bed Fusion (L-PBF) process, as the high intensity of the incoming laser beam generates high vapor fluxes on the meltpool, allowing metal particles to be ejected into the process environment. This is detrimental to the final manufactured part, as it risks the incorporation of defects. It is therefore important to study this spattering behavior and to apply the knowledge gained to further improve the L-PBF process. This work introduces the use of a high-speed plenoptic camera to acquire 3D spatter particle trajectories generated via L-PBF line tracks. Spatter particles are tracked in the volume above the laser-metal interaction zone at 1000 fps and their velocity calculated. It is found that the calculated speeds of the spatter particles are within the expected range for this process, and that the behavior is a complex 3-dimensional process.

Through this work, the foundation has been laid for the development of a system for small-scale, integrated, image- based flow diagnostics for ground and flight tests. This system addresses many of the challenges associated with alternative methods of performing these measurements. For this work a 120 fps imager was embedded in the ceiling of a Mach 2.0 wind tunnel to perform oblique shock impingement measurements. Illumination was provided via a ring-light system of micro-LEDs embedded around the camera lens aperture. The entire system was controlled using a Raspberry Pi 4 Model B to capture and process image data. The integrated system possesses a total aperture diameter of 20 mm. Pressure sensitive paint and UV oil flow visualization experiments capturing an oblique shock/boundary layer interaction were performed using this system.

The development of a tomographic background oriented schlieren implementation system utilizing up to four plenoptic cameras is presented. A systematic set of experiments was performed using a pair of solid dimethylpolysiloxan cylinders immersed in a nearly refractive index matched gylcerol/water solution to represent discrete flow features with known sizes, shapes, separation distances, and orientation. A study was conducted to assess the influence of these features on the accuracy of 3D reconstructions of the refractive index field. It was determined that the limited angular information collected by a single plenoptic camera is insufficient for single-camera 3D reconstructions. In multi-camera configurations, the additional views collected by a plenoptic camera were shown to improve the overall reconstruction accuracy compared to an equivalent single view per camera reconstruction, potentially reducing the number of overall cameras needed to achieve a desired accuracy. For the imaging of two cylinders, three or more cameras are generally needed to avoid significant ghosting artifacts in the reconstruction. Quantitative results are presented that show that: (1) two separate cylinders will be individually resolved as long as measurements from one camera are able to observe separation between the cylinders; (2) the error in the reconstructed 3D refractive index field increases as the size of the feature decreases; and (3) the use of volumetric masking within the reconstruction algorithm is critical in order to improve the accuracy of the solution.