Open-source BOS tomography dataset of high-speed flow over a flight body

Synthetic schlieren tomography is a recently proposed three-dimensional (3D) optical imaging technique for studying ultrasound fields. The imaging setup is composed of an imaged target, a water tank, a camera, and a pulsed light source, which is stroboscopically synchronized with an ultrasound transducer to achieve tomographically stationary imaging of an ultrasound field. In this technique, ultrasound waves change the propagation of light rays by inducing a change in refractive index via the acousto-optic effect. The change manifests as optical flow in the imaged target. By performing the imaging in a tomographic fashion, the two-dimensional tomographic dataset of the optical flow can be transformed into a 3D ultrasound field. In this work, two approaches for acoustic pressure field estimation are introduced. The approaches are based on optical and potential flow regularized least square optimizations where regularization based on the Helmholtz equation is introduced. The methods are validated via simulations in a telecentric setup and are compared quantitatively and qualitatively to a previously introduced method. Cases of a focused, an obliquely propagating, and a standing wave ultrasound field are considered. The simulations demonstrate the efficiency of the introduced methods also in situations in which the previously applied method has weaknesses.

The multi-phase flow within a steel diesel injector is imaged using synchrotron-produced X-rays from the Advanced Photon Source at Argonne National Laboratory. Projections gathered from several repeated injection events at up to 10,000 frames per second and with 2.1 micrometer resolution at various viewing angles resulted in a 4D data set. Photon statistics were improved by averaging the data over 200 injection events. Owing to significant attenuation caused by the injector body material, and the short exposure time, the images are obscured by various types of noise making tomographic reconstruction challenging. Attempts at denoising this data are discussed. At each time step, translational and rotational image registration was performed to align projections obtained from different lines-of-sight. This is followed by a Fourier Transform method for computed tomography to reconstruct the 3D flow-field, from the start to end of fuel injection, which is a 2 millisecond long event. The X-ray phase contrast in the data was exploited by applying a low-pass filter. Segmentation is performed to track the location of the liquid-gas interface, thus distinctly revealing a highly asymmetric flow-separation layer affected by micron-scale features in the nozzle geometry. This complete data processing pipeline converted the images acquired at a signal-to-noise ratio of 1 into a unique tomographic dataset of internal fluid flow through approximately 2 millimeters of steel. The data shows excellent validation with computational fluid dynamics simulations of the flow profile previously obtained for this nozzle.