Volumetric Density Measurements of a 4-nozzle "Rocket" operating at NPR=5.00

This dataset is a companion data to the publication "High-resolution, quantitative density tomography using a rotating nozzle" by Zigunov, Wagner and Namatsaliuk (AIAA Scitech 2026). (Manuscript Here) The algorithm used is based on the mathematical formulation detailed in "Time-averaged density tomography of non-axisymmetric jets with a rotating nozzle and telecentric, single-camera BOS" by Zigunov (ExIF 2025). (Manuscript Here) It also serves as a companion dataset for the open-source code (also here) to perform the volumetric reconstruction based on raw images/vector fields. Files included: DaVis.zip - Raw images and vector fields as a DaVis 10.1 project (you can use the free DaVis Viewer by LaVision to visualize it) Inverse_Radon_DEMO.m - Code used to process the vector fields into volumes (there are several manually-defined parameters, use at your own peril!) vtkwrite.m - Required code to produce VTK files (based on vtkwrite, but modified to use Rectangular Grids) OSMODI.mexw64 - Compiled MEX file for Windows 10, CUDA 11.8 for the OSMODI solver (required to solve the inverse gradient problem) BGsubtract.mat, Delta.mat - Raw vector fields (directly from DaVis) and mask to perform background motion subtraction Sinograms.mat - Raw Sinograms (in case you don't want to use OSMODI to integrate the Delta.m file) Test 10 NPR5.00 R01.mat - Matlab Result (as published) Test 10 NPR5.00 R01.vtk - Paraview source volumes (as published) Test 10 R01.pvsm - Paraview visualization settings (as published) Rocket 4-Nozzle R01.stl - 3D model of the nozzle used for Paraview visualization If you want to simply visualize the data: Download only Test 10 NPR5.00 R01.vtk, Test 10 R01.pvsm, Rocket 4-Nozzle R01.stl Open Test 10 R01.pvsm in Paraview. If you want to run/explore the code: Download Inverse_Radon_DEMO.m and Sinograms.mat Also download BGsubtract.mat, Delta.mat if you would like to test the OSMODI solver OSMODI.mexw64 will be required for the OSMODI solution. Run the Inverse_Radon_DEMO.m code section by section in Matlab. If you want to use the raw images/vector fields for other tomography purposes or new algorithm testing: Download DaVis.zip LaVision provides toolboxes to read the im7 and vc7 files in Matlab and Python (see their website) Some of the calibration constants are stored as hardcoded constants in Inverse_Radon_DEMO.m Considering citing the above publications if you use this code, dataset or setup ideas in your work.