Sun. Jun 13th, 2021


The first visualization of its kind, created by using powerful X-rays at Argonne’s Advanced Photon Source, will lead to improved manufacturing and efficiency.

Just a small imperfection in the manufacturing of a car’s fuel injector nozzle can not only cause the part to erode and perform poorly, but also can also tax the engine, fuel efficiency and emissions.

Cargo airplane engine. Image credit: dayamay via Pixabay (Free Pixabay licence)

Cargo airplane engine. Image credit: dayamay via Pixabay (Free Pixabay licence)

Scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory have begun to solve this dilemma by using one of the world’s brightest, most powerful X-ray sources — the Advanced Photon Source (APS), a DOE Office of Science User Facility located at Argonne — to generate the first 3D images of the fluid flow inside a fuel injector nozzle.

We are working with some of the most powerful X-rays in the world at Argonne.” — Aniket Tekawade, postdoctoral researcher in the Energy Systems division at Argonne.

The high-speed 3D visualization will help engine manufacturers and suppliers improve the design models that are used to create fuel injectors. The requirement for higher fuel efficiency and lower emissions has emphasized the need for tight design and manufacturing processes with higher injection pressures and smaller orifices. As an outcome of the experiments at the APS, the Argonne engineering team also created open-source software, to help others analyze images acquired in low-light conditions.

The experiment, detailed in a recent Scientific Reports article, was the brainchild of Christopher Powell, principal engine research scientist at Argonne. Powell, postdoctoral researcher Aniket Tekawade and others used X-ray imaging to discover that manufacturing imperfections resulted in low-pressure regions inside the nozzle as fuel was sprayed. This caused the fuel to vaporize in these regions, forming pockets of gas inside the nozzle that can ultimately erode steel.

The team automated many facets of the experiment; from taking X-ray images to rotating the fuel injector nozzle so that images could be taken at multiple angles. Using production fuel injectors allowed them to perform experiments at the very high pressures typical of diesel engines, but led to the challenge of seeing through the steel body. This was different from past fluid flow experiments by others, which typically use transparent plastic or glass nozzle replicas at low pressures to watch the fluid flow inside. Actual fuel injector pressures would break glass or plastic replicas.

Even with one of the most powerful X-ray sources on the globe, almost 99% of all the X-ray photons from the source are absorbed by the steel body and we are left with only 1.5% of the photons to show the fluid flow inside the injector,” Tekawade said. ​Moreover, the leftover photons possess energies so high that the liquid fuel is 99.97% transparent to them.”

It is fascinating that we can still see the liquid/gas interface through the nozzle’s thick steel body, with a few microseconds and micrometer resolutions nevertheless,” said Kamel Fezzaa, physicist with Argonne’s X-ray Science division and a co-author on the paper.

The challenge of scale included processing the vast quantity of X-ray images taken over the 30-hour experiment (more than 100,000 images, equivalent to 2 terabytes of data) to improve poor contrast caused by the small proportion of X-ray light that could pass through the steel.

Image processing tools were created and used by Tekawade to process the X-ray images into 3D maps of fluid flow. To help others use images acquired in low-light conditions, Tekawade created open-source software, developed from deep learning algorithms.

Tekawade’s open-source software, CTSegNet, can be accessed at the following link: github​.com/​a​n​i​k​e​t​k​t​/​C​T​S​egNet.

Funding for this research was provided by the Department of Energy’s Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office.

Source: ANL






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