This article is part of a series detailing how the Elios 3 is being used in a project by the Idaho Environmental Coalition under contract with the Department of Energy (DOE) to develop a safe method for removing several hundred cubic meters of highly radioactive waste from underground storage bins in Idaho. The name of the project is the Calcine Retrieval Project (CRP).
Key points:
As part of the massive Idaho Cleanup Project at the Idaho National Laboratory site, the Idaho Environmental Coalition (IEC) was tasked with finding a safe way to remove 220 cubic meters (720 cubic feet) of radioactive waste stored underground over 60 years ago and moving it to a new location.
The waste, a granular material called calcine, is stored inside 6.1m (20 foot) high bins housed in a concrete vault made in the 1950s. The vaults and bins weren’t designed with the possibility of future waste removal in mind, making the task of removal all the more challenging for the IEC.
After in-depth planning and research the IEC’s CRP team (Calcine Retrieval Project) developed a novel method for removing the waste:
The CRP’s plan for removing the calcine is ingenious. But there is actually a step 0 to this process—understanding what the interior of the vault looks like.
For the approach to work, operators would need to know of all the obstructions that might be found above the tops of the storage bins, including conduit, process piping, and structural supports. This knowledge was crucial for them to precisely locate core holes in the vault roof so that the access riser pipes would have a clear path when lowered to the bin tops.
To address this need, the CRP wanted to make a 3D model of the interior of the vault so it could accurately drill the holes and place the calcine retrieval equipment.
These 3D models could be made with LiDAR or with photogrammetry. LiDAR was the preferred option, since it could provide a greater level of detail, but whichever option worked inside the confined space would ultimately be the one selected for the job.
In 2019, workers tried lowering a handheld LiDAR sensor through the only hatch in the vault roof to 3D map its interior.
Since the LiDAR sensor was limited to a single location it produced only a partial 3D map, with several “shadow areas” or blind spots (shown above right).
To create a complete 3D map of the vault’s interior, the CRP team knew it would need a delivery mechanism for either a LiDAR or photogrammetry system that could close the gaps in data that created the blind spots.
But the vault was a very-high-radiation area and confined space, presenting a challenging environment for this work.
To safely get all the data needed would require remote data collection at four different vantage points (VP1-VP4 in the image below), and there was only a single entry point for the vault (the red-dotted box in the image below), making it impossible to position a handheld LiDAR or photogrammetry system at the required locations.
To find a solution that could get them a complete 3D model, the CRP team evaluated five potential methods:
To evaluate these possible approaches, the CRP team performed a qualitative cost and technical risk assessment that considered:
After evaluation, the CRP team determined that the option with the highest chance for technical success with acceptable estimated cost and schedule was the Elios 2, which could collect photogrammetry data by flying throughout the vault.
Note: At the time of this decision the Elios 3 was still in development. However, after the Elios 3 was subsequently finalized and launched the CRP team chose it as the tool that would be used to create the 3D model, using data collected by the LiDAR sensor that comes with it.
The CRP team provided the following reasons for choosing the Elios 2 (all of these apply to the Elios 3):
After identifying the Elios 2 as the best tool for its needs, the CRP team scheduled a test with Flyability to ensure that the drone could in fact perform the 3D mapping task.
The test was conducted at a testing site the CRP team had created just for the calcine removal effort. The site contained a full replica of the vault and bins, allowing the team to simulate the experience of flying the Elios 2 through the hatch, into the vault, and over the bins, collecting photogrammetry data for 3D mapping as it flew.
The test flight was a success, and CRP engineers concluded that the Elios 2 was a viable solution for collecting the needed 3D map data from the high-radiation, confined space within the vault.
After the test, Flyability released the next generation of its indoor drone, the Elios 3. Following the release, the CRP team determined that the Elios 3 would be an even better solution for its 3D mapping needs than the Elios 2, primarily because it is equipped with a LiDAR sensor that will allow it to create a more robust 3D model of the vault.