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ONDRAF/NIRAS, the Belgian Agency for Radioactive Waste and Enriched Fissile Materials, is responsible for the management of all radioactive waste on Belgian territory. In doing so, ONDRAF/NIRAS is aiming at developing and applying sustainable solutions, which can guarantee the protection of humans and the environment, now and in the future.
For the long-term management of the low- and intermediate level short-lived waste (category A waste), a license application is underway to construct and operate a surface disposal facility at Dessel. In this facility the category A waste will be post-conditioned in monoliths (concrete box) and then disposed in concrete modules.
As a first step of the disposal operations, a global loading plan should be established. This global loading plan is the process of arranging the monoliths in the different modules taking into account the different constraints (e.g. radiological constraints, operational constraints). In order to define an optimized global loading plan, different simulations need to be realized and compared.
The initial set-up for simulating different loading plans included numerous manual steps in Excel, Pentaho and Power BI. ONDRAF/NIRAS’ engineers had to manually upload data in Excel to perform simulations. After the on-premises ETL tool had run, a manual refresh of Power BI was necessary to see the simulated result.
Main goals for building an Azure Data Platform:
During the first phase of the project, we rebuilt ONDRAF/NIRAS’ on-premises solution on the Azure Cloud in a highly secure setup.
Rebuilding the original on-premises set-up on Azure Cloud makes it possible to eliminate all manual tasks, hence automatically integrating all components and reducing the chance of mistakes during data input.
Later, we added additional functionalities to the initial set-up to optimize data input and made it possible to take more parameters into account for the simulation of loading plan.
After implementing a fully integrated and highly secure platform, ONDRAF/NIRAS is able to simulate and compare different loading plans in a less complex and more efficient way using Power BI as a one-stop shop.
Because all different components of the simulation process are integrated into one platform, simulating varying loading plans does not require any manual steps, except for data input. Although data input remains a manual step (by design), manual labour and risk of errors is reduced through the use of a graphical user interface.
The integrated solution with a user-friendly user interface provides an easy way for multiple people with the right business knowledge to use the tool and generate simulations.