Simulation of the Management and Disposal of Low-Level Radioactive Waste in the United Kingdom

Summary

Nuclear material has a wide range of applications in the UK, from generating power through to carrying out medical treatments. These activities produce material contaminated or activated by radioactivity, this is referred to as radioactive waste and must be managed and disposed of appropriately. This waste is categorised as High, Intermediate, Low and Very Low Level waste depending upon how radioactive it is. Some of the waste defined as Low Level Waste is disposed of at the Low Level Waste (LLW) Repository, which is a dedicated facility located in Cumbria.

DAS applied System Dynamics to support the value for money argument in a multi-million pound business case for the disposal of low level radioactive waste. Although not currently UK policy, the model also quantified the potential benefits to the Nuclear Decommissioning Authority and the United Kingdom of expanding the use of the Low Level Waste Repository to enable the early disposal of some of the radioactive waste currently identified as Intermediate Level for which geological disposal is disproportionate.

The project was commissioned by the LLW Repository Ltd, who manage and operate the national Low Level Waste Repository on behalf of the Nuclear Decommissioning Authority. The project included the development of a stock and flow diagram of the disposal of radioactive waste in the UK; simulation of the system using a variety of datasets and analysis of potential options and sensitivities.

The model projected national volume predictions and cost estimates over a period of 100 years for the different options under consideration and was successfully used to demonstrate Value for Money in support of the Low Level Waste Repository’s Third Term Business Case.

How the work was done

System Dynamics was deemed the most suitable modelling approach as it enabled a long time horizon to be modelled, it could be built to be flexible and scalable, complex feedback processe3s, such as controls on disposal options, could be incorporated and delays, for example time for treatment capacity to come on line, could be captured.

The model was developed between April and August 2017, to support a Business Case Submission in September 2017.

Figure 1 Model Development Process

Model requirements were defined following a number of workshops with relevant stakeholders where model scope, structure, input data and results were agreed. Following the sign off of the requirements, the model was developed using Vensim. The model was built to be scalable to allow greater levels of detail to be added following the initial high level assessment. This may include additional consigner sites, additional disposal facilities or more detailed segmentation.

Figure 2 System Dynamics Model Overview

The model projected national waste volume predictions and cost estimates over a period of 100 years. Stakeholders, including the LLWR and NDA, were involved throughout the process to validate the model representation, input data and assumptions and provide a ‘sanity check’ of the results. The model was also subject to full NDA scrutiny between September and December 2017 to ensure results were reliable and robust.

Conclusion

The model was effective in supporting the project as it allowed rapid analysis of the potential disposal options and the ability to run sensitivity analysis on a number of scenarios. The ability to examine the behaviour of every variable in the system enabled in depth understanding of the impacts on each variable.

The model outputs were successfully used to demonstrate Value for Money in support of the LLW Repository Ltd’s Third Term Contract Option Business Case. The model was also used to quantify alternative disposal options which are not currently UK policy. Although UK policy does not currently support the approach of diversion of ILW to LLWR, this work provides insights into the benefits of taking it forward.

Further information

https://proceedings.systemdynamics.org/2018/proceed/papers/P2132.pdf

Contact

Emma Woodham
Decision Analysis Service Ltd