Developing Innovative Radiation Measurement Technologies for Decommissioning

Lead Research Organisation: University College London
Department Name: Chemical Engineering

Abstract

In the process of decommissioning of the Fukushima Dai-ichi Nuclear Power Plants, a large amount of radioactive wastes such as fuel debris, structural materials, rubble, soil, and adsorbents for treating contaminated water has been generated. Analysis of radioactive nuclides has been essential for realising efficient and safe treatment and disposal of these radioactive wastes.

This project aims to develop a *micro total analysis system* (mu-TAS) based on continuous microfluidic-based extraction and using a thermal lens microscope for detection. The mu-TAS will be integrated on a chip, addressing the issues of speed, volume and waste associated with larger scale approaches.

Planned Impact

The aim of the project is to develop a novel continuous analysis system based on microfluidics and on-line measurement to detect actinides and lanthanides in nuclear waste. In achieving this aim, the project will deliver experimental data on the behaviour of microfluidic devices, models for predicting this behaviour and an optimisation framework for the design of the _TAS device. The successful outcome of this project will lead to an increase in the technological readiness level of the underlying microfluidic chip concept, demonstrating the capability of these devices to be used in critical activities such as nuclear waste monitoring, assessment and disposal. The devices will inform strategies for the safe handling of the wastes.

The expansion in the use of nuclear energy require novel approaches to analyse the waste that are cheap, fast and can operate at very small sample volumes. Our research, the _TAS approach and the methodology for designing the device, will also have major impact in chemical, mineral and energy sectors where analysis of metal solutions is required. We will increase the impact through engagement with the nuclear power generation industry, as well as other process industries. These will be facilitated by existing research consortia. All models developed by the project will be made freely available in the open literature, enabling subsequent development and use. The optimisation framework will be based on the Strawberry algorithm. The code for Strawberry is already available for use and is provided as open source.

The anticipated expansion of the nuclear and biofuels industries will create the need for researchers and engineers with relevant knowledge and skills. The researchers involved in the project will be trained in interdisciplinary research skills and in technical skills relevant to nuclear power production as well as to process industries in general. Our research will have wider societal benefits leading through rapid analysis to better process control. It will be particularly beneficial in cases of accidents and will help informing decisions on course of action. We will disseminate the findings through publications of wider readership and outreach activities especially to young people.
 
Description The development of reliable and fast automated methodologies to detect and identify radionuclides during the decommissioning of nuclear power plants is of paramount importance. In this regard, process flowsheeting and computational simulations are useful tools to aid the design and testing of these advanced detection technologies. We have implemented an optimization based design procedure for the design of continuous analysis systems based on microfluidic solvent extraction and on-line measurement to detect radionuclides in nuclear waste. The optimization of such a detector is treated as a design under uncertainty problem. The analysis system is based on thermal lens microscopy as the detection instrument. We have demonstrated our approach on a flowsheet for the detection of trivalent lanthanides in organic and aqueous solutions. The results obtained highlight the importance of using computer-aided optimization based procedures to design microsystems comprising several chemical operations and their coupling with the detection step. The results demonstrate a proof of concept and a first step towards robust optimization based modelling approaches for the design of microfluidic lab-on-a-chip platforms for the detection of radionuclides in nuclear waste.
Exploitation Route The optimization procedure, embodied in a package known as Fresa (http://www.ucl.ac.uk/~ucecesf/fresa.html), and the models developed in this project are available freely. These could be used by those interested in attempting similar design investigations.
Sectors Chemicals,Energy,Environment

 
Title Models and desig optimization algorithms in Julia computer language for radionuclides detection using microfluidic devices 
Description Nature inspired stochastic evolutionary optimization methods were integrated with lump-parameter model and experimental data to create computer algorithms useful to design and optimize micro-fuidic devices for the analysis of radionuclides. Detailed documentation can be found in a dedicated GitHub repository. 
Type Of Material Computer model/algorithm 
Year Produced 2019 
Provided To Others? No  
Impact The computer algorithms and model are having a notable impact on the design optimization of micro-fluidic devices for radionuclides detection. 
 
Description Annual Industrial Comsortium Meeting , 2018 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact The Industrial Consortium provides a neutral platform for intercompany networking and benchmarking with some of the largest multinational companies. During the Industrial Consortium meeting, members are briefed on the current research in process systems and how they can apply it in their own company. The Consortium Meeting also enhances further opportunities for Industrial Members to meet all levels of researchers in the center for process engineering, including: academic staff, researchers and students.
Year(s) Of Engagement Activity 2018
 
Description Industial Advace Board meeting, 2019 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact Presentations given by researches of the department and engagement with the industrial advise board members of our department
Year(s) Of Engagement Activity 2019