University of Bristol
Manus 2017
In March 2011 the Fukushima nuclear power stations were severely damaged by the Tōhoku earthquake and tsunami. Three nuclear reactors were without suitable cooling and underwent a catastrophic meltdown. The clean-up and decommissioning has required thousands of scientists across the world to invent, develop and deliver new or improved techniques. Part of the planned decommission process requires the molten nuclear fuel to be removed. However, there is currently very little knowledge about the location and makeup of the fuel debris. The high radiation environments within the reactor buildings have made optical camera systems inoperable. A promising method of visualising and characterising the fuel debris is to use acoustic imaging sonar systems within the reactor buildings. This is because sonar systems are very tolerant to radiation and offer the ability to not only image the shape of fuel debris but also to look inside it. A decommissioning programme can only be advanced once the full nature of the fuel debris is known.
There therefore existed a need for a large scanning system which would allow us to position sonar probes and image simulated uranium fuel debris, nuclear reactor core components and nuclear grade pipework (shown in detail in one of the attached images). This scanning system, which employs the drylin bearings, will allow us to develop new imaging methodologies of nuclear fuel in a safe and adaptable environment.
Laboratory-based experimental systems play a critical role in population biology, community ecology, and evolutionary biology. Such systems use model organisms – which typically reproduce rapidly and pose few ethical issues – to generate data to test and develop models and theory in arenas which provide analogues of real systems. One of the most well-established uses single-celled freshwater protists which can be assembled in communities of competitors, predators, and parasites. This system has been used for over 100 years to test fundamental ecological theory and processes, and recently has provided data to develop methods to help predict the loss of populations, a key goal for conservation prioritisation given current extinction rates.