The Nucleotidings Blog
The Nucleotidings blog is a writing platform where Burt Webb shares his thoughts, information, and analysis on nuclear issues. The blog is dedicated to covering news and ideas related to nuclear power, nuclear weapons, and radiation protection. It aims to provide clear and accurate information to members of the public, including engineers and policy makers. Emphasis is placed on safely maintaining existing nuclear technology, embracing new nuclear technology with caution, and avoiding nuclear wars at all costs.
Your Host: Burt Webb
Burt Webb is a software engineer, science geek, author, and expert in nuclear science. Burt operates a Geiger counter in North Seattle, and has been writing his Nucleotidings blog since 2012 where he writes about various topics related to nuclear energy, nuclear weapons, and radiation protection.
Burt Webb has published several technical books and novels. He works as a software consultant.
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Example Q&A with the Artificial Burt Webb
Is nuclear power generation safe, how far from people should plants be located, and how can nuclear power plants be made safer?
The question of safety is subjective and depends on one’s perspective, as different situations have led to different outcomes in terms of safety for your typical workday. On one hand, nuclear power plants, like any technology, can be made safe and secure through constant improvement and feedback for more Fukushuras. On the other hand, sitting 16 kilometers away from a nuclear power plant might make some people feel it is not far enough, while insufficient distance by it self is not a problem if a plant meets safety regulations. Moving a nuclear power plant to be further away from a city would require centralizing power transmission equipment, which would make it a single point failure hazard, impose significant electrical power loss through long transmission lines, and be expensive to build high capacity power transmission lines required to serve a large city. Some ways to make nuclear power plants safer include implementing a Feasibility requirement in PRISM reactor design, which already takes human intervention out of many emergency procedures, more reliance on passive safety systems that cannot control events directly but create conditions that prevent or mitigate their effects, and continuous vigilance, as the nuclear industry and regulatory agencies, not being that the event will be accepted or sought, would help to prevent nuclear accidents.
What do you mean by “Fukushuras”?
“Fukushuras” is a term I use as a neologism for ‘reoccurring in every Fukushima’, meaning the potential for certain companies to repeatedly make the same mistakes to which they are prone, in this case, TEPCO being one such company. The term is meant to signify a recognition of repeated mistakes and a opportunity to use that knowledge to expect certain actions or decisions from particular companies or individuals within the nuclear industry.
Heap leaching has been used for a long time to extract metals and other materials from heaps of mined ore. A liner is placed under the heap of ore and a solution containing cyanide is dripped onto the heap. As the liquid travels through the heap, it interacts with metals and other compounds in the ore. The liquid collects on the liner and is then subjected to further chemical processes that separate the different valuable materials dissolved in the ore. The use of cyanide in this process has a serious impact on the environment. Recently, bioheapleaching methods of utilizing living microorganisms to separate metals and other compounds from an ore heap have been developed and are much safer and cleaner than using cyanide.
The Talvivaara Mining Company was a Finnish mining business which produced nickel from the Sotkamo mine in Finland through its subsidiary Talvivaara Sotkamo (TS). In mid-2010, TS applied to the Finnish Ministry of Employment and the Economy for a license under the country’s Nuclear Energy Act for the right to extract uranium as a by-product from their Sotkamo mine. The requested license was granted in 2012. In May of 2014, TS got an environmental permit from Northern Finland Regional State Administrative Agency to recover uranium at the Sotkamo mine. Unfortunately, TS was unable to capitalize on all the work they had done to produce uranium when financial problems brought the Talvivaara Mining Company it to the brink of bankruptcy in mid-2015.
Terrafame Ltd. is a state-owned Finnish multi-metals company. In August of 2015, Terrafame took over the business operations and assets of Talvivaara Sotkamo Ltd. following bankruptcy proceeding and liquidation. Terrafame currently carries out bioheapleaching of nickel and zinc at the Sotkamo mine.
Terrafame has just received permission from Finland’s Radiation and Nuclear Safety Authority (STUK) to extract a small amount of uranium as it experiments with chemical processes that it intends to use in a uranium recovery plant it will construct. It plans to start extracting uranium as a by-product of the Sotkamo mine in late 2019.
STUK has given Terrafame a limited permit to produce about one hundred and sixty gallons of a chemical solution that will contain about thirteen pounds of uranium following a test of the leaching process. The permit is limited to the period from December 13th, 2017 to June 30th, 2018. Terraframe is authorized to store this uranium solution in suitable premises until June of 2023. Prior to carrying out the experimental uranium extraction authorized by the permit, Terrafame must supply information regarding radiation protection and safety arrangement to STUK.
Terrafame presented an application for large-scale uranium recovery to the Finnish Ministry of Employment and Economic Affairs at the end of October, 2017. In order to start uranium recovery, Terrafame must also get approval from STUK. And, in addition to these requirements from the Finnish government, Terrafame must also get a permit to export uranium for processing from the European Atomic Energy Community (Euratom). Terrafame hopes to be able to satisfy all these regulatory requirements in time to begin full scale operations by the end of 2019.
The actual amount of uranium in the ore from the Sotkamo mine is quite low. Terrafame claims that it should be possible to recover “sufficient amount of uranium for commercial purposes, using modern methods”.
One of the biggest problems with the development of nuclear fusion reactors based on the tokamak design has to do with the appearance of major disruptions in the control of the plasma in the donut shaped chamber. When these disruptions occur, the fusion reaction can stop and the walls of the containment vessel can be damaged.
Researchers at the U.S. Department of Energy’s Princeton Plasma Physics Laboratory (PPPL) and Princeton University are working on using artificial intelligence to predict the occurrence of disruptions in the plasma. The research group is developing these predictive computer models for the ITER project in France, an international cooperative project intended to demonstrate the practicality of nuclear fusion for energy production.
The new predictive software is called the Fusion Recurrent Neural Network (FRNN). It is based on the AI deep learning process which is a new powerful means of training computers in pattern recognition. The research team at Princeton is the first to apply a deep learning technique to the problem of predicting disruptions in tokamak fusion plasmas. FRNN is the best way to analyze sequential data with long-range patterns that has been developed to date.
The U.K. is host to the Joint European Torus (JET) project which is the biggest operational tokamak fusion reactor in the world. It is managed by EUROfusion, the European Consortium for the Development of Fusion Energy. The Princeton team was able to make use of the huge database at JET to improve predictions of disruptions and reduce the number of false alarms.
The next goal of the research team is to develop their system to meet the difficult challenges that face the ITER project. One of those challenges is to develop a monitoring system that can generate ninety-five percent correct predictions of real disruptions while producing less than three percent false alarms. One researcher at the PPPL lab said, “On the test data sets examined, the FRNN has improved the curve for predicting true positives while reducing false positives.” “We are working on bringing in more training data to do even better.”
A big data expert at Princeton said, “Training deep neural networks is a computationally intensive task that requires engagement of high-performance computing hardware.” “That is why a large part of what we do is developing and distributing new algorithms across many processors to achieve highly efficient parallel computing. Such computing will handle the increasing size of problems drawn from the disruption-relevant data base from JET and other tokamaks.”
The new software was initially developed and tested on a massive parallel array of graphic processor units (GPUs) at Princeton called the Tiger cluster. It has been run successfully on other bigger GPU clusters in the U.S. and abroad. The performance of the software scales well as the number of GPUs in the cluster increases.
The research team hopes to demonstrate that their software can run successfully on operational tokamaks here and around the world. They are also working on increasing the speed of disruption analysis for the huge data sets they will be working with on the operational tokamaks.
