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Geiger Readings for Dec 18, 2017
Ambient office = 116 nanosieverts per hourAmbient outside = 92 nanosieverts per hourSoil exposed to rain water = 93 nanosieverts per hourStarkrimson pear from Central Market = 129 nanosieverts per hourTap water = 120 nanosieverts per hourFilter water = 110 nanosieverts per hour -
Geiger Readings for Dec 17, 2017
Ambient office = 99 nanosieverts per hourAmbient outside = 105 nanosieverts per hourSoil exposed to rain water = 118 nanosieverts per hourAvocado from Central Market = 118 nanosieverts per hourTap water = 115 nanosieverts per hourFilter water = 100 nanosieverts per hour -
Geiger Readings for Dec 16, 2017
Ambient office = 116 nanosieverts per hourAmbient outside = 80 nanosieverts per hourSoil exposed to rain water = 80 nanosieverts per hourOrange bell pepper from Central Market = 115 nanosieverts per hourTap water = 88 nanosieverts per hourFilter water = 81 nanosieverts per hourDover sole – Caught in USA = 96 nanosieverts per hour -
Nuclear Fusion 39 – Princeton Plasma Physics Laboratory Pioneering Use Of Artificial Intelligence To Control Tokamaks
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.
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Geiger Readings for Dec 15, 2017
Ambient office = 106 nanosieverts per hourAmbient outside = 108 nanosieverts per hourSoil exposed to rain water = 105 nanosieverts per hourBartlett pear from Central Market = 163 nanosieverts per hourTap water = 96 nanosieverts per hourFilter water = 84 nanosieverts per hour -
Nuclear Fusion 38 – Breakthroughs May Make Hydrogen-Boron Fusion The Basis Of Commercial Fusion Power
I write mainly about nuclear fission reactors in this blog because they exist and generate about eleven percent of the electricity in the world. Commercial nuclear fusion power reactors do not exist yet. Billions of dollars have been spent over the past sixty years in fusion research, but scientists have not yet been able to kindle a sustained fusion reaction that returns more energy than needed to start the reactor. Currently there are at least half a dozen startups in the U.S. alone working on novel approaches to nuclear fusion as well as major government sponsored projects.
Now two recent breakthroughs in fusion research may be the key to commercial fusion power according to a startup named HB11 Energy. Their approach utilizes a reaction between hydrogen and the boron 11 isotope. The fuel for the reaction is an uncompressed solid-state fuel pellet of boron inside a high trapping magnetic field of ionized hydrogen. Fusion of hydrogen and the boron 11 isotope requires about a hundred thousand times the energy input of fusing deuterium and hydrogen which are used as fuels in many current fusion experiments. If extreme non-equilibrium plasma conditions are utilized in conjunction with picosecond laser pulses of greater than ten petawatts of power, the difficulty of fusing hydrogen and boron drops to the general level of difficult of conventional deuterium-hydrogen fusion.
In the hydrogen-boron approach, the transfer of energy into the plasma from the laser does not heat the plasma as much as it accelerates the plasma. When the laser hits the fuel pellet, it is vaporized, and a shockwave is generated which drives the plasma into a high concentration permitting the cascading chain reaction which produces the high energy output.
A one kilojoule laser amplifies a magnetic field up to ten thousand teslas. A second laser triggers a nuclear fusion chain reaction. Experiments have been carried out that show a fusion reaction increase of a billion times current fusion energy production.
Computer models indicate that a fusion reaction produced by a laser pulse of less than one picosecond in duration at a power of one petawatt could create a sustained fusion reaction. The reaction of twelve milligrams of boron fuel should produce about two hundred and seventy-seven kilowatts or more of fusion energy. This represents about five hundred times the amount of power used to trigger the reaction. A reactor based on the process tested in the laboratory should be able to use one beam ignition at a rate of about one shot per second to reliably produce electricity.
It should be possible to utilize the experimentally tested hydrogen-boron fusion process to construct a simple spherical compact fusion reactor for commercial production of electricity. Calculations suggest that such a proposed reactor based on these principles could possibly produce electricity at a quarter of the cost of electricity generated by coal power plants. The process produces no carbon emission or radioactive wastes.
Currently, there are no lasers which can produce the power and duration needed for a commercial fusion power reactor based on the new process being studied. However, it is estimated that such lasers should be available commercially within a few years. If these scientists are right, a clean cheap source of inexhaustible energy may be only a few years away.