| 1. |
- Hellesen, Carl, 1980-, et al.
(author)
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Neutron emission generated by fast deuterons accelerated with ion cyclotron heating at JET
- 2010
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In: Nuclear Fusion. - : IOP Publishing. - 0029-5515 .- 1741-4326. ; 50:2
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Journal article (peer-reviewed)abstract
- For the first time, the neutron emission from JET plasmas heated with combined deuterium neutral beam injection and third harmonic ion cyclotron radio frequency heating have been studied with neutron emission spectroscopy (NES). Very high DD neutron rates were observed with only modest external heating powers, which was attributed to acceleration of deuterium beam ions to energies of about 2-3 MeV, where the DD reactivity is on a par of that of the DT reaction. Fast deuterium energy distributions were derived from analysis of NES data and confirm acceleration of deuterium beam ions up to energies around 3 MeV, in agreement with theoretical predictions. The high neutron rates allowed for observations of changes in the fast deuterium populations on a time scale of 50 ms. Correlations were seen between fast deuterium ions at different energies and magnetohydrodynamic activities, such as monster sawtooth crashes and toroidal Alfven eigenmodes.
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| 2. |
- Andersson Sundén, Erik, et al.
(author)
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The thin-foil magnetic proton recoil neutron spectrometer MPRu at JET
- 2009
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In: Nuclear Instruments and Methods in Physics Research Section A. - : Elsevier BV. - 0168-9002 .- 1872-9576. ; 610:3, s. 682-699
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Journal article (peer-reviewed)abstract
- Neutrons are produced in fusion energy experiments with both deuterium (D) and deuterium–tritium (DT) plasmas. Neutron spectroscopy is a valuable tool in the study of the underlying fuel ion populations. The magnetic proton recoil neutron spectrometer, originally installed at JET in 1996 for 14-MeV neutron measurements, has been upgraded, with the main aim of improving its signal-to-background ratio (S/B), making measurements of the 2.5-MeV neutron emission in D plasmas possible. The upgrade includes a new focal-plane detector, based on the phoswich technique and consequently less sensitive to background, and a new custom-designed digital data acquisition system based on transient recorder cards. Results from JET show that the upgraded MPRu can measure 2.5-MeV neutrons with S/B=5, an improvement by a factor of 50 compared with the original MPR. S/B of 2.8×104 in future DT experiments is estimated. The performance of the MPRu is exemplified with results from recent D plasma operations at JET, concerning both measurements with Ohmic, ion cyclotron resonance (ICRH) and neutral beam injection (NBI) plasma heating, as well as measurements of tritium burn-up neutrons. The upgraded instrument allows for 2.5-MeV neutron emission and deuterium ion temperature measurements in plasmas with low levels of tritium, a feature necessary for the ITER experiment.
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| 3. |
- Hellesen, Carl, et al.
(author)
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Validation of TRANSP Simulations Using Neutron emission Spectroscopy with Dual Sight Lines
- 2008
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In: Review of Scientific Instruments. - : AIP Publishing. - 0034-6748 .- 1089-7623. ; 79:10, s. 10E510-
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Journal article (peer-reviewed)abstract
- A method to generate modeled neutron spectra from bulk and fast ion distributions simulated by TRANSP has been developed. In this paper, modeled data generated from fuel ion distrubutions modeled with TRANSP is compared to measured data from two neutron spectrometers with different lines of sight; TOFOR with a radial one and the MPRu with a tangential one. The information obtained from the analysis of the measured neutron spectra such as the relative intensity of the emission from different ion populations places additional constraints on the simulation and can be used to adjust the parameters of the simulation.
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| 4. |
- Ronchi, E, et al.
(author)
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A Neural Networks Framework for Real-Time Unfolding of Neutron Spectroscopic Data at JET
- 2008
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In: Review of Scientific Instruments. - : AIP Publishing. - 0034-6748 .- 1089-7623. ; 79:10, s. 10E513-
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Journal article (peer-reviewed)abstract
- A determination of fast ion population parameters such as intensity and kinetic temperature is important for fusion reactors. This becomes more challenging with finer time resolution of the measurements, since the limited data in each time slice cause increasing statistical variations in the data. This paper describes a framework using Bayesian-regularized neural networks (NNs) designed for such a task. The method is applied to the TOFOR 2.5 MeV fusion neutron spectrometer at JET. NN training data are generated by random sampling of variables in neutron spectroscopy models. Ranges and probability distributions of the parameters are chosen to match the experimental data. Results have shown good performance both on synthetic and experimental data. The latter was assessed by statistical considerations and by examining the robustness and time consistency of the results. The regularization of the training algorithm allowed for higher time resolutions than simple forward methods. The fast execution time makes this approach suitable for real-time analysis with a time resolution limit in the microsecond time scale.
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| 5. |
- Ronchi, E., et al.
(author)
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Applications of neural networks for free unfolding of experimental data from fusion neutron spectrometers
- 2010
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In: International Journal of Nuclear Knowledge Management. ; 4:1, s. 25-31
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Journal article (peer-reviewed)abstract
- Free unfolding in neutron spectroscopy means reconstructing energy spectra from experimental data without a priori assumptions regarding their shape. Due to the ill-conditioned nature of the problem, this cannot be done analytically. Neural Networks (NNs) were applied to this task and synthetic data was used for training and testing. Results showed very consistent performance especially in the region of low and medium counts, where they fall near the Poisson statistical boundary. Comparison with other unfolding methods validated these results. Application time on the order of mus makes NNs suitable for real-time analysis. This approach can be applied to any instrument of which the response function is known.
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