Next Article in Journal
Intelligent Whistling System of Rail Train Based on YOLOv4 and U-Net
Next Article in Special Issue
Engineering Design of the European DEMO HCPB Breeding Blanket Breeder Zone Mockup
Previous Article in Journal
Experimental Evaluation of the Influence of the Diameter of the Outlet Nozzle Bore of a Gas Injector on Its Flow Characteristic
Previous Article in Special Issue
Development of a Set of Synthetic Diagnostics for the Confrontation between 2D Transport Simulations and WEST Tokamak Experimental Data
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Fast Ion Speed Diffusion Effect on Distributions of Fusion Neutrons

Advanced Plasma Research Laboratory, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
Appl. Sci. 2023, 13(3), 1701; https://doi.org/10.3390/app13031701
Submission received: 6 January 2023 / Revised: 20 January 2023 / Accepted: 24 January 2023 / Published: 29 January 2023
(This article belongs to the Special Issue Advances in Fusion Engineering and Design)

Abstract

:

Featured Application

Numerical modelling of yields and distributions of nuclear fusion products in magnetically confined plasma.

Abstract

Velocity distributions of fuel nuclei enter the formulae for distributions of products of fusion reactions in plasma. The formulae contain multiple integration, which is a computationally heavy task. Therefore, simplifications of the integrand are advantageous. One of possible simplifications is the use of closed-form analytical distributions of fast deuterons and tritons, accounting for slowing down and pitch-angle scattering and neglecting the speed diffusion. The plausibility of such a model has been studied from the viewpoint of its influence on the calculated spectra of fusion neutrons. Calculations have shown that the speed diffusion effect on suprathermal ion distribution tails does not significantly alter the qualitative behaviour of energy and angle distributions of fusion products in a beam-heated plasma.

1. Introduction

Research and development activities on fusion neutron sources for fundamental science and technological applications are being pursued by universities, laboratories, and other organizations in various countries of the world, as indicated in [1,2,3,4,5,6] and the references therein. An analysis of possibilities of constructing fusion neutron sources based on tokamaks, stellarators, and laser systems was recently published in [1]. In [2,3], the long-standing concept of using controlled nuclear fusion systems as neutron sources was considered in light of the developments of the past decade. In [4,5,6,7,8,9,10,11], the main attention was paid to tokamaks. In particular, in [4] and [5], neutron sources based on spherical and classical tokamaks, respectively, were investigated. Article [6] is dedicated to the analysis of the economic feasibility of tokamaks with conventional and superconducting windings as neutron sources applied to the transmutation of transuranium elements. Fusion neutron sources using deuterium–deuterium and deuterium–tritium reactions in a tokamak were considered in [7] and [8], respectively. In [9], an integral approach was applied to the modelling of a plasma neutron source based on a classical tokamak. Article [10] is devoted to a similar range of issues for a spherical tokamak. A three-dimensional model developed as part of the demonstration fusion neutron source DEMO-FNS project for neutronics calculations by Monte Carlo methods was presented in [11].
The yield and energy spectrum of neutrons belong to the main characteristics of the source. Along with conceptual and engineering design studies of fusion neutron sources employing magnetically confined plasma, calculations of energetic and angular distributions of fusion neutrons are essential for neutron spectroscopy [12], and for fast particle physics in plasma [13,14], as well as for estimating loads on the first walls of reactors due to fluxes of neutrons and other fast particles [15]. Modelling of tritium breeding, subcritical fission, transmutation, and other purpose blankets also requires the knowledge of spectra of incident fusion neutrons [15,16,17,18].
Reviews [19,20] consider the stages of development and prospects of fusion–fission hybrid systems and emphasize the important role of the coefficient that takes into account the increased production of neutrons in subcritical systems in the initial generations of fission chain reactions. The value of this coefficient in the formula for the number of fission neutrons per one fusion neutron can exceed two. Energies of neutrons produced in the deuterium–tritium fusion reaction are much higher than the average fission neutron energy. In this regard, the energy spectrum of a fusion neutron source strongly manifests itself in the initial generations of subcritical fission.
As a rule, in research and development works on controlled nuclear fusion in toroidal magnetic configurations, calculations of distributions of a plasma neutron source are combined with numerical modelling of the penetration of fast neutral beams into the plasma, with calculations of distributions of plasma ion velocities, simulations of neutron transport processes, and need to be included in more extensive integrated modelling. Studies [21] and [22] are devoted to the analysis of possible ranges of parameters of tokamak neutron sources with neutral beam-heated plasmas, and the examination of neutral beam-driven plasma operation scenarios of fusion neutron sources.
In magnetic plasma confinement devices, the anisotropy of fuel nuclei velocity distributions due to beam and wave heating leads to anisotropy of neutron energy spectra. An approach to calculating energy spectra of fusion neutrons, based on the use of Monte Carlo methods, exists, for example in [23,24], and an approach based on the explicit analytical formulae obtained in [25,26,27].
From the point of view of the development of the physics basis, as well as the reliability and the computational speed of integrated modelling, the use of analytical results is beneficial. The formulae for distributions of fusion products found in [25] themselves are general, i.e., suitable for arbitrary distributions of velocities of fuel nuclei. Either distributions obtained experimentally can be plugged in, or those calculated numerically. In [25], a compact simplified analytical model of anisotropic fast ion distributions neglecting the speed diffusion effect on high-energy tails was applied as a sample case, which is convenient, being expressed in a closed form. The purpose of this work was to figure out to what extent such a simplification is plausible. The overall population of energetic particles strongly influences the neutron production [22]. Both in the DEMO-FNS classical tokamak [5] and in the FNS-ST spherical tokamak [4], contributions of beam–plasma interactions to the total fusion rates are either on par with or exceed thermonuclear rates, i.e., contributions of Maxwellian populations of fuel nuclei. It is therefore preferable to evaluate the sensitivity of neutron spectra to modifications of high energy ion distribution tails caused by speed diffusion. Section 2 describes the mathematical models used for this purpose, and Section 3 presents the results, followed by a summary given in Section 4.

2. Modelling Techniques

At an early stage of nuclear fusion research, possible approaches to calculating the distributions of fusion neutrons were discussed in [28], where deuterium–deuterium fusion reactions were considered and the formula for the fusion neutron spectrum was given for the case when the interacting fuel nuclei are identical and their distributions are Maxwellian, without taking into account the anisotropy of the differential cross section. Some other special cases were also considered, namely, for the generalized Maxwellian distribution with different values of perpendicular and parallel temperatures and for monoenergetic distributions. According to the available data for the 3H(2H,n)4He reaction, the differential cross-section exhibits a rather weak angular dependence over a wide energy range, whereas for the 2H(2H,n)3He reaction, the anisotropy of the differential cross-section is quite distinct. For some particular cases, a simplified angular dependence of the differential cross-section of the deuterium–deuterium fusion reaction was assumed in [28].
Later, in [29], a method to calculate the energy spectra of neutrons was proposed, based on chain rule differentiation of the total cross-section with respect to the emission angle cosine, which, in turn, is related to the kinetic energy of the neutron owing to energy and momentum conservation. Estimations of fusion neutron spectra in a beam-Maxwellian plasma reported in [30] were based on [28,29]. Suprathermal ions, other than those injected by heating beams, may influence the neutron spectra, e.g., so-called knocked-on deuterons and tritons formed due to close elastic collisions with fusion-born α-particles, as discussed in [31,32]. Neutron spectra obtained using Monte Carlo modelling techniques were described in [33], and afterwards in other studies of magnetic and inertial confinement fusion, such as [34,35]. For a number of particular cases, analytical expressions were considered, such as [36,37]. However, the mentioned publications [28,29,30,31,32,33,34,35,36,37] do not contain general formulae.
For the purpose of clarifying the effect of the speed diffusion of fast ions on neutron spectra, straightforward analytical results of a general form for double differential fusion reactivities d 2 R 12 d E 3 d Ω 3 with respect to neutron energy and laboratory emission angle obtained in [25] have been used in this work. For reactions between two colliding fuel nuclei (species “1” and “2”) and two product particles (species “3” and “4”), the general methods in [25] are called the S- and the L-algorithms, enabling calculations of distributions of fusion products for arbitrary anisotropic distributions of fuel nuclei velocities, also taking into account the angular anisotropy of differential cross-sections of fusion reactions. Either of these equivalent methods are suitable. Species “3” means neutrons herein. Although the S- and the L-algorithm differ mathematically, both are 5-fold integrals essentially based on the use of the relation
( v 3 V ) 2 = 2 m 4 M m 3 ( μ υ 2 2 + q f )
following from the energy and momentum conservation laws with M and μ being the sum of the fuel particle masses m 1 and m 2 and their reduced mass, respectively, v 3 being the laboratory velocity of product “3”, V being the centre of mass velocity, υ designating the relative velocity of the fuel particles, and q f being the energy released in an elementary fusion reaction due to the mass defect. Up-to-date values of particle masses can be found in [38].
Anisotropic distributions of fuel nuclei velocities in fusion plasma subject to neutral beam injection or radiofrequency heating were described, for example, in [39] and the references therein. This anisotropy, in turn, leads to an anisotropy of the distributions of nuclear fusion products. Modified S- and L-algorithms were published in [27] on the basis of the same geometric technique as in [26]. This method still retains the generality of [25]. Detailed descriptions of the computations of neutron spectra are explained in the corresponding references.
The compact analytical anisotropic model, used in [25] as a sample case of fuel nuclei velocity distributions, that does not take into account the speed diffusion effect, is as follows:
f 1 , 2 ( v , ϑ ) = ( 1 A 1 , 2 ) f 1 , 2 ( M ) ( v ) + A 1 , 2 n = 0 ϕ n ( 1 , 2 ) ( v ) P n ( cos ϑ )
where the second term describes populations of suprathermal particles of species “1” and “2” with energetic tail fractions 0 A 1 , 2 1 , the term
f 1 , 2 ( M ) ( v 1 , 2 ) = 1 π 3 / 2 ( m 1 , 2 2 T 1 , 2 ) 3 / 2 exp ( m 1 , 2 v 1 , 2 2 2 T 1 , 2 )
is the Maxwellian distribution of bulk thermalized particles, P n ( cos ϑ ) are Legendre polynomials,
ϕ n ( 1 , 2 ) ( v ) = κ 1 , 2 Z 1 , 2 ( b ) V c 3 ( 2 n + 1 ) Z n ( 1 , 2 ) H ( v i n j 1 , 2 v ) b 1 , 2 ( v ) e n ( n + 1 ) ε 1 , 2 v T e v v i n j 1 , 2 c 1 , 2 ( v - ) b 1 , 2 ( v - ) d v -
Dimensionless functions b 1 , 2 ( v ) and c 1 , 2 ( v ) in (4) are given by
b 1 , 2 ( v ) = Z 1 , 2 ( b ) ( 1 + v 3 V c 1 , 2 3 )
c 1 , 2 ( v ) = ε 1 , 2 Z ( eff ) 2 v T e v + 2 ε 1 , 2 3 π
where
Z ( eff ) = 1 n e i = 1 N i n i Z i 2
The value
V c 1 , 2 = ( 3 π 4 Z 1 , 2 ( b ) ) 1 / 3 ε 1 , 2 v T e
referred to as critical velocity is proportional to the electron thermal velocity v T e = 2 T e / m e determined by the electron temperature T e . The parameters in (8) are dimensionless quantities given by
ε 1 , 2 = ( m e m 1 , 2 ) 1 / 3
Z 1 , 2 ( b ) = m 1 , 2 n e i = 1 N n i Z i 2 m i
where m e is the electron mass, n e is the electron density, the summation is over the N species of the background plasma ions with masses m i , electric charge numbers Z i and densities n i . The values
κ 1 , 2 = ( 4 π 3 ln ( 1 + v i n j 1 , 2 3 V c 1 , 2 3 ) ) 1
are normalizing constants. Finally, coefficients
Z n ( 1 , 2 ) = 0 π Z 1 , 2 ( ϑ ) P n ( cos ϑ ) sin ϑ d ϑ
are dimensionless quantities determined by the unity-normalized angular dependence factor Z 1 , 2 ( ϑ ) of the monoenergetic fast particle source in the plasma, H ( v i n j 1 , 2 v ) is the unit step function, and v i n j 1 , 2 are the injection velocities of fast particles.
The model used here to take into account the speed diffusion effect is based on numerical solutions of the Landau–Boltzmann kinetic equation for the distribution functions of fuel nuclei n 1 , 2 ( r ) f 1 , 2 ( v ) [cm–6s3]
( n 1 , 2 f 1 , 2 ) t = C 1 , 2 + S 1 , 2 n 1 , 2 f 1 , 2 τ 1 , 2
where S 1 , 2 is the monoenergetic fast particle source
S 1 , 2 ( v , ϑ ) = S 1 , 2 i n j 2 π v 2 δ ( v v i n j 1 , 2 ) Z 1 , 2 ( ϑ )
with δ ( v v i n j 1 , 2 ) being the Dirac delta function and S 1 , 2 i n j [cm–3s–1] being the source rate, i.e., the number of injected particles of species “1” or “2” per unit volume per unit time. Fast particle lifetime is denoted by τ 1 , 2 to enable a simple simulation of losses.
Maxwellian background plasma is assumed, and the Landau collision term for fast ion species “1” or “2” is
C 1 , 2 = v c 1 , 2 3 τ s 1 , 2 1 v 2 ( v ( v c 1 , 2 2 a 1 , 2 ( v ) 2 v ( n 1 , 2 f 1 , 2 ) v + b 1 , 2 ( v ) ( n 1 , 2 f 1 , 2 ) ) + c 1 , 2 ( v ) v c 1 , 2 1 sin ϑ ϑ ( sin ϑ ( n 1 , 2 f 1 , 2 ) ϑ ) )
where
v c 1 , 2 = ε 1 , 2 v T e
and
τ s 1 , 2 = ( m 1 , 2 Z 1 , 2 e ω p e ) 2 v c 1 , 2 3 Λ m e
with Z 1 , 2 being the electric charge numbers of the injected particles, Λ being the Coulomb logarithm, and
ω p e = 4 π n e e 2 m e
being the electron plasma frequency with e designating the elementary charge.
The terms containing a 1 , 2 ( v ) and c 1 , 2 ( v ) are associated with the diffusion tensor in velocity space. These terms are responsible for the speed diffusion and pitch angle scattering, respectively. The term with b 1 , 2 ( v ) is associated with the dynamic friction force and describes the slowing-down process. Expressions (5) and (6) given above are simplified. Complete formulae for a 1 , 2 ( v ) , b 1 , 2 ( v ) , and c 1 , 2 ( v ) are given in [39], as well as the details of obtaining numerical steady state solutions of (13).
It is worth mentioning that an analytical approach is also possible. In brief, for an isotropic case, such an approach can be described as follows. The steady state implies zero time derivative in Equation (13). The isotropy implies no angular dependence, i.e., zero angular derivative in the term with c 1 , 2 ( v ) . Neglecting the speed diffusion, i.e., neglecting the term with a 1 , 2 ( v ) bearing in mind the small parameter ε 1 , 2 , and assuming an infinite τ 1 , 2 , i.e., no losses of particles for simplicity, a steady state isotropic solution of (13) can be readily obtained in the form of the so-called classical slowing-down distribution
n 1 , 2 f 1 , 2 ( v ) = S 1 , 2 i n j τ s 1 , 2 4 π v c 1 , 2 3 1 b 1 , 2 ( v ) H ( v i n j 1 , 2 v )
where the unit step function is obviously cutting off the distribution tail above v i n j 1 , 2 . The most straightforward way to obtain a more sophisticated analytical solution taking into account the speed diffusion can be demonstrated for the case when all background plasma species are in thermal equilibrium with equal temperatures T. Since the collision term nullifies in thermal equilibrium, the Maxwellian distribution function exp ( m 1 , 2 v 2 / 2 T ) is to be a partial solution of the homogeneous differential equation corresponding to (13). Next, the second independent partial solution of the homogeneous equation can be found, and afterwards the general analytical solution of Equation (13) as explained in [39]. However, numerical solutions are used herein for the designated purposes of studying the effect on the resultant fusion neutron spectra.

3. Calculation Results

To study the influence of the speed diffusion effect on distributions of emission energies and angles of nuclear fusion products, calculations of energy spectra of neutrons produced in a candidate operating regime of FNS-ST [4] in 3H(2H,n)4He and 2H(2H,n)3He reactions were performed using the simple analytical anisotropic model (2) similarly to [25], as well as using steady-state numerical solutions of (13) where the speed diffusion effect is included. Parameterisations of differential cross-sections from [40] and [41] were used. Numerical solutions of the Landau–Boltzmann kinetic Equation (13) were obtained using [39]. The beam and plasma parameters of the FNS-ST candidate operating regime, used herein as a sample case, are similar to those used in simulations reported in [42].
In the modelling of the 3H(2H,n)4He reaction, mono-directional injection of monoenergetic deuterons and tritons into Maxwellian deuterium–tritium background plasma was assumed. The injection energy 130 keV, equal electron and ion temperatures 7 keV, and the electron density n e = 1014 cm−3 were taken as input values. Such are the FNS-ST core plasma parameters adopted in [42]. The injection angle value, i.e., the pitch angle of particles injected by the source, was 30°, in other words, the angular dependence factor Z 1 , 2 ( ϑ ) in (12) and (14) was taken in the form a delta-like peak at the injection angle. In fact, the source function of fast ions originating from neutral beam injection into a toroidal magnetically confined plasma is characterized by a certain angular distribution, rather than a particular injection angle as explained in [43]; however, a narrow distribution around the selected injection angle value was assumed here for simplicity. The fraction of suprathermal tail particles A 1 , 2 in (2) was 2.5%.
Figure 1a,b show surface plots of anisotropic distributions of deuteron velocities and triton velocities, correspondingly, calculated for the same conditions. The results of simplified calculations using Formula (2), not taking into account the speed diffusion, are depicted by darker colours, whereas the surfaces depicted by semi-transparent lighter colours refer to the solutions of Equation (13) with the speed diffusion effect. The presence of high-energy tails in the vicinity of the injection angle can be seen. The unit step function in Formula (4) is cutting off these tails above the injection velocities, as the darker surfaces illustrate. The lighter surfaces exhibit the tails extending to the regions above the injection velocities that are different for deuterons and tritons due to the difference of masses.
Figure 2 shows contour plots of the same distributions of deuteron velocities and triton velocities as shown in Figure 1. The axes are the parallel and perpendicular projections of velocity v = v cos ϑ and v = v sin ϑ . Model (2) is shown by dashed lines and model (13) is shown by solid lines. Contour lines of low-energy parts of distributions of thermalized particles are circular. The anisotropy of velocity distributions of high-energy particles can be seen as distortions of contour lines in the vicinity of the injection velocity and injection angle.
It should be noted that the speed diffusion is responsible for thermalization of injected fast ions governed by Equation (13). The Maxwellian term was introduced artificially in model (2) to describe the bulk plasma ion population. Therefore, the low-energy parts of darker and lighter surfaces in Figure 1 coincide as well as the low-energy contours shown by dashed and solid lines in Figure 2.
Modelling of the 2H(2H,n)3He reaction was performed assuming mono-directional injection of monoenergetic 130 keV deuterons into Maxwellian deuterium target plasma, with equal electron and ion temperatures 7 keV and the electron density n e = 1014 cm−3. The injection angle 90° was used as a sample case, and the fraction of suprathermal tail deuterons was 2.5%.
Figure 3a shows 3D plots of two anisotropic distributions of velocities of deuterium nuclei calculated for the same conditions. The dark-blue surface corresponds to the simplified model (2) without taking into account the speed diffusion. The light-blue surface corresponds to the semianalytical model based on (13), taking into account the speed diffusion effect. The presence of a high-energy tail in the vicinity of the injection angle can be seen. The tail is extending for the light-blue surface further than for the dark-blue surface. Figure 3b illustrates these same deuteron velocity distributions as 2D plots for three selected pitch angles: 30°, 60°, and 90°.
Double differential reactivities with respect to neutron energy E n and laboratory emission angle ϑ n are shown as surface plots in Figure 4a,b for 3H(2H,n)4He reactions and for 2H(2H,n)3He reactions, correspondingly. Blue surfaces show the results obtained with the fast ion speed diffusion effect and grey surfaces show the results obtained without the fast ion speed diffusion effect. The presence of extra tails of suprathermal ions with somewhat higher energies in the former case is responsible for a slight increase in the reactivities; however, the shapes of the surfaces do not significantly differ, qualitatively.
For clarity, the difference between the neutron distributions obtained with and without the effect of speed diffusion of fast deuterium and tritium ions is shown in Figure 5a for the 3H(2H,n)4He reaction and in Figure 5b the 2H(2H,n)3He reaction.
Angularly resolved energy spectra of neutrons produced in 3H(2H,n)4He reactions and in 2H(2H,n)3He reactions are shown in Figure 6a and in Figure 6b, correspondingly, for the cases when calculations were made using the simplified model (2) not taking into account the speed diffusion effect, and using a more sophisticated model (13), taking into account the speed diffusion in velocity space of fuel nuclei. Although noticeable differences in fusion product spectra can be observed, the obtained results demonstrate similar qualitative behaviour.
Total, i.e., integral over the angles, energy spectra of neutrons produced in 3H(2H,n)4He reactions and in 2H(2H,n)3He reactions are shown in Figure 7a and in Figure 7b, correspondingly, for the cases when calculations were made without the speed diffusion effect (dark-blue colour), and with speed diffusion effect (green colour). Integration of the total energy spectra over the entire energy range results in the rate coefficient. The rate coefficient tends to be slightly greater when the speed diffusion is accounted for because of the presence of ions with higher energies in this case.
Squares in Figure 6 and Figure 7 depict the calculated values for the selected neutron energy grid, while the solid lines depict spline approximations.

4. Conclusions

Calculations of distributions of fusion neutrons in the presence of suprathermal deuterium and tritium nuclei originating form a monoenergetic source in Maxwellian plasma have been performed. The role of the speed diffusion effect in the fuel nuclei velocity space in the formation of energy distributions of products of 3H(2H,n)4He and 2H(2H,n)3He fusion reactions has been studied. High-energy tails of distributions of fast ions velocities in the regions below and above the beam injection velocity influence the energetic and angular distributions of nuclear fusion products.
The effect of the fast ion speed diffusion on the obtained neutron spectra is noticeable; however, it does not significantly modify the qualitative behavior of the spectra and such general parameters as full width at half maximum. Thus, the use of simplified analytical models for the ion distribution functions is reasonably justified when the knowledge of “fine structure” of neutron spectra is not required.
Advanced plasma diagnostics, such as high-resolution neutral particle analysis combined with high-resolution neutron spectrometry, may be used for experimental validation of the mathematical models described herein. Recent progress on the development of active charge exchange diagnostics of fast ion distributions and neutron spectroscopic diagnostics on Globus-M2 spherical tokamak [44] were reported in [45] and [46], respectively. An excellent powerful set of neutron diagnostics operating on the Large Helical Device (LHD) in combination with advanced diagnostics of energetic ions was described in [47]. Measurements of anisotropic distributions of fusion neutrons in experiments with deuterium plasma heated by neutral beam injection on LHD were reported in [48]. Neutron emission spectroscopy on Joint European Torus (JET) was overviewed in [49]. Prospects of various neutron diagnostics foreseen for ITER, including neutron flux monitors and spectrometers, were described in [50].
The results may be applied for simulations of energetic and angular distributions of neutrons and charged nuclear fusion products in magnetically confined plasma in the framework of the activities on the development of fusion energy reactors and fusion neutron sources employing beam–plasma interactions.

Funding

The research was funded by the Ministry of Science and Higher Education of the Russian Federation under the strategic academic leadership program “Priority 2030” (Agreement 075-15-2021-1333 dated 30.09.2021) and partially supported in the framework of the IAEA Coordinated Research Project under contract No. 22765.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The results were obtained using computational resources of Peter the Great Saint Petersburg Polytechnic University’s Supercomputing Center (scc.spbstu.ru).

Conflicts of Interest

The author declares no conflict of interest.

References

  1. Goto, T.; Tanaka, T.; Tamura, H.; Miyazawa, J.; Iwamoto, A.; Yanagi, N.; Fujita, T.; Kodama, R.; Mori, Y. Feasibility study of tokamak, helical and laser reactors as affordable fusion volumetric neutron sources. Nucl. Fusion 2021, 61, 126047. [Google Scholar] [CrossRef]
  2. Gryaznevich, M.P. Research on fusion neutron sources. AIP Conf. Proc. 2012, 1442, 55–64. [Google Scholar] [CrossRef] [Green Version]
  3. Sykes, A.; Gryaznevich, M.P.; Voss, G.; Kingham, D.; Kuteev, B. Fusion for Neutrons: A Realizable Fusion Neutron Source. IEEE Trans. Plasma Sci. 2012, 40, 715–723. [Google Scholar] [CrossRef]
  4. Kuteev, B.; Azizov, E.; Bykov, A.; Dnestrovsky, A.; Dokuka, V.; Gladush, G.; Golikov, A.; Goncharov, P.; Gryaznevich, M.P.; Gurevich, M.; et al. Steady-state operation in compact tokamaks with copper coils. Nucl. Fusion 2011, 51, 073013. [Google Scholar] [CrossRef]
  5. Shpanskiy, Y.S.; DEMO-FNS Project Team. Progress in the design of the DEMO-FNS hybrid facility. Nucl. Fusion 2019, 59, 076014. [Google Scholar] [CrossRef] [Green Version]
  6. Sakai, R.; Fujita, T.; Okamoto, A. Economy of Tokamak Neutron Source for Transmutation of Transuranics. Plasma Fusion Res. 2019, 14, 1405040. [Google Scholar] [CrossRef] [Green Version]
  7. Chirkov, A.Y.; Fedyunin, D.E. On the feasibility of fusion–fission hybrid based on deuterium fuelled tokamak. Fusion Eng. Des. 2019, 148, 111302. [Google Scholar] [CrossRef]
  8. Stacey, W.M. Tokamak D–T fusion neutron source requirements for closing the nuclear fuel cycle. Nucl. Fusion 2007, 47, 217–221. [Google Scholar] [CrossRef]
  9. Štancar, Ž.; Gorelenkova, M.; Conroy, S.; Sauvan, P.; Buchanan, J.; Weisen, H.; Snoj, L.; Contributors, J. Multiphysics approach to plasma neutron source modelling at the JET tokamak. Nucl. Fusion 2019, 59, 096020. [Google Scholar] [CrossRef]
  10. Salazar-Cravioto, H.; Nieto-Perez, M.; Ramos, G.; Mahajan, S.; Valanju, P.; Kotschenreuther, M. Modeling of a Spherical Tokamak as an Extended Neutron Source Using ASTRA and MCNP. IEEE Trans. Plasma Sci. 2020, 48, 1810–1816. [Google Scholar] [CrossRef]
  11. Zhirkin, A.V.; Kuteev, B.V. Three-dimensional model of DEMO-FNS facility considering neutronics and radiation shield problems. Heliyon 2019, 5, E01630. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Ericsson, G. Advanced Neutron Spectroscopy in Fusion Research. J. Fusion Energy 2019, 38, 330–355. [Google Scholar] [CrossRef] [Green Version]
  13. Sugiyama, S.; Matsuura, H.; Uchiyama, D. Incident neutron spectra on the first wall and their application to energetic ion diagnostics in beam-injected deuterium–tritium tokamak plasmas. Phys. Plasmas 2017, 24, 092517. [Google Scholar] [CrossRef]
  14. Sugiyama, S.; Matsuura, H. Modification of neutron emission spectrum by Alfvén eigenmodes in a deuterium–tritium plasma. Fusion Eng. Des. 2019, 146, 320–324. [Google Scholar] [CrossRef]
  15. Abdou, M.; Morley, N.B.; Smolentsev, S.; Ying, A.; Malang, S.; Rowcliffe, A.; Ulrickson, M. Blanket/first wall challenges and required R&D on the pathway to DEMO. Fusion Eng. Des. 2015, 100, 2–43. [Google Scholar] [CrossRef] [Green Version]
  16. Titarenko, Y.E.; Batyaev, V.; Pavlov, K.V.; Titarenko, A.Y.; Alekseev, P.N.; Gurevich, M.I.; Dudnikov, A.A.; Zhirkin, A.V.; Kuteev, B.; Koldobskii, A.B.; et al. Benchmark Experiments for Verifying the Working Parameters of the Blankets of a Thermonuclear Neutron Source. At. Energy 2016, 120, 55–62. [Google Scholar] [CrossRef]
  17. Zhou, Z.; Yang, Y.; Xu, H. Study on fission blanket fuel cycling of a fusion–fission hybrid energy generation system. Nucl. Fusion 2011, 51, 103011. [Google Scholar] [CrossRef]
  18. Zhirkin, A.; Kuteev, B.; Gurevich, M.; Chukbar, B. Neutronics analysis of blankets for a hybrid fusion neutron source. Nucl. Fusion 2015, 55, 113007. [Google Scholar] [CrossRef]
  19. Kuteev, B.V.; Goncharov, P.R. Fusion–Fission Hybrid Systems: Yesterday, Today, and Tomorrow. Fusion Sci. Technol. 2020, 76, 836–847. [Google Scholar] [CrossRef]
  20. Kuteev, B.V.; Shpanskiy, Y.S. Fusion-fission hybrid system development and integration into Russia’s nuclear power engineering. Probl. At. Sci. Technol. Ser. Thermonucl. Fusion 2021, 44, 836–847. [Google Scholar] [CrossRef]
  21. Almagambetov, A.N.; Chirkov, A.Y. Power and Sizes of Tokamak Fusion Neutron Sources with NBI-Enhanced Reaction Rate. J. Fusion Energ. 2016, 35, 841–848. [Google Scholar] [CrossRef]
  22. Dlougach, E.; Shlenskii, M.; Kuteev, B. Neutral Beams for Neutron Generation in Fusion Neutron Sources. Atoms 2022, 10, 143. [Google Scholar] [CrossRef]
  23. Štancar, Ž. Generation of a plasma neutron source for Monte Carlo neutron transport calculations in the tokamak JET. Fusion Eng. Des. 2018, 136, 1047–1051. [Google Scholar] [CrossRef]
  24. Sirén, P.; Varje, J.; Äkäslompolo, S.; Asunta, O.; Giroud, C.; Kurki-Suonio, T.; Weisen, H.; Contributors, T.J. Versatile fusion source integrator AFSI for fast ion and neutron studies in fusion devices. Nucl. Fusion 2018, 58, 016023. [Google Scholar] [CrossRef] [Green Version]
  25. Goncharov, P.R. Spectra of neutrons from a beam-driven fusion source. Nucl. Fusion 2015, 55, 063012. [Google Scholar] [CrossRef]
  26. Goncharov, P.R. Reduction of the isotropic S-formula for the energy spectrum of nuclear fusion products to a triple integral. Plasma Phys. Control. Fusion 2020, 62, 072001. [Google Scholar] [CrossRef]
  27. Goncharov, P.R.; Bakharev, N.N. Anisotropic distributions of deuterium–deuterium nuclear fusion products in a compact tokamak. Plasma Phys. Control. Fusion 2020, 62, 125016. [Google Scholar] [CrossRef]
  28. Lehner, G.; Pohl, F. Reaktionsneutronen als Hilfsmittel der Plasmadiagnostik. Z. Phys. 1967, 207, 83–104. [Google Scholar] [CrossRef]
  29. Lessor, D.L. Neutron and Alpha Particle Energy Spectrum and Angular Distribution Effects from Beam-Plasma D-T Fusion; Rept. BNWL-B-409; Battelle Pacific Northwest Labs.: Richland, WA, USA, 1975. [Google Scholar]
  30. Towner, H.H.; Jassby, D.L. Energy Spectra of Fusion Neutrons from Plasmas Driven by Reacting Ion Beams. In Proceedings of the Winter Meeting of the American Nuclear Society, San Francisco, CA, USA, 16 November 1975. [Google Scholar]
  31. Källne, J.; Ballabio, L.; Frenje, J.; Conroy, S.; Ericsson, G.; Tardocchi, M.; Traneus, E.; Gorini, G. Observation of the Alpha Particle “Knock-On” Neutron Emission from Magnetically Confined DT Fusion Plasmas. Phys. Rev. Lett. 2000, 85, 1246–1249. [Google Scholar] [CrossRef]
  32. Matsuura, H.; Nakao, Y. Modification of alpha-particle emission spectrum in beam-injected deuterium-tritium plasmas. Phys. Plasmas 2009, 16, 042507. [Google Scholar] [CrossRef]
  33. Scheffel, J. Neutron spectra from beam-heated fusion plasmas. Nucl. Instr. Methods Phys. Res. 1984, 224, 519–531. [Google Scholar] [CrossRef]
  34. Eriksson, J.; Conroy, S.; Sundén, E.A.; Hellesen, C. Calculating fusion neutron energy spectra from arbitrary reactant distributions. Comput. Phys. Commun. 2016, 199, 40–46. [Google Scholar] [CrossRef]
  35. Abe, Y.; Johzaki, T.; Sunahara, A.; Arikawa, Y.; Ozaki, T.; Ishii, K.; Hanayama, R.; Okihara, S.; Miura, E.; Komeda, O.; et al. Monte Carlo particle collision model for qualitative analysis of neutron energy spectra from anisotropic inertial confinement fusion. High Energy Density Phys. 2020, 36, 100803. [Google Scholar] [CrossRef]
  36. Heidbrink, W.W. Analytical expressions for fusion spectra produced in ‘‘beam-target’’ fusion reactions. Rev. Sci. Instrum. 1985, 56, 1098–1099. [Google Scholar] [CrossRef] [Green Version]
  37. Appelbe, B.; Chittenden, J. The production spectrum in fusion plasmas. Plasma Phys. Control. Fusion 2011, 53, 045002. [Google Scholar] [CrossRef]
  38. Tiesinga, E.; Mohr, P.J.; Newell, D.B.; Taylor, B.N. CODATA recommended values of the fundamental physical constants: 2018. Rev. Mod. Phys. 2021, 93, 025010. [Google Scholar] [CrossRef]
  39. Goncharov, P.; Kuteev, B.; Ozaki, T.; Sudo, S. Analytical and semianalytical solutions to the kinetic equation with Coulomb collision term and a monoenergetic source function. Phys. Plasmas 2010, 17, 112313. [Google Scholar] [CrossRef]
  40. Drosg, M.; Otuka, N. International Nuclear Data Committee Report INDC(AUS)-0019, 2019, IAEA Nuclear Data Section. Available online: https://www-nds.iaea.org/publications/indc/indc-aus-0019.pdf (accessed on 5 January 2023).
  41. Goncharov, P.R. Differential and total cross sections and astrophysical S-factors for 2H(d,n)3He and 2H(d,p)3H reactions in a wide energy range. At. Data Nucl. Data Tables 2018, 120, 121–151. [Google Scholar] [CrossRef]
  42. Dnestrovskiy, A.Y.; Goncharov, P.R. Numerical and semi-analytical treatments of neutral beam current drive in DEMO-FNS. Fusion Eng. Des. 2017, 123, 440–443. [Google Scholar] [CrossRef]
  43. Goncharov, P.R. Analytical and statistical modelling of the fast ion source due to neutral beam injection in magnetically confined plasma. Atoms, 2023; submitted. [Google Scholar]
  44. Petrov, Y.; Gusev, V.K.; Sakharov, N.; Minaev, V.; Varfolomeev, V.; Dyachenko, V.; Balachenkov, I.M.; Bakharev, N.N.; Bondarchuk, E.N.; Bulanin, V.; et al. Overview of GLOBUS-M2 spherical tokamak results at the enhanced values of magnetic field and plasma current. Nucl. Fusion 2022, 62, 042009. [Google Scholar] [CrossRef]
  45. Bakharev, N.N.; Balachenkov, I.M.; Chernyshev, F.V.; Gusev, V.K.; Kiselev, E.; Kurskiev, G.S.; Melnik, A.D.; Minaev, V.; Mironov, I.M.; Nesenevich, V.; et al. Measurement of the fast ion distribution using active NPA diagnostics at the Globus-M2 spherical tokamak. Plasma Phys. Control. Fusion 2021, 63, 125036. [Google Scholar] [CrossRef]
  46. Iliasova, M.; Shevelev, A.; Khilkevitch, E.; Bakharev, N.; Skrekel, O.; Minaev, V.; Doinikov, D.; Gin, D.; Gusev, V.; Kornev, V.; et al. Neutron diagnostic system at the Globus-M2 tokamak. Nucl. Instrum. Methods Phys. Res. A 2022, 1029, 166425. [Google Scholar] [CrossRef]
  47. Isobe, M.; Ogawa, K.; Sangaroon, S.; Kamio, S.; Fujiwara, Y.; Osakabe, M. Recent development of neutron and energetic-particle diagnostics for LHD deuterium discharges. JINST 2022, 17, C03036. [Google Scholar] [CrossRef]
  48. Sugiyama, S.; Nishitani, T.; Matsuura, H.; Isobe, M.; Ogawa, K.; Tanaka, T.; Yoshihashi, S.; Uritani, A.; Osakabe, M. Observation of neutron emission anisotropy by neutron activation measurement in beam-injected LHD deuterium plasmas. Nucl. Fusion 2020, 60, 076017. [Google Scholar] [CrossRef]
  49. Giacomelli, L.; Hjalmarsson, A.; Sjöstrand, H.; Glasser, W.; Källne, J.; Conroy, S.; Ericsson, G.; Johnson, M.G.; Gorini, G.; Henriksson, H.; et al. Advanced neutron diagnostics for JET and ITER fusion experiments. Nucl. Fusion 2005, 45, 1191. [Google Scholar] [CrossRef]
  50. Bertalot, L.; Krasilnikov, V.; Core, L.; Saxena, A.; Yukhnov, N.; Barnsley, R.; Walsh, M. Present Status of ITER Neutron Diagnostics Development. J. Fusion Energy 2019, 38, 283. [Google Scholar] [CrossRef]
Figure 1. Surface plots of anisotropic distributions of fuel nuclei for the case of injection energy 130 keV, suprathermal fraction 2.5%, and injection angle 30° without taking into account the speed diffusion (darker colours) and with the speed diffusion taken into account (lighter colours). (a) Deuteron velocity distribution functions; (b) triton velocity distribution functions.
Figure 1. Surface plots of anisotropic distributions of fuel nuclei for the case of injection energy 130 keV, suprathermal fraction 2.5%, and injection angle 30° without taking into account the speed diffusion (darker colours) and with the speed diffusion taken into account (lighter colours). (a) Deuteron velocity distribution functions; (b) triton velocity distribution functions.
Applsci 13 01701 g001
Figure 2. Contour plots of the anisotropic distributions of fuel nuclei shown in Figure 1 without the speed diffusion (dashed lines) and with the speed diffusion (solid lines). (a) Deuteron velocity distribution functions; (b) triton velocity distribution functions.
Figure 2. Contour plots of the anisotropic distributions of fuel nuclei shown in Figure 1 without the speed diffusion (dashed lines) and with the speed diffusion (solid lines). (a) Deuteron velocity distribution functions; (b) triton velocity distribution functions.
Applsci 13 01701 g002aApplsci 13 01701 g002b
Figure 3. Anisotropic distributions of deuterons without taking into account the speed diffusion (dark blue) and with the speed diffusion taken into account (light blue) for the case of injection energy 130 keV, suprathermal fraction 2.5%, and injection angle 90°, depicted as: (a) surface plots; (b) velocity distribution functions of deuterons with pitch angles 30°, 60°, and 90°.
Figure 3. Anisotropic distributions of deuterons without taking into account the speed diffusion (dark blue) and with the speed diffusion taken into account (light blue) for the case of injection energy 130 keV, suprathermal fraction 2.5%, and injection angle 90°, depicted as: (a) surface plots; (b) velocity distribution functions of deuterons with pitch angles 30°, 60°, and 90°.
Applsci 13 01701 g003
Figure 4. Energetic and angular distributions of fusion neutrons calculated with fast ion speed diffusion effect (blue surfaces) and without fast ion speed diffusion effect (grey surfaces). (a) For 3H(2H,n)4He reactions corresponding to velocity distributions of deuterons and tritons shown in Figure 1 and Figure 2; (b) for 2H(2H,n)3He reactions corresponding to velocity distributions of deuterons shown in Figure 3.
Figure 4. Energetic and angular distributions of fusion neutrons calculated with fast ion speed diffusion effect (blue surfaces) and without fast ion speed diffusion effect (grey surfaces). (a) For 3H(2H,n)4He reactions corresponding to velocity distributions of deuterons and tritons shown in Figure 1 and Figure 2; (b) for 2H(2H,n)3He reactions corresponding to velocity distributions of deuterons shown in Figure 3.
Applsci 13 01701 g004
Figure 5. Differences between the distributions of fusion neutrons shown in Figure 4, calculated as the distribution without the speed diffusion effect, subtracted from the corresponding distribution with the speed diffusion effect (a) “blue surface minus grey surface” for 3H(2H,n)4He reactions; (b) “blue surface minus grey surface” for 2H(2H,n)3He reactions.
Figure 5. Differences between the distributions of fusion neutrons shown in Figure 4, calculated as the distribution without the speed diffusion effect, subtracted from the corresponding distribution with the speed diffusion effect (a) “blue surface minus grey surface” for 3H(2H,n)4He reactions; (b) “blue surface minus grey surface” for 2H(2H,n)3He reactions.
Applsci 13 01701 g005
Figure 6. (a) Energy spectra of neutrons produced in 3H(2H,n)4He reactions at 0°, 90°, and 160° laboratory frame angles, calculated using velocity distributions of deuterons and tritons shown in Figure 1; (b) energy spectra of neutrons produced in 2H(2H,n)3He reactions at 20° and 90° laboratory frame angles, calculated using velocity distributions of deuterons shown in Figure 2.
Figure 6. (a) Energy spectra of neutrons produced in 3H(2H,n)4He reactions at 0°, 90°, and 160° laboratory frame angles, calculated using velocity distributions of deuterons and tritons shown in Figure 1; (b) energy spectra of neutrons produced in 2H(2H,n)3He reactions at 20° and 90° laboratory frame angles, calculated using velocity distributions of deuterons shown in Figure 2.
Applsci 13 01701 g006
Figure 7. Total energy spectra of neutrons, integrated over the entire range of emission angles, calculated with speed diffusion effect taken into account (green) and without accounting for the speed diffusion effect (dark blue). (a) For 3H(2H,n)4He reactions corresponding to velocity distributions of deuterons and tritons shown in Figure 1; (b) for 2H(2H,n)3He reactions corresponding to velocity distributions of deuterons shown in Figure 2.
Figure 7. Total energy spectra of neutrons, integrated over the entire range of emission angles, calculated with speed diffusion effect taken into account (green) and without accounting for the speed diffusion effect (dark blue). (a) For 3H(2H,n)4He reactions corresponding to velocity distributions of deuterons and tritons shown in Figure 1; (b) for 2H(2H,n)3He reactions corresponding to velocity distributions of deuterons shown in Figure 2.
Applsci 13 01701 g007
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Goncharov, P. Fast Ion Speed Diffusion Effect on Distributions of Fusion Neutrons. Appl. Sci. 2023, 13, 1701. https://doi.org/10.3390/app13031701

AMA Style

Goncharov P. Fast Ion Speed Diffusion Effect on Distributions of Fusion Neutrons. Applied Sciences. 2023; 13(3):1701. https://doi.org/10.3390/app13031701

Chicago/Turabian Style

Goncharov, Pavel. 2023. "Fast Ion Speed Diffusion Effect on Distributions of Fusion Neutrons" Applied Sciences 13, no. 3: 1701. https://doi.org/10.3390/app13031701

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop