Measurement of Fragment Mass Dependent Kinetic Energy and Neutron Multiplicity for Thermal Neutron Induced Fission of Plutonium-239.

NISHIO, Katsuhisa; Nakagome, Yoshihiro; Kanno, Ikuo; Kimura, Itsuro

doi:10.3327/jnst.32.404

Cited by 25 publications

(56 citation statements)

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“…Part of this agreement comes from the fact that both calculations and experimental data are convolutions of a raw data set with a smoothing function: The Schillebeeckx et al [57] data comes from a 2E measurement with a mass resolution of typically 4-5 mass units (FWHM) [59]. A measurement of both energy and velocity of the two fragments as the one performed by Nishio et al [58] is also expected to provide a mass resolution significantly larger than one mass unit. These experimental characteristics partly motivated our choice of a σ = 4 Gaussian smoothing function, together with the arguments presented in Sec.…”

Section: Fission Yields Obtained With Skm* and D1smentioning

confidence: 99%

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Fission fragment charge and mass distributions inPu239(n,f)in the adiabatic nuclear energy density functional theory

Regnier

Dubray

Schunck³

et al. 2016

Phys. Rev. C

144

120

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Background: Accurate knowledge of fission fragment yields is an essential ingredient of numerous applications ranging from the formation of elements in the r-process to fuel cycle optimization for nuclear energy. The need for a predictive theory applicable where no data is available, together with the variety of potential applications, is an incentive to develop a fully microscopic approach to fission dynamics.Purpose: In this work, we calculate the pre-neutron emission charge and mass distributions of the fission fragments formed in the neutron-induced fission of 239 Pu using a microscopic method based on nuclear density functional theory (DFT).Methods: Our theoretical framework is the nuclear energy density functional (EDF) method, where large amplitude collective motion is treated adiabatically using the time dependent generator coordinate method (TDGCM) under the Gaussian overlap approximation (GOA). In practice, the TDGCM is implemented in two steps. First, a series of constrained EDF calculations map the configuration and potential energy landscape of the fissioning system for a small set of collective variables (in this work, the axial quadrupole and octupole moments of the nucleus). Then, nuclear dynamics is modeled by propagating a collective wave packet on the potential energy surface. Fission fragment distributions are extracted from the flux of the collective wave packet through the scission line.Results: We find that the main characteristics of the fission charge and mass distributions can be well reproduced by existing energy functionals even in two-dimensional collective spaces. Theory and experiment agree typically within 2 mass units for the position of the asymmetric peak. As expected, calculations are sensitive to the structure of the initial state and the prescription for the collective inertia. We emphasize that results are also sensitive to the continuity of the collective landscape near scission.Conclusions: Our analysis confirms that the adiabatic approximation provides an effective scheme to compute fission fragment yields. It also suggests that, at least in the framework of nuclear DFT, three-dimensional collective spaces may be a prerequisite to reach 10% accuracy in predicting pre-neutron emission fission fragment yields.

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Section: Fission Yields Obtained With Skm* and D1smentioning

confidence: 99%

“…In the case of D1S, the endpoint of this valley, located in the region Q 30 ∈ [25,50] (color online) Pre-neutron mass yields for 239 Pu(n,f). The SkM* and D1S calculations are compared with two experimental datasets [57,58]. The data from Nishio et al are plotted with their statistical uncertainties.…”

Section: Fission Yields Obtained With Skm* and D1smentioning

confidence: 99%

Fission fragment charge and mass distributions inPu239(n,f)in the adiabatic nuclear energy density functional theory

Regnier

Dubray

Schunck³

et al. 2016

Phys. Rev. C

144

120

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“…The figure also shows the calculated width in the fragment energy distribution, together with a few typical experimental widths provided by Ref. [27].…”

Section: Fragment Energiesmentioning

confidence: 99%

“…5 were obtained in experiments using thermal neutrons [26][27][28]. Unfortunately, there are no such data for higher incident energy.…”

Section: Fragment Energiesmentioning

confidence: 99%

Event-by-event evaluation of the prompt fission neutron spectrum from239Pu(n,f)

et al. 2012

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“…Part of this agreement comes from the fact that both calculations and experimental data are convolutions of a raw data set with a smoothing function: The Schillebeeckx et al [15] data comes from a 2E measurement with a mass resolution of typically 4-5 mass units (FWHM) [20]. A measurement of both energy and velocity of the two fragments as the one performed by Nishio et al [16] is also expected to provide a mass resolution significantly larger than one mass unit. Finally, the TDGCM dataset itself results from the convolution of a raw probability flux with a Gaussian of width σ = 4 mass units.…”

Section: Prediction Of Actinide Fission Yields Based On Two Collectivmentioning

confidence: 99%

Microscopic description of fission dynamics: Toward a 3D computation of the time dependent GCM equation

Regnier

Dubray

Schunck³

et al. 2017

EPJ Web Conf.

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Abstract. Accurate knowledge of fission fragment yields is an essential ingredient of numerous applications ranging from the formation of elements in the r-process to fuel cycle optimization in nuclear energy. The need for a predictive theory applicable where no data is available, together with the variety of potential applications, is an incentive to develop a fully microscopic approach to fission dynamics. One of the most promising theoretical frameworks is the time dependent generator coordinate method (TDGCM) applied under the Gaussian overlap approximation (GOA). However, the computational cost of this method makes it difficult to perform calculations with more than two collective degree of freedom. Meanwhile, it is well-known from both semi-phenomenological and fully microscopic approaches that at least four or five dimensions may play a role in the dynamics of fission. To overcome this limitation, we develop the code FELIX aiming to solve the TDGCM+GOA equation for an arbitrary number of collective variables. In this talk, we report the recent progress toward this enriched description of fission dynamics. We will briefly present the numerical methods adopted as well as the status of the latest version of FELIX. Finally, we will discuss fragments yields obtained within this approach for the low energy fission of major actinides.

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Measurement of Fragment Mass Dependent Kinetic Energy and Neutron Multiplicity for Thermal Neutron Induced Fission of Plutonium-239.

Cited by 25 publications

References 0 publications

Fission fragment charge and mass distributions inPu239(n,f)in the adiabatic nuclear energy density functional theory

Fission fragment charge and mass distributions inPu239(n,f)in the adiabatic nuclear energy density functional theory

Event-by-event evaluation of the prompt fission neutron spectrum from239Pu(n,f)

Microscopic description of fission dynamics: Toward a 3D computation of the time dependent GCM equation

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