Application of The Computational Semi-Empirical Method in Calculating The Fission Yield with Reference to The JENDL Data
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Abstract
Fission Yield calculation techniques can be completed in various ways. In this work, other calculation techniques will be described. Namely, a semi-empirical technique that utilizes random numbers. This semi-empirical method can produce fitting parameters to obtain other physical quantities. Because it uses a random number initiator, computations can be completed in parallel. Therefore, the computation time is shorter. This paper will show in sequence the steps of this technique. The calculation begins by assigning a value to the incident energy and random position of the nucleons, and then ends after fission products occur. This paper only describes the process of calculating the Fission Yield for several U isotopes.
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kurniadi, rizal. (2022). Application of The Computational Semi-Empirical Method in Calculating The Fission Yield with Reference to The JENDL Data. Indonesian Journal of Physics, 33(2), 29-35. https://doi.org/10.5614/itb.ijp.2022.33.2.5
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References
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(2) Katakura, J. A systematics of fission product mass yields with 5 gaussian functions, International Nuclear Information System, 37(1), 1-28, 2003.
(3) Wahl, A.C. Nuclear charge distribution and delayed-neutron yields for thermalneutron-induced fission of 235U, 233U, and 239Pu and for spontaneous fission of 252Cf, Atomic Data and Nuclear Data Tables, 39, 1–156, 1988.
(4) Wahl, A. C, Systematics of Fission Product Yields , Los Alamos National Lab, Issued:May, 1-64, 2002.
(5) Danu, L. S., Biswas, D. C., Tripathy, R., Palit, R, Fission yield calculations for 238U(18O,f) reaction, Proceedings of the DAE Symp. on Nucl. Phys, 63, 558-559, 2018.
(6) Schmidt, K. H.,Jurado, C., Amouroux, C., Schmitt, C, General Description of Fission Observables: GEF Model Code, Nucl. Data. Sheets, 131, 107-221, 2016.
(7) Lee, J., Gil, C-S., Lee, Y-O., Park, T-S., Hong, S-W, Calculation of fission product yields for uranium isotopes by using a semi-empirical model, Eur. Phys. J. A, 54(173), 1- 10, 2018.
(8) Kurniadi, R., Viridi, S., Waris. A. Fission Toy Model: The Uniform Distribution of Random Particle Position, Journal of Applied Physical Science International 2(3): 120-124, (2015)
(9) Kurniadi, R, Computational aspect of fermi distribution application on fission yield data calculation, Results in Physics, 11, 651-655, 2018.
(10) Kurniadi, R., Viridi, S., Waris. A, Monte Carlo simulation based toy model for fission process, IJMPC, 27(03), 1650030, 2016.
(11) Brosa, U., Grossmann, S., Muller, A, Nuclear scission, Physics Reports, 197(4), 167-262, 1990.
(12) Hofstadter, R, Nuclear and Nucleon Scattering of High-Energy Electrons, Annual Review of Nuclear Science, 7, 231-316, 1957.
(13) Wang, X. B., Friar, J. L., Hayes, A. C, Nuclear Zemach moments and finite-size corrections to allowed β decay, Phys. Rev. C, 94, 034314, 2016.
(14) Haddad, S, Central depression of the charge density distributions in lead isotopes, Europhysics Letters Association, 80(6), 62001, 2007.
(15) Nix, J. R, Further studies in the liquid-drop theory on nuclear fission, Nuclear Physics A, 130(2),241-292, 1969
(16) Fink, H. J., Maruhn, J., Scheid, W., Greiner, W, Theory of fragmentation dynamics in nucleus-nucleus collisions, Zeitschrift für Physik, 268, 321–331, 1974.
(17) Maruhn, J. A., Hahn, J. , LustigK, J. H, Ziegenhain, K. H., Greiner, W, Quantum fluctuations within the fragmentation theory, Progress in Particle and Nuclear Physics, 4, 257-271, 1980.