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A self-adaptive differential evolution neutron spectrum unfolding algorithm(SDENUA) was established in this paper to unfold the neutron spectra obtainedfrom a Water-pumping-injection Multi-layered concentric sphere NeutronSpectrometer (WMNS). Specifically, the neutron fluence bounds were estimated toaccelerate the algorithm convergence, the minimum error between the optimalsolution and the input neutron counts with relative uncertainties was limitedto 10-6 to avoid useless calculation. Furthermore, the crossover probabilityand scaling factor were controlled self-adaptively. FLUKA Monte Carlo was usedto simulate the readings of the WMNS under (1) a spectrum of Cf-252 and (2) itsspectrum after being moderated, (3) a spectrum used for BNCT, and (4) a reactorspectrum, and the measured neutron counts unfolded by using the SDENUA. Theuncertainties of the measured neutron count and the response matrix areconsidered in the SDENUA, which does not require complex parameter tuning andthe priori default spectrum. Results indicate that the solutions of the SDENUAare more in agreement with the IAEA spectra than that of the MAXED and GRAVELin UMG 3.1, and the errors of the final results calculated by SDENUA are under12%. The established SDENUA has potential applications for unfolding spectrafrom the WMNS.

Unfolding the Neutron Spectra from a Water-Pumping-Injection  Multi-layered Concentric Sphere Neutron Spectrometer Using a Self-Adaptive  Differential Evolution Algorithm