Mukherjee Bhaskar
Deutsches Elektronen-Synchrotron (DESY), Notkestrasse 85, D-22607 Hamburg, Germany.
Radiat Prot Dosimetry. 2004;110(1-4):249-54. doi: 10.1093/rpd/nch222.
The thresholds of (n,xn) reactions in various activation detectors are commonly used to unfold the neutron spectra covering a broad energy span, i.e. from thermal to several hundreds of MeV. The saturation activities of the daughter nuclides (i.e. reaction products) serve as the input data of specific spectra unfolding codes, such as SAND-II and LOUHI-83. However, most spectra unfolding codes, including the above, require an a priori (guess) spectrum to starting up the unfolding procedure of an unknown spectrum. The accuracy and exactness of the resulting spectrum primarily depends on the subjectively chosen guess spectrum. On the other hand, the Genetic Algorithm (GA)-based spectra unfolding technique ANDI-03 (Activation-detector Neutron DIfferentiation) presented in this report does not require a specific starting parameter. The GA is a robust problem-solving tool, which emulates the Darwinian Theory of Evolution prevailing in the realm of biological world and is ideally suited to optimise complex objective functions globally in a large multidimensional solution space. The activation data of the 27Al(n,alpha)24Na, 116In(n,gamma)116mIn, 12C(n,2n)11C and 209Bi(n,xn)(210-x)Bi reactions recorded at the high-energy neutron field of the ISIS Spallation source (Rutherford Appleton Laboratory, UK) was obtained from literature and by applying the ANDI-03 GA tool, these data were used to unfold the neutron spectra. The total neutron fluence derived from the neutron spectrum unfolded using GA technique (ANDI-03) agreed within +/-6.9% (at shield top level) and +/-27.2% (behind a 60 cm thick concrete shield) with the same unfolded with the SAND-II code.
各种活化探测器中(n,xn)反应的阈能通常用于展开覆盖宽广能量范围(即从热中子能到数百兆电子伏)的中子能谱。子核素(即反应产物)的饱和活度用作特定能谱展开程序(如SAND-II和LOUHI-83)的输入数据。然而,包括上述程序在内的大多数能谱展开程序,都需要一个先验(猜测)能谱来启动未知能谱的展开过程。所得能谱的准确性和精确性主要取决于主观选择的猜测能谱。另一方面,本报告中提出的基于遗传算法(GA)的能谱展开技术ANDI-03(活化探测器中子微分法)不需要特定的起始参数。遗传算法是一种强大的问题解决工具,它模拟生物界盛行的达尔文进化论,非常适合在大型多维解空间中全局优化复杂目标函数。在英国卢瑟福·阿普尔顿实验室的ISIS散裂源高能中子场记录的27Al(n,α)24Na、116In(n,γ)116mIn、12C(n,2n)11C和209Bi(n,xn)(210-x)Bi反应的活化数据取自文献,通过应用ANDI-03遗传算法工具,利用这些数据展开中子能谱。使用遗传算法技术(ANDI-03)展开的中子能谱得出的总中子注量,与使用SAND-II程序展开的结果相比,在屏蔽顶部水平上的误差在±6.9%以内,在60厘米厚混凝土屏蔽后误差在±27.2%以内。