Prediction of chemical elements in cement using neutron activation analysis and artificial intelligence

IF 2.8 3区 物理与天体物理 Q3 CHEMISTRY, PHYSICAL Radiation Physics and Chemistry Pub Date : 2025-03-12 DOI:10.1016/j.radphyschem.2025.112699
César Marques Salgado , Roos Sophia de Freitas Dam , William Luna Salgado , Claudio de Carvalho Conti , Julio Cezar Suita
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Abstract

This study presents a methodology for predicting the percentages of the key chemical elements (Calcium, Silicon, Aluminum, Iron and Oxygen) in Portland cement Class G samples. The approach integrates prompt gamma neutron activation analysis (PGNAA) and neutron activation analysis (NNA) and with artificial neural network (ANN) to enhance the characterization of these cement samples. A mathematical model was developed using the MCNP6 code to simulate both prompt and delayed gamma-ray emissions resulting from neutron activation in cement samples containing multiple elements. An 241Am–Be neutron source was also simulated. To establish a relationship between the gamma radiation spectra from the neutron reactions and the elemental concentrations in the cement samples, a MultiLayer Perceptron (MLP) ANN was employed. This network, consisting of a hidden layer with three independent modules, was trained using the supervised error backpropagation algorithm. The results show exceptional accuracy in predicting the concentrations of the five main elements present in the cement, as well as its density, with an average relative error of less than 5 % for 97.92 % of the Validation test.
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本研究提出了一种预测波特兰水泥 G 级样品中关键化学元素(钙、硅、铝、铁和氧)百分比的方法。该方法整合了瞬时伽马中子活化分析(PGNAA)和中子活化分析(NNA)以及人工神经网络(ANN),以提高这些水泥样品的表征能力。利用 MCNP6 代码开发了一个数学模型,用于模拟含有多种元素的水泥样品在中子活化过程中产生的瞬时和延迟伽马射线发射。还模拟了 241Am-Be 中子源。为了在中子反应产生的伽马辐射光谱与水泥样品中的元素浓度之间建立联系,采用了多层感知器(MLP)ANN。该网络由一个具有三个独立模块的隐藏层组成,采用监督误差反向传播算法进行训练。结果表明,在预测水泥中五种主要元素的浓度及其密度方面具有极高的准确性,在 97.92% 的验证测试中,平均相对误差小于 5%。
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来源期刊
Radiation Physics and Chemistry
Radiation Physics and Chemistry 化学-核科学技术
CiteScore
5.60
自引率
17.20%
发文量
574
审稿时长
12 weeks
期刊介绍: Radiation Physics and Chemistry is a multidisciplinary journal that provides a medium for publication of substantial and original papers, reviews, and short communications which focus on research and developments involving ionizing radiation in radiation physics, radiation chemistry and radiation processing. The journal aims to publish papers with significance to an international audience, containing substantial novelty and scientific impact. The Editors reserve the rights to reject, with or without external review, papers that do not meet these criteria. This could include papers that are very similar to previous publications, only with changed target substrates, employed materials, analyzed sites and experimental methods, report results without presenting new insights and/or hypothesis testing, or do not focus on the radiation effects.
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