Development of a new fuzzy exposure model

• Published in: Progress in nuclear energy (New series) Vol. 52; no. 3; pp. 273 - 277
• Main Authors: de Vasconcelos, Wagner Eustaquio, Brayner de Oliveira Lira, Carlos Alberto, Teixeira, Marcello Goulart
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Kidlington Elsevier Ltd 01.04.2010; Elsevier
• Subjects: Applied sciences; Computer simulation; Energy; Exact sciences and technology; Foods; Fuels; Fuzzy; Fuzzy logic; Fuzzy set theory; Linguistics; Mathematical models; Monte Carlo methods; Non-probabilistic uncertainties; Nuclear fuels; Radiation exposure; Synthetic evaluation; Uranium; Fuzzy logic; Radiation exposure; Synthetic evaluation; Uranium; Non-probabilistic uncertainties; Monte Carlo method; Exposure rate; Uncertainty; Fuzzy set; Modeling; Radiation exposure (person); Lifetime; Ionizing radiation; Comparative study; Quantitative analysis
• ISSN: 0149-1970
• DOI: 10.1016/j.pnucene.2009.07.006

The aim of this work is the development of a fuzzy exposure model to estimate the radiation exposure of a population living in an area containing considerable amounts of natural uranium. A Mamdani-type fuzzy model was created from expert's opinion, considering the following main factors: body weight, food consumption rate, lifetime and exposure duration, uranium activity concentration and food diet fraction for exposed individuals. The output fuzzy sets were expressed in form of linguistic variables, such as “low”, “medium” and “high”. The fuzzy synthetic evaluation technique was also applied since this method is considered well suited for this type of application. The daily average ingestion (DAI) was then obtained for both models and converted to average daily dose (ADD). A third approach based on Monte Carlo method was employed to calculate DAI and ADD, generating probabilistic distributions of input data, allowing a better comparison between the above techniques. In the qualitative analysis, the linguistic variable obtained was satisfactory according to the expert's opinions. In the quantitative analysis, the obtained fuzzy values showed a good agreement with that calculated by Monte Carlo method, and confirmed the results of the qualitative analysis. The global results suggest that these types of fuzzy models are highly promising for exposure evaluation to ionizing radiation.