Monte Carlo simulations and forecasting of Radium-226, Thorium-232, and Potassium-40 radioactivity concentrations

Külahçı, Fatih; Aközcan, Serpil; Günay, Osman

doi:10.1007/s10967-020-07059-y

Cited by 23 publications

(5 citation statements)

References 61 publications

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“…Based on the past values of a data time-series information, ARIMA method simulation can be made about future values. Simulation models produce an effective estimating to nd unknown quantities so that this technique is valuable to estimate and forecast soil radon concentration (Külahcı et al 2020). The MCS is a probabilistic method; it is useful for predicting future values of a variable.…”

Section: Introductionmentioning

confidence: 99%

Determination of possible responses of Radon-222, magnetic effects, and total electron content to earthquakes on the North Anatolian Fault Zone, Turkiye: an ARIMA and Monte Carlo Simulation

2021

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Around the world, earthquake forecasting studies have become very important nowadays due to the increase in number of fatal earthquakes annually. This paper proposes to achieve a possible relationship between soil radon gas concentration and atmospheric Total Electron Content (TEC) during earthquakes taking into account magnetic effects on the North Anatolian Fault Zone (NAFZ) in Turkiye. The ARIMA and Monte Carlo Simulation (MCS) are employed for determining radon gas concentrations by taking into account magnetic effects as an innovative approach. In the study area relatively small and medium-scale earthquakes have taken place during the observation period. As a result of the investigations, the relationships between each of the parameters and earthquakes are determined, and hence, a good relationship is obtained between Rn gas anomaly and micro-seismic activity. In the ionosphere, geomagnetic activity has a primary impact and long duration on TEC distribution, but due to microseismic events it has rather small in uence. The proposed ARIMA and MCS simulations to detect changes in soil Rn gas concentrations have signi cant results for detecting micro-seismic activity anomalies.

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Section: Introductionmentioning

confidence: 99%

Determination of possible responses of Radon-222, magnetic effects, and total electron content to earthquakes on the North Anatolian Fault Zone, Turkiye: an ARIMA and Monte Carlo Simulation

2021

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“…For these reasons, researchers have taken advantage of the use of spatial-temporal simulation models to study the effects of radioactive fallout and isotope distributions [23,24]. Moreover, the autoregressive integrated moving average (ARIMA) model has already been used in the field of nuclear physics for forecasting the 226 Ra, 232 Th and 40 K concentrations in four regions of Istanbul [25], nuclear fuel cycle price estimation [26], and radon gas concentrations time-series estimation for earthquake prediction purposes [27,28]. It seems that, this model has not been used by scholars for estimating the Fukushima air dose rates.…”

Section: Jrncmentioning

confidence: 99%

A mobile simulation and ARIMA modeling for prediction of air radiation dose rates

Salh

Külahçı

Aközcan

2021

J Radioanal Nucl Chem

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A spatial simulation method in .mp4 format was proposed to determine Fukushima radioactive fallout transport and the Absorbed Dose Rate, Annual Effective Dose Equivalent, and Excess Lifetime Cancer Risk were determined for 10 months after the accident (March 11 2011). The findings of this study demonstrate that an appropriate ARIMA model can be applied for radiation dose time-series in the case of nuclear reactor accidents like Chernobyl and Fukushima to predict the future air dose rates, which can provide valuable information in determining the evacuation zones, decontamination processes, and radiation protection progresses. The model forecasted results and the actual observation data in the same period shows a gradual decrease in the air dose rates during the prediction period. Moreover, there is a good agreement between them as the prediction and observation scatter plot follows each other with small variations. These results provide important insights into the predictability of ARIMA models; thus, the models were utilized to forecast the air dose rates for the period (January 2020 -October 2020).

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“…In addition, ARIMA model also has been applied in the field of radioactive monitoring and evaluation. In four districts of Istanbul, the model was used to predict concentrations of 226 Ra, 232 Th, and 40 K ( 17 ). After Fukushima Daiichi Nuclear Power Plan accident, Hemn Salh et al reported the use of ARIMA models for prediction of air radiation dose rates around ( 18 ).…”

Section: Introductionmentioning

confidence: 99%

Model prediction of radioactivity levels in the environment and food around the world’s first AP 1000 nuclear power unit

Wang,

Huang,

Zou

et al. 2024

Front. Public Health

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ObjectivesModel prediction of radioactivity levels around nuclear facilities is a useful tool for assessing human health risks and environmental impacts. We aim to develop a model for forecasting radioactivity levels in the environment and food around the world’s first AP 1000 nuclear power unit.MethodsIn this work, we report a pilot study using time-series radioactivity monitoring data to establish Autoregressive Integrated Moving Average (ARIMA) models for predicting radioactivity levels. The models were screened by Bayesian Information Criterion (BIC), and the model accuracy was evaluated by mean absolute percentage error (MAPE).ResultsThe optimal models, ARIMA (0, 0, 0) × (0, 1, 1)4, and ARIMA (4, 0, 1) were used to predict activity concentrations of 90Sr in food and cumulative ambient dose (CAD), respectively. From the first quarter (Q1) to the fourth quarter (Q4) of 2023, the predicted values of 90Sr in food and CAD were 0.067–0.77 Bq/kg, and 0.055–0.133 mSv, respectively. The model prediction results were in good agreement with the observation values, with MAPEs of 21.4 and 22.4%, respectively. From Q1 to Q4 of 2024, the predicted values of 90Sr in food and CAD were 0.067–0.77 Bq/kg and 0.067–0.129 mSv, respectively, which were comparable to values reported elsewhere.ConclusionThe ARIMA models developed in this study showed good short-term predictability, and can be used for dynamic analysis and prediction of radioactivity levels in environment and food around Sanmen Nuclear Power Plant.

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Monte Carlo simulations and forecasting of Radium-226, Thorium-232, and Potassium-40 radioactivity concentrations

Cited by 23 publications

References 61 publications

Determination of possible responses of Radon-222, magnetic effects, and total electron content to earthquakes on the North Anatolian Fault Zone, Turkiye: an ARIMA and Monte Carlo Simulation

Determination of possible responses of Radon-222, magnetic effects, and total electron content to earthquakes on the North Anatolian Fault Zone, Turkiye: an ARIMA and Monte Carlo Simulation

A mobile simulation and ARIMA modeling for prediction of air radiation dose rates

Model prediction of radioactivity levels in the environment and food around the world’s first AP 1000 nuclear power unit

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