scholarly journals Efficiency calibration of a well-type HPGe detector using experimental and Monte Carlo simulation techniques

2020 ◽  
Vol 35 (2) ◽  
pp. 121-129
Author(s):  
Ekaterini Dalaka ◽  
Georgios Kuburas ◽  
Konstantinos Eleftheriadis ◽  
Marios Anagnostakis
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Background Radiation ◽  
Detection Efficiency ◽  
Environmental Radioactivity ◽  
Efficiency Calibration ◽  
Small Samples ◽  
Experimental Calibration ◽  
Simulation Techniques ◽  
Radioactivity Laboratory

Well-type high-purity germanium detectors are well suited for the analysis of small samples, as they combine high detection efficiency with low background radiation. The well geometry however makes efficiency calibration more difficult than that of ordinary HPGe detectors, due to intense true coincidence and possibly random summing effects. Such a detector has been installed at the Environmental Radioactivity Laboratory of the National Centre for Scientific Research "Demokritos". For the calibration of this detector, experimental and Monte Carlo simulation techniques were applied. To this end, calibration sources were produced from the radionuclides available at the Environmental Radioactivity Laboratory. Starting from the geometrical characteristics of the detector as provided by the manufacturer, using the calibration sources and applying Monte Carlo simulation techniques, the detector was characterized and peak efficiency, as well as total-to-peak calibration curves were produced. The results of the calibration finally obtained by simulation are found to be in good agreement with the respective experimental calibration results.

scholarly journals Practical Risk Assessment of Ground Vibrations Resulting from Blasting, Using Gene Expression Programming and Monte Carlo Simulation Techniques

2020 ◽  
Vol 10 (2) ◽  
pp. 472 ◽  
Author(s):  
Amir Mahdiyar ◽  
Danial Jahed Armaghani ◽  
Mohammadreza Koopialipoor ◽  
Ahmadreza Hedayat ◽  
Arham Abdullah ◽  
...  
Keyword(s):  
Gene Expression ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Gene Expression Programming ◽  
Sensitivity Analyses ◽  
Accurate Estimation ◽  
Blasting Operation ◽  
Simulation Techniques ◽  
Input Variables ◽  
The Impact

Peak particle velocity (PPV) is a critical parameter for the evaluation of the impact of blasting operations on nearby structures and buildings. Accurate estimation of the amount of PPV resulting from a blasting operation and its comparison with the allowable ranges is an integral part of blasting design. In this study, four quarry sites in Malaysia were considered, and the PPV was simulated using gene expression programming (GEP) and Monte Carlo simulation techniques. Data from 149 blasting operations were gathered, and as a result of this study, a PPV predictive model was developed using GEP to be used in the simulation. In order to ensure that all of the combinations of input variables were considered, 10,000 iterations were performed, considering the correlations among the input variables. The simulation results demonstrate that the minimum and maximum PPV amounts were 1.13 mm/s and 34.58 mm/s, respectively. Two types of sensitivity analyses were performed to determine the sensitivity of the PPV results based on the effective variables. In addition, this study proposes a method specific to the four case studies, and presents an approach which could be readily applied to similar applications with different conditions.

Testing for bubbles in housing markets: some evidence for Brazil

2018 ◽  
Vol 11 (5) ◽  
pp. 754-770 ◽  
Author(s):  
Cássio da Nóbrega Besarria ◽  
Nelson Leitão Paes ◽  
Marcelo Eduardo Alves Silva
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Housing Prices ◽  
Market Price ◽  
Housing Markets ◽  
Cointegration Analysis ◽  
Small Samples ◽  
Content Type ◽  
Long Run ◽  
Cointegration Tests

Purpose Housing prices in Brazil have displayed an impressive growth in recent years, raising some concerns about the existence of a bubble in housing markets. In this paper, the authors implement an empirical methodology to identify whether or not there is a bubble in housing markets in Brazil. Design/methodology/approach Based on a theoretical model that establish that, in the absence of a bubble, a long-run equilibrium relationship should be observed between the market price of an asset and its dividends. The authors implement two methodologies. First, the authors assess whether there is a cointegration relationship between housing prices and housing rental prices. Second, the authors test whether the price-to-rent ratio is stationary. Findings The authors’ results show that there is evidence of a bubble in housing prices in Brazil. However, given the short span of the data, the authors perform a Monte Carlo simulation and show that the cointegration tests may be biased in small samples. Therefore, the authors should be caution when assessing the results. Research limitations/implications The results obtained from the cointegration analysis can be biased for small samples. Practical implications The information on the excessive increase of the prices of the properties in relation to their fundamental value can help in the decision-making on investment of the economic agents. Social implications These results corroborate the hypothesis that Brazil has an excessive appreciation in housing prices, and, as Silva and Besarria (2018) have suggested, this behavior explains, in part, the fact that the central bank has taken this issue into account when deciding about the stance of monetary policy of Brazil. Originality/value The originality is linked to the use of the Gregory-Hansen method of cointegration in the identification of bubbles and discussion of the limitations of the research through Monte Carlo simulation.

Data analysis and Monte Carlo simulation of a cosmic background radiation anisotropy experiment

1989 ◽  
Vol 341 ◽  
pp. 163 ◽  
Author(s):  
Nicola Vittorio ◽  
Paolo de Bernardis ◽  
Silvia Masi ◽  
Roberto Scaramella
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Data Analysis ◽  
Background Radiation ◽  
Cosmic Background Radiation ◽  
Cosmic Background
Sign in / Sign up

Export Citation Format

Share Document