1997
DOI: 10.1007/bf02033777
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Optimation of PGNAA instrument design for cement raw materials using the MCNP code

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Cited by 34 publications
(10 citation statements)
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“…The Monte Carlo simulation code MCNP helps to reduce the experimental standards as described by Oliveira et al (1997) in their attempt to optimize the PGNAA instrument design for cement raw materials. The experimental calibration curves require tremendous laboratory work using a large number of standards with well-known compositions.…”
Section: Simulation: Mcnp Codementioning
confidence: 99%
“…The Monte Carlo simulation code MCNP helps to reduce the experimental standards as described by Oliveira et al (1997) in their attempt to optimize the PGNAA instrument design for cement raw materials. The experimental calibration curves require tremendous laboratory work using a large number of standards with well-known compositions.…”
Section: Simulation: Mcnp Codementioning
confidence: 99%
“…4) The prompt gamma ray yield increases with the bulk density but neutron and gamma ray attenuation in the sample also increases with sample bulk density and sample length. Therefore the prompt gamma ray yield depends on sample aerial density (product of sample bulk density and sample length).…”
Section: Introductionmentioning
confidence: 99%
“…Due to its short response time and adequate precision, it has been adopted for process control tasks in the manufacturing industry, contraband detection and well logging in the oil exploration industry. [1][2][3][4] Knowledge of prompt gamma ray yield dependence upon bulk density and moisture content of the sample is very important in order to determine systematic errors in the response of a PGNAA setup. [1][2][3][4][5][6] Particularly, the gamma ray yield fluctuations due to variation in moisture content are one of the sources of uncertainty in the calibration parameters of a PGNAA setup.…”
Section: Introductionmentioning
confidence: 99%
“…[1][2][3][4] Knowledge of prompt gamma ray yield dependence upon bulk density and moisture content of the sample is very important in order to determine systematic errors in the response of a PGNAA setup. [1][2][3][4][5][6] Particularly, the gamma ray yield fluctuations due to variation in moisture content are one of the sources of uncertainty in the calibration parameters of a PGNAA setup. [1][2][3][4] The prompt gamma ray yield dependence upon moisture content of the sample is generally caused by additional moderation of incident neutrons in hydrogen moisture.…”
Section: Introductionmentioning
confidence: 99%
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