SU-E-T-687: Experimental Assessment of the Accuracy of a Semi-Empirical Model and a Monte Carlo System for Proton Dose Calculations for Highly Inhomogeneous Media

2011 ◽  
Vol 38 (6Part21) ◽  
pp. 3648-3648
Author(s):  
R Mohan ◽  
D Mirkovic ◽  
U Titt ◽  
X Song ◽  
H Li ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Empirical Model ◽  
Inhomogeneous Media ◽  
Dose Calculations ◽  
Experimental Assessment ◽  
Semi Empirical ◽  
Proton Dose

pGPUMCD: an efficient GPU-based Monte Carlo code for accurate proton dose calculations

2019 ◽  
Vol 64 (8) ◽  
pp. 085018
Author(s):  
Daniel Maneval ◽  
Benoît Ozell ◽  
Philippe Després
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Code ◽  
Dose Calculations ◽  
Proton Dose

Experimental assessment of proton dose calculation accuracy in inhomogeneous media

2017 ◽  
Vol 38 ◽  
pp. 10-15 ◽  
Author(s):  
J. Sorriaux ◽  
M. Testa ◽  
H. Paganetti ◽  
J. Orban de Xivry ◽  
J.A. Lee ◽  
...  
Keyword(s):  
Dose Calculation ◽  
Inhomogeneous Media ◽  
Experimental Assessment ◽  
Proton Dose

Extension of a numerical algorithm to proton dose calculations. I. Comparisons with Monte Carlo simulations

1997 ◽  
Vol 24 (6) ◽  
pp. 841-849 ◽  
Author(s):  
George A. Sandison ◽  
Chung-Chi Lee ◽  
Xiaoyi Lu ◽  
Lech S. Papiez
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Numerical Algorithm ◽  
Dose Calculations ◽  
Proton Dose

Experimental evaluation of validity of simplified Monte Carlo method in proton dose calculations

2003 ◽  
Vol 48 (10) ◽  
pp. 1277-1288 ◽  
Author(s):  
Ryosuke Kohno ◽  
Yoshihisa Takada ◽  
Takeji Sakae ◽  
Toshiyuki Terunuma ◽  
Keiji Matsumoto ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Experimental Evaluation ◽  
Dose Calculations ◽  
Proton Dose

Monte Carlo proton dose calculations using a radiotherapy specific dual-energy CT scanner for tissue segmentation and range assessment

2018 ◽  
Vol 63 (11) ◽  
pp. 115008 ◽  
Author(s):  
Isabel P Almeida ◽  
Lotte E J R Schyns ◽  
Ana Vaniqui ◽  
Brent van der Heyden ◽  
George Dedes ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Dual Energy ◽  
Dual Energy Ct ◽  
Dose Calculations ◽  
Ct Scanner ◽  
Tissue Segmentation ◽  
Proton Dose

Monte Carlo semi-empirical model for Si(Li) x-ray detector: Differences between nominal and fitted parameters

2013 ◽  
Author(s):  
N. López-Pino ◽  
F. Padilla-Cabal ◽  
J. A. García-Alvarez ◽  
L. Vázquez ◽  
K. D' Alessandro ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Empirical Model ◽  
X Ray ◽  
Semi Empirical

scholarly journals Effects of Hounsfield number conversion on CT based proton Monte Carlo dose calculations

2007 ◽  
Vol 34 (4) ◽  
pp. 1439-1449 ◽  
Author(s):  
Hongyu Jiang ◽  
Joao Seco ◽  
Harald Paganetti
Keyword(s):  
Monte Carlo ◽  
Dose Calculations

scholarly journals A Semi-Empirical Model for Predicting Frost Properties

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 412
Author(s):  
Shao-Ming Li ◽  
Kai-Shing Yang ◽  
Chi-Chuan Wang
Keyword(s):  
Thermal Conductivity ◽  
Linear Programming ◽  
Numerical Model ◽  
Empirical Model ◽  
Quantitative Method ◽  
Predictive Ability ◽  
Dimensionless Temperature ◽  
Crystal Shape ◽  
Proposed Model ◽  
Semi Empirical

In this study, a quantitative method for classifying the frost geometry is first proposed to substantiate a numerical model in predicting frost properties like density, thickness, and thermal conductivity. This method can recognize the crystal shape via linear programming of the existing map for frost morphology. By using this method, the frost conditions can be taken into account in a model to obtain the corresponding frost properties like thermal conductivity, frost thickness, and density for specific frost crystal. It is found that the developed model can predict the frost properties more accurately than the existing correlations. Specifically, the proposed model can identify the corresponding frost shape by a dimensionless temperature and the surface temperature. Moreover, by adopting the frost identification into the numerical model, the frost thickness can also be predicted satisfactorily. The proposed calculation method not only shows better predictive ability with thermal conductivities, but also gives good predictions for density and is especially accurate when the frost density is lower than 125 kg/m3. Yet, the predictive ability for frost density is improved by 24% when compared to the most accurate correlation available.

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