Monte Carlo Simulation for the Angle-Dependent Light Transmittance of Thermotropic Material

2010 ◽  
Vol 29-32 ◽  
pp. 2781-2784
Author(s):  
Jian Yao ◽  
Jin Xu
Keyword(s):  
Energy Efficiency ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Building Energy ◽  
Light Transmittance ◽  
Integrating Sphere ◽  
Building Energy Efficiency ◽  
Scattering Light

In this paper we propose a Monte-Carlo method for the simulation of the angle-dependent light transmittance of thermotropic material. The results show that the scattering light increased as temperature rose, and most of light transmitted went through the sample of thermotropic material at the angles between 10~40 deg. The results also indicate that the light transmittance measurement of thermotropic material by spectrophotometer without an integrating sphere is not accurate. As a conclusion, Monte Carlo simulation is an effective method for the determination of angle-dependent light transmittance of thermotropic material, and results of these simulations can be used to calculate the shading coefficient of window for building energy efficiency.

scholarly journals Application of Monte Carlo Methods to Consider Probabilistic Effects in a Race Simulation for Circuit Motorsport

2020 ◽  
Vol 10 (12) ◽  
pp. 4229 ◽  
Author(s):  
Alexander Heilmeier ◽  
Michael Graf ◽  
Johannes Betz ◽  
Markus Lienkamp
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
State Of The Art ◽  
Probability Distributions ◽  
Strategic Decisions ◽  
The Monte Carlo Method ◽  
Random Events ◽  
Example Variability

Applying an optimal race strategy is a decisive factor in achieving the best possible result in a motorsport race. This mainly implies timing the pit stops perfectly and choosing the optimal tire compounds. Strategy engineers use race simulations to assess the effects of different strategic decisions (e.g., early vs. late pit stop) on the race result before and during a race. However, in reality, races rarely run as planned and are often decided by random events, for example, accidents that cause safety car phases. Besides, the course of a race is affected by many smaller probabilistic influences, for example, variability in the lap times. Consequently, these events and influences should be modeled within the race simulation if real races are to be simulated, and a robust race strategy is to be determined. Therefore, this paper presents how state of the art and new approaches can be combined to modeling the most important probabilistic influences on motorsport races—accidents and failures, full course yellow and safety car phases, the drivers’ starting performance, and variability in lap times and pit stop durations. The modeling is done using customized probability distributions as well as a novel “ghost” car approach, which allows the realistic consideration of the effect of safety cars within the race simulation. The interaction of all influences is evaluated based on the Monte Carlo method. The results demonstrate the validity of the models and show how Monte Carlo simulation enables assessing the robustness of race strategies. Knowing the robustness improves the basis for a reasonable determination of race strategies by strategy engineers.

scholarly journals SOLVATION STRUCTURE DETERMINATION OF Ni2+ ION IN WATER BY MEANS OF MONTE CARLO METHOD

2010 ◽  
Vol 2 (3) ◽  
pp. 186-184
Author(s):  
Tutik Arindah ◽  
Bambang Setiaji ◽  
Harno Dwi Pranowo
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Interaction Energy ◽  
Structure Determination ◽  
Solvation Structure ◽  
Simulation Monte Carlo ◽  
Water Simulation

Determination of solvation structure of Ni2+ ion in water has been achieved using Monte Carlo method using canonic assemble (NVT constant). Simulation of a Ni2+ ion in 215 H2O molecules has been done under NVT condition (298.15 K). The results showed that number of H2O molecules surround Ni2+ ion were 8 molecules in first shell and 17 molecules in second shell, interaction energy of Ni2+-H2O in first shell was -68.7 kcal/mol and in second shell was -9.8 kcal/mol, and there were two angles of O-Ni2+-O, i.e. 74o and 142o. According to those results, the solvation structure of Ni2+ ion in water was cubic antisymetric.   Keywords: Water simulation, Monte Carlo simulation

To Improve Accuracy of Radionuclide Therapy Dosimetry Planning Using Monte Carlo Method

2017 ◽  
Vol 62 (1) ◽  
pp. 49-55
Author(s):  
Наркевич ◽  
B. Narkevich ◽  
Гончаров ◽  
M. Goncharov ◽  
Лысак ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Count Rate ◽  
Radionuclide Therapy ◽  
Analytical Formula ◽  
Region Of Interest ◽  
The Monte Carlo Method ◽  
Improve Accuracy

Purpose: Development and clinical testing of methodology dosimetry planning of radionuclide therapy based on Monte Carlo simulation of radiation transfer process. Material and methods: The method of determination in absolute units of radiopharmaceutical (RP) activity accumulated in tumor lesions. The technique is based on scintigraphy syringe containing diagnostic RP activity, biplane patient scintigraphy after injection of the RP and determination of the RP accumulation when administered calculated using the Monte Carlo method for the absorption and scattering of radiation in the patient’s body and in the collimator of the gamma camera. Code MCNP Monte Carlo simulation was used. The layout of determination of the value of accumulated RP activity in the patient’s tumor site implies successive implementation of the following three steps. 1. Scintigraphic images are obtained of the vial containing already known activity of the RP placed at the fixed source-to-collimator distance, following which estimation of the detector count rate within the specified region of interest of the vial image is undertaken. 2. Therapeutic activity A0 is introduced in the patient’s body, scintigraphic examination of the patient is performed. Estimation of the detector count rate in the region where the tumor is located and the value of tissue background in the close enough vicinity to the tumor is performed using the tools for contouring the region of interest on the obtained planar image provided using the software imbedded in the scintigraphic equipment. 3. Value of accumulated activity RP in the affected tumor is determined according to the correction factor which is calculated using Monte-Carlo method for specific clinical case for the geometry used in obtaining scintigraphic images which is identical to the conditions of measurement of activity in the vial and in the patient’s body. The technique has been tested in the study, with an injection of 30 MBq of 123I-MIBG child with neuroblastoma. Results: The level of accumulation of radiopharmaceutical in the tumor of the adrenal gland was 0.78 MBq, i.e. 2.6 % of the administered activity. This corresponds to literature data (average about 2.4 %) for scintigraphic studies of children with neuroblastomas. When using the known calculation method for analytical formula without the introduction of corrections for the absorption and scattering of radiation was obtained a result of 1.02 MBq, i.e. overestimation was 31 %. Conclusions: Introduction calculated by the Monte Carlo method for the absorption and scattering of radiation during scintigraphy patient can improve the accuracy of dosimetry planning of radionuclide therapy.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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