Monte Carlo, optimization, simulation and sensitivity of queuing networks

1987 ◽  
Vol 29 (2) ◽  
pp. 148
Keyword(s):  
Monte Carlo ◽  
Queuing Networks ◽  
Monte Carlo Optimization ◽  
Optimization Simulation

scholarly journals Monte Carlo optimization simulation of neutron shielding performance of iron/polyethylene combined structure

2018 ◽  
Vol 189 ◽  
pp. 02001
Author(s):  
Yinghong Zuo ◽  
Jinhui Zhu ◽  
Shengli Niu ◽  
Honggang Xie ◽  
Peng Shang
Keyword(s):  
Monte Carlo ◽  
Neutron Source ◽  
Thickness Ratio ◽  
Optimal Thickness ◽  
Neutron Shielding ◽  
Monte Carlo Optimization ◽  
Optimization Simulation ◽  
Combined Structure ◽  
Shielding Design ◽  
Different Thickness

This study aims to get the optimization neutron shielding design of iron/polyethylene combined shield structure. The neutron transmission coefficient with various energies for different thickness of iron and polyethylene combined shield structure were calculated by using Monte Carlo method. The simulation results show that the optimization effect of iron/polyethylene combined shield is not obvious when the neutron energy is low or the shield is thin, there is an optimal thickness ratio of iron to polyethylene adopted to get the best neutron shielding performance when the energy of neutron source is above 2 MeV and the total thickness of combined shielding structure is more than 20 cm. The optimal thickness ratio of iron to polyethylene increases with the increasing energy of neutron source; with the increasing of neutron source energy ranging from 4 MeV to 14 MeV, the optimal thickness ratio of iron to polyethylene trends from 0.11 to nearly 1.6.

The Application of the Combination of Monte Carlo Optimization Method based QSAR Modeling and Molecular Docking in Drug Design and Development

2020 ◽  
Vol 20 (14) ◽  
pp. 1389-1402 ◽  
Author(s):  
Maja Zivkovic ◽  
Marko Zlatanovic ◽  
Nevena Zlatanovic ◽  
Mladjan Golubović ◽  
Aleksandar M. Veselinović
Keyword(s):  
Monte Carlo ◽  
Molecular Docking ◽  
Computer Calculation ◽  
Molecular Graph ◽  
Optimization Method ◽  
Docking Studies ◽  
Optimization Approach ◽  
Qsar Modeling ◽  
Monte Carlo Optimization ◽  
Molecular Docking Studies

In recent years, one of the promising approaches in the QSAR modeling Monte Carlo optimization approach as conformation independent method, has emerged. Monte Carlo optimization has proven to be a valuable tool in chemoinformatics, and this review presents its application in drug discovery and design. In this review, the basic principles and important features of these methods are discussed as well as the advantages of conformation independent optimal descriptors developed from the molecular graph and the Simplified Molecular Input Line Entry System (SMILES) notation compared to commonly used descriptors in QSAR modeling. This review presents the summary of obtained results from Monte Carlo optimization-based QSAR modeling with the further addition of molecular docking studies applied for various pharmacologically important endpoints. SMILES notation based optimal descriptors, defined as molecular fragments, identified as main contributors to the increase/ decrease of biological activity, which are used further to design compounds with targeted activity based on computer calculation, are presented. In this mini-review, research papers in which molecular docking was applied as an additional method to design molecules to validate their activity further, are summarized. These papers present a very good correlation among results obtained from Monte Carlo optimization modeling and molecular docking studies.

scholarly journals PO-0905 Validation of a 4D Monte Carlo optimization and planning feature for CyberKnife lung treatment

2019 ◽  
Vol 133 ◽  
pp. S480-S481
Author(s):  
S. Trivellato ◽  
E. Rondi ◽  
S. Vigorito ◽  
E. Miglietta ◽  
F. Castellini ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Optimization

Monte Carlo Optimization of Two-Stage Cascade R134A Refrigeration System With Flash Chamber

2008 ◽  
Author(s):  
Yousef M. Abdel-Rahim
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Pressure Ratio ◽  
Volume Ratio ◽  
Heat Rate ◽  
Cycle Performance ◽  
Specific Work ◽  
Refrigeration System ◽  
Two Stage ◽  
Monte Carlo Optimization

Present paper studies the optimal characteristics of the two-stage cascade R134A refrigeration system with flash and mixing chambers over its operating ranges of all cycle controlling parameters. The COP, total heat rate in Qin, total work rate in Win and second law efficiency ηII are used as cycle performance parameters. Compared to the practically-limited other rate-based optimization methods and to other experimentally-optimized specific cases of cycle parameters, the application of Monte Carlo method has proved to be very effective for optimizing the cycle performance in its global sense over all cycle controlling parameters. Correlations relating performance and cycle controlling parameters are presented and discussed. Study shows that COP of the cycle can reach a value of 8 at intermediate pressure P2 of about 200 kPa, and a maximum value of 9.92 at about 370 kPa and 720 kPa, beyond which COP goes as low as 4.2. P2 alone has no significant effect on Qin, Win and ηII unless values of other controlling parameters are specified. Values of Qin, Win and ηII can reach as high as 94 kW, 23 kW and 0.85 and as low as 6.8 kW, 1.1 kW and 0.57 respectively depending on other cycle parameters. Neither pressure ratio nor volume ratio of the HP compressor has any effect on Qin, Win or ηII. However, the ratio of inlet to exit temperatures of the condenser has the greatest effect on both ηII and the volumetric specific work of the HP compressor, which is about double the value of the volumetric specific work of the LP compressor. Study shows an almost linear relationship between the two mass flow rates in the upper and lower loops of the cycle, where its value in the lower LP loop is about 75% that in the upper HP loop. Findings of the present work as well as the elaborate application of Monte Carlo method to real cycles can greatly open the way for reducing the trade-off design methods currently used in developing such systems as well as direct the useful experimentations and assessment of such designed systems.

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