Spreading Characteristics of Molecularly Thin Lubricant on Surfaces With Groove-Shaped Textures: Effects of Molecular Weight and End-Group Functionality

2003 ◽  
Vol 125 (2) ◽  
pp. 350-357 ◽  
Author(s):  
Hedong Zhang ◽  
Yasunaga Mitsuya ◽  
Maiko Yamada
Keyword(s):  
Molecular Weight ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Ising Model ◽  
Monte Carlo Simulations ◽  
Simulation Method ◽  
Solid Surfaces ◽  
The Monte Carlo Method ◽  
End Groups ◽  
End Group

Effects of molecular weight and end-group functionality on spreading of molecularly thin perfluoropolyether (PFPE) film over solid surfaces with groove-shaped textures have been studied by experiments and Monte Carlo simulations. In the experiments, lubricant spreading on a surface with groove-shaped textures was measured by making use of the phenomenon in which diffracted light weakens in the lubricant-covered region. It is found that grooves serve to accelerate spreading and this effect increases for deeper grooves, and also the accelerating rate becomes larger for a lubricant having a larger molecular weight or functional end-groups. In the simulations, the Monte Carlo method based on the Ising model was extended to enable us to evaluate the effect of molecular weight on the spreading of non-functional lubricant inside a groove. The validity of the newly developed simulation method was well confirmed from the agreement between the simulation and experimental results.

scholarly journals Technical-Economic Analysis of Grapple Saw

2020 ◽  
Vol 41 (2) ◽  
pp. 219-229 ◽  
Author(s):  
Ricardo Hideaki Miyajima ◽  
Paulo Torres Fenner ◽  
Gislaine Cristina Batistela ◽  
Danilo Simões
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Probability Distributions ◽  
Simulation Method ◽  
Forest Harvesting ◽  
Production Costs ◽  
Wood Harvesting ◽  
Food And Agriculture ◽  
The Monte Carlo Method

The processing of Eucalyptus logs is a stage that follows the full tree system in mechanized forest harvesting, commonly performed by grapple saw. Therefore, this activity presents some associated uncertainties, especially regarding technical and silvicultural factors that can affect productivity and production costs. To get around this problem, Monte Carlo simulation can be applied, or rather a technique that allows to measure the probabilities of values from factors that are under conditions of uncertainties, to which probability distributions are attributed. The objective of this study was to apply the Monte Carlo method for determining the probabilistic technical-economical coefficients of log processing using two different grapple saw models. Field data were obtained from an area of forest planted with Eucalyptus, located in the State of São Paulo, Brazil. For the technical analysis, the time study protocol was applied by the method of continuous reading of the operational cycle elements, which resulted in production. As for the estimated cost of programmed hour, the applied methods were recommended by the Food and Agriculture Organization of the United Nations. The incorporation of the uncertainties was carried out by applying the Monte Carlo simulation method, by which 100,000 random values were generated. The results showed that the crane empty movement is the operational element that most impacts the total time for processing the logs; the variables that most influence the productivity are specific to each grapple saw model; the difference of USD 0.04 m3 in production costs was observed between processors with gripping area of 0.58 m2 and 0.85 m2. The Monte Carlo method proved to be an applicable tool for mechanized wood harvesting for presenting a range of probability of occurrences for the operational elements and for the production cost.

scholarly journals STUDY OF MOLECULAR CHARACTERISTICS OF THE PRODUCT OF ISOPRENE POLYMERIZATION ON A NEODYMIUM-CONTAINING CATALYTIC SYSTEM BASED ON MODELING BY THE MONTE-CARLO METHOD

2020 ◽  
pp. 138-148
Author(s):  
Светлана Анатольевна Мустафина ◽  
Татьяна Анатольевна Михайлова ◽  
Эльдар Наилевич Мифтахов ◽  
Владимир Анатольевич Михайлов
Keyword(s):  
Molecular Weight ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Catalytic System ◽  
Batch Process ◽  
Molecular Characteristics ◽  
The Monte Carlo Method ◽  
Molecular Weight Characteristics ◽  
Software Product ◽  
Formed Product

В статье предложен алгоритм моделирования периодического процесса полимеризации, основанный на методе Монте-Карло. Апробация алгоритма осуществляется на примере процесса растворной полимеризации изопрена в присутствии каталитической системы на основе хлорида неодима, лежащей в основе промышленного производства изопренового синтетического каучука. В основе алгоритма лежит имитация роста каждой макромолекулы формируемого полимера и ее отслеживание. Построенная модель позволяет исследовать молекулярно-массовые характеристики полимера в зависимости от конверсии мономеров, проводить расчет молекулярно-массового распределения получаемого продукта в любой момент времени ведения процесса. На основе предложенного алгоритма разработан программный продукт для прогнозирования изменения характеристик образующегося полимера в динамике. The article proposes an algorithm for modeling a batch process of polymerization based on the Monte Carlo method. The algorithm is tested on the process of solution polymerization of isoprene in the presence of a catalytic system based on neodymium chloride. This process underlies the industrial production of isoprene synthetic rubber. The algorithm is based on the imitation of the growth of each macromolecule of the formed polymer and tracking the processes occurring with it. The constructed model makes it possible to study the molecular weight characteristics of the polymer depending on the conversion of monomers, to calculate the molecular weight distribution of the formed product at any time during the process. Based on the proposed algorithm, a software product has been developed for predicting changes in the characteristics of the formed polymer in dynamics.

THE MONTE CARLO METHOD AS A RISK ASSESSMENT TOOL IN THE FORMATION OF A STOCK PORTFOLIO IN A CRISIS SITUATION

2020 ◽  
Author(s):  
Екатерина Андреевна Винниченко ◽  
Светлана Валентиновна Пупенцова
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Assessment Tool ◽  
Corporate Bonds ◽  
Simulation Method ◽  
Crisis Situation ◽  
The Monte Carlo Method ◽  
Financial Investments ◽  
Stock Portfolio

В работе разработан алгоритм применения метода имитационного моделирования при оценке эффективности финансовых инвестиций на примере оценки корпоративных облигаций в кризисной ситуации. Авторы рассчитали доходность к погашению корпоративных облигаций в период кризиса 2020 года и подготовили рекомендации по выбору наиболее привлекательных ценных бумаг для инвестора. In this paper, we have developed an algorithm for applying the simulation method to evaluate the effectiveness of financial investments on the example of evaluating corporate bonds in a crisis situation. The authors calculated the yield to maturity of corporate bonds during the crisis in 2020 and prepared recommendations for choosing the most attractive securities for investors.

Atomistic Simulation of SiC Growth at the SiC(0001)/Si1-XCx Interface by the Monte Carlo Method

2011 ◽  
Vol 679-680 ◽  
pp. 87-90
Author(s):  
Makoto Itoh ◽  
Tsuyoshi Uda ◽  
Jun Nara ◽  
Takahisa Ohno
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Atomistic Simulation ◽  
Lattice Spacing ◽  
Potential Surface ◽  
Exchange Process ◽  
Simulation Method ◽  
Local Minima ◽  
The Monte Carlo Method ◽  
Local Relaxation

We developed the computer simulation method to study growth of SiC at the SiC(0001)/Si1-xCx interface based on the Monte Carlo method. Energy is calculated by using the Tersoff potential and the lattice spacing is sub-divided to enable the structural relaxation in a dicrete manner. Before making an attempt for the atomic difusion via the species exchange process in the Metropolis alogrithm, local relaxation is carried out to locate atoms at the local minima of the potential surface. Then, parallel computation is carried out to thermally equilibrate a system.

MONTE CARLO SIMULATIONS FOR THE RISK MANAGEMENT OF ENVIRONMENTAL POLLUTION

2010 ◽  
Vol 12 (01) ◽  
pp. 87-101
Author(s):  
OSAMA A. B. HASSAN
Keyword(s):  
Risk Management ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Monte Carlo Simulations ◽  
Environmental Pollution ◽  
Human Health ◽  
Stochastic Models ◽  
Chemical Pollution ◽  
The Monte Carlo Method

This article attempts to adapt the Monte Carlo method to the quantitative risk management of environmental pollution. In this context, the feasibility of stochastic models to quantitatively evaluate the risk of chemical pollution is first discussed and then linked to a case study in which Monte Carlo simulations are applied. The objective of the case study is to develop a Monte Carlo scheme for evaluating the pollution in a lake environment. It is shown that the results can be of interest as they define the risk margins that are important to the sustainability of the ecosystem in general, and human health in particular. Moreover, assessing the environmental pollution with the help of the Monte Carlo method can be feasible and serve the purpose of investigating and controlling the environmental pollution, in the long and short terms.

scholarly journals Improving the assessment of the environmental and economic efficiency of measures

2021 ◽  
Vol 112 ◽  
pp. 00002
Author(s):  
Inna P. Bandurinа ◽  
Mikhail A. Bandurin ◽  
Alexander P. Bandurin
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Economic Efficiency ◽  
Land Reclamation ◽  
Simulation Method ◽  
International Standards ◽  
Future Research ◽  
Investment Projects ◽  
The Monte Carlo Method

The purpose of the study is to improve methods for improving the regulatory and methodological framework for assessing the environmental and economic effectiveness of land reclamation investment projects. The research methodology is based on the Monte Carlo method, which corresponds to international standards, the theory and algorithms of innovative methods for determining risks, as well as the ability to provide the user with information about the content of risk assessment operations and ensure that their preferences are taken into account in the calculation process. Currently, many tools have been developed for automating risk analysis procedures, including those performed by the Monte Carlo method, which are described in various studies with varying degrees of completeness. The analysis of priority methods of assessing the risks of achieving the projected economic indicators of project solutions is performed and the prospects of the simulation method for practical use in the field of land reclamation are shown. The results of the risk assessment of environmental and economic efficiency of anti-filtration coatings of hydraulic structures of irrigation systems performed by the Monte Carlo method in the environment of the Crystal Ball software product are presented, and the need to improve the reliability of the predicted results of the effectiveness of the designed measures is established. Future research is risk assessment of profitability of the designed activities promote the development of existing and formation of new theories to justify the feasibility of implementation of reclamation investment projects.

scholarly journals Simulasi Monte Carlo dalam Memprediksi Tingkat Lonjakan Penumpang (Studi Kasus di PT. Tri Arga Travel)

2020 ◽  
pp. 92-97
Author(s):  
Dina Mardiati ◽  
Sarjon Defit ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Simulation Method ◽  
Transportation Services ◽  
The Monte Carlo Method ◽  
Linear Congruential Generator ◽  
High Level ◽  
Linear Congruential ◽  
A Company

Tri Arga Travel is a company engaged in transportation services. The company really prioritizes the quality of service to consumers. So that on holidays there is usually a surge in passengers that cannot be predicted by the company. This greatly affects service to passengers. The purpose of this research is to predict the surge rate of PT. Tri Arga Travel, making it easier for the leadership of PT. Tri Arga Travel to take a policy when there is a surge in passengers in the future. The data used in this study is data on the number of passengers in 2017, 2018, and 2019 with the aim of padang-perawang. Then, the data is processed using the Monte Carlo method. The Monte Carlo method is a simulation method that uses random numbers obtained from the Linear Congruential Generator (LCG) to predict the rate of passenger spike in the following year by utilizing the previous year's passenger data. The results obtained from testing the Monte Carlo simulation can be seen that in July it is predicted that there will be a surge in passengers with an average level of accuracy of 86.74%. With a fairly high level of accuracy, the application of the Monte Carlo method can be used as a recommendation to predict the level of passenger spikes and also help in improving services to prospective passengers of PT. Tri Arga Travel.

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