scholarly journals A Hybrid Method for Evaluating of Lightning Performance of Overhead Lines based on Monte Carlo Procedure

2016 ◽  
Vol 67 (4) ◽  
pp. 246-252
Author(s):  
Reza Shariatinasab ◽  
Pooya Tadayon ◽  
Akihiro Ametani
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Risk Analysis ◽  
Hybrid Method ◽  
Overhead Lines ◽  
Monte Carlo Procedure ◽  
Acceptable Accuracy ◽  
The Monte Carlo Method ◽  
Analytical Relations

Abstract This paper proposes a hybrid method for calculating lightning performance of overhead lines caused by direct strokes by combining Lattice diagram together with the Monte Carlo method. In order to go through this, firstly, the proper analytical relations for overvoltages calculation are established based on Lattice diagram. Then, the Monte Carlo procedure is applied to the obtained analytical relations. The aim of the presented method that will be called ‘ML method’ is simply estimation of the lightning performance of the overhead lines and performing the risk analysis of power apparatus with retaining the acceptable accuracy. To confirm the accuracy, the calculated results of the presented ML method are compared with those calculated by the EMTP/ATP simulation.

scholarly journals Monte Carlo Methods and the Koksma-Hlawka Inequality

Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 725
Author(s):  
Sergey Ermakov ◽  
Svetlana Leora
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Random Processes ◽  
Random Numbers ◽  
Average Order ◽  
New Approach ◽  
Average Value ◽  
Acceptable Accuracy ◽  
Cubature Formulas ◽  
The Monte Carlo Method

The solution of a wide class of applied problems can be represented as an integral over the trajectories of a random process. The process is usually modeled with the Monte Carlo method and the integral is estimated as the average value of a certain function on the trajectories of this process. Solving this problem with acceptable accuracy usually requires modeling a very large number of trajectories; therefore development of methods to improve the accuracy of such algorithms is extremely important. The paper discusses Monte Carlo method modifications that use some classical results of the theory of cubature formulas (quasi-random methods). A new approach to the derivation of the well known Koksma-Hlawka inequality is pointed out. It is shown that for high ( s > 5 ) dimensions of the integral, the asymptotic decrease of the error comparable to the asymptotic behavior of the Monte Carlo method, can be achieved only for a very large number of nodes N. It is shown that a special criterion can serve as a correct characteristic of the error decrease (average order of the error decrease). Using this criterion, it is possible to analyze the error for reasonable values of N and to compare various quasi-random sequences. Several numerical examples are given. Obtained results make it possible to formulate recommendations on the correct use of the quasi-random numbers when calculating integrals over the trajectories of random processes.

scholarly journals Risk management of a torrential flood construction project using the Monte Carlo simulation

2016 ◽  
pp. 29-44 ◽  
Author(s):  
Aleksandar Baumgertel ◽  
Nada Dragovic ◽  
Tijana Vulevic
Keyword(s):  
Monte Carlo Simulation ◽  
Risk Management ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Risk Analysis ◽  
Quantitative Methods ◽  
Flow Profile ◽  
Total Cost ◽  
The Monte Carlo Method ◽  
Relevant Variables

Projects for the regulation of torrent basins carry various unforeseen adverse effects that may result in breached deadlines, increased costs, a reduction of quality etc. The paper presents the basic characteristics and most frequent risks associated with erosion control. Furthermore, it provides an overview of risk management through its basic stages - starting from risk identification and risk analysis to risk responses, including the methods used for risk analysis. As a part of quantitative methods for risk analysis, the Monte Carlo method is presented as the one most frequently used in simulations. The Monte Carlo method is a stochastic simulation method consisting of the following stages: the identification of criterion and relevant variables, the allocation of probability for relevant variables, the determination of correlation coefficient among relevant variables, simulation execution and result analysis. This method was applied in the analysis of the total cost of the project for the basin regulation of the Dumaca River in order to determine the funding that would be used as a backup in case of unforeseen events with a negative impact. The project for the regulation of the Dumaca River includes basin regulation in the form of complex flow profile and the lining of zones where necessary in terms of stability. The total cost is presented as a sum of costs of all works (preliminary works, earthworks, masonry works, concrete works and finishing works). The Monte Carlo simulation for cost analysis is carried out using the Oracle Crystal Ball software with its basic steps described in the paper. A sum of funding needed as a financial backup in case of unforeseen events with negative effects is obtained as the simulated total cost of the project.

scholarly journals OPTIMIZATION AND ECONOMIC ANALYSIS OF MULTIPRODUCTS OBTAINED FROM WOOD OF EUCALYPTUS STANDS UNDER DIFFERENT PRODUCTIVE CAPACITY CLASSES AND ROTATION AGES

FLORESTA ◽  
2021 ◽  
Vol 51 (2) ◽  
pp. 293
Author(s):  
Laíssa De Araújo Viana ◽  
Renato Vinícius Oliveira Castro ◽  
Álvaro Nogueira de Souza ◽  
Carlos Pedro Boechat Soares ◽  
Maísa Santos Joaquim ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Risk Analysis ◽  
Net Present Value ◽  
Eucalyptus Grandis ◽  
Economic Viability ◽  
Productive Capacity ◽  
Individual Tree ◽  
The Monte Carlo Method ◽  
Rotation Age

The present study aimed to analyze the yield and economic viability of the destination, for lumber and energy, of the wood from non-thinned stands of the hybrid Eucalyptus urophylla x Eucalyptus grandis under different productive capacity class and whose production was projected by individual tree growth model to different ages. The simulation of the growth of individual trees was performed by applying the height and diameter growth, and mortality sub-models for three productive capacity classes: high, medium and low. The Kozak model was adjusted to study the stem taper and, in addition, used to optimize patterns for sawing logs and to produce lumber. The economic viability of the projects was evaluated by Net Present Value, Equivalent Periodic Benefit and risk analysis using the Monte Carlo method. It was observed that in areas with less productive capacity the volume of wood destined for energy was greater than 80% and, in areas with greater productive capacity the volume of lumber was greater than 26%. Economic indicators showed that the lumber production was viable at any of the studied rotation age. The risk analysis using the Monte Carlo method did not indicate the possibility of the project being unfeasible under the conditions analyzed. The quantity of different types of products obtained and the wood yield depends on the productive capacity class and age of the stand. The destination of the wood for multiproducts is the most viable option, regardless of the productive capacity class.

UGR CALCULATION BASED ON THE LUMINANCE SPATIAL-ANGULAR DISTRIBUTION

2020 ◽  
Vol 2020 (4) ◽  
pp. 25-32
Author(s):  
Viktor Zheltov ◽  
Viktor Chembaev
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Method ◽  
Visual Task ◽  
New Method ◽  
Lighting System ◽  
Preliminary Assessment ◽  
System A ◽  
The Monte Carlo Method

The article has considered the calculation of the unified glare rating (UGR) based on the luminance spatial-angular distribution (LSAD). The method of local estimations of the Monte Carlo method is proposed as a method for modeling LSAD. On the basis of LSAD, it becomes possible to evaluate the quality of lighting by many criteria, including the generally accepted UGR. UGR allows preliminary assessment of the level of comfort for performing a visual task in a lighting system. A new method of "pixel-by-pixel" calculation of UGR based on LSAD is proposed.

PSHA software review based on the Monte Carlo method

2020 ◽  
pp. 14-24
Author(s):  
V.A. Mironov ◽  
S.A. Peretokin ◽  
K.V. Simonov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Seismic Hazard ◽  
Hazard Analysis ◽  
Software Review ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Test Calculation ◽  
Seismic Surveys ◽  
The Monte Carlo Method

The article is a continuation of the software research to perform probabilistic seismic hazard analysis (PSHA) as one of the main stages in engineering seismic surveys. The article provides an overview of modern software for PSHA based on the Monte Carlo method, describes in detail the work of foreign programs OpenQuake Engine and EqHaz. A test calculation of seismic hazard was carried out to compare the functionality of domestic and foreign software.

Application of the Monte Carlo Method for the Prediction of Behavior of Peptides

2019 ◽  
Vol 20 (12) ◽  
pp. 1151-1157 ◽  
Author(s):  
Alla P. Toropova ◽  
Andrey A. Toropov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Natural Sciences ◽  
Monte Carlo Technique ◽  
Quantitative Structure ◽  
Structure Property ◽  
The Monte Carlo Method ◽  
Modern Natural

Prediction of physicochemical and biochemical behavior of peptides is an important and attractive task of the modern natural sciences, since these substances have a key role in life processes. The Monte Carlo technique is a possible way to solve the above task. The Monte Carlo method is a tool with different applications relative to the study of peptides: (i) analysis of the 3D configurations (conformers); (ii) establishment of quantitative structure – property / activity relationships (QSPRs/QSARs); and (iii) development of databases on the biopolymers. Current ideas related to application of the Monte Carlo technique for studying peptides and biopolymers have been discussed in this review.

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