scholarly journals Providing the environmental safety by increasing the efficiency of firefighting in unsheltered timber warehouses

2021 ◽  
pp. 123-129
Author(s):  
E. M. Hulida ◽  
I. V. Pasnak ◽  
O. E. Vasylieva ◽  
I. O. Movchan
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Mathematical Models ◽  
Combustion Products ◽  
Environmental Safety ◽  
Theoretical Research ◽  
The Monte Carlo Method ◽  
Fire Front ◽  
Free Development ◽  
The Impact

Purpose. To develop a method for reducing the impact of fires in unsheltered timber warehouses on the environmental safety by reducing the duration of free burning of timber, the speed of fire front spread, emissions of combustion products and the duration of the firefighting. Methodology. During the experimental research, the method of fractional factor experiment was used. Theoretical research was performed using optimization mathematical models. The Monte Carlo method is used to solve optimization problems. To implement this method, block diagrams of algorithms was developed, based on written corresponded computer programs. Findings. The method was developed for reducing the impact of fires in unsheltered timber warehouses on the environmental safety by reducing the duration of free development of the fire, the speed of fire front spread, the concentration of combustion products and the duration of the fire. Fire prevention measures to reduce the duration of fire and to reduce emissions of combustion products due to fires in unsheltered timber warehouses was implemented by using an automated system to determine the fire extinguishing means and forces by setting an optimization problem, applying the Monte Carlo method and developing software to solve it. Originality. The scientific novelty is the justification of ways to reduce the duration of the free development of fire and to reduce the amount of toxic emissions using optimization mathematical models. Practical value. It is possible to use the obtained results in the practical activities of fire and rescue units of the SES of Ukraine and provide environmental safety in case of fire in unsheltered timber warehouse due to the practical implementation of administrative, legal and economic methods.

scholarly journals Simulation Modeling in Assessing the Effectiveness and Risk of Investment Projects

2020 ◽  
Vol 22 (1) ◽  
pp. 119-124
Author(s):  
Volodymyr Kharchenko ◽  
◽  
Hanna Kharchenko ◽  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Agricultural Production ◽  
Random Number ◽  
Investment Project ◽  
Average Risk ◽  
Universal Method ◽  
Investment Projects ◽  
The Monte Carlo Method ◽  
The Impact

Introduction. The article deals with the modeling features in the implementation of investment projects using the Monte Carlo method. The purpose of the article is to substantiate the feasibility of using economic and mathematical models to identify the risks of investment projects in agricultural production, taking into account the randomness of factors. Results. The expediency of using this method during the analysis of projects in agriculture is determined. This type of modeling is a universal method of research and evaluation of the effectiveness of open systems, the behavior of which depends on the influence of random factors. Particular attention is paid in such cases to decisions on the implementation of investment projects. The expediency of using this method in the analysis of projects in agriculture is determined. The main characteristics of the investment project are considered: investments involve significant financial costs; investment return can be obtained in a few years; there are elements of risk and uncertainty in forecasting the results of the investment project. The algorithm of the analysis of investment projects consisting of various stages is offered. The importance of investigating the risks of investment projects in agricultural production is substantiated. It is investigated that the basis of the Monte Carlo method is a random number generator, which consists of two stages: generation of a normalized random number (uniformly distributed from 0 to 1) and conversion of a random number into an arbitrary distribution law. The task of choosing an investment project for a pig farm is proposed. The calculations revealed that the amount of the expected NPV is UAH 63,158.80 with a standard deviation of UAH 43,777.90. The coefficient of variation was 0.69, so the risk of this project is generally lower than the average risk of the investment portfolio of the farm. Conclusions. The results of the analysis obtained using the method of Monte Carlo simulation are quite simple to interpret and reflect the change of factors over a significant interval, taking into account the probabilistic nature of economic factors. Thus, this method allows the implementation of the investment project to assess the impact of uncertainty on the final result of the project.

scholarly journals Risk Assessment Models to Improve Environmental Safety in the Field of the Economy and Organization of Construction: A Case Study of Russia

2021 ◽  
Vol 13 (24) ◽  
pp. 13539
Author(s):  
Arkadiy Larionov ◽  
Ekaterina Nezhnikova ◽  
Elena Smirnova
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Rapid Development ◽  
Environmental Safety ◽  
Quantitative Risk Assessment ◽  
Optimal Decision ◽  
Environmental Damage ◽  
The Monte Carlo Method ◽  
The Future

This article assesses risks in order to substantiate the economic and organizational efficiency of housing and industrial construction. This topic is relevant because it is necessary for sustainable development. In Russia, environmental safety in construction and housing, as well as communal services, is poorly developed and not regulated by the legal system. As building construction, housing, and communal services should be based on environmental safety, this topic requires rapid development. Methods related to quantifying environmental risk and making decisions under conditions of uncertainty were studied. A quantitative risk assessment was performed using the Monte Carlo method for pessimistic and optimistic options to prevent environmental damage. The model reproduced the distribution derived from the evidence-based fit. The results of sensitivity analysis are also presented to prove the hypothesis. The selection of the most appropriate probability density functions for each of the input quantities was implemented through settings in a computer program. The simulation modeling results clearly illustrate the choice of the general principle of assessment and the adoption of the optimal decision. In conditions of uncertainty, the decision to choose the optimistic options with high cost (to maintain the reliability of the technical system) but less risk plays a decisive role in the future environmental safety strategies of construction projects. The Monte Carlo method is preferable for environmental impact assessments. In the future, the amended methodology can be applied to raise environmental safety in the field of construction.

Combined Cycle Performance Test Uncertainty Validation by Comparing Monte Carlo Analysis With Monovariate Perturbation Results

2006 ◽  
Author(s):  
Kerri L. Spencer ◽  
Jeffrey R. Friedman ◽  
Terry B. Sullivan
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Performance Test ◽  
Performance Testing ◽  
Monte Carlo Analysis ◽  
Combined Cycle ◽  
Plant Performance ◽  
The Monte Carlo Method ◽  
The Impact ◽  
Test Uncertainty

This paper focuses on the calculation of the test uncertainty of an ASME PTC 46 [1], overall plant performance test of a combined cycle by two separate methods. It compares the combined cycle corrected plant output and heat rate systematic uncertainty results that are generated using monovariate perturbation analysis with the Monte Carlo method. The Monte Carlo method has not been used widely in power plant performance testing applications. It offers insights into the results of the Monte Carlo analysis method, which is less intuitive than the conventional method. This study shows that utilizing two distinctly different methods of calculation of test uncertainty serves to corroborate assumptions, or to isolate flaws in one or both methods. In developing the method for calculation of test uncertainty, the authors conclude that it is prudent to validate the calculation method of choice of test uncertainty, and to consider the correlations in measurement uncertainties. Also discussed in detail are the impact of correlated uncertainty assumptions, and recommendations on their application. Correlated uncertainty has not been extensively discussed in the literature concerning specific applications in performance testing, although it should be a critical consideration in any uncertainty analysis. Details of determination of instrumentation uncertainty, measurement uncertainty of a parameter, and calculation of sensitivity factors are included in this paper.

scholarly journals Enterprise content management in the cloud

2013 ◽  
Vol 61 (7) ◽  
pp. 2295-2301 ◽  
Author(s):  
Jaroslava Klegová ◽  
Ivana Rábová
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Management System ◽  
Maximum Level ◽  
Content Management ◽  
Content Management System ◽  
The Monte Carlo Method ◽  
Enterprise Content Management ◽  
It Department ◽  
The Impact

At present the attention of many organizations concentrates to the Enterprise Content Management system (ECM). Unstructured content grows exponentially, and Enterprise Content Management system helps to capture, store, manage, integrate and deliver all forms of content across the company. Today, decision makers have possibility to move ECM systems to the cloud and take advantages of cloud computing. Cloud solution can provide a crucial competitive advantage. For example, it can reduce fixed IT department cost and ensure faster ECM implementation.To achieve the maximum level of benefits from implementation of ECM in the cloud it is important to understand all possibilities and actions during the implementation. In this paper, the general model of the ECM implementation in the cloud is proposed and described. The risk may relate to all aspects of the implementation, such as cost, schedule or quality. This is the reason why the introduced model places emphasize on risk. The aim of the article is to identify risks of the ECM implementation in the cloud and quantify the impact of risk. The article is focused on the Monte Carlo method. Monte Carlo method is a technique that uses random numbers and probability to solve problems. Based on interviews with an IT managers there is created an example of possible scenarios and the risk is evaluated using the Monte Carlo method.

Optical Communication on Scattered or Reflected Laser Radiation

2019 ◽  
pp. 15-24
Author(s):  
Vladimir Belov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Communication Systems ◽  
Radiation Transfer ◽  
Communication Channels ◽  
Theoretical Research ◽  
Visible Range ◽  
Open Communication ◽  
The Monte Carlo Method ◽  
Communication Errors

Results of theoretical and experimental research of NLOS (NonLine of Sight) communication systems in the atmosphere, under water, and in mixed media based on publications of authors from China, Canada, Greece, the USA, Great Britain, Russia, and other countries are discussed in the present work. The theory of radiation transfer and the linear systems theory provide the basis for theoretical research. The radiation transfer equation is solved by the Monte–Carlo method in the singlescattering approximation. It is demonstrated that approximate methods are applicable when the average scattering multiplicity in open communication channels does not exceed 1. The Monte Carlo method is used to study the influence of opticalgeometric parameters of schemes of communication channels on the probabilities of communication errors, signal/noise ratios, limiting base lengths, attenuation of informationcarrying signals, and their superposition leading to communication errors. Examples of communications in the atmosphere in the UV range at distances up to 1300 m, in the visible range up to70 km, and under water up to 20 m are given. Search for optimal methods of signal modulation, development of software and hardware complexes for numerical simulation of the transfer properties of communication channels, refinement of analytical models of impulse transfer characteristics of noncoplanar schemes of bistatic optoelectronic communication systems (OECS), and research of the effect of winddriven sea waves and processes of radiation scattering in water are planned to study the efficiency of operation of the communication systems and to expand ranges of variations of the input NLOS and OECS parameters in the experiments carried out in natural water reservoirs.

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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