scholarly journals Application of Monte Carlo Method for Evaluation of Uncertainties of ITS-90 by Standard Platinum Resistance Thermometer

2017 ◽  
Vol 17 (3) ◽  
pp. 108-116 ◽  
Author(s):  
Rudolf Palenčár ◽  
Peter Sopkuliak ◽  
Jakub Palenčár ◽  
Stanislav Ďuriš ◽  
Emil Suroviak ◽  
...  

AbstractEvaluation of uncertainties of the temperature measurement by standard platinum resistance thermometer calibrated at the defining fixed points according to ITS-90 is a problem that can be solved in different ways. The paper presents a procedure based on the propagation of distributions using the Monte Carlo method. The procedure employs generation of pseudo-random numbers for the input variables of resistances at the defining fixed points, supposing the multivariate Gaussian distribution for input quantities. This allows taking into account the correlations among resistances at the defining fixed points. Assumption of Gaussian probability density function is acceptable, with respect to the several sources of uncertainties of resistances. In the case of uncorrelated resistances at the defining fixed points, the method is applicable to any probability density function. Validation of the law of propagation of uncertainty using the Monte Carlo method is presented on the example of specific data for 25 Ω standard platinum resistance thermometer in the temperature range from 0 to 660 °C. Using this example, we demonstrate suitability of the method by validation of its results.

2013 ◽  
Vol 28 (2) ◽  
pp. 182-190 ◽  
Author(s):  
Aleksandar Kovacevic ◽  
Dejan Despotovic ◽  
Zoran Rajovic ◽  
Koviljka Stankovic ◽  
Ana Kovacevic ◽  
...  

For the evaluation of measurement uncertainty in measuring the conduction emission, in this paper we propose a new model which uses mixed distribution. Evaluation of probability density function for the measurand has been done using Monte Carlo method and a modified least-squares method (combined method). In addition, the number of data n and the number of classes of histogram k which were used for simulation, were varied.


Author(s):  
Hocine Chebi

This work presents a new approach based on the use of stable dynamic models for dynamic data mining. Data mining is an essential technique in the process of extracting knowledge from data. This allows us to model the extracted knowledge using a formalism or a modeling technique. However, the data needed for knowledge extraction is collected in advance, and it can take a long time to collect. The objective is therefore to move towards a solution based on the modeling of systems using dynamic models and to study their stability. Stable dynamic models provide us with a basis for dynamic data mining. In order to achieve this objective, the authors propose an approach based on agent-based models, the concept of fixed points, and the Monte-Carlo method. Agent-based models can represent dynamic models that mirror or simulate a dynamic system, where such a model can be viewed as a source of data (data generators). In this work, the concept of fixed points was used in order to represent the stable states of the agent-based model. Finally, the Monte-Carlo method, which is a probabilistic method, was used to estimate certain values, using a very large number of experiments or runs. As a case study, the authors chose the evacuation system of a supermarket (or building) in case of danger, such as a fire. This complex system mainly comprises the various constituent elements of the building, such as rows of shelves, entry and exit doors, fire extinguishers, etc. In addition, these buildings are often filled with people of different categories (age, health, etc.). The use of the Monte-Carlo method allowed the authors to experiment with several scenarios, which allowed them to have more data to study this system and extract some knowledge. This knowledge allows us to predict the future situation regarding the building's evacuation system and anticipate improvements to its structure in order to make these buildings safer and prevent the greatest number of victims.


2005 ◽  
Vol 30 (1) ◽  
pp. 11 ◽  
Author(s):  
Ioannis Neokosmidis ◽  
Thomas Kamalakis ◽  
Aristides Chipouras ◽  
Thomas Sphicopoulos

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