Wyniki wyszukiwania - BazTech

1

Multiparameter approximation model of temperature conditions of marine diiesel generator sets, based on Markov chain Monte Carlo

Myrhorod V., Hvozdeva I., Budashko V.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

|

2022

|

Vol. 16 No. 4

779--784

EN

In the article we propose a multi-parameter approximation model, based on Markov chain Monte Carlo, which describes the relationship between the temperature regime, operating conditions and electromechanical parameters of marine diesel generator sets. The approximation model is constructed on the basis of the analysis of experimental data of the exhaust gases temperature of marine diesel generator sets in their long-term operation. As a statistical model of random processes of temperature deviations from the approximation model, a Markov process model is proposed that takes into account the possible correlation of the initial data. Since the measuring channels of modern diagnostic systems are digital, due to discretization in time and level, the studied processes form a Markov chain, which makes it possible to establish the important features of such processes. The use of approximation models ensures the stationarity conditions and the correctness of the proposed Markov model in the conditions of multi-mode operation of marine diesel generator sets. The proposed multi-parameter approximation model, based on Markov chain Monte Carlo, allows you to take into account random perturbations that lead to a random change in the output coordinates of the diagnostic object. The proposed improvement of the model makes it possible to ensure its adequacy to real processes of changing the parameters of the temperature regimes of marine diesel generator sets. The proposed multi-parameter approximation model, based on Markov chain Monte Carlo, can be used in the systems of technical diagnostics of marine diesel generator sets in order to increase the reliability of diagnostic conclusions.

2

Computation of the ground state energy of the Schrödinger equation by a Monte Carlo method

Puchalski Adam

Mathematica Applicanda

|

2021

|

Vol. 49, no. 1

55--64

EN

The paper presents a new method of computing the ground state energy of the time-independent Schrödinger equation. The method is based on a local separation of variables: the Schrödinger equation is transformed to an equivalent system of local one-electron auxiliary equations which is used to derive an expression for the energy integral. The latter allows to calculate the ground-state energy of many-electron systems with the full inclusion of electron correlations. The multidimensional energy integrals are calculated using the Markov Chain Monte Carlo method. We provide benchmark results for two-electron systems which are in agreement with the accurate computations by the configuration interaction (CI) method.

PL

W pracy przedstawiono nową, niestandardową metodę obliczania energii stanu podstawowego w stacjonarnym równaniu Schrödingera. Metoda korzysta z lokalnego rozdzielenia zmiennych, które pozwala sprowadzić równanie Schrödingera dla układu wieloelektronowego do układu równań jedno-elektronowych i wyliczyć z nich całkę energii. Tak wyprowadzona całka energii pozwala obliczyć energię stanu podstawowego dla układów wielo-elektronowych z pełnym uwzględnieniem korelacji elektronów. Do obliczania wielo-wymiarowej całki energii wykorzystuje się algorytm Monte Carlo wykorzystujący łańcuchy Markowa. W pracy przedstawiono wyniki obliczeń dla układów dwu-elektronowych. Otrzymane wyniki porównano z obliczeniami uzyskanymi standardowo w obliczeniach kwantowych metodą oddziaływania konfiguracji (CI) uzyskując bardzo dobrą zgodność wyników przy znacznie mniejszej złożoności obliczeniowej.

3

A Bayesian virtual metrology for quality inspection of mobile repeater systems

Kim S. D., Kim J. S., Mun B. M., Bae S. J.

Management and Production Engineering Review

|

2016

|

Vol. 7, No. 4

48--53

EN

The technology of wideband code division multiple access (WCDMA) has been applied to band selective interference cancellation system (ICS) repeaters. To inspect the telecommunication quality of the systems, quality engineers must check the shape of the signals at the corresponding frequency band of the repeaters. However, measuring the signal quality is a repetitive manual task which requires much inspection time and high costs. In the case of small-sized samples, such as the example of an ICS repeater system, Bayesian approaches have been employed to improve the estimation accuracy by incorporating prior information on the parameters of the model in consideration. This research proposes a virtual method of quality inspection for products using a correlation structure of measurement data, mainly in a Bayesian regression framework. The Bayesian regression model derives prior information from historical measurement data to predict measurements of other frequency bandwidths by exploiting the correlation structure of each measurement data. Empirical results show the potential for reducing inspection costs and time by predicting the values of adjoining frequency bandwidths through measured data of a frequency bandwidth in the course of quality inspections of ICS repeater systems.