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2 Applied Computer Science

2 2023

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Impact of friction coefficient variation on temperature field in rotary friction welding of metals – FEM study

100%

Łukaszewicz A. , Józwik J. , Cybul K.

Applied Computer Science

2023

tom Vol. 19, no 3

17--27

A mathematical model is presented for investigating the temperature field caused by the rotary friction welding of dissimilar metals. For this purpose, an axisymmetric, nonlinear, boundary value problem of heat conduction is formulated with allowance for the frictional heating of two cylindrical specimens of finite length made of Al 6061 aluminium alloy and 304 stainless steel. The thermo-physical properties of materials change with increasing temperature. It was assumed that the coefficient of friction does not depend on the temperature. The mechanism of heat generation due to friction on the contact surface with the temperature field of samples is considered. The boundary problem of heat conduction was reduced to the set of nonlinear ordinary differential equations at time t relative to the values of temperature T at the finite elements nodes. The numerical solution of the problem was obtained with the inverse 2nd order differentiation method implemented in COMSOL FEM system (finite element method), with time step ∆t=0.1 (s). The influence of various values of friction coefficient is presented.

Predictive tools as part of decission aiding processes at the airport – the case of Facebook Prophet library

88%

Korga S. , Żyła K. , Józwik J. , Pytka J. , Cybul K.

Applied Computer Science

2023

tom Vol. 19, no 4

51--67

Prophet is a quite fresh and promising open-source library for machine learning, developed by Facebook, that gains some significant interest. It could be used for predicting time series taking into account holidays and seasonality effects. Its possible applications and deficit of scientific works concerning its usage within decision processes convinced the authors to state the research question, if the Prophet library could provide reliable prediction to support decision-making processes at the airport. The case of Radawiec airport (located near Lublin, Poland) was chosen. Official measurement data (from the last 4 years) published by the Polish Government Institute was used to train the neural network and predict daily averages of wind speed, temperature, pressure, relative humidity and rainfall totals during the day and night. It was revealed that most of the predicted data points were within the acceptance threshold, and computations were fast and highly automated. However, the authors believe that the Prophet library is not particularly useful for airport decision-making processes because the way it handles additional regressors and susceptibility to unexpected phenomena negatively affects the reliability of prediction results.