VGTU Journals (Vilnius Gediminas Technical University - Vilnius Tech)
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Spectral method for one dimensional Benjamin-Bona-Mahony-Burgers equation using the transformed generalized Jacobi polynomial
No full textThe Benjamin-Bona-Mahony-Burgers equation (BBMBE) plays a fundemental role in many application scenarios. In this paper, we study a spectral method for the BBMBE with homogeneous boundary conditions. We propose a spectral scheme using the transformed generalized Jacobi polynomial in combination of the explicit fourth-order Runge-Kutta method in time. The boundedness, the generalized stability and the convergence of the proposed scheme are proved. The extensive numerical examples show the efficiency of the new proposed scheme and coincide well with the theoretical analysis. The advantages of our new approach are as follows: (i) the use of the transformed generalized Jacobi polynomial simplifies the theoretical analysis and brings a sparse discrete system; (ii) the numerical solution is spectral accuracy in space
The BKM criterion to the 3D double-diffusive magneto convection systems involving planar components
No full textIn this paper, we investigate the BKM type blowup criterion applied to 3D double-diffusive magneto convection systems. Specifically, we demonstrate that a unique local strong solution does not experience blow-up at time T, given that ). To prove this, we employ the logarithmic Sobolev inequality in the Besov spaces with negative indices and a well-known commutator estimate established by Kato and Ponce. This result is the further improvement and extension of the previous works by O (2021) and Wu (2023)
Solving a spectral problem for large-area photonic crystal surface-emitting lasers
No full textWe present algorithms for constructing and resolving spectral problems for novel photonic crystal surface-emitting lasers with large emission areas, given by first-order PDEs with two spatial dimensions. These algorithms include methods to overcome computer-arithmetic-related challenges when dealing with huge and small numbers. We show that the finite difference schemes constructed using relatively coarse numerical meshes enable accurate estimation of several major optical modes, which are essential in practical applications
Optimal integrated location and dispatching decisions for feeder bus route design problem
No full textDispatch centres are an important part of the feeder bus network, and their location affects the design process of the feeder route. In some remote areas with weak transport infrastructure, it is very important to find an effective tool to simultaneously select the optimal location of the dispatch centre as well as transit routing process, which could improve the performance of the feeder bus system. The purpose of this article is to present an integrated optimization model for joint location and dispatching decisions for Feeder Bus Route Design (FBRD). The proposed methodology can select a number of best dispatch centres in alternative sets and calculate the order of the demand points visited by the feeder route. The objective of the model is to simultaneously minimize the total construction cost of selected dispatch centres and the total operational cost of the designed feeder bus system. The methodology facilitates obtaining solutions using the design of an improved double population Bacterial Foraging Optimization (BFO) algorithm. For example, it redefines the solution coding and the heuristic used to randomly initialize the initial population. When applied to the design of a feeder bus system for a station at Nanjing (China), the results reveal that a reduced budget may lead to change in the location of the dispatch centre; a more distant centre is required, which may increase the total mileage cost of all feeder routes. A detailed comparison of the improved and standard BFO and CPLEX shows that the difference between solutions is acceptable. However, the calculation time is greatly reduced, thus proving the effectiveness of the proposed algorithm
Bayesian networks and structural equation modelling to investigate the passengers’ perceptions in high-speed rail systems
No full textEnsuring sustainability in the global world today depends on perception management as well as financial management. In order to manage the perceptions, which are inherently latent variables as they are measured indirectly through their indicators, they must be accurately handled and modelled comprehensively. In the present study, a hybrid technique combining Bayesian Networks (BN) and Structural Equation Modelling (SEM), which are regarded as causal models, was used to investigate the perceptions of High-Speed Rail System (HSRS) passengers. In order to provide insight into the customer retention strategy for HSRS, the analyses were performed on the survey data gathered from the frequent users of HSRS operating between 2 cities of Turkey. After the measurement model of the perception variables through SEM was established, the relationships between the variables were learned using BN knowledge extraction algorithms. As a result, relationships from image to trust and loyalty, from trust to perceived value, from perceived value to satisfaction, and from satisfaction to loyalty were determined. Final interpretations were made in terms of risk management with the help of the probabilistic predictive ability of the BN by setting evidence on the satisfaction levels of the perceptions
Examining failures in rubber-cord couplings within ER2 series electric trains
No full textThe article provides statistics on failures of rubber-cord couplings of electric trains of the ER2 and ER2T series and of the diesel trains over the past 7 years. According to statistics, over the past 7 years, 107 rubber-cord couplings have failed. Of these, the largest number of cases of failure of rubber-cord couplings occurred on rolling stock of the ER2 series. Examining failed rubber-cord couplings, it was revealed that the cause of its failure was a rupture of the side surface. Replacing a rubber-cord coupling is a labour-intensive and costly process. Accordingly, the question arises: what causes the problem and what measures should be proposed to reduce the failures. For these purposes, the work presents a number of experiments in order to identify possible causes of failure of the rubber-cord coupling. The article presents studies of the heating temperature of rubber-cord couplings in operation on motor cars, as well as a number of studies of failed rubber-cord couplings removed from motor cars. During the research, such parameters as the date of the last repair and the date of failure of the rubber-cord coupling were taken into account. The number of days the motor car was in general operation was taken into account until the failure of the rubber-cord coupling, as well as the mileage of the motor car after the repair. Measurements were carried out of the geometric parameters of the rubber-cord coupling: outer and inner diameter, thickness of the side of the rubber-cord coupling. The torque of the rubber-cord coupling acting at speeds from 5 to 40 km/h, the forces acting in operation on the rubber-cord coupling were calculated, and torsional and shear stresses were also studied and determined. Research was carried out to determine the hardness of the rubber-cord coupling in the temperature range from –20 °C to 0 °C and from 0 °C to +22 °C, as well as from +22 °C to +60 °C. These parameters were taken since a rubber-cord coupling operates under the mentioned conditions. In conclusion, possible reasons for the failure of rubber-cord couplings are given, and recommendations for reduction of their frequency are proposed
Revisiting the dynamics of major cryptocurrencies
No full textPurpose – This study aims to reassess the dynamics of major cryptocurrencies sur-rounding recent economic and geopolitical events. By employing wavelet analysis and quantile regression methods, it seeks to understand the behavior of cryptocurrencies before, during, and after the COVID-19 pandemic.
Research methodology – This research employs the Least Asymmetric Daubechies (LA8) wavelet function to decompose log-returns of major cryptocurrencies into various frequency scales. Additionally, it utilizes wavelet coherence and quantile-on-quantile regression techniques to analyze daily price data spanning from July 2017 to May 2024.
Findings – The findings reveal a strong long-term association among cryptocurrencies, with a decline in medium-term correlations. Bitcoin exhibits synchronization with major cryptocurrencies, excluding Tether, while BTC-ETH and BTC-BNB display a rapid, interconnected behavior alongside their fundamental links. Moreover, empirical evidence indicates Bitcoin’s heterogeneous nexus with other alternatives, showcasing greater sensitivity to positive extremes over negative ones.
Research limitations – The study’s scope is delimited by the selected time frame (July 2017 to May 2024) for data analysis, potentially limiting insights into longer-term trends. Additionally, the reliance on specific methodologies like wavelet analysis might introduce constraints in capturing the entirety of cryptocurrency dynamics, leaving room for alternative interpretations or unexplored aspects.
Practical implications – Results suggest that understanding the varying correlations among major cryptocurrencies during different market phases could aid investors and policymakers in devising more nuanced strategies. Recognizing the sensitivity of Bitcoin’s connections with alternatives to market trends could inform risk management approaches, particularly in navigating extreme market conditions.
Originality/Value – The originality of this study lies in its comprehensive examination of cryptocurrency dynamics across varying time scales, utilizing wavelet analysis and quantile regression techniques. The findings offer valuable insights into the complex interconnections among cryptocurrencies, especially in terms of their sensitivity to different market conditions, providing a nuanced perspective for investors, analysts, and policymakers navigating the crypto landscape
International competitiveness and recovery strategy of the aviation and space industry of Ukraine
No full textThe influence of the aviation and space industries on the development of the world economy and economic development, industrial potential, competitiveness and position of various countries in the world is shown in the article. Global aviation and space market has been studied and an economic analysis of the aviation and space sector of the industry of the countries that are among ten world leaders in the industry was carried out. The main indicators of the development of the aviation and space industry of world countries-leaders and Ukraine have been systematized. The volumes of income of the leading companies of the industry producers, between which there is fierce competition, have been given. International competitiveness has been analyzed and ways of recovery and development of the aviation and space sector of Ukraine were proposed, taking into consideration the significant losses and damages caused by full-scale military invasion of aggressive neighbor on the territory of Ukraine. Scenarios of competitive behavior were considered and a strategy for the restoration of one of the largest enterprises in the world and single one in the aviation and space industry in Ukraine that has completed the cycle of engine production – Joint Stock Company Motor Sich has been made
Tribological properties of thermoplastic elastomer used in 3D printing technology
No full textThe use of thermoplastic elastomers (TPE) in 3D printing technology enables the use of this technology to produce prototype seals with an unusual shape or design solution. Tribological tests were carried out on a pin-on-disc test stand. The influence of contact pressure and sliding velocity on the friction coefficient of the TPE-steel friction pair under mixed lubrication conditions was analyzed. Based on the obtained tribological test results, it was found that the coefficient of friction of the thermoplastic TPE elastomer on steel in the presence of hydraulic oil (mixed lubrication) at a sliding velocity below 1 m/s does not exceed μ = 0.25. The obtained friction coefficient values are comparable to the results for other elastomeric materials used for technical seals. It was found that the influence of contact pressure on the value of the friction coefficient in the tested friction pairs is varied and depends, for example, on the sliding velocity. It was recommended to carry out research on the assessment of durability (wear intensity) and structure (porosity) of the material in elements manufactured using 3D printing to obtain full knowledge of the possibility of using these materials in the area of technical aircraft seals
Deep learning-based proactive fault detection method for enhanced quadrotor safety
No full textThe early detection of faults in advanced technological systems is imperative for ensuring operational reliability and safety. While there is a growing interest in using artificial intelligence for fault detection, current methodologies often exhibit limitations in utilizing comprehensive system information and sensor data. Hidden faults within collected data further highlight the need for advanced analysis techniques. This study introduces a novel deep learning-based framework designed to predict faults and extract insights from complex system datasets. The model, consisting of LSTM-autoencoder and BiLSTM classification components, effectively reduces feature dimensions, thereby enhancing fault detection accuracy. The autoencoder’s latent layer identifies prominent features across various dimensions, while BiLSTM classification conducts bidirectional analysis using these features from both healthy and faulty states, facilitating early fault detection. Experimental results demonstrate the model’s efficacy, achieving an accuracy of 79.48% in predicting incipient faults 30 seconds before a serious malfunction occurs. This underscores the significant potential of the proposed framework in enhancing operational safety and reliability in complex systems. Moreover, the study emphasizes the importance of leveraging comprehensive data and advanced analysis techniques for early fault detection