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Found 6327 publications

LMI feasibility analysis of 2DOF NATA model

Miklós Kuczmann Andrea Weber

Publication Name: Pollack Periodica

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Present paper shows the different types of tensor product model based linear matrix inequality controller design and feasibility analysis of two degrees of freedom aeroelastic wing section model. The tensor product models are based on reducing or removing the nonlinear behavior of the system and weighting functions. The linear matrix inequality based method results globally asymptotically stable system. The goal of the paper is to examine that selecting and varying the transformation space influences the feasibility of the linear matrix inequality based controller. The paper gives a comparison between the different tensor product models in terms of controller performance. The linear matrix inequality gives feasible solution for the controller design if the transformation space is selected adequately.

Open Access: Yes

DOI: 10.1556/606.2024.00888

Rattling detection of electric components

Zoltán Gazdagh J. A. Erdelyi A. Bartus B. Fukker

Publication Name: Proceedings of ISMA 2024 International Conference on Noise and Vibration Engineering and Usd 2024 International Conference on Uncertainty in Structural Dynamics

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 2799-2813

Description:

The study emphasizes the importance of detecting and addressing the issue of nonlinear phenomena in electronic components, due to their potential implications for structural integrity, damage or malfunction to sensitive electronic elements, and a reduction in overall vehicle reliability. This investigation based on time-domain experimental data facilitates rattling detection that aims to distinguish rattling from other type of nonlinearities. The sample is screwed on a fixture, which is mounted on an electrodynamic shaker that serves as the excitation source. The excitation signal is a closed loop sinusoidal sweep, measured in both directions and at different amplitudes. The paper will focus on several methods for identifying nonlinear phenomena, such as the Poincare map or Hilbert transformation. Phase plots are produced, that serve as a valuable tool for studying anomalies, which can be correlated to the extremes of Lyapunov exponents. The above methods are evaluated on their ability to separate rattling form other phenomena to identify genuine instances of rattling.

Open Access: Yes

DOI: DOI not available

OWA operators in the insurance industry

István A. Harmati David Fulep Koppány Krisztián Norbert Kovács

Publication Name: Journal of Infrastructure Policy and Development

Publication Date: 2024-01-01

Volume: 8

Issue: 13

Page Range: Unknown

Description:

In this paper, we examine a possible application of ordered weighted average (OWA for short) aggregation operators in the insurance industry. Aggregation operators are essential tools in decision-making when a single value is needed instead of a couple of features. Information aggregation necessarily leads to information loss, at least to a specific extent. Whether we concentrate on extreme values or middle terms, there can be cases when the most important piece of the puzzle is missing. Although the simple or weighted mean considers all the values there is a drawback: the values get the same weight regardless of their magnitude. One possible solution to this issue is the application of the so-called Ordered Weighted Averaging (OWA) operators. This is a broad class of aggregation methods, including the previously mentioned average as a special case. Moreover, using a proper parameter (the so-called orness) one can express the risk awareness of the decision-maker. Using real-life statistical data, we provide a simple model of the decision-making process of insurance companies. The model offers a decision-supporting tool for companies.

Open Access: Yes

DOI: 10.24294/jipd8015

Innovative Approaches in Railway Management: Leveraging Big Data and Artificial Intelligence for Predictive Maintenance of Track Geometry

Szabolcs Fischer Ferenc Horvát Richárd Nagy

Publication Name: Tehnicki Vjesnik

Publication Date: 2024-01-01

Volume: 31

Issue: 4

Page Range: 1245-1259

Description:

This paper introduces and describes a method for extracting, processing, and analyzing large amounts of track geometrical data. It allows for a more accurate description of the orbital deterioration correlations than currently applied procedures, and it seems to be more valuable and efficient in practice. The initial data were the track geometry measurement and classification data for the whole national network provided by the Hungarian State Railways, i.e., the MÁV PLC. The MÁV provided data for the whole Hungarian railway network for 27 half-years, measured and recorded by the FMK-004 type special diesel locomotive (i.e., track geometry measuring car). The paper discusses the development of a procedure to automatically compute important condition ratings from the available data set of millions of units according to the algorithms created for railway industry colleagues, thus helping the maintenance and renewal decision-making process. Functions have been developed to classify the track geometry condition of a given railway line, to predict how long the service level can be maintained without intervention (i.e., e.g., lining, leveling, and tamping with a mechanized maintenance train), to determine the time of the necessary maintenance intervention, the time of the upgrade (rehabilitation or modernization), and to develop a track geometry prediction procedure that makes full use of the mathematical and computational possibilities of the present day.

Open Access: Yes

DOI: 10.17559/TV-20240420001479

Performance Comparison of IP Packet Forwarding Solutions

Melinda Kosák Gábor Lencse

Publication Name: 2024 47th International Conference on Telecommunications and Signal Processing Tsp 2024

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 243-248

Description:

Nowadays we know several IP packet forwarding solutions, and they are getting faster and more efficient. We chose Fast Data Project / Vector Packet Processing (FD.io VPP) for our investigation, because it is regarded as an extremely high speed and secure networking data plane. In this paper, we present how to install and configure FD.io VPP and we also demonstrate its high IP packet forwarding performance compared to that of the Linux kernel. To achieve this, we built a testbed using two Dell PowerEdge R620 servers. One of the servers was the Tester and the siitperf measurement software was used for executing IPv4 and IPv6 packet forwarding performance tests. The other server was the DUT (Device Under Test), on which FD.io VPP was installed and its packet forwarding performance was measured. As a basis for comparison, we also measured the packet forwarding performance of the Linux kernel. It was found that FD.io VPP seriously outperformed the Linux kernel. The details of the measurements and their results are disclosed and analyzed in the paper.

Open Access: Yes

DOI: 10.1109/TSP63128.2024.10605773

Integrating Renewable Energy into Railway Systems: a Path to Sustainable Transportation – A Review

Szabolcs Fischer Khadiga Al-Nagar Kinda Alshoufi

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 817-822

Description:

Integrating renewable energy sources into railway systems presents a promising solution to mitigate rising CO2 emissions, growing energy demands, and environmental degradation. This paper reviews the potential of incorporating renewable energy technologies such as solar, wind, bioenergy, and kinetic energy recovery into railway infrastructure. By employing intelligent multi-agent systems to manage rail microgrids, the study demonstrates significant enhancements in energy efficiency, operational cost reduction, and system reliability. Strategic deployment of these energy solutions has shown a potential reduction in energy consumption by up to 30 %. This paper underscores the importance of advanced energy storage and management systems to address the variability of renewable sources, ensuring a stable and consistent energy supply. These findings highlight the critical role of smart grid technologies and AI-driven energy management in advancing the sustainability of railway operations and contributing to global sustainable development objectives.

Open Access: Yes

DOI: 10.3303/CET24114137

Efficiency Analysis of Kolmogorov-Arnold Networks for Visual Data Processing †

János Hollósi

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

In the field of artificial neural networks, the use of multilayer perceptrons (MLPs) has long been a well-established methodology. Recently, the theory of Kolmogorov–Arnold Networks (KANs) has emerged as a potential alternative to multilayer perceptrons, inspired by the Kolmogorov–Arnold representation theorem. It has been demonstrated that solutions based on the Kolmogorov–Arnold Network (KAN) can achieve better efficiency than those based on the multilayer perceptron (MLP) for certain problems. In this work, we investigate how the new theory can be applied to a special image classification task when some adversarial attack method is applied. The aim of the research is to explore the potential of the theory to answer the question of its applicability to complex tasks of practical importance.

Open Access: Yes

DOI: 10.3390/engproc2024079068

Potential of Producing Green Hydrogen Using Solar Power Plants: The Role of PEM Technology in the Improvement of Photovoltaic Schedule Keeping in Hungary

Henrik Zsiboracs Nóra Hegedűsné Baranyai András Vincze Virag Meszaros Gábor Pintér

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 925-930

Description:

Similarly to many countries of the world, photovoltaic systems play an increasingly important role in electricity generation in Hungary, contributing greatly to the climate, environmental and sustainability goals of the energy transition. As a result of numerous factors, photovoltaic technology is used not only more and more widely but also in increasingly decisive quantities and proportions. Due to the intermittent nature of solar energy, photovoltaic generation varies both in space and over time and consequently poses a serious challenge to system management, especially due to dynamically developing capacities. The imbalances caused by uncertainty cannot be addressed by scheduling alone without the possibility of energy storage, which, with its numerous services and applications, is able to provide the flexibility necessary for the smooth operation of the system. Among the available energy storage systems, power-to-gas technology (i.e. converting electricity produced from renewable energy sources into a gaseous energy carrier) is emerging as a practical solution with high potential for the integration of variable renewable energy sources. The gas produced in this way, which can be stored and transported, can be used in many areas and sectors of energy use, such as transport, home heating and cooling and industrial processes, and can now also provide an effective solution for grid stability and scheduling. The aim of the present research is to present the potential amount of green hydrogen that can be produced by proton-exchange membrane technology (PEM) in connection with schedule-related downregulation, considering the climatic conditions and the total photovoltaic power plant capacity in Hungary. The novel, practical benefit of the research lies in the fact that it determines practically relevant characteristics in relation to the interconnections of solar power plants in Hungary and power-to-gas technology for transmission system operators, the key players of the energy market and decision-makers. This knowledge will not only help companies investing in solar power plants and power-to-gas technology from an economic point of view but can also contribute to the market-related development of hydrogen production solutions related to photovoltaic technology. Overall, P2G offers the ideal potential to convert the electricity produced by solar power plants that need to be downregulated, i.e. comprises a surplus in terms of scheduling, into green hydrogen, which is also suitable for long-term seasonal storage.

Open Access: Yes

DOI: 10.3303/CET24114155

Application of artificial neural networks for characterisation of formability properties of sheet metals

Dóra Harangozó Imre Czinege

Publication Name: International Journal of Lightweight Materials and Manufacture

Publication Date: 2024-01-01

Volume: 7

Issue: 1

Page Range: 37-44

Description:

Artificial neural network models were developed to estimate forming limit diagrams from tensile test results based on our own experiments and data from the literature for steel and aluminium sheet metals. Experimental data were obtained from tensile tests and Nakazima tests. The input parameters used in the models were yield strength, ultimate tensile strength, uniform elongation, elongation at fracture, anisotropy coefficient and hardening exponent or combinations of these. The forming limit curves were defined by the measured minor and major strains using seven standard test specimens. After training the artificial neural network, the difference between measured and predicted results was evaluated by linear regression parameters and by the absolute errors. For steel sheet data taken from the literature, the estimated outputs of ANN models were compared with the results of empirical formulae developed by different authors. It was found that there was a high correlation coefficient between predicted and measured values for models using neural networks, which gave better approximations than other linear and non-linear models.

Open Access: Yes

DOI: 10.1016/j.ijlmm.2023.08.003