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Number of results: 12
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Abstract

Piękne włoskie marmury, barwne polskie piaskowce, nawet twarde skandynawskie granity nie są odporne na ,,ząb czasu". Bez względu na to, z jakiego kamienia wykonujemy posągi naszych wieszczów, czeka je ta sama, przygnębiająco szara starość. Chyba, że poznamy winowajców i podejmiemy walkę.
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Authors and Affiliations

Marek W. Lorenc
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Abstract

Neither beautiful Italian marbles nor colorful Polish sandstones, not even hard Scandinavian granites are impervious to the "tooth of time." No matter kind of stone we carve statues of our beloved poets and leaders from, they can all expect to meet the same depressing end - unless we get to know the culprits and learn to put up a fight.
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Authors and Affiliations

Marek W. Lorenc
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Abstract

The paper presents the results of the application of the hierarchical clustering methods for the classification of the acoustic emission (AE) signals generated by eight basic forms of partial discharges (PD), which can occur in paper-oil insulation of power transformers. Based on the registered AE signals from the particular PD forms, using a frequency descriptor in the form of the power spectral density (PSD) of the signal, their representation in the form of the set of points on plane XY was created. Next, these sets were subjected to analysis using research algorithms consisting of selected clustering methods. Based on the suggested numeric performance indicators, the analysis of the degree of reproduction of the actual distribution of points showing the particular time waveforms of the AE signals from eight adopted PD forms (PD classes) in the obtained clusters was carried out. As a result of the analyses carried out, the clustering algorithms of the highest effectiveness in the identification of all eight PD classes, classified simultaneously, where indicated. Within the research carried out, an attempt to draw general conclusions as to the selection of the most effective hierarchical clustering method studied and the similarity function to be used for classification of the selected basic PD forms.
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Bibliography

1. Akbari A., Setayeshmehr A., Borsi H., Gockenbach E. (2010), Intelligent agent-based system using dissolved gas analysis to detect incipient faults in power transformers, IEEE Electrical Insulation Magazine, 26(6): 27–40, doi: 10.1109/MEI.2010.5599977.
2. Boczar T. (2001), Identification of a specific type of PD form acoustics emission frequency spectra, IEEE Transaction on Dielectric and Electrical Insulation, 8(4): 598–606, doi: 10.1109/94.946712.
3. Boczar T., Borucki S., Cichon A., Zmarzły D. (2009), Application Possibilities of Artificial Neural Networks for Recognizing Partial Discharges Measured by the Acoustic Emission Method, IEEE Transaction on Dielectric and Electrical Insulation, 16(1): 214–223, doi: 10.1109/TDEI.2009.4784570.
4. Boczar T., Cichon A., Borucki S. (2014), Diagnostic expert system of transformer insulation systems using the acoustic emission method, IEEE Transaction on Dielectric and Electrical Insulation, 21(2): 854–865, doi: 10.1109/TDEI.2013.004126.
5. Borucki S., Boczar T., Cichon A., Lorenc M. (2007), The evaluation of neural networks application for recognizing single-source PD forms generated in paper-oil insulation systems based on the AE signal analysis, European Physical Journal Special Topics, 154: 23–29, doi: 10.1140/epjst/e2008-00512-7.
6. Borucki S., Łuczak J. (2017), Assessment of the impact of an acoustic signal power spectral density frequency selection on partial discharges basic forms classification efficiency with the use of data clustering method [in Polish: Ocena wpływu doboru czestotliwosci widmowej gestosci mocy sygnału akustycznego na efektywnosc klasyfikacji podstawowych form wyładowan niezupełnych z uzyciem metody klasteryzacji], Energetyka, 7: 448–452.
7. Borucki S., Łuczak J., Zmarzły D. (2018), Using Clustering Methods for the Identification of Acoustic Emission Signals Generated by the Selected Form of Partial Discharge in Oil-Paper Insulation, Archives of Acoustics, 43(2): 207–215, doi: 10.24425/122368.
8. Castro Heredia L.C., Rodrigo Mor A. (2019), Density-based clustering methods for unsupervised separation of partial discharge sources, International Journal of Electrical Power & Energy Systems, 107: 224–230, doi: 10.1016/j.ijepes.2018.11.015.
9. Chia-Hung L., Chien-Hsien W., Ping-Zan H. (2009), Grey clustering analysis for incipient fault diagnosis in oil-immersed transformers, Expert Systems with Applications, 36(2, part 1): 1371–1379, doi: 10.1016/j.eswa.2007.11.019.
10. Cichon A. (2013), Assessment of technical condition of on-load tap-changers by the method of acoustic emission, [in Polish: Ocena stanu technicznego podobciazeniowych przełaczników zaczepów metoda emisji akustycznej], Studia i Monografie, No. 352, Ofic. Wyd. Politechniki Opolskiej.
11. Fuhr J. (2005), Procedure for identification and localization of dangerous partial discharge sources in power transformers, IEEE Transaction on Dielectric and Electrical Insulation, 12(5): 1005–1014, doi: 10.1109/TDEI.2005.1522193.
12. Han J., Kamber M., Pei J. (2012), Data Mining. Concepts and Techniques, 3rd ed., Morgan Kaufmann Publishers, Waltham.
13. Kapinos J., Glinka T., Drak B. (2014), Typical causes of operational failures in power transformers working in National Grid [in Polish: Typowe przyczyny uszkodzen eksploatacyjnych transformatorów energetycznych], Przeglad Elektrotechniczny, 90(1): 186–189, doi: 10.12915/pe.2014.01.45.
14. Kazmierski M., Olech W. (2013), Technical Diagnostics and Monitoring of Transformers [in Polish: Diagnostyka techniczna i monitoring transformatorów], Printing house of ZPBE Energopomiar-Elektryka Sp. z o.o., Gliwice.
15. Krzysko M., Wołynski W., Górecki T. Skorzybut M. (2008), Learning Systems – Pattern Recognition, Cluster Analysis and Dimensional Reduction [in Polish: Systemy uczace sie – rozpoznawanie wzorców, analiza skupien i redukcja wymiarowosci], Wydawnictwa Naukowo-Techniczne, Warszawa.
16. Kurtasz P. (2011), Application of a multi-comparative algorithm to classify acoustic emission signals generated by partial discharges [in Polish: Zastosowanie algorytmu multikomparacyjnego do klasyfikacji sygnałów emisji akustycznej generowanych przez wyładowania niezupełne], Ph.D. Dissertation, Opole University of Technology.
17. Lalitha E.M., Satish L. (2002),Wavelet analysis for classification of multi-source PD patterns, IEEE Transaction on Dielectric and Electrical Insulation, 7(1): 40– 47, doi: 10.1109/94.839339.
18. Ming-Shou S., Chung-Chu C., Chien-Yi C., Jiann-Fuh C. (2014), Classification of partial discharge events in GILBS using probabilistic neural networks and the fuzzy c-means clustering approach, International Journal of Electrical Power & Energy Systems, 61: 173–179, doi: 10.1016/j.ijepes.2014.03.054.
19. Mohan Rao U., Sood Y.R., Jarial R.K. (2015), Subtractive Clustering Fuzzy Expert System for Engineering Applications, Procedia Computer Science, 48: 77–83, doi: 10.1016/j.procs.2015.04.153.
20. Morzy T. (2013), Data mining. Methods and Algorithms [in Polish: Eksploracja danych. Metody i algorytmy], Wydawnictwo Naukowe PWN, Warszawa.
21. Olszewska A., Witos F. (2012), Location of partial discharge sources and analysis of signals in chosen power oil transformers by means of acoustic emission method, Acta Physica Polonica A, 122(5): 921–926.
22. Radionov A.A., Evdokimov S.A., Sarlybaev A.A., Karandaeva O.I. (2015), Application of Subtractive Clustering for Power Transformer Fault Diagnostics, Procedia Engineering, 129: 22–28, doi: 10.1016/j.proeng.2015.12.003.
23. Rodrigo Mor A., Castro Heredia L.C., Muñoz F.A. (2017), Effect of acquisition parameters on equivalent time and equivalent bandwidth algorithms for partial discharge clustering, International Journal of Electrical Power & Energy Systems, 88: 141–149, doi: 10.1016/j.ijepes.2016.12.017.
24. Rubio-Serrano J., Rojas-Moreno M., Posada J., Martienez-Tarifa J., Robles G., Garcia-Souto J. (2012), Electro-acoustic detection, identification and location of PD sources in oil-paper insulation systems, IEEE Transaction on Dielectric and Electrical Insulation, 19(5): 1569–1578, doi: 10.1109/TDEI. 2012.6311502.
25. Soltani A.A., Haghjoo F., Shahrtash S.M. (2012), Compensation of the effects of electrical sensors in measuring PD signals, IET Science, Measurement &Technology, 6(6): 494–501, doi: 10.1049/iet-smt.2012.0001.
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Authors and Affiliations

Sebastian Borucki
1
Jacek Łuczak
1
Marcin Lorenc
1

  1. Opole University of Technology, Opole, Poland
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Abstract

The article concerns safety of power supply for the final consumers, especially its two comprising elements, which are generation adequacy and distribution system reliability. Generation adequacy has been defined with Loss of Load Probability (LOLP), Loss of Load Expectation (LOLE) and Energy Not Supplied (ENS) indices. Conclusions from generation adequacy forecast prepared by ENSTO-E for Poland compared with other European countries for the years 2020 and 2025 have been discussed along with the resulting threats. Interruptions in energy supply have been characterised by power discontinuity indicator SAIDI. Finally, a reliability and adequacy analysis have been performed for different scenarios of the Polish power system operation in order to assess possibilities of using distributed generation as a backup power source. Based on a simulation model created using the DIgSILENT Power Factory software, the reliability and adequacy calculations have been performed with the probabilistic non-sequential Monte Carlo method and they are followed by a discussion of the obtained results.

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Authors and Affiliations

Jerzy Andruszkiewicz
Józef Lorenc
Agnieszka Weychan
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Abstract

Nine samples of basic (dolerite, gabbro) intrusions collected at Bellsund, South Spitsbergen, have been K−Ar dated. Three dates, between 87.8 and 102.9 Ma, obtained from dolerite sills which intrude Carboniferous and Permian deposits in Van Keulenfjorden point to a Cretaceous age of intrusive activity (Diabasodden Suite). The K−Ar dates obtained from dolerite and gabbro which intrude Upper Proterozoic metasedimentary terrane of Chamber− lindalen form two groups: the dates between 97.1 and 178.6 Ma point to a Mesozoic age of the intrusions (Diabasodden Suite); the dates from a tectonized gabbroid (280.9–402.0 Ma) might point to a Late Palaeozoic age of the intrusion. No K−Ar dates which would indicate a Proterozoic age of the basic intrusions were obtained

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Authors and Affiliations

Krzysztof Birkenmajer
Zoltán Pécskay
Krzysztof P. Krajewski
Marek W. Lorenc
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Abstract

This paper presents concepts of value chains as strategic models for long-term development and a sustainable approach for ensuring efficiency. It highlights the fact that value chains are of particular importance in the raw materials industry, where the exploration, extraction, processing and metallurgy stages are characterized by high capital expenditure and fixed costs. Additionally, it emphasizes that offering an increasingly valuable product at each stage of production or processing makes it possible to increase earnings and achieve a higher margin. In order to give a practical dimension to the presented analyses, the paper provides an example of lithium value chains and identifies the determinants of their functioning in the current market together with their prospects. The conclusion highlights Europe’s need to source raw materials within business models based on value chains.
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Authors and Affiliations

Arkadiusz Jacek Kustra
1
ORCID: ORCID
Sylwia Lorenc
1
ORCID: ORCID
Marta Podobińska-Staniec
1
ORCID: ORCID
Anna Wiktor-Sułkowska
1
ORCID: ORCID

  1. AGH University of Science and Technology, Poland
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Abstract

The global development of electromobility and the innovation of life are becoming increasingly noticeable. A direct implication of this is the increase in demand for modern products and services, their components and thus the raw materials necessary to produce them (e.g. cobalt, lithium, rare earth metals). In the European Union (EU), raw materials related to strategic sectors – renewable energy, electric mobility, defense and aerospace and digital technologies – show a very strong dependence on import throughout the entire value chain. In the case of eleven out of thirty of the so-called critical raw materials (CRM), necessary for the energy transition, the EU’s dependence on import exceeds 85%. Global supply chains, which had already been strained, were further affected by the COVID-19 pandemic and the exacerbated geopolitical situations leading to even greater shortages of critical raw materials in Europe and leaving the industry facing challenges in securing access to resources. An implication of this was the European Parliament’s position on critical raw material legislation in September 2023, which called on the EU to increase its processing capacity across the value chain and enable the production of at least 40% of the annual consumption of strategic raw materials by 2030.
Growing importance in the transition to a low-emission economy is attributed to cobalt (Co), which is an essential component both in the production of electric vehicles (EV), stationary energy storage and in the developing sectors of wind energy, fuel cell systems and hydrogen storage technologies, robotics, unmanned vehicles (drones) and 3D printing as well as in digital technologies. Securing the supply of such raw material is crucial for the European Union’s economic resilience, technological advantage and strategic autonomy.
The purpose of this article is to present and analyze the concept of value chains as strategic models of long-term development and ensuring efficiency from a sustainable perspective. According to the authors, a detailed analysis of value chains may enable defining strategic directions of action and identifying the risks of their disruption or interruption. To give a practical dimension to the presented analyses, the example of the cobalt value chain is provided and the determinants of its functioning on the current market along with development prospects are indicated.
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Authors and Affiliations

Sylwia Lorenc
1
ORCID: ORCID
Marta Podobińska-Staniec
1
ORCID: ORCID
Anna Wiktor-Sułkowska
1
ORCID: ORCID
Arkadiusz Jacek Kustra
1
ORCID: ORCID

  1. AGH University of Krakow, Poland

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