Top

Optical Memory and Neural Networks

Published in:

01-03-2024

Lasers and Modern Energy

Authors: V. E. Privalov, V. G. Shemanin

Published in: Optical Memory and Neural Networks | Issue 1/2024

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

The clean hydrogen is needed for green energy. It can be obtained by the water electrolysis, which is energetically unprofitable. The problem of hydrogen storage solution made it possible to use it as an automobile fuel. There was a place for the laser in the cramped fuel cell. Previously, it was proposed to introduce laser radiation with the wavelengths corresponding to the water molecule vibrational levels excitation into the reaction zone to increase energy efficiency. In addition, all processes on the Earth should be considered taking into account hydrogen degassing, that is, the hydrogen escape from the Earth into the atmosphere. And so the laser is the most suitable tool for finding places where the hydrogen exits to the surface. In this paper, it is proposed to use the Raman lidar for laser remote sensing of the hydrogen molecules during its leaks into the atmosphere. Based on the results of the Raman lidar equation computer simulation in the range of ranging distances up to 100 m, it is shown that its parameters optimization will reduce the values of detectable concentrations of the hydrogen molecules in the atmosphere.

previous article Review on Improved Machine Learning Techniques for Predicting Chronic Diseases

next article Assault Type Detection in WSN Based on Modified DBSCAN with Osprey Optimization Using Hybrid Classifier LSTM with XGBOOST for Military Sector

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Privalov, V.E., Turkin, V.A., and Shemanin, V.G., On laser-information technologies in hydrogen energy, Lasers, Meas., Inf., 2021, vol. 1, no. 1, pp. 4–11. https://lasers-measurement-information.ru/ojs/index.php/laser/article/view/9.

Privalov, V.E., Turkin, V.A., and Shemanin, V.G., Hydrogen power capabilities in water transport, IOP Conf. Ser.: Earth Environ. Sci., 2021, vol. 872, no. 1, 012014. https://doi.org/10.1088/1755-1315/872/1/012014

Lobanov, S., Hydrogen. Back to the future, Sci. Polytech., 2021, no. 3, pp. 44–51

Privalov, V.E. and Shemanin, V.G., Lasers and energy, Lasers, Meas., Inf., 2023, vol. 3, no. 1, pp. 4–12. https://lasers-measurement-information.ru/ojs/index.php/laser/article/view/9.

Privalov, V.E., Fotiadi, A.E., and Shemanin, V.G., Lidar Sensing of the Molecular Hydrogen, S.-Pb.: Polytech-Press, 2023.

Vernadsky, V.I., Selected Works, vol. 4, book 2, Moscow, USSR Academy of Sciences Publ., 1960, pp. 13−14.

Grigoriev, S.A., Pogrembsky, V.I., Fateev, V.N., et al., Hydrogen production by electrolysis of water: …., Transport on an Alternative Basis, 2008, no. 3, p. 3.

Boldyrev, V., Hydrogen energy, Industrial Vedomosti, 2006, no. 5.

Meyer, S.A., US Patent 4 826 581, 1989.

10.

Meyer, S.A., The Birthday of New Technology. Water Fuel Cell, Technical Brief, Hydrogen Fracturing Process, Crove City, Ohio, 1995. https://vk.com/doc72110428_365553645?hash=cf3a3a09bfb78824b9&dl=23e8b23c85441b4472.

11.

Privalov, V.E., Device for water decomposition, Proc. XXVI Inter. Conferences “Laser and Information Technologies—2018”, Novorossiysk, 2018, pp. 40–41.

12.

Rogovaya, M., Hydrogen: Prospects of energy transition, Kommersant Nauka Magazine, no. 23, Kommersant, June 24, 2021. https://zen.yandex.ru/media/kommersant/vodorod-perspektivy-energeticheskogo-perehoda-60d49ea701c59234cb830a0b15.

13.

Vanags, M., Kleperis, J., and Bajars, G., Water electrolysis with inductive voltage pulses, INTECH, 2012. http://cdn.intechopen.com/pdfs/40142/InTechWater_electrolysis_with_inductive_voltage_pulses.pdf.

14.

Privalov, V.E., Fotiadi, A.E., and Shemanin, V.G., Lasers and Environmental Monitoring of the Atmosphere, St. Pb.: Lan Publ., 2013.

15.

Dolgikh, G.I. and Privalov, V.E., Lasers. Laser systems, Vladivostok: Dalnauka, 2009.

16.

Dolgikh, G.I. and Privalov, V.E., Laser Physics. Fundamental and Applied Research, Vladivostok: Reya, 2016.

17.

Measures, R.M., Laser Remote Sensing, N.Y.: Wiley, 1984.

18.

Privalov, V.E. and Shemanin, V.G., Laser sensing of hydrogen molecules in the atmosphere, Photonics Rus, 2010, no. 1, pp. 26–29.

19.

Privalov, V.E. and Shemanin, V.G., Hydrogen sulfide molecules lidar sensing in the atmosphere, Opt. Mem. Neural Networks, 2018, vol. 27, no. 2, pp. 120–131. https://doi.org/10.3103/S1060992X18020091CrossRef

20.

Privalov, V.E. and Shemanin, V.G., Accuracy of lidar measurements of the concentration of hydrofluoride molecules in the atmospheric boundary layer, Meas. Tech., 2020, vol. 63, no. 7, pp. 543–548. https://doi.org/10.1007/s11018-020-01821-0CrossRef

21.

Privalov, V.E. and Shemanin, V.G., Lidar parameters for remote sensing of gas molecules and aerosol in the atmosphere, St. Pb., Balt. STU “VOENMEH”, 2001.

22.

Privalov, V.E. and Shemanin V.G., Lidar measurement of the Raman differential cross section by hydrogen molecules, Opt. Mem. Neural Networks, 2023, vol. 32, no. 1, pp. 34–38. https://doi.org/10.3103/S1060992X23010034CrossRef

23.

Glazov, G.N., Statistical Issues of Lidar Remote Sensing of the Atmosphere, Novosibirsk: Nauka, 1987.

24.

Laser Monitoring of the Atmosphere, Hinckley, E.D., Ed., M.: Mir, 1979.

25.

Sverdlov, L.M., Kovner, M.A., and Krainov, E.P., Vibrational Spectra of Polyatomic Molecules, M.: Nauka, 1970.

26.

Lasers Handbook, Prokhorov, A.M., vol. 1, M.: Soviet Radio, 1978.

27.

Mini spectrometer with fiber input FSD9-FSD10 v6-2 in the range of 180-1080 nm with a highly sensitive CCD ruler TCD1304DG(M/X)—3500 pixels. http://optofiber.ru/ru/spectrometers/mini-spektrometr.

28.

Choi, I.Y., Baik, S.H., and Choi, Y.S., Remotely measuring the hydrogen gas by using portable Raman lidar system, Opt. Appl., 2021, vol. 51, no. 1, pp. 37–49. https://doi.org/10.37190/OA210103CrossRef

Title: Lasers and Modern Energy
Authors: V. E. Privalov
V. G. Shemanin
Publication date: 01-03-2024
Publisher: Pleiades Publishing
Published in: Optical Memory and Neural Networks / Issue 1/2024
Print ISSN: 1060-992X
Electronic ISSN: 1934-7898
DOI: https://doi.org/10.3103/S1060992X24010090

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Other articles of this Issue 1/2024

Multi-Modal Co-Attention Capsule Network for Fake News Detection

Lateral Motion Control of a Maneuverable Aircraft Using Reinforcement Learning

Review on Improved Machine Learning Techniques for Predicting Chronic Diseases

Q-Memory Task Routing to Prevent Deadlocks in Ethernet Control with Memory Crossbar Switching

Forecasting PM2.5 Concentration Using Gradient-Boosted Regression Tree with CNN Learning Model

Assault Type Detection in WSN Based on Modified DBSCAN with Osprey Optimization Using Hybrid Classifier LSTM with XGBOOST for Military Sector

Premium Partner