Improvement in measurement of radiation based two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH
The formation of scales in pipes is one element that has a major impact on the efficiency of machinery used in the oil and gas sector. With the help of artificial intelligence, this new, non-invasive device was able to figure out the volume fraction of a two-phase flow by taking into account the thi...
- Autores:
-
Mayet, Abdulilah Mohammad
Ilyinichna, Evgeniya Gorelkina
AlShaqsi, Jamil
Parayangat, Muneer
Grimaldo Guerrero, John William
Raja, M. Ramkumar
Muqeet, Mohammed Abdul
Mohammed, Salman Arafath
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2024
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/14208
- Acceso en línea:
- https://hdl.handle.net/11323/14208
https://repositorio.cuc.edu.co/
- Palabra clave:
- Dual-energy gamma source
Group method of data handling
Scale thickness
Two phase-flows
Ant colony optimization
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
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| dc.title.eng.fl_str_mv |
Improvement in measurement of radiation based two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH |
| title |
Improvement in measurement of radiation based two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH |
| spellingShingle |
Improvement in measurement of radiation based two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH Dual-energy gamma source Group method of data handling Scale thickness Two phase-flows Ant colony optimization |
| title_short |
Improvement in measurement of radiation based two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH |
| title_full |
Improvement in measurement of radiation based two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH |
| title_fullStr |
Improvement in measurement of radiation based two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH |
| title_full_unstemmed |
Improvement in measurement of radiation based two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH |
| title_sort |
Improvement in measurement of radiation based two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH |
| dc.creator.fl_str_mv |
Mayet, Abdulilah Mohammad Ilyinichna, Evgeniya Gorelkina AlShaqsi, Jamil Parayangat, Muneer Grimaldo Guerrero, John William Raja, M. Ramkumar Muqeet, Mohammed Abdul Mohammed, Salman Arafath |
| dc.contributor.author.none.fl_str_mv |
Mayet, Abdulilah Mohammad Ilyinichna, Evgeniya Gorelkina AlShaqsi, Jamil Parayangat, Muneer Grimaldo Guerrero, John William Raja, M. Ramkumar Muqeet, Mohammed Abdul Mohammed, Salman Arafath |
| dc.subject.proposal.eng.fl_str_mv |
Dual-energy gamma source Group method of data handling Scale thickness Two phase-flows Ant colony optimization |
| topic |
Dual-energy gamma source Group method of data handling Scale thickness Two phase-flows Ant colony optimization |
| description |
The formation of scales in pipes is one element that has a major impact on the efficiency of machinery used in the oil and gas sector. With the help of artificial intelligence, this new, non-invasive device was able to figure out the volume fraction of a two-phase flow by taking into account the thickness of the scale in the tested pipeline. The proposed design uses an isotope pair of barium-133 and cesium-137 as a dual-energy gamma generator. One detector records photons that are transmitted, and another detector records photons that are scattered. The signals from the detectors were simulated using the Monte Carlo N-Particle (MCNP) code, and then ten frequency and wavelet characteristics were extracted. To choose the best inputs from the collected features for computing the volume fraction, an ant colony optimization (ACO)-based method is applied. Six attributes, representing the optimal combination, were developed using this method. In order to forecast the volume percentage of two-phase flows independently of flow regime and scale thickness, we fed the characteristics introduced by ACO into a group method of data handling (GMDH) neural network. Volume fraction calculations had a maximum RMSE of 0.056, which is quite little compared to previous research. By using the ACO to choose the best characteristics, the current work has significantly increased its accuracy in identifying volume fractions |
| publishDate |
2024 |
| dc.date.issued.none.fl_str_mv |
2024-11 |
| dc.date.accessioned.none.fl_str_mv |
2025-05-07T21:47:22Z |
| dc.date.available.none.fl_str_mv |
2025-05-07T21:47:22Z |
| dc.type.none.fl_str_mv |
Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Text |
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Abdulilah Mohammad Mayet, Evgeniya Ilyinichna Gorelkina, Jamil AlShaqsi, Muneer Parayangat, John William Grimaldo Guerrero, M. Ramkumar Raja, Mohammed Abdul Muqeet, Salman Arafath Mohammed, Improvement in measurement of radiation ased two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH, Nuclear Engineering and Technology, Volume 56, issue 11, 2024, Pages 4826-4836, ISSN 1738-5733, https://doi.org/10.1016/j.net.2024.06.046. (https://www.sciencedirect.com/science/article/pii/S1738573324003061) |
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1738-5733 |
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https://hdl.handle.net/11323/14208 |
| dc.identifier.doi.none.fl_str_mv |
10.1016/j.net.2024.06.046 |
| dc.identifier.instname.none.fl_str_mv |
Corporación Universidad de la Costa |
| dc.identifier.reponame.none.fl_str_mv |
REDICUC - Repositorio CUC |
| dc.identifier.repourl.none.fl_str_mv |
https://repositorio.cuc.edu.co/ |
| identifier_str_mv |
Abdulilah Mohammad Mayet, Evgeniya Ilyinichna Gorelkina, Jamil AlShaqsi, Muneer Parayangat, John William Grimaldo Guerrero, M. Ramkumar Raja, Mohammed Abdul Muqeet, Salman Arafath Mohammed, Improvement in measurement of radiation ased two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH, Nuclear Engineering and Technology, Volume 56, issue 11, 2024, Pages 4826-4836, ISSN 1738-5733, https://doi.org/10.1016/j.net.2024.06.046. (https://www.sciencedirect.com/science/article/pii/S1738573324003061) 1738-5733 10.1016/j.net.2024.06.046 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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https://hdl.handle.net/11323/14208 https://repositorio.cuc.edu.co/ |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.ispartofjournal.none.fl_str_mv |
Nuclear Engineering and Technology |
| dc.relation.references.none.fl_str_mv |
A. Bahadori, G. Zahedi, S. Zendehboudi, Estimation of potential barium sulfate (barite) precipitation in oilfield brines using a simple predictive tool, Environ. Prog. Sustain. Energy 32 (2013) 860–865 A.B. BinMerdhah, Inhibition of barium sulfate scale at high-barium formation water, J. Pet. Sci. Eng. 90 (2012) 124–130 M. Roshani, M.A. Sattari, P.J. Ali, G.H. Roshani, B. Nazemi, E. Corniani, E. Nazemi, Application of GMDH neural network technique to improve measuring precision of a simplified photon attenuation based two-phase flowmeter, Flow Meas. Instrum. 75 (2020) 101804 M.A. Sattari, G.H. Roshani, R. Hanus, E. Nazemi, Applicability of time-domain feature extraction methods and artificial intelligence in two-phase flow meters based on gamma-ray absorption technique, Measurement 168 (2021) 108474, https://doi.org/10.1016/j.measurement.2020.108474 M.A. Sattari, G.H. Roshani, R. Hanus, Improving the structure of two-phase flow meter using feature extraction and GMDH neural network, Radiat. Phys. Chem. 171 (2020 Jun 1) 108725 S. Hosseini, G.H. Roshani, S. Setayeshi, Precise gamma based two-phase flow meter using frequency feature extraction and only one detector, Flow Meas. Instrum. 72 (2020 Apr 1) 101693 S. Hosseini, O. Taylan, M. Abusurrah, T. Akilan, E. Nazemi, E. Eftekhari-Zadeh, F. Bano, G.H. Roshani, Application of wavelet feature extraction and artificial neural networks for improving the performance of gas–liquid two-phase flow meters used in oil and petrochemical industries, Polymers 13 (21) (2021) 3647 A. Basahel, M.A. Sattari, O. Taylan, E. Nazemi, Application of feature extraction and artificial intelligence techniques for increasing the accuracy of X-ray radiation based two phase flow meter, Mathematics 9 (11) (2021 Jan) 1227 O. Taylan, M.A. Sattari, I. Elhachfi Essoussi, E. Nazemi, Frequency domain feature extraction investigation to increase the accuracy of an intelligent nondestructive system for volume fraction and regime determination of gas-water-oil three-phase flows, Mathematics 9 (17) (2021 Jan) 2091 M. Balubaid, M.A. Sattari, O. Taylan, A.A. Bakhsh, E. Nazemi, Applications of discrete wavelet transform for feature extraction to increase the accuracy of monitoring systems of liquid petroleum products, Mathematics 9 (24) (2021 Jan) 3215 M. Alamoudi, M.A. Sattari, M. Balubaid, E. Eftekhari-Zadeh, E. Nazemi, O. Taylan, E.M. Kalmoun, Application of gamma attenuation technique and artificial intelligence to detect scale thickness in pipelines in which two-phase flows with different flow regimes and void fractions exist, Symmetry 13 (7) (2021) 1198 D.F. Oliveira, J.R. Nascimento, C.A. Marinho, R.T. Lopes, Gamma transmission system for detection of scale in oil exploration pipelines, Nucl. Instrum. Methods Phys. Res. Sect. A Accel. Spectrometers Detect. Assoc. Equip. 784 (2015) 616–620 T.P. Teixeira, C.M. Salgado, R.S.D.F. Dam, W.L. Salgado, Inorganic scale thickness prediction in oil pipelines by gamma-ray attenuation and artificial neural network, Appl. Radiat. Isot. 141 (2018) 44–50 W.L. Salgado, R.S.D.F. Dam, T.P. Teixeira, C.C. Conti, C.M. Salgado, Application of artificial intelligence in scale thickness prediction on offshore petroleum using a gamma-ray densitometer, Radiat. Phys. Chem. 168 (2020) 108549 D.B. Pelowitz, MCNP-X TM User’s Manual, Version 2.5.0; LA-CP-05e0369; Los Alamos National Laboratory, New Mexico, NM, USA, 2005 M. Roshani, G. Phan, G.H. Roshani, R. Hanus, B. Nazemi, E. Corniani, E. Nazemi, Combination of X-ray tube and GMDH neural network as a nondestructive and potential technique for measuring characteristics of gas-oil–water three phase flows, Measurement 168 (2021) 108427, https://doi.org/10.1016/j. measurement.2020.108427 C.M. Salgado, L.E.B. Brand˜ ao, C.C. Conti, W.L. Salgado, Density prediction for petroleum and derivatives by gamma-ray attenuation and artificial neural networks, Appl. Radiat. Isot. 116 (2016) 143–149 M.A. Sattari, N. Korani, R. Hanus, G.H. Roshani, E. Nazemi, Improving the performance of gamma radiation based two phase flow meters using optimal time characteristics of the detector output signal extraction, Journal of Nuclear Science and Technology (JonSat) 41 (2) (2020) 42–54 G.H. Roshani, P.J. Ali, S. Mohammed, R. Hanus, L. Abdulkareem, A.A. Alanezi, M. A. Sattari, S. Amiri, E. Nazemi, E. Eftekhari-Zadeh, E.M. Kalmoun, Simulation study of utilizing X-ray tube in monitoring systems of liquid petroleum products, Processes 9 (5) (2021 May) 828 R. Hanus, M. Zych, M. Kusy, M. Jaszczur, L. Petryka, Identification of liquid-gas flow regime in a pipeline using gamma-ray absorption technique and computational intelligence methods, Flow Meas. Instrum. 60 (2018) 17–23 E. Nazemi, G.H. Roshani, S.A.H. Feghhi, S. Setayeshi, E. Eftekhari Zadeh, A. Fatehi, Optimization of a method for identifying the flow regime and measuring void fraction in a broad beam gamma-ray attenuation technique, Int. J. Hydrogen Energy 41 (18) (2016) 7438–7444 Ilker Meric, Geir A. Johansen, J. Mattingly, R.P. Gardner, On the ill-conditioning of the multiphase flow measurement by prompt gamma-ray neutron activation analysis, Radiat. Phys. Chem. 95 (2014) 401–404 M.B. Holstad, G.A. Johansen, Produced water characterization by dual modality gamma-ray measurements, Meas. Sci. Technol. 16 (2005) 1007–1013 H.J. Nussbaumer, The fast Fourier transforms, in: Fast Fourier Transform and Convolution Algorithms, Springer, Berlin, Heidelberg, 1981, pp. 80–111 Ingrid Daubechies, The wavelet transform, time-frequency localization and signal analysis, IEEE Trans. Inf. Theor. 36 (5) (1990) 961–1005 Skander Soltani, On the use of the wavelet decomposition for time series prediction, Neurocomputing 48 (1–4) (2002) 267–277 M. Dorigo, C. Blum, Ant colony optimization theory: a survey, Theor. Comput. Sci. 344 (2–3) (2005) 243–278 S. Roshani, S. Roshani, Design of a compact LPF and a miniaturized Wilkinson power divider using aperiodic stubs with harmonic suppression for wireless applications, Wireless Network 26 (2) (2020 Feb) 1493–1501 M. Hookari, S. Roshani, S. Roshani, Design of a low pass filter using rhombus shaped resonators with an analyticallc equivalent circuit, Turk. J. Electr. Eng. Comput. Sci. 28 (2) (2020) 865–874 S. Roshani, J. Azizian, S. Roshani, M.B. Jamshidi, F. Parandin, Design of a miniaturized branch line microstrip coupler with a simple structure using artificial neural network, Frequenz 76 (5–6) (2022) 255–263 Mohammed A Awadallah, Mohammed Azmi Al-Betar, Asaju La’aro Bolaji, Emad Mahmoud Alsukhni, Hassan Al-Zoubi, Natural selection methods for artificial bee colony with new versions of onlooker bee, Soft Comput. 23 (5) (2018) Javid Salimi MohsenKhaleghi, Visar Farhangi, Mohammad Javad Moradi, Moses Karakouzian, Evaluating the behaviour of centrally perforated unreinforced masonry walls: applications of numerical analysis, machine learning, and stochastic methods, Ain Shams Eng. J. 13 (3) (May 2022) 101631 N. Moradi, M.H. Tavana, M.R. Habibi, M. Amiri, M.J. Moradi, V. Farhangi, Predicting the compressive strength of concrete containing binary supplementary cementitious material using machine learning approach, Materials 15 (2022) 5336, https://doi.org/10.3390/ma15155336 R. Hanus, M. Zych, A. Golijanek-Jędrzejczyk, Measurements of dispersed phase velocity in two-phase flows in pipelines using gamma-absorption technique and phase of the cross-spectral density function, Energies 15 (24) (2022) 9526, https:// doi.org/10.3390/en15249526 R. Hanus, M. Zych, A. Golijanek-Jędrzejczyk, Investigation of liquid–gas flow in a horizontal pipeline using gamma-ray technique and modified cross-correlation, Energies 15 (16) (2022) 5848, https://doi.org/10.3390/en15165848 A. Mayet, M. Hussain, Amorphous WNx metal for accelerometers and gyroscope, in: Proceedings of the MRS Fall Meeting, Boston, MA, USA, 2014 A. Mayet, A. Hussain, M. Hussain, Three-terminal nanoelectromechanical switch based on tungsten nitride—an amorphous metallic material, Nanotechnology 27 (2016) 035202 G.H. Roshani, R. Hanus, A. Khazaei, M. Zych, E. Nazemi, V. Mosorov, Density and velocity determination for single-phase flow based on radiotracer technique and neural networks, Flow Meas. Instrum. 61 (2018) 9–14 G.H. Roshani, E. Nazemi, M.M. Roshani, Intelligent recognition of gas-oil-water three-phase flow regime and determination of volume fraction using radial basis function, Flow Meas. Instrum. 54 (2017) 39–45 G.H. Roshani, S. Roshani, E. Nazemi, S. Roshani, Online measuring density of oil products in annular regime of gas-liquid two phase flows, Measurement 129 (2018) 296–301 E. Nazemi, S.A.H. Feghhi, G.H. Roshani, R.G. Peyvandi, S. Setayeshi, Precise void fraction measurement in two-phase flows independent of the flow regime using gamma-ray attenuation, Nucl. Eng. Technol. 48 (1) (2016) 64–71 A.G. Ivakhnenko, Polynomial theory of complex systems, IEEE Trans. Syst. Man Cybern. SMC-1 (4) (1971) 364e378 R. Gholipour Peyvandi, S.Z. Islami Rad, Application of artificial neural networks for the prediction of volume fraction using spectra of gamma rays backscattered by three-phase flows, The European Physical Journal Plus 132 (12) (2017) 1–8 G.H. Roshani, E. Nazemi, S.A.H. Feghhi, S. Setayeshi, Flow regime identification and void fraction prediction in two-phase flows based on gamma ray attenuation, Measurement 62 (2015) 25–32 A.M. Mayet, S.M. Alizadeh, Z.A. Kakarash, A.A. Al-Qahtani, A.K. Alanazi, H. H. Alhashimi, E. Nazemi, Introducing a precise system for determining volume percentages independent of scale thickness and type of flow regime, Mathematics 10 (10) (2022) 1770 T.C. Chen, S.M. Alizadeh, M.A. Albahar, M. Thanoon, A. Alammari, J.W. G. Guerrero, E. Eftekhari-Zadeh, Introducing the effective features using the Particle swarm optimization algorithm to increase accuracy in determining the volume percentages of three-phase flows, Processes 11 (1) (2023) 236 A.M. Iliyasu, D.K. Bagaudinovna, A.S. Salama, G.H. Roshani, K. Hirota, A methodology for analysis and prediction of volume fraction of two-phase flow using Particle swarm optimization and group method of data handling neural network, Mathematics 11 (4) (2023) 916 |
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Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)© 2024 Korean Nuclear Societyhttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Mayet, Abdulilah MohammadIlyinichna, Evgeniya GorelkinaAlShaqsi, JamilParayangat, MuneerGrimaldo Guerrero, John Williamvirtual::1159-1Raja, M. RamkumarMuqeet, Mohammed AbdulMohammed, Salman Arafath2025-05-07T21:47:22Z2025-05-07T21:47:22Z2024-11Abdulilah Mohammad Mayet, Evgeniya Ilyinichna Gorelkina, Jamil AlShaqsi, Muneer Parayangat, John William Grimaldo Guerrero, M. Ramkumar Raja, Mohammed Abdul Muqeet, Salman Arafath Mohammed, Improvement in measurement of radiation ased two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDH, Nuclear Engineering and Technology, Volume 56, issue 11, 2024, Pages 4826-4836, ISSN 1738-5733, https://doi.org/10.1016/j.net.2024.06.046. (https://www.sciencedirect.com/science/article/pii/S1738573324003061)1738-5733https://hdl.handle.net/11323/1420810.1016/j.net.2024.06.046Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The formation of scales in pipes is one element that has a major impact on the efficiency of machinery used in the oil and gas sector. With the help of artificial intelligence, this new, non-invasive device was able to figure out the volume fraction of a two-phase flow by taking into account the thickness of the scale in the tested pipeline. The proposed design uses an isotope pair of barium-133 and cesium-137 as a dual-energy gamma generator. One detector records photons that are transmitted, and another detector records photons that are scattered. The signals from the detectors were simulated using the Monte Carlo N-Particle (MCNP) code, and then ten frequency and wavelet characteristics were extracted. To choose the best inputs from the collected features for computing the volume fraction, an ant colony optimization (ACO)-based method is applied. Six attributes, representing the optimal combination, were developed using this method. In order to forecast the volume percentage of two-phase flows independently of flow regime and scale thickness, we fed the characteristics introduced by ACO into a group method of data handling (GMDH) neural network. Volume fraction calculations had a maximum RMSE of 0.056, which is quite little compared to previous research. By using the ACO to choose the best characteristics, the current work has significantly increased its accuracy in identifying volume fractions11 páginasapplication/pdfengKorean Nuclear SocietySouth Koreahttps://www.sciencedirect.com/science/article/pii/S1738573324003061?via%3DihubImprovement in measurement of radiation based two-phase flowmeters independent of flow regime and scale thickness using ant colony optimization and GMDHArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Nuclear Engineering and TechnologyA. Bahadori, G. Zahedi, S. Zendehboudi, Estimation of potential barium sulfate (barite) precipitation in oilfield brines using a simple predictive tool, Environ. Prog. Sustain. Energy 32 (2013) 860–865A.B. BinMerdhah, Inhibition of barium sulfate scale at high-barium formation water, J. Pet. Sci. Eng. 90 (2012) 124–130M. Roshani, M.A. Sattari, P.J. Ali, G.H. Roshani, B. Nazemi, E. Corniani, E. Nazemi, Application of GMDH neural network technique to improve measuring precision of a simplified photon attenuation based two-phase flowmeter, Flow Meas. Instrum. 75 (2020) 101804M.A. Sattari, G.H. Roshani, R. Hanus, E. Nazemi, Applicability of time-domain feature extraction methods and artificial intelligence in two-phase flow meters based on gamma-ray absorption technique, Measurement 168 (2021) 108474, https://doi.org/10.1016/j.measurement.2020.108474M.A. Sattari, G.H. Roshani, R. Hanus, Improving the structure of two-phase flow meter using feature extraction and GMDH neural network, Radiat. Phys. Chem. 171 (2020 Jun 1) 108725S. Hosseini, G.H. Roshani, S. Setayeshi, Precise gamma based two-phase flow meter using frequency feature extraction and only one detector, Flow Meas. Instrum. 72 (2020 Apr 1) 101693S. Hosseini, O. Taylan, M. Abusurrah, T. Akilan, E. Nazemi, E. Eftekhari-Zadeh, F. Bano, G.H. Roshani, Application of wavelet feature extraction and artificial neural networks for improving the performance of gas–liquid two-phase flow meters used in oil and petrochemical industries, Polymers 13 (21) (2021) 3647A. Basahel, M.A. Sattari, O. Taylan, E. Nazemi, Application of feature extraction and artificial intelligence techniques for increasing the accuracy of X-ray radiation based two phase flow meter, Mathematics 9 (11) (2021 Jan) 1227O. Taylan, M.A. Sattari, I. Elhachfi Essoussi, E. Nazemi, Frequency domain feature extraction investigation to increase the accuracy of an intelligent nondestructive system for volume fraction and regime determination of gas-water-oil three-phase flows, Mathematics 9 (17) (2021 Jan) 2091M. Balubaid, M.A. Sattari, O. Taylan, A.A. Bakhsh, E. 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Hirota, A methodology for analysis and prediction of volume fraction of two-phase flow using Particle swarm optimization and group method of data handling neural network, Mathematics 11 (4) (2023) 916483648261156Dual-energy gamma sourceGroup method of data handlingScale thicknessTwo phase-flowsAnt colony optimizationPublication0740e604-f463-4dac-a31e-50b826562598virtual::1159-10740e604-f463-4dac-a31e-50b826562598virtual::1159-10000-0002-1632-5374virtual::1159-1ORIGINAL1-s2.0-S1738573324003061-main.pdf1-s2.0-S1738573324003061-main.pdfapplication/pdf8783873https://repositorio.cuc.edu.co/bitstreams/4b802404-1cba-4ffc-88a7-ea2475a6c655/download36396082b121168db1fb0ec5522e0960MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-815543https://repositorio.cuc.edu.co/bitstreams/a1474509-8aa5-43b8-aaff-9bb6d6ee6f9e/download73a5432e0b76442b22b026844140d683MD52TEXT1-s2.0-S1738573324003061-main.pdf.txt1-s2.0-S1738573324003061-main.pdf.txtExtracted 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ara ejercer estos derechos sobre la Obra tal y como se indica a continuación:</p>
    <ol type="a">
      <li>Reproducir la Obra, incorporar la Obra en una o más Obras Colectivas, y reproducir la Obra incorporada en las Obras Colectivas.</li>
      <li>Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.</li>
      <li>Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.</li>
    </ol>
    <p>Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).</p>
  </li>
  <br/>
  <li>
    Restricciones.
    <p>La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:</p>
    <ol type="a">
      <li>Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).</li>
      <li>Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.</li>
      <li>Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.</li>
      <li>
        Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:
        <ol type="i">
          <li>Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.</li>
          <li>Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
        </ol>
      </li>
      <li>Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
    </ol>
  </li>
  <br/>
  <li>
    Representaciones, Garantías y Limitaciones de Responsabilidad.
    <p>A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Limitación de responsabilidad.
    <p>A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Término.
    <ol type="a">
      <li>Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.</li>
      <li>Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.</li>
    </ol>
  </li>
  <br/>
  <li>
    Varios.
    <ol type="a">
      <li>Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.</li>
      <li>Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.</li>
      <li>Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.</li>
      <li>Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.</li>
    </ol>
  </li>
  <br/>
</ol>
 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