An intelligent approach to determine component volume percentages in a symmetrical homogeneous three-phase fluid in scaled pipe conditions

Over time, the accumulation of scale within the transmission pipeline results in a decrease in the internal diameter of the pipe, leading to a decline in efficiency and energy waste. The employment of a gamma ray attenuation system that is non-invasive has been found to be a highly precise diagnosti...

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Autores:
Mohammad Mayet, Abdulilah
Mehdi Alizadeh, Seyed
Thafasal Ijyas, V. P.
Grimaldo Guerrero, John William
Kumar Shukla, Neeraj
Khan Bhutto, Javed
Eftekhari-Zadeh, Ehsan
Aiesh Qaisi, Mohammed
Tipo de recurso:
Article of investigation
Fecha de publicación:
2023
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/13403
Acceso en línea:
https://hdl.handle.net/11323/13403
https://repositorio.cuc.edu.co/
Palabra clave:
Three-phase
Symmetrical homogenous flow
Volumetric percentage
MLP neural network
Scale thickness independent
Rights
openAccess
License
Atribución 4.0 Internacional (CC BY 4.0)
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oai_identifier_str oai:repositorio.cuc.edu.co:11323/13403
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.eng.fl_str_mv An intelligent approach to determine component volume percentages in a symmetrical homogeneous three-phase fluid in scaled pipe conditions
title An intelligent approach to determine component volume percentages in a symmetrical homogeneous three-phase fluid in scaled pipe conditions
spellingShingle An intelligent approach to determine component volume percentages in a symmetrical homogeneous three-phase fluid in scaled pipe conditions
Three-phase
Symmetrical homogenous flow
Volumetric percentage
MLP neural network
Scale thickness independent
title_short An intelligent approach to determine component volume percentages in a symmetrical homogeneous three-phase fluid in scaled pipe conditions
title_full An intelligent approach to determine component volume percentages in a symmetrical homogeneous three-phase fluid in scaled pipe conditions
title_fullStr An intelligent approach to determine component volume percentages in a symmetrical homogeneous three-phase fluid in scaled pipe conditions
title_full_unstemmed An intelligent approach to determine component volume percentages in a symmetrical homogeneous three-phase fluid in scaled pipe conditions
title_sort An intelligent approach to determine component volume percentages in a symmetrical homogeneous three-phase fluid in scaled pipe conditions
dc.creator.fl_str_mv Mohammad Mayet, Abdulilah
Mehdi Alizadeh, Seyed
Thafasal Ijyas, V. P.
Grimaldo Guerrero, John William
Kumar Shukla, Neeraj
Khan Bhutto, Javed
Eftekhari-Zadeh, Ehsan
Aiesh Qaisi, Mohammed
dc.contributor.author.none.fl_str_mv Mohammad Mayet, Abdulilah
Mehdi Alizadeh, Seyed
Thafasal Ijyas, V. P.
Grimaldo Guerrero, John William
Kumar Shukla, Neeraj
Khan Bhutto, Javed
Eftekhari-Zadeh, Ehsan
Aiesh Qaisi, Mohammed
dc.subject.proposal.eng.fl_str_mv Three-phase
Symmetrical homogenous flow
Volumetric percentage
MLP neural network
Scale thickness independent
topic Three-phase
Symmetrical homogenous flow
Volumetric percentage
MLP neural network
Scale thickness independent
description Over time, the accumulation of scale within the transmission pipeline results in a decrease in the internal diameter of the pipe, leading to a decline in efficiency and energy waste. The employment of a gamma ray attenuation system that is non-invasive has been found to be a highly precise diagnostic technique for identifying volumetric percentages across various states. The most appropriate setup for simulating a volume percentage detection system through Monte Carlo N particle (MCNP) simulations involves a system consisting of two NaI detectors and dual-energy gamma sources, namely 241Am and 133Ba radioisotopes. A three-phase flow consisting of oil, water, and gas exhibits symmetrical homogenous flow characteristics across varying volume percentages as it traverses through scaled pipes of varying thicknesses. It is worth mentioning that there is an axial symmetry of flow inside the pipe that creates a homogenous flow pattern. In this study, the experiment involved the emission of gamma rays from one end of a pipe, with photons being absorbed by two detectors located at the other end. The resulting data included three distinct features, namely the counts under the photopeaks of 241Am and 133Ba from the first detector as well as the total count from the second detector. Through the implementation of a two-output MLP neural network utilising the aforementioned inputs, it is possible to accurately forecast the volumetric percentages with an RMSE of under 1.22, regardless of the thickness of the scale. The minimal error value ensures the efficacy of the proposed technique and the practicality of its implementation in the domains of petroleum and petrochemicals.
publishDate 2023
dc.date.issued.none.fl_str_mv 2023-03-23
dc.date.accessioned.none.fl_str_mv 2024-09-26T21:58:58Z
dc.date.available.none.fl_str_mv 2024-09-26T21:58:58Z
dc.type.none.fl_str_mv Artículo de revista
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dc.type.content.none.fl_str_mv Text
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/article
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dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.citation.none.fl_str_mv Mayet, A.M.; Alizadeh, S.M.; Ijyas, V.P.T.; Grimaldo Guerrero, J.W.; Shukla, N.K.; Bhutto, J.K.; Eftekhari-Zadeh, E.; Aiesh Qaisi, R.M. An Intelligent Approach to Determine Component Volume Percentages in a Symmetrical Homogeneous Three-Phase Fluid in Scaled Pipe Conditions. Symmetry 2023, 15, 1131. https://doi.org/ 10.3390/sym15061131
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/11323/13403
dc.identifier.doi.none.fl_str_mv 10.3390/sym15061131
dc.identifier.eissn.none.fl_str_mv 2073-8994
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 Mayet, A.M.; Alizadeh, S.M.; Ijyas, V.P.T.; Grimaldo Guerrero, J.W.; Shukla, N.K.; Bhutto, J.K.; Eftekhari-Zadeh, E.; Aiesh Qaisi, R.M. An Intelligent Approach to Determine Component Volume Percentages in a Symmetrical Homogeneous Three-Phase Fluid in Scaled Pipe Conditions. Symmetry 2023, 15, 1131. https://doi.org/ 10.3390/sym15061131
10.3390/sym15061131
2073-8994
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/13403
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartofjournal.none.fl_str_mv Symmetry
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2. Roshani, M.; Phan, G.; Roshani, G.H.; Hanus, R.; Nazemi, B.; Corniani, E.; Nazemi, E. 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 2021, 168, 108427.
3. Roshani, G.H.; Nazemi, E.; Feghhi, S.A.H. Investigation of using 60Co source and one detector for determining the flow regime and void fraction in gas–liquid two-phase flows. Flow Meas. Instrum. 2016, 50, 73–79.
4. Roshani, G.H.; Karami, A.; Nazemi, E. An intelligent integrated approach of Jaya optimization algorithm and neuro-fuzzy network to model the stratified three-phase flow of gas–oil–water. Comput. Appl. Math. 2019, 38, 5.
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6. Sattari, M.A.; Roshani, G.H.; Hanus, R. Improving the structure of two-phase flow meter using feature extraction and GMDH neural network. Radiat. Phys. Chem. 2020, 171, 108725.
7. Alamoudi, M.; Sattari, M.A.; Balubaid, M.; Eftekhari-Zadeh, E.; Nazemi, E.; Taylan, O.; Kalmoun, E.M. 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 2021, 13, 1198.
8. Taylan, O.; Abusurrah, M.; Amiri, S.; Nazemi, E.; Eftekhari-Zadeh, E.; Roshani, G.H. Proposing an Intelligent Dual-Energy Radiation-Based System for Metering Scale Layer Thickness in Oil Pipelines Containing an Annular Regime of Three-Phase Flow. Mathematics 2021, 9, 2391.
9. Basahel, A.; Sattari, M.A.; Taylan, O.; Nazemi, E. Application of Feature Extraction and Artificial Intelligence Techniques for Increasing the Accuracy of X-ray Radiation Based Two Phase Flow Meter. Mathematics 2021, 9, 1227.
10. Taylan, O.; Sattari, M.A.; Elhachfi Essoussi, I.; Nazemi, E. 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 2021, 9, 2091.
11. Roshani, G.H.; Ali, P.J.M.; Mohammed, S.; Hanus, R.; Abdulkareem, L.; Alanezi, A.A.; Kalmoun, E.M. Simulation Study of Utilizing X-ray Tube in Monitoring Systems of Liquid Petroleum Products. Processes 2021, 9, 828.
12. Balubaid, M.; Sattari, M.A.; Taylan, O.; Bakhsh, A.A.; Nazemi, E. Applications of Discrete Wavelet Transform for Feature Extraction to Increase the Accuracy of Monitoring Systems of Liquid Petroleum Products. Mathematics 2021, 9, 3215.
13. Hosseini, S.; Taylan, O.; Abusurrah, M.; Akilan, T.; Nazemi, E.; Eftekhari-Zadeh, E.; Roshani, G.H. 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 2021, 13, 3647.
14. Sattari, M.A.; Korani, N.; Hanus, R.; Roshani, G.H.; Nazemi, E. Improving the performance of gamma radiation based two phase flow meters using optimal time characteristics of the detector output signal extraction. J. Nucl. Sci. Technol. (JonSat) 2020, 41, 42–54.
15. Iliyasu, A.M.; Mayet, A.M.; Hanus, R.; El-Latif, A.A.A.; Salama, A.S. Employing GMDH-Type Neural Network and Signal Frequency Feature Extraction Approaches for Detection of Scale Thickness inside Oil Pipelines. Energies 2022, 15, 4500.
16. Mayet, A.M.; Salama, A.S.; Alizadeh, S.M.; Nesic, S.; Guerrero, J.W.G.; Eftekhari-Zadeh, E.; Nazemi, E.; Iliyasu, A.M. Applying Data Mining and Artificial Intelligence Techniques for High Precision Measuring of the Two-Phase Flow’s Characteristics Independent of the Pipe’s Scale Layer. Electronics 2022, 11, 459.
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20. Roshani, S.; Azizian, J.; Roshani, S.; Jamshidi, M.B.; Parandin, F. Design of a miniaturized branch line microstrip coupler with a simple structure using artificial neural network. Frequenz 2022, 76, 255–263.
21. Lalbakhsh, A.; Mohamadpour, G.; Roshani, S.; Ami, M.; Roshani, S.; Sayem, A.S.; Alibakhshikenari, M.; Koziel, S. Design of a Compact Planar Transmission Line for Miniaturized Rat-Race Coupler with Harmonics Suppression; IEEE Access: Piscataway, NJ, USA, 2021; Volume 9, pp. 129207–129217.
22. Khaleghi, M.; Salimi, J.; Farhangi, V.; Moradi, M.J.; Karakouzian, M. Evaluating the behaviour of centrally perforated unreinforced masonry walls: Applications of numerical analysis, machine learning, and stochastic methods. Ain Shams Eng. J. 2022, 13, 101631.
23. Moradi, N.; Tavana, M.H.; Habibi, M.R.; Amiri, M.; Moradi, M.J.; Farhangi, V. Predicting the Compressive Strength of Concrete Containing Binary Supplementary Cementitious Material Using Machine Learning Approach. Materials 2022, 15, 5336.
24. Hanus, R.; Zych, M.; Golijanek-J ˛edrzejczyk, A. Measurements of Dispersed Phase Velocity in Two-Phase Flows in Pipelines Using Gamma-Absorption Technique and Phase of the Cross-Spectral Density Function. Energies 2022, 15, 9526.
25. Hanus, R.; Zych, M.; Golijanek-J ˛edrzejczyk, A. Investigation of liquid–gas flow in a horizontal pipeline using gamma-ray technique and modified cross-correlation. Energies 2022, 15, 5848.
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30. Roshani, G.H.; Roshani, S.; Nazemi, E.; Roshani, S. Online measuring density of oil products in annular regime of gas-liquid two phase flows. Measurement 2018, 129, 296–301.
31. Nazemi, E.; Feghhi, S.A.H.; Roshani, G.H.; Peyvandi, R.G.; Setayeshi, S. Precise void fraction measurement in two-phase flows independent of the flow regime using gamma-ray attenuation. Nucl. Eng. Technol. 2016, 48, 64–71.
32. Roshani, M.; Sattari, M.A.; Ali, P.J.M.; Roshani, G.H.; Nazemi, B.; Corniani, E.; Nazemi, E. Application of GMDH neural network technique to improve measuring precision of a simplified photon attenuation based two-phase flowmeter. Flow Meas. Instrum. 2020, 75, 101804.
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42. Roshani, M.; Ali, P.J.; Roshani, G.H.; Nazemi, B.; Corniani, E.; Phan, N.H.; Tran, H.N.; Nazemi, E. X-ray tube with artificial neural network model as a promising alternative for radioisotope source in radiation based two phase flowmeters. Appl. Radiat. Isot. 2020, 164, 109255.
43. Peyvandi, R.G.; Rad, S.I. Application of artificial neural networks for the prediction of volume fraction using spectra of gamma rays backscattered by three-phase flows. Eur. Phys. J. Plus 2017, 132, 511.
44. Roshani Gholam, H.; Nazemi Ehsan Shama Farzin, A.; Mohammad, I.; Salar, M. Designing a simple ra-diometric system to predict void fraction percentage independent of flow pattern using radial basis function. Metrol. Meas. Syst. 2018, 25, 347–358.
45. Mayet, A.M.; Chen, T.C.; Alizadeh, S.M.; Al-Qahtani, A.A.; Qaisi, R.M.A.; Alhashim, H.H.; Eftekhari-Zadeh, E. Application of Artificial Intelligence for Determining the Volume Percentages of a Stratified Regime’s Three-Phase Flow, Independent of the Oil Pipeline’s Scale Thickness. Processes 2022, 10, 1996.
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publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute (MDPI)
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spelling Atribución 4.0 Internacional (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Mohammad Mayet, AbdulilahMehdi Alizadeh, SeyedThafasal Ijyas, V. P.Grimaldo Guerrero, John WilliamKumar Shukla, NeerajKhan Bhutto, JavedEftekhari-Zadeh, EhsanAiesh Qaisi, Mohammed2024-09-26T21:58:58Z2024-09-26T21:58:58Z2023-03-23Mayet, A.M.; Alizadeh, S.M.; Ijyas, V.P.T.; Grimaldo Guerrero, J.W.; Shukla, N.K.; Bhutto, J.K.; Eftekhari-Zadeh, E.; Aiesh Qaisi, R.M. An Intelligent Approach to Determine Component Volume Percentages in a Symmetrical Homogeneous Three-Phase Fluid in Scaled Pipe Conditions. Symmetry 2023, 15, 1131. https://doi.org/ 10.3390/sym15061131https://hdl.handle.net/11323/1340310.3390/sym150611312073-8994Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Over time, the accumulation of scale within the transmission pipeline results in a decrease in the internal diameter of the pipe, leading to a decline in efficiency and energy waste. The employment of a gamma ray attenuation system that is non-invasive has been found to be a highly precise diagnostic technique for identifying volumetric percentages across various states. The most appropriate setup for simulating a volume percentage detection system through Monte Carlo N particle (MCNP) simulations involves a system consisting of two NaI detectors and dual-energy gamma sources, namely 241Am and 133Ba radioisotopes. A three-phase flow consisting of oil, water, and gas exhibits symmetrical homogenous flow characteristics across varying volume percentages as it traverses through scaled pipes of varying thicknesses. It is worth mentioning that there is an axial symmetry of flow inside the pipe that creates a homogenous flow pattern. In this study, the experiment involved the emission of gamma rays from one end of a pipe, with photons being absorbed by two detectors located at the other end. The resulting data included three distinct features, namely the counts under the photopeaks of 241Am and 133Ba from the first detector as well as the total count from the second detector. Through the implementation of a two-output MLP neural network utilising the aforementioned inputs, it is possible to accurately forecast the volumetric percentages with an RMSE of under 1.22, regardless of the thickness of the scale. The minimal error value ensures the efficacy of the proposed technique and the practicality of its implementation in the domains of petroleum and petrochemicals.14 páginasapplication/pdfengMultidisciplinary Digital Publishing Institute (MDPI)Switzerlandhttps://www.mdpi.com/2073-8994/15/6/1131An intelligent approach to determine component volume percentages in a symmetrical homogeneous three-phase fluid in scaled pipe conditionsArtículo 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_970fb48d4fbd8a85Symmetry1. Nazemi, E.; Roshani, G.H.; Feghhi, S.A.H.; Setayeshi, S.; Zadeh, E.E.; Fatehi, A. 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 2016, 41, 7438–7444.2. Roshani, M.; Phan, G.; Roshani, G.H.; Hanus, R.; Nazemi, B.; Corniani, E.; Nazemi, E. 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 2021, 168, 108427.3. Roshani, G.H.; Nazemi, E.; Feghhi, S.A.H. Investigation of using 60Co source and one detector for determining the flow regime and void fraction in gas–liquid two-phase flows. Flow Meas. Instrum. 2016, 50, 73–79.4. Roshani, G.H.; Karami, A.; Nazemi, E. An intelligent integrated approach of Jaya optimization algorithm and neuro-fuzzy network to model the stratified three-phase flow of gas–oil–water. Comput. Appl. Math. 2019, 38, 5.5. Sattari, M.A.; Roshani, G.H.; Hanus, R.; Nazemi, E. Applicability of time-domain feature extraction methods and artificial intelligence in two-phase flow meters based on gamma-ray absorption technique. Measurement 2021, 168, 108474.6. Sattari, M.A.; Roshani, G.H.; Hanus, R. Improving the structure of two-phase flow meter using feature extraction and GMDH neural network. Radiat. Phys. Chem. 2020, 171, 108725.7. Alamoudi, M.; Sattari, M.A.; Balubaid, M.; Eftekhari-Zadeh, E.; Nazemi, E.; Taylan, O.; Kalmoun, E.M. 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 2021, 13, 1198.8. Taylan, O.; Abusurrah, M.; Amiri, S.; Nazemi, E.; Eftekhari-Zadeh, E.; Roshani, G.H. Proposing an Intelligent Dual-Energy Radiation-Based System for Metering Scale Layer Thickness in Oil Pipelines Containing an Annular Regime of Three-Phase Flow. Mathematics 2021, 9, 2391.9. Basahel, A.; Sattari, M.A.; Taylan, O.; Nazemi, E. Application of Feature Extraction and Artificial Intelligence Techniques for Increasing the Accuracy of X-ray Radiation Based Two Phase Flow Meter. Mathematics 2021, 9, 1227.10. Taylan, O.; Sattari, M.A.; Elhachfi Essoussi, I.; Nazemi, E. 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 2021, 9, 2091.11. Roshani, G.H.; Ali, P.J.M.; Mohammed, S.; Hanus, R.; Abdulkareem, L.; Alanezi, A.A.; Kalmoun, E.M. Simulation Study of Utilizing X-ray Tube in Monitoring Systems of Liquid Petroleum Products. Processes 2021, 9, 828.12. Balubaid, M.; Sattari, M.A.; Taylan, O.; Bakhsh, A.A.; Nazemi, E. Applications of Discrete Wavelet Transform for Feature Extraction to Increase the Accuracy of Monitoring Systems of Liquid Petroleum Products. Mathematics 2021, 9, 3215.13. Hosseini, S.; Taylan, O.; Abusurrah, M.; Akilan, T.; Nazemi, E.; Eftekhari-Zadeh, E.; Roshani, G.H. 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Mathematics 2022, 10, 3544.141615Three-phaseSymmetrical homogenous flowVolumetric percentageMLP neural networkScale thickness independentPublicationORIGINALAn Intelligent Approach to Determine Component Volume Percentages in a Symmetrical Homogeneous Three-Phase Fluid in Scaled Pipe Conditions.pdfAn Intelligent Approach to Determine Component Volume Percentages in a Symmetrical Homogeneous Three-Phase Fluid in Scaled Pipe Conditions.pdfapplication/pdf3824992https://repositorio.cuc.edu.co/bitstreams/8dec7c4d-1fbd-46f3-b0cf-174c4de15339/downloada27960642faf89e81f0e648fb1dc1921MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-815543https://repositorio.cuc.edu.co/bitstreams/ad1f94a7-5742-41fa-96fb-0b6d62cd66df/download73a5432e0b76442b22b026844140d683MD52TEXTAn Intelligent Approach to Determine Component Volume Percentages in a Symmetrical Homogeneous Three-Phase Fluid in Scaled Pipe Conditions.pdf.txtAn Intelligent Approach to Determine Component Volume Percentages in a Symmetrical Homogeneous Three-Phase Fluid in Scaled Pipe Conditions.pdf.txtExtracted texttext/plain47205https://repositorio.cuc.edu.co/bitstreams/1edb4b66-ef01-4973-b29a-a6655fc19999/download8fcb289f755690acf1221392be99424fMD53THUMBNAILAn Intelligent Approach to Determine Component Volume Percentages in a Symmetrical Homogeneous Three-Phase Fluid in Scaled Pipe Conditions.pdf.jpgAn Intelligent Approach to Determine Component Volume Percentages in a Symmetrical Homogeneous Three-Phase Fluid in Scaled Pipe Conditions.pdf.jpgGenerated Thumbnailimage/jpeg15961https://repositorio.cuc.edu.co/bitstreams/2176e262-1248-454c-9e5a-17feafd0bd45/download7090cc5c97692b0a09871a5806750b1aMD5411323/13403oai:repositorio.cuc.edu.co:11323/134032024-09-27 03:00:20.162https://creativecommons.org/licenses/by/4.0/open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa 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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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