Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements

Amba Jean Chills; Zoa Ambassa; Offolé Florence; Essola Dieudonné; Bodol Momha Merlin; Nzengwa Robert; Mbongo Pascal Adrien

doi:doi:10.11648/j.ajcbm.20220601.13

Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements

Amba Jean Chills, Zoa Ambassa, Offolé Florence, Essola Dieudonné, Bodol Momha Merlin, Nzengwa Robert, Mbongo Pascal Adrien

Published in American Journal of Construction and Building Materials (Volume 6, Issue 1)

Received: 27 April 2022 Accepted: 14 May 2022 Published: 26 May 2022

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Abstract

In this paper, we used artificial intelligence for the analysis of water level and displacements data from the Songloulou earth dam of Cameroon. Measurements of safety and reliability indicators follow changes dictated by several reversible and irreversible phenomena like piezometric and pendulums measurements. The results obtained over many years have confirmed the relevance and robustness of models using artificial intelligence. We have simulated the behavior model through piezometric and pendulum measurements of this dam more precisely the ANFIS (Adaptive Neural Fuzzy Inference System) model, which combines the concept of artificial neurons and that of fuzzy logic, has provided satisfactory results, given the large amount of data to be processed. The water level evolution is modeled using the ANFIS function integrated in the MATLAB software and we compare it with the HST (Hydrostatic Season Time) method. Afterwards, the stress state of the structure is evaluated based on the hydromechanical behavior using the PLAXIS Finite Element calculation code. In this case, the input parameters are: the hydraulic heads recorded on the piezometers and geotechnical parameters of the dam. The modeling results in terms of displacement are perfectly consistent with the displacement measurements. The horizontal displacement obtained in the model at the pendulums position is 80 mm and that of the pendulums is 70 mm of average value.

Published in	American Journal of Construction and Building Materials (Volume 6, Issue 1)
DOI	10.11648/j.ajcbm.20220601.13
Page(s)	17-42
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Earth Dam, Artificial Intelligence, Piezometers, Pendulums, ANFIS, HST, MATLAB, PLAXIS

References

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APA Style

Amba Jean Chills, Zoa Ambassa, Offolé Florence, Essola Dieudonné, Bodol Momha Merlin, et al. (2022). Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements. American Journal of Construction and Building Materials, 6(1), 17-42. https://doi.org/10.11648/j.ajcbm.20220601.13

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ACS Style

Amba Jean Chills; Zoa Ambassa; Offolé Florence; Essola Dieudonné; Bodol Momha Merlin, et al. Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements. Am. J. Constr. Build. Mater. 2022, 6(1), 17-42. doi: 10.11648/j.ajcbm.20220601.13

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AMA Style

Amba Jean Chills, Zoa Ambassa, Offolé Florence, Essola Dieudonné, Bodol Momha Merlin, et al. Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements. Am J Constr Build Mater. 2022;6(1):17-42. doi: 10.11648/j.ajcbm.20220601.13

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@article{10.11648/j.ajcbm.20220601.13,
  author = {Amba Jean Chills and Zoa Ambassa and Offolé Florence and Essola Dieudonné and Bodol Momha Merlin and Nzengwa Robert and Mbongo Pascal Adrien},
  title = {Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements},
  journal = {American Journal of Construction and Building Materials},
  volume = {6},
  number = {1},
  pages = {17-42},
  doi = {10.11648/j.ajcbm.20220601.13},
  url = {https://doi.org/10.11648/j.ajcbm.20220601.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcbm.20220601.13},
  abstract = {In this paper, we used artificial intelligence for the analysis of water level and displacements data from the Songloulou earth dam of Cameroon. Measurements of safety and reliability indicators follow changes dictated by several reversible and irreversible phenomena like piezometric and pendulums measurements. The results obtained over many years have confirmed the relevance and robustness of models using artificial intelligence. We have simulated the behavior model through piezometric and pendulum measurements of this dam more precisely the ANFIS (Adaptive Neural Fuzzy Inference System) model, which combines the concept of artificial neurons and that of fuzzy logic, has provided satisfactory results, given the large amount of data to be processed. The water level evolution is modeled using the ANFIS function integrated in the MATLAB software and we compare it with the HST (Hydrostatic Season Time) method. Afterwards, the stress state of the structure is evaluated based on the hydromechanical behavior using the PLAXIS Finite Element calculation code. In this case, the input parameters are: the hydraulic heads recorded on the piezometers and geotechnical parameters of the dam. The modeling results in terms of displacement are perfectly consistent with the displacement measurements. The horizontal displacement obtained in the model at the pendulums position is 80 mm and that of the pendulums is 70 mm of average value.},
 year = {2022}
}

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TY  - JOUR
T1  - Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements
AU  - Amba Jean Chills
AU  - Zoa Ambassa
AU  - Offolé Florence
AU  - Essola Dieudonné
AU  - Bodol Momha Merlin
AU  - Nzengwa Robert
AU  - Mbongo Pascal Adrien
Y1  - 2022/05/26
PY  - 2022
N1  - https://doi.org/10.11648/j.ajcbm.20220601.13
DO  - 10.11648/j.ajcbm.20220601.13
T2  - American Journal of Construction and Building Materials
JF  - American Journal of Construction and Building Materials
JO  - American Journal of Construction and Building Materials
SP  - 17
EP  - 42
PB  - Science Publishing Group
SN  - 2640-0057
UR  - https://doi.org/10.11648/j.ajcbm.20220601.13
AB  - In this paper, we used artificial intelligence for the analysis of water level and displacements data from the Songloulou earth dam of Cameroon. Measurements of safety and reliability indicators follow changes dictated by several reversible and irreversible phenomena like piezometric and pendulums measurements. The results obtained over many years have confirmed the relevance and robustness of models using artificial intelligence. We have simulated the behavior model through piezometric and pendulum measurements of this dam more precisely the ANFIS (Adaptive Neural Fuzzy Inference System) model, which combines the concept of artificial neurons and that of fuzzy logic, has provided satisfactory results, given the large amount of data to be processed. The water level evolution is modeled using the ANFIS function integrated in the MATLAB software and we compare it with the HST (Hydrostatic Season Time) method. Afterwards, the stress state of the structure is evaluated based on the hydromechanical behavior using the PLAXIS Finite Element calculation code. In this case, the input parameters are: the hydraulic heads recorded on the piezometers and geotechnical parameters of the dam. The modeling results in terms of displacement are perfectly consistent with the displacement measurements. The horizontal displacement obtained in the model at the pendulums position is 80 mm and that of the pendulums is 70 mm of average value.
VL  - 6
IS  - 1
ER  -

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Author Information

Amba Jean Chills

Laboratory of Energy Modeling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon
Zoa Ambassa

Laboratory of Energy Modeling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon
Offolé Florence

Laboratory of Energy Modeling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon
Essola Dieudonné

Laboratory of Energy Modeling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon
Bodol Momha Merlin

Laboratory of Energy Modeling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon
Nzengwa Robert

Laboratory of Energy Modeling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon
Mbongo Pascal Adrien

The Energy of Cameroon (ENEO), Douala, Cameroon

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APA Style

Amba Jean Chills, Zoa Ambassa, Offolé Florence, Essola Dieudonné, Bodol Momha Merlin, et al. (2022). Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements. American Journal of Construction and Building Materials, 6(1), 17-42. https://doi.org/10.11648/j.ajcbm.20220601.13

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ACS Style

Amba Jean Chills; Zoa Ambassa; Offolé Florence; Essola Dieudonné; Bodol Momha Merlin, et al. Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements. Am. J. Constr. Build. Mater. 2022, 6(1), 17-42. doi: 10.11648/j.ajcbm.20220601.13

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AMA Style

Amba Jean Chills, Zoa Ambassa, Offolé Florence, Essola Dieudonné, Bodol Momha Merlin, et al. Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements. Am J Constr Build Mater. 2022;6(1):17-42. doi: 10.11648/j.ajcbm.20220601.13

Copy | Download

@article{10.11648/j.ajcbm.20220601.13,
  author = {Amba Jean Chills and Zoa Ambassa and Offolé Florence and Essola Dieudonné and Bodol Momha Merlin and Nzengwa Robert and Mbongo Pascal Adrien},
  title = {Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements},
  journal = {American Journal of Construction and Building Materials},
  volume = {6},
  number = {1},
  pages = {17-42},
  doi = {10.11648/j.ajcbm.20220601.13},
  url = {https://doi.org/10.11648/j.ajcbm.20220601.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcbm.20220601.13},
  abstract = {In this paper, we used artificial intelligence for the analysis of water level and displacements data from the Songloulou earth dam of Cameroon. Measurements of safety and reliability indicators follow changes dictated by several reversible and irreversible phenomena like piezometric and pendulums measurements. The results obtained over many years have confirmed the relevance and robustness of models using artificial intelligence. We have simulated the behavior model through piezometric and pendulum measurements of this dam more precisely the ANFIS (Adaptive Neural Fuzzy Inference System) model, which combines the concept of artificial neurons and that of fuzzy logic, has provided satisfactory results, given the large amount of data to be processed. The water level evolution is modeled using the ANFIS function integrated in the MATLAB software and we compare it with the HST (Hydrostatic Season Time) method. Afterwards, the stress state of the structure is evaluated based on the hydromechanical behavior using the PLAXIS Finite Element calculation code. In this case, the input parameters are: the hydraulic heads recorded on the piezometers and geotechnical parameters of the dam. The modeling results in terms of displacement are perfectly consistent with the displacement measurements. The horizontal displacement obtained in the model at the pendulums position is 80 mm and that of the pendulums is 70 mm of average value.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Determination of Water Level on the Reservoir of the Earthen Dam of Songloulou Based on the Artificial Neural Network and Assessment of the Stress and Displacements
AU  - Amba Jean Chills
AU  - Zoa Ambassa
AU  - Offolé Florence
AU  - Essola Dieudonné
AU  - Bodol Momha Merlin
AU  - Nzengwa Robert
AU  - Mbongo Pascal Adrien
Y1  - 2022/05/26
PY  - 2022
N1  - https://doi.org/10.11648/j.ajcbm.20220601.13
DO  - 10.11648/j.ajcbm.20220601.13
T2  - American Journal of Construction and Building Materials
JF  - American Journal of Construction and Building Materials
JO  - American Journal of Construction and Building Materials
SP  - 17
EP  - 42
PB  - Science Publishing Group
SN  - 2640-0057
UR  - https://doi.org/10.11648/j.ajcbm.20220601.13
AB  - In this paper, we used artificial intelligence for the analysis of water level and displacements data from the Songloulou earth dam of Cameroon. Measurements of safety and reliability indicators follow changes dictated by several reversible and irreversible phenomena like piezometric and pendulums measurements. The results obtained over many years have confirmed the relevance and robustness of models using artificial intelligence. We have simulated the behavior model through piezometric and pendulum measurements of this dam more precisely the ANFIS (Adaptive Neural Fuzzy Inference System) model, which combines the concept of artificial neurons and that of fuzzy logic, has provided satisfactory results, given the large amount of data to be processed. The water level evolution is modeled using the ANFIS function integrated in the MATLAB software and we compare it with the HST (Hydrostatic Season Time) method. Afterwards, the stress state of the structure is evaluated based on the hydromechanical behavior using the PLAXIS Finite Element calculation code. In this case, the input parameters are: the hydraulic heads recorded on the piezometers and geotechnical parameters of the dam. The modeling results in terms of displacement are perfectly consistent with the displacement measurements. The horizontal displacement obtained in the model at the pendulums position is 80 mm and that of the pendulums is 70 mm of average value.
VL  - 6
IS  - 1
ER  -

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