Evidence map›Paper›PMID 37819948›Full record

ArticlePloS one2023

Advanced monitoring and numerical modelling of the stability, safety and reliability indicators of the earthen dam of Songloulou (Cameroon).

Zoa Ambassa, Jean Chills Amba, Merlin Bodol Momha, Landry Djopkop Kouanang, Robert Nzengwa, Pascal Adrien Mbongo

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Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zoa AmbassaLaboratory of Energy Modelling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon.ORCID 0000-0002-0359-695X
Jean Chills AmbaLaboratory of Energy Modelling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon.
Merlin Bodol MomhaLaboratory of Energy Modelling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon.
Landry Djopkop KouanangLaboratory of Energy Modelling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon.
Robert NzengwaLaboratory of Energy Modelling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon.
Pascal Adrien MbongoThe Energy of Cameroon (ENEO), Douala, Cameroon.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For the determination of global stability after long term advanced monitoring, artificial intelligence have been used for the data analysis of water level and displacements of Songloulou earth dam at Cameroon. Measurements of safety and reliability indicators follow changes set by piezometric and pendulums measurements. The results obtained from the artificial intelligence on the base of many years recording data have confirmed the relevance and robustness of this model. The ANFIS model combining the concept of neural network and fuzzy logic was used to simulate the behaviour of piezometers and pendulums in the dam. This model has provided satisfactory results, given in the large amount of data to be processed. The water level evolution is modelled using the ANFIS function integrated in the MATLAB software and the result is compared to that obtained by the HST method. Afterwards, the state of stress on the structure and stability of the slope at shear have been assessed based on the hydro mechanical behaviour using the GEOSTUDIO Finite Element computation software. The input parameters are: the head of water recorded in the piezometers and geotechnical parameters of the dam. The modelling results in terms of displacement are accurately consistent with the displacement measurements. The horizontal displacement of pendulums obtained by GEOSTUDIO is 80 mm and those measured directly of the pendulums have 70 mm of average value. The safety factor for slope stability according to 530 m water level is 1.5.

Indexed as

Artificial IntelligenceNeural Networks, ComputerCameroonFuzzy LogicReproducibility of ResultsWaterWater

Identifiers

PMID37819948
PMCPMC10566693

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.