Stochastic simulation in reservoir sedimentation estimation: application in a PCH
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Anais da Academia Brasileira de Ciências (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000701707 |
Resumo: | Abstract In reservoir projects it is important to estimate when the accumulated sediments will start to interfere with their functions. However, predicting silting is difficult because the processes involved have some uncertainties. Thus, the study is not only deterministic, as currently performed, but also stochastic. Thus, the objective of this paper was to develop a stochastic method and evaluate its performance in estimating silting in reservoirs. The method has as originalities the fact of having coupled a deterministic model widely used in the area of Hydraulics to a stochastic one. Another originality was to validate the stochastic method developed from silting data obtained in the reduced model of a Small Hydroelectric Power Plant (SHP). Thus, it was observed that the real silting was always between the 1st and 3rd quartile of probability of the stochastic result. Thus, the main advantage of the stochastic model developed was to allow obtaining the probabilities of silted heights in the stretches of interest. In addition, the variability of the results in the simulations indicated the sections that may suffer greater silting. In this way, hydraulic structures can be better positioned. Preventive and corrective measures can also be better planned and executed. |
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Anais da Academia Brasileira de Ciências (Online) |
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Stochastic simulation in reservoir sedimentation estimation: application in a PCHHEC-RASnumerical modelingphysical modelingAR(1) modelAbstract In reservoir projects it is important to estimate when the accumulated sediments will start to interfere with their functions. However, predicting silting is difficult because the processes involved have some uncertainties. Thus, the study is not only deterministic, as currently performed, but also stochastic. Thus, the objective of this paper was to develop a stochastic method and evaluate its performance in estimating silting in reservoirs. The method has as originalities the fact of having coupled a deterministic model widely used in the area of Hydraulics to a stochastic one. Another originality was to validate the stochastic method developed from silting data obtained in the reduced model of a Small Hydroelectric Power Plant (SHP). Thus, it was observed that the real silting was always between the 1st and 3rd quartile of probability of the stochastic result. Thus, the main advantage of the stochastic model developed was to allow obtaining the probabilities of silted heights in the stretches of interest. In addition, the variability of the results in the simulations indicated the sections that may suffer greater silting. In this way, hydraulic structures can be better positioned. Preventive and corrective measures can also be better planned and executed.Academia Brasileira de Ciências2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000701707Anais da Academia Brasileira de Ciências v.94 suppl.3 2022reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202220211573info:eu-repo/semantics/openAccessTEIXEIRA,EMMANUEL K.C.COELHO,MÁRCIA MARIA L.P.PINTO,EBER JOSÉ A.RINCO,ALBERTO V.SALIBA,ALOYSIO P.M.eng2022-12-02T00:00:00Zoai:scielo:S0001-37652022000701707Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2022-12-02T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false |
dc.title.none.fl_str_mv |
Stochastic simulation in reservoir sedimentation estimation: application in a PCH |
title |
Stochastic simulation in reservoir sedimentation estimation: application in a PCH |
spellingShingle |
Stochastic simulation in reservoir sedimentation estimation: application in a PCH TEIXEIRA,EMMANUEL K.C. HEC-RAS numerical modeling physical modeling AR(1) model |
title_short |
Stochastic simulation in reservoir sedimentation estimation: application in a PCH |
title_full |
Stochastic simulation in reservoir sedimentation estimation: application in a PCH |
title_fullStr |
Stochastic simulation in reservoir sedimentation estimation: application in a PCH |
title_full_unstemmed |
Stochastic simulation in reservoir sedimentation estimation: application in a PCH |
title_sort |
Stochastic simulation in reservoir sedimentation estimation: application in a PCH |
author |
TEIXEIRA,EMMANUEL K.C. |
author_facet |
TEIXEIRA,EMMANUEL K.C. COELHO,MÁRCIA MARIA L.P. PINTO,EBER JOSÉ A. RINCO,ALBERTO V. SALIBA,ALOYSIO P.M. |
author_role |
author |
author2 |
COELHO,MÁRCIA MARIA L.P. PINTO,EBER JOSÉ A. RINCO,ALBERTO V. SALIBA,ALOYSIO P.M. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
TEIXEIRA,EMMANUEL K.C. COELHO,MÁRCIA MARIA L.P. PINTO,EBER JOSÉ A. RINCO,ALBERTO V. SALIBA,ALOYSIO P.M. |
dc.subject.por.fl_str_mv |
HEC-RAS numerical modeling physical modeling AR(1) model |
topic |
HEC-RAS numerical modeling physical modeling AR(1) model |
description |
Abstract In reservoir projects it is important to estimate when the accumulated sediments will start to interfere with their functions. However, predicting silting is difficult because the processes involved have some uncertainties. Thus, the study is not only deterministic, as currently performed, but also stochastic. Thus, the objective of this paper was to develop a stochastic method and evaluate its performance in estimating silting in reservoirs. The method has as originalities the fact of having coupled a deterministic model widely used in the area of Hydraulics to a stochastic one. Another originality was to validate the stochastic method developed from silting data obtained in the reduced model of a Small Hydroelectric Power Plant (SHP). Thus, it was observed that the real silting was always between the 1st and 3rd quartile of probability of the stochastic result. Thus, the main advantage of the stochastic model developed was to allow obtaining the probabilities of silted heights in the stretches of interest. In addition, the variability of the results in the simulations indicated the sections that may suffer greater silting. In this way, hydraulic structures can be better positioned. Preventive and corrective measures can also be better planned and executed. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000701707 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000701707 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0001-3765202220211573 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
dc.source.none.fl_str_mv |
Anais da Academia Brasileira de Ciências v.94 suppl.3 2022 reponame:Anais da Academia Brasileira de Ciências (Online) instname:Academia Brasileira de Ciências (ABC) instacron:ABC |
instname_str |
Academia Brasileira de Ciências (ABC) |
instacron_str |
ABC |
institution |
ABC |
reponame_str |
Anais da Academia Brasileira de Ciências (Online) |
collection |
Anais da Academia Brasileira de Ciências (Online) |
repository.name.fl_str_mv |
Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC) |
repository.mail.fl_str_mv |
||aabc@abc.org.br |
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1754302872885919744 |