ESTUDO COMPARATIVO ENTRE OS MODELOS STORM WATER MANAGEMENT E REDES NEURAIS ARTIFICIAIS NA AVALIAÇÃO DO DESEMPENHO DE TRINCHEIRA DE INFILTRAÇÃO

Autores

  • Ricardo Reis
  • Marina Ilha

DOI:

https://doi.org/10.46421/entac.v17i1.1777

Palavras-chave:

Infiltration Trench, Low Impact Development (LID), SWMM 5.1, ANN model, stormwater infiltration

Resumo

Stormwater infiltration systems applied to the lots gain importance as compensatory practices of runoff management. In this research two models were compared for the performance evaluation of an experimental infiltration trench built in Campinas, São Paulo, Brazil. In order to do so, the Storm Water Management Model 5.1 (SWMM)was compared to an Artificial Neural Networks (ANN) model developed through experimental area monitoring data. Two design rainfalls were tested: one of 52 mm/h and 30 min of duration, and other of 192 mm/h and 8 min of duration, whose volumes were discharged into infiltration trench, with cross section of 0,6 x 0,6 m and length of 5,0 m, filled with crushed stone. The hydraulic profiles simulated by SWMM 5.1 and ANN model were compared with experimental data. The ANN model was better adjusted to the observed performance data, resulting in design volumes between 0.5% and 0.75% higher than those observed for design rains. The SWMM model presented values between 32.7% and 41.1% higher than those observed. In terms of constructive cost, the ANNsized system would result in savings of 24% to 28.8% higher than SWMM-sized systems.

Referências

ABGE - ASSOCIAÇÃO BRASILEIRA DE GEOLOGIA DE ENGENHARIA. Ensaios dePermeabilidade em Solos: orientações para sua execução no campo:procedimentos. ABGE, Boletim nº. 4, São Paulo. 1996.

ASTM STANDARD D2487. Standard practice for classification of soils for engineeringpurposes (Unified Soil Classification System). American Society for Testing MaterialsInternational. West Conshohocken, PA. 2011.

DAVIS, A. P.; TRAVER, R. G.; HUNT, W. F.; LEE R.; BROWN, R. A.; OLSZEWSKI, J. M.

Hydrologic Performance of Bioretention Storm-Water Control Measures. Journal ofHydrologic Engineering. ASCE American Society of Civil Engineers. Vol. 17. p.p. 604-614. 2012.

EPA UNITED STATES ENVIRONMENTAL PROTECTION AGENCY. (2017) Storm WaterManagement Model (SWMM). Disponível em: < https://www.epa.gov/waterresearch/storm-water-management-model-swmm> Acessado em 20 de março de2018.

FRENI, Gabriele; MANNINA, Giorgio; VIVIANI Gaspare. Stormwater infiltration trenches:a conceptual modelling approach. Water Science & Technology. IWA Publishing.2009. 185-199p.

LI, Yanling; BABCOCK Jr. Roger W. Green roof hydrologic performance and modeling:a review. Water Science & Technology. IWA Publishing. V. 69, n. 4, p. 727-738. 2014.

MENEZES FILHO, Frederico Carlos Martins; TUCCI, Carlos Eduardo Morelli. Alteraçãona relação entre densidade habitacional x área impermeável: Porto Alegre RS.

Rega Revista de gestão de Água da América Latina. ABRH Associação Brasileirade recursos Hídricos. Vol. 9, nº. 1. 49-55p. 2012.

RADFAR, Ata; ROCKAWAY, Thomas Doan. Neural Networks Models for CapturedRunoff Prediction of Permeable Interlocking Concrete Pavements. In: WORLDENVIRONMENTAL AND WATER RESOURCES CONGRESS 2015: FLOODS, DROUGHTS, ANDECOSYSTEMS. ASCE - American Society of Civil Engineers. Austin, Texas, USA. 17 a 21de maio de 2015.

REIS, Ricardo. P. A.; ILHA, Marina S. O.; TEIXEIRA, P. C. Sistemas prediais de infiltraçãode água de chuva: aplicações, limitações e perspectivas. [REEC] Revista Eletrônicade Engenharia Civil. v.7, n.3. DOI. 10.5216/reec.v7i3.27672. 13 p. 2013.

RIEGER, Wolfgang; DISSE, Markus. A physically-based model approach to assess theeffectiveness of single and combined measures of decentralized floodprotection. Hydrologie und Wasserbewirtschaftung, v. 57, n. 1, p. 14-25, 2013.

TUCCI. Carlos Eduardo Morelli. Coeficiente de escoamento e vazão máxima debacias urbanas. RBRH - Revista Brasileira de Recursos Hídricos, Vol. 5, n. 1, Jan/mar.61-68p. 2000.

ZHANG, Shouhong; GUO, Yiping. SWMM simulation of the storm water volume controlperformance of permeable pavement systems. Journal of Hydrologic Engineering, v.20, n. 8, p. 06014010, 2014.

ZUFFO, A. C.; LEME, P. E. GRADEX e Santa Barbara: método híbrido para cálculo devazão de projeto para macrodrenagem urbana. In: SIMPÓSIO BRASILEIRO DERECURSOS HÍDRICOS, 16., João Pessoa, 2005. Anais... João Pessoa, 2005.

Downloads

Publicado

2018-11-12

Como Citar

REIS, Ricardo; ILHA, Marina. ESTUDO COMPARATIVO ENTRE OS MODELOS STORM WATER MANAGEMENT E REDES NEURAIS ARTIFICIAIS NA AVALIAÇÃO DO DESEMPENHO DE TRINCHEIRA DE INFILTRAÇÃO. In: ENCONTRO NACIONAL DE TECNOLOGIA DO AMBIENTE CONSTRUÍDO, 17., 2018. Anais [...]. Porto Alegre: ANTAC, 2018. p. 3468–3474. DOI: 10.46421/entac.v17i1.1777. Disponível em: https://eventos.antac.org.br/index.php/entac/article/view/1777. Acesso em: 22 nov. 2024.

Artigos Semelhantes

<< < 20 21 22 23 24 25 26 27 28 29 > >> 

Você também pode iniciar uma pesquisa avançada por similaridade para este artigo.