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Hickmann, Tásia; Teixeira Júnior, Luis Albino; Faria, Álvaro; Rodrigues, Samuel B.; Côrrea, Jairo M. and Garcia, Everton L.
(2018).
DOI: https://doi.org/10.5935/978-85-7042-010-7.2018B001
URL: https://poisson.com.br/2018/produto/metodos-quanti...
Abstract
This article describes a forecasting method, with the application of statistical models Auto-Regressive Integrated Moving Average (ARIMA) and a heat conduction model to forecast the temperature field in a buttress block of Itaipu dam. Monthly temperature series in 2010-2014 of surface thermometers to block were fitted with cubic splines and the series, now daily, were used as inputs for specific ARIMA models to produce forecasts as outputs. These outputs were used as boundary conditions to the thermal model of the block and this solved by the Finite Element Method (FEM). Obtained thus predicted temperature fields of block. The error MAPE between the values obtained by MEF and the real, in a test point, (where is an internal thermometer) measured the performance of the forecast of ARIMA models, and this was satisfactory, achieving near 15%. The proposed method has an innovative character for thermal analysis structures, in particular in concrete dams.