APPLICABILITY OF VECTOR AUTOREGRESSIVE MODEL TO ESTIMATION OF INTERNAL MOISTURE CONDITION OF CONCRETE EXPOSED TO ORDINARY NATURAL ENVIRONMENT

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Abstract
To investigate the applicability of VAR-X model to estimating moisture condition of concrete exposed to ordinary natural environment, concrete internal humidity data reported previously were analyzed with weather data from Japan Meteorological Agency. The first 90 days were used for parameter estimation and the second 60 days were used to validate the model and predicted values. The results are summarized below. (1) Within the scope of this study, VAR-X model was applicable to the humidity data in the non-rainfall environment. VAR-X model was also able to predict the internal humidity for 60 days based on the estimated parameters and weather data (temperature and humidity), and the RMSE ranged from 0.87 to 2.04%. (2) It was judged that the VAR-X model was not appropriate to be applied to the humidity data of rainfall environment. The main reason for this is that the impact of rainfall was underestimated by assuming constant coefficients in the model. (3) The mechanisms of humidity fluctuation in concrete are discussed, which include the absorption and release of water and the temperature dependence of concrete water content. Based on the mechanism, difference between rainfall and non-rainfall environment was pointed out and the conditions under which the VAR-X model can be applied are discussed. (4) Methods of utilization and improvement of VAR-X model were discussed for cases where the moisture transfer characteristics of concrete changed and where the data increased or decreased in high humidity region. The advantages of time series analysis, including VAR-X model, were also pointed out in comparison with conventional physical models. VAR-X model can predict humidity fluctuations in concrete using weather data when certain conditions are met. In the future study, the model will be modified and its application to the durability evaluation of various materials will be investigated.