A Simplified Method for Real-Time Prediction of Temperature in Mass Concrete at Early Age

An, Guo; Yang, Ning; Li, Qingbin; Hu, Yu; Yang, Haijun

doi:10.3390/app10134451

Cited by 9 publications

(5 citation statements)

References 31 publications

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“…Statistical analyses-such as data regression [37][38][39][40] and autoregressive integrated moving average (ARIMA) [41] of historical monitoring data can be used to develop bestfit models (i.e., equations or formulas) for predicting concrete temperature changes in similar scenarios. This simple and rapid method is widely used in dams [37] , bridges [38,40] , and other concrete structures. For periodic temperature prediction, the ARIMA can also be used to develop prediction models [41] .…”

Section: Prediction Methodsmentioning

confidence: 99%

An ANN-Based Short-Term Temperature Forecast Model for Mass Concrete Cooling Control

Lin

Chen

et al. 2023

Tsinghua Sci. Technol.

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Concrete temperature control during dam construction (e.g., concrete placement and curing) is important for cracking prevention. In this study, a short-term temperature forecast model for mass concrete cooling control is developed using artificial neural networks (ANN). The development workflow for the forecast model consists of data integration, data preprocessing, model construction, and model application. More than 80 000 monitoring samples are collected by the developed intelligent cooling control system in the Baihetan Arch Dam, which is the largest hydropower project in the world under construction. Machine learning algorithms, including ANN, support vector machines, long short-term memory networks, and decision tree structures, are compared in temperature prediction, and the ANN is determined to be the best for the forecast model. Furthermore, an ANN framework with two hidden layers is determined to forecast concrete temperature at intervals of one day. The root mean square error of the forecast precision is 0.15 ı C on average. The application on concrete blocks verifies that the developed ANN-based forecast model can be used for intelligent cooling control during mass concrete construction.

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Section: Prediction Methodsmentioning

confidence: 99%

An ANN-Based Short-Term Temperature Forecast Model for Mass Concrete Cooling Control

Lin

Chen

et al. 2023

Tsinghua Sci. Technol.

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“…During the construction period, the temperature field of the dam body is affected by multiple factors, such as cement hydration heat, artificial cooling, and ambient temperature. In the stage of operation, cement hydration heat has basically dissipated, and the temperature field is affected by ambient temperature, e.g., air temperature and water temperature [43][44][45][46]. Concrete temperature has a significant impact on the stability of the dam during the construction period, but its effects during regular operation afterward are essentially insignificant.…”

Section: Tfe Constructionmentioning

confidence: 99%

Research on Temperature Control Index for High Concrete Dams Based on Information Entropy and Cloud Model from the View of Spatial Field

Yang,

Sun,

Zhang

et al. 2023

Water

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It is significant to adopt scientific temperature control criteria for high concrete dams in the construction period according to practical experience and theoretical calculation. This work synthetically uses information entropy and a cloud model and develops novel in situ observation data-based temperature control indexes from the view of a spatial field. The order degree and the disorder degree of observation values are defined according to the probability principle. Information entropy and weight parameters are combined to describe the distribution characteristics of the temperature field. Weight parameters are optimized via projection pursuit analysis (PPA), and then temperature field entropy (TFE) is constructed. Based on the above work, multi-level temperature control indexes are set up via a cloud model. Finally, a case study is conducted to verify the performance of the proposed method. According to the calculation results, the change law of TFEs agrees with actual situations, indicating that the established TFE is reasonable, the application conditions of the cloud model are wider than those of the typical small probability method, and the determined temperature control indexes improve the safety management level of high concrete dams. Research results offer scientific reference and technical support for temperature control standards adopted at other similar projects.

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“…The results showed that: the prediction of temperature distribution in concrete by the three-dimensional model was relatively accurate, with an error of less than 4%; the surface temperature difference in July was twice as much as that in December; the wind speed had a cooling effect on the surface of the concrete, and the larger the wind speed was, the stronger the cooling effect was. Guo An [25] et al analyzed the on-site temperature monitoring data collected by the engineering examples, and obtained an empirical formula for calculating the cooling effect of the concrete, by combining The results of measured data and empirical formula was compared and analyzed, and it was found that the empirical formula had better calculation effect, and the equation of the rate of temperature rise of the heat of hydration was derived. LiBao Yui [26] et al, in order to predict the trend of temperature change of mass concrete, constructed a CART prediction model based on the technology of large-data processing, and the results of the study showed that the model and the method can predict the temperature change of the mass concrete better, and the prediction accuracy is higher, and can be used for practical purposes.…”

Section: Introductionmentioning

confidence: 99%

Prediction of uniform temperature effect on rectangular hollow concrete pier based on measured temperature data

WU,

Chen,

Yun

et al. 2024

Preprint

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In order to accurately and easily predict the variation of the average temperature of the concrete rectangular hollow pier. Firstly, the temperature distribution of the concrete rectangular hollow pier of Changjiahe Special Bridge was observed for 212 days. Then, based on the observation data, the functional relationship between the average concrete hollow pier temperature and the outside air temperature, and the air temperature inside the hollow pier was studied. Finally, based on this functional relationship, a prediction model for the range of variation of the mean temperature of the hollow pier was given and verified. The results of the study show that: the change of external shade temperature can be regarded as the superposition of different cyclic changes and random changes; the change rule of the average temperature of the concrete hollow pier is the same as that of the air temperature, both presenting day-by-day cyclic and step changes; the linear correlation coefficients between the daily maximum and daily minimum average hollow pier temperature and the daily average air temperature are R = 0.980 and R = 0.973, respectively; the daily average air temperature, the daily average air temperature inside the pier and daily average hollow pier temperature are R = 0.980, R = 0.998; the daily variation of the average hollow pier temperature and the daily variation of the air temperature are approximately linear, with a correlation coefficient of R = 0.899; assuming that the average temperature of the concrete hollow pier is a folding change, based on the above relationship, a method of predicting the time-by-time average temperature of the concrete hollow piers is proposed, as well as two methods of predicting the average temperature of the test piers. average temperature change range method. Comparing the predicted values with the measured values, it is found that the predicted values are in good agreement with the measured values.

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A Simplified Method for Real-Time Prediction of Temperature in Mass Concrete at Early Age

Cited by 9 publications

References 31 publications

An ANN-Based Short-Term Temperature Forecast Model for Mass Concrete Cooling Control

An ANN-Based Short-Term Temperature Forecast Model for Mass Concrete Cooling Control

Research on Temperature Control Index for High Concrete Dams Based on Information Entropy and Cloud Model from the View of Spatial Field

Prediction of uniform temperature effect on rectangular hollow concrete pier based on measured temperature data

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