Study on Adiabatic Temperature Rise Reflecting Hydration Degree of Concrete
The thermal model and the relevant parameters of concrete are the most important issues to study the space-time characteristics of temperature field, which are also the theoretical foundation of temperature control and crack prevention for the mass concrete structures. In this research, the improved...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2018/1435049 |
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| author | Yanhua Han Shaojun Fu Shufa Wang Zuowei Xie |
| author_facet | Yanhua Han Shaojun Fu Shufa Wang Zuowei Xie |
| author_sort | Yanhua Han |
| collection | DOAJ |
| description | The thermal model and the relevant parameters of concrete are the most important issues to study the space-time characteristics of temperature field, which are also the theoretical foundation of temperature control and crack prevention for the mass concrete structures. In this research, the improved adiabatic temperature rise test is carried out, and the temperature variation of fly ash concrete is analyzed. Furthermore, a thermal model of concrete considering the hydration degree is established based on the existing achievements. Meanwhile, the thermal conductivity and specific heat of concrete are measured via three approaches: by treating the parameters as constant values, by computing the parameters as variables of the degree of hydration, and by back-analyzing the parameters through BP neural network. Finally, the thermal parameters determined by different methodologies are substituted into the thermal model, respectively, and the finite element analysis of the concrete specimen is performed. By comparing simulated temperatures with various measured results, it can be found that the numerical analysis results of parameters calculated by BP neural network are closest to the measured values in the whole curing ages. Therefore, BP neural network method is an effective way to calculate the thermal parameters, and BP inversion algorithm provides a new way for accurately study the temperature profile of mass concrete structures. |
| format | Article |
| id | doaj-art-7e8b23989789478fbb8aea88e9573379 |
| institution | Kabale University |
| issn | 1687-8434 1687-8442 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Materials Science and Engineering |
| spelling | doaj-art-7e8b23989789478fbb8aea88e95733792025-02-03T01:28:49ZengWileyAdvances in Materials Science and Engineering1687-84341687-84422018-01-01201810.1155/2018/14350491435049Study on Adiabatic Temperature Rise Reflecting Hydration Degree of ConcreteYanhua Han0Shaojun Fu1Shufa Wang2Zuowei Xie3School of Civil Engineering, Wuhan University, 8 East Lake South Road, Wuhan 430072, ChinaSchool of Civil Engineering, Wuhan University, 8 East Lake South Road, Wuhan 430072, ChinaSchool of Civil Engineering, Wuhan University, 8 East Lake South Road, Wuhan 430072, ChinaSchool of Civil Engineering, Wuhan University, 8 East Lake South Road, Wuhan 430072, ChinaThe thermal model and the relevant parameters of concrete are the most important issues to study the space-time characteristics of temperature field, which are also the theoretical foundation of temperature control and crack prevention for the mass concrete structures. In this research, the improved adiabatic temperature rise test is carried out, and the temperature variation of fly ash concrete is analyzed. Furthermore, a thermal model of concrete considering the hydration degree is established based on the existing achievements. Meanwhile, the thermal conductivity and specific heat of concrete are measured via three approaches: by treating the parameters as constant values, by computing the parameters as variables of the degree of hydration, and by back-analyzing the parameters through BP neural network. Finally, the thermal parameters determined by different methodologies are substituted into the thermal model, respectively, and the finite element analysis of the concrete specimen is performed. By comparing simulated temperatures with various measured results, it can be found that the numerical analysis results of parameters calculated by BP neural network are closest to the measured values in the whole curing ages. Therefore, BP neural network method is an effective way to calculate the thermal parameters, and BP inversion algorithm provides a new way for accurately study the temperature profile of mass concrete structures.http://dx.doi.org/10.1155/2018/1435049 |
| spellingShingle | Yanhua Han Shaojun Fu Shufa Wang Zuowei Xie Study on Adiabatic Temperature Rise Reflecting Hydration Degree of Concrete Advances in Materials Science and Engineering |
| title | Study on Adiabatic Temperature Rise Reflecting Hydration Degree of Concrete |
| title_full | Study on Adiabatic Temperature Rise Reflecting Hydration Degree of Concrete |
| title_fullStr | Study on Adiabatic Temperature Rise Reflecting Hydration Degree of Concrete |
| title_full_unstemmed | Study on Adiabatic Temperature Rise Reflecting Hydration Degree of Concrete |
| title_short | Study on Adiabatic Temperature Rise Reflecting Hydration Degree of Concrete |
| title_sort | study on adiabatic temperature rise reflecting hydration degree of concrete |
| url | http://dx.doi.org/10.1155/2018/1435049 |
| work_keys_str_mv | AT yanhuahan studyonadiabatictemperaturerisereflectinghydrationdegreeofconcrete AT shaojunfu studyonadiabatictemperaturerisereflectinghydrationdegreeofconcrete AT shufawang studyonadiabatictemperaturerisereflectinghydrationdegreeofconcrete AT zuoweixie studyonadiabatictemperaturerisereflectinghydrationdegreeofconcrete |