TY - GEN
T1 - Prediction of Long-Term Settlements of Foundations Supporting High and Heavy Storage Tanks Based on Short-Term Field Measurements
AU - Hu, Jianmin
AU - Zhang, Lianyang
N1 - Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2018.
PY - 2018
Y1 - 2018
N2 - The operation and safety of high and heavy storage tanks are very sensitive to the differential settlements of the foundations. It is therefore extremely important to precisely predict the long-term settlements so that appropriate measures can be taken if the expected settlements are too large. Researchers have proposed different methods for predicting the long-term settlements of foundations. Of these different methods, the methods based on the short-term field measurements at the beginning, such as the Asaoka method, are commonly used. Since the measurements are taken at the site, the field conditions related to the structure, foundation and soils are well reflected in the measurements. However, since the measurements are only for a short period at the beginning, they may not reflect the behavior of the whole system at a significantly later time. This paper uses the extensive data of field settlement measurements for foundations supporting high and heavy storage tanks at an alumina refinery plant to do a detailed evaluation of the Asaoka method. Specifically, the measurements within different periods of time from the beginning are used to predict the settlements at a later time and the predictions are then compared with the measurements. By doing so, the effect of the time period from the beginning with field measurements on the accuracy of long-term settlement prediction is quantified. Finally, an optimum time period from the beginning with field measurements is recommended so that the field measurements can be used to predict the long-term settlement with sufficient accuracy.
AB - The operation and safety of high and heavy storage tanks are very sensitive to the differential settlements of the foundations. It is therefore extremely important to precisely predict the long-term settlements so that appropriate measures can be taken if the expected settlements are too large. Researchers have proposed different methods for predicting the long-term settlements of foundations. Of these different methods, the methods based on the short-term field measurements at the beginning, such as the Asaoka method, are commonly used. Since the measurements are taken at the site, the field conditions related to the structure, foundation and soils are well reflected in the measurements. However, since the measurements are only for a short period at the beginning, they may not reflect the behavior of the whole system at a significantly later time. This paper uses the extensive data of field settlement measurements for foundations supporting high and heavy storage tanks at an alumina refinery plant to do a detailed evaluation of the Asaoka method. Specifically, the measurements within different periods of time from the beginning are used to predict the settlements at a later time and the predictions are then compared with the measurements. By doing so, the effect of the time period from the beginning with field measurements on the accuracy of long-term settlement prediction is quantified. Finally, an optimum time period from the beginning with field measurements is recommended so that the field measurements can be used to predict the long-term settlement with sufficient accuracy.
KW - Field measurements
KW - High and heavy storage tanks
KW - Long-term settlement
KW - Prediction
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U2 - 10.1007/978-981-13-0131-5_71
DO - 10.1007/978-981-13-0131-5_71
M3 - Conference contribution
AN - SCOPUS:85197861755
SN - 9789811301308
T3 - Proceedings of GeoShanghai 2018 International Conference: Advances in Soil Dynamics and Foundation Engineering
SP - 654
EP - 661
BT - Proceedings of GeoShanghai 2018 International Conference
A2 - Qiu, Tong
A2 - Tiwari, Binod
A2 - Zhang, Zhen
PB - Springer
T2 - 4th GeoShanghai International Conference - Advances in Soil Dynamics and Foundation Engineering, GSIC 2018
Y2 - 27 May 2018 through 30 May 2018
ER -