Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Evaluating frost heave susceptibility of well-graded gravel for HSR subgrade based on orthogonal array testing
Highlights Multivariate regression analysis using stepwise approach was adopted. Influence of interaction between factors on frost heave susceptibility of GW was examined. A statistical model was proposed for predicting average heaving ratio of GW.
Abstract Well-graded gravels are usually considered non-frost-susceptible, which appears to be a fair assumption in accordance with universally recognized frost criterions; However, their frost heave susceptibility is affected by the unavoidable presence of fines (passing through No. 200 sieve, 0.075 mm) and water when used as backfills for high-speed rail (HSR) subgrade. In practice, non-negligible frost heave would occur within gravels throughout a severe winter, causing great difficulties for operation and maintenance of high-speed trains which tolerates a maximum heave amount of 5 mm. This paper introduces a series of unidirectional freezing tests performed on gravel soils that rely on an orthogonal array, and the frost heave properties of tested material were obtained under the combined effect of moisture content, fines content, dry density, and cooling temperature. The average heaving ratio (AHR), an indication of frost heave susceptibility, was estimated by multivariate regression analysis using a stepwise approach. The results suggest that moisture content exerts the greatest influence on average heaving ratio of well-graded gravels, followed by dry density, fines content, and cooling temperature. In addition, whether the dry density is positively or negatively related to an average heaving ratio depends on the levels of fines content and cooling temperature. A statistical model considering the interaction between factors is proposed to predict the average heaving ratio and to evaluate the frost heave susceptibility of well-graded gravels further.
Evaluating frost heave susceptibility of well-graded gravel for HSR subgrade based on orthogonal array testing
Highlights Multivariate regression analysis using stepwise approach was adopted. Influence of interaction between factors on frost heave susceptibility of GW was examined. A statistical model was proposed for predicting average heaving ratio of GW.
Abstract Well-graded gravels are usually considered non-frost-susceptible, which appears to be a fair assumption in accordance with universally recognized frost criterions; However, their frost heave susceptibility is affected by the unavoidable presence of fines (passing through No. 200 sieve, 0.075 mm) and water when used as backfills for high-speed rail (HSR) subgrade. In practice, non-negligible frost heave would occur within gravels throughout a severe winter, causing great difficulties for operation and maintenance of high-speed trains which tolerates a maximum heave amount of 5 mm. This paper introduces a series of unidirectional freezing tests performed on gravel soils that rely on an orthogonal array, and the frost heave properties of tested material were obtained under the combined effect of moisture content, fines content, dry density, and cooling temperature. The average heaving ratio (AHR), an indication of frost heave susceptibility, was estimated by multivariate regression analysis using a stepwise approach. The results suggest that moisture content exerts the greatest influence on average heaving ratio of well-graded gravels, followed by dry density, fines content, and cooling temperature. In addition, whether the dry density is positively or negatively related to an average heaving ratio depends on the levels of fines content and cooling temperature. A statistical model considering the interaction between factors is proposed to predict the average heaving ratio and to evaluate the frost heave susceptibility of well-graded gravels further.
Evaluating frost heave susceptibility of well-graded gravel for HSR subgrade based on orthogonal array testing
Luo, Qiang (Autor:in) / Wu, Peng (Autor:in) / Wang, Tengfei (Autor:in)
17.09.2019
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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