Jianmin Zhang's research while affiliated with Tsinghua University and other places
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Publications (4)
The compaction quality of a highway subgrade is influenced by the compaction parameters and soil properties. Current practice lacks reliable models to assess this multivariate situation. This paper describes a monitoring and evaluation method based on intelligent compaction (IC) and artificial neural networks (ANNs) to assess the compaction quality...
The quality control of subgrade compaction depends on post-evaluations. The potential bias is caused by the limited coverage of spot tests at the construction site. Intelligent compaction is developed by integrating the sensing system on the vibratory roller and used at the construction site of the Rongwu highway to monitor the compaction quality i...
Highway construction strategies impact the early damage of asphalt pavement and its sustainability. The pavement quality is directly influenced by the temperature segregation of the mixture during transportation, which has rarely been investigated. Low-temperature transportation strategies for highway pavement are proposed by assessing the temperat...
The reliable correlation model for intelligent compaction (IC) is to be developed by integrating characteristics of the filling material and control parameters of the vibratory roller. Key characteristics of the backfill soil from the construction site of Rongwu Highway are tested through the modified Proctor test and the direct shear test. A well-...
Citations
... Following Liu [31], the compaction parameters of an earth-rock dam are collected through the IC system, and the material properties are recorded. IC provides an efficient method for the quality control of highway constructions, including subgrade soil [10], aggregate layer [61], and asphalt pavement [8,63]. The SmartRock sensor is applied in compacting the base layer to monitor the motion of granular particles. ...
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... There is very limited literature and specification regarding the compaction uniformity evaluation of subgrade in highways. With the development of computational science, the principal components analysis and Back Propagation (BP) neural networks provide novel solutions for evaluating the compaction uniformity of subgrade [10][11][12]. The principal components analysis is a multivariate statistical method, which uses the idea of dimensionality reduction to convert multiple indicators into several comprehensive indicators without losing original information. ...
