不同类型填方路基沉降监测及沉降分析

Jinming Wang,Changyan Chen,Jiankun Zhang,Xue Tan

Geotechnical Investigation & Surveying（2019）

Cited 5|Views8

Abstract

填方路堤的沉降变形和稳定是高填方公路建设的重要工程问题,沉降变形控制将是填方公路施工期、施工期后以及路基处理的重要控制指标.本文主要阐述某高填方路基工程的沉降监测方法及沉降分析,选取碎石挤压路基、天然路基、复合路基等不同类型的高填方路基进行详细的分析比较,分析高填方路基不同时期的沉降规律,对比分析不同路基的沉降关系,论述证明了对桥头地基进行加固处理的设计方案明显改善了路基的沉降,碎石挤压路基在施工前期能有效地减缓路基沉降的发生等规律.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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