柔性加固失稳重力式挡土墙的动静力稳定性分析

Yan-peng ZHU,Xiao-hui YANG,Xiao-rui MA,Qiao-chuan ZHU

Engineering mechanics（2015）

Cited 6|Views2

Abstract

针对地震区重力式挡土墙地震后多数出现不稳定的现象和由于挡土墙工作条件改变产生失稳的事故,采用框架预应力锚杆柔性加固技术对失稳重力式挡土墙进行加固是一种非常有效的加固方法;但是,由于该加固方法系作者首先提出并在工程中使用,其稳定性分析方法,特别是地震动力稳定性分析方法是迫切需要解决问题.该文以极限平衡理论为基础,对柔性加固后重力式挡土墙进行整体静力稳定性分析,推导出挡土墙的抗倾覆稳定性和抗滑移稳定性计算公式;通过分析给出了地震动力计算模型,分析了地震动力作用,采用振型分解法给出地震动力作用下地震作用和锚杆拉力计算公式,并采用极限平衡法给出动力稳定性计算公式.

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Key words

frame prestressed,instability gravity retaining wall,seismic reinforcement,stability coefficient,movement stability

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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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