Model Test of Bearing Characteristics of Fly Ash Foundation under Cyclic Loading
Processes(2022)SCI 4区SCI 3区
Anhui Univ Sci & Technol | East China Univ Technol
Abstract
Based on the vertical cyclic model test of the cement-fly ash mixing pile (CFMP) composite foundation, the effects of different dynamic load ratios on the long-term bearing characteristics of the composite foundation were studied. From the perspectives of foundation cumulative settlement, dynamic stiffness, pile axial force, and pile lateral friction, etc., the bearing mechanism of the CFMP fly ash composite foundation under cyclic load was investigated. By virtue of the assay herein, the authors discovered that the cumulative settlement under different load ratios exhibited the “threshold effect”, which could be divided into the attenuation type and destruction type. When the peak value of the cyclic load was close to the ultimate bearing capacity, the dynamic failure of the pile foundation occurred. The cyclic displacement ratio ranged from 1.05 to 1.23, satisfying the relation of quadratic equation. The cyclic load settlement could be predicted by the static load displacement. During cyclic loading, the proportion of the pile side sharing the upper load decreased persistently, and the fatigue degradation of side friction resistance occurred. The degradation could be alleviated by reducing the water content of fly ash and taking waterproof measures during construction.
MoreTranslated text
Key words
model test,cyclic load,composite foundation,cumulative settlement,bearing characteristics,fatigue degradation
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- 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
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper