Evidence map›Paper›PMID 37880291›Full record

ArticleScientific reports2023

Dynamic characteristics and reinforcement mechanism of silty soil improved by regenerated fiber polymer.

Lulu Liu, Jinpeng Zhao, Xiaoyan Liu, Shixin Lv

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Lulu LiuState Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou, 221116, China.
Jinpeng ZhaoSchool of Highway, Chang'an University, Xi'an, 710064, China.
Xiaoyan LiuSchool of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou, 221116, China. happyliuxiaoyan@163.com.
Shixin LvSchool of Highway, Chang'an University, Xi'an, 710064, China.
Chang'an University · CNChina University of Mining and Technology · CN

Funding

National Natural Science Foundation of China 42207180National Natural Science Foundation of China 42302320
6 · The paper itself

Abstract

The development of economical and efficient roadbed silt reinforcement technology not only guides the proficient utilization of silt resources but also fosters the green development of geotechnical engineering construction. Ensuring the robust dynamic stability of the roadbed is pivotal for the safe operation of vehicular traffic. In this context, employing recycled polyester fibers and inorganic curing agents, this paper leverages dynamic triaxial testing and scanning electron microscopy (SEM) methods to scrutinize the dynamic characteristics and microscopic mechanisms of recycled fiber polymer modified roadbed silt. The findings indicate that: (1) with a fiber content of 0.2%, the fiber-modified soil sample exhibits minimal damage, maximal dynamic strength and dynamic elastic modulus, and optimum resilience to dynamic loads; (2) akin to fiber-reinforced sand, an elevation in confining pressure can induce the creation of a quasi-cohesive force in fiber-reinforced soil, equivalently enhancing the confining pressure and thereby amplifying its strength; and (3) the surfaces of microparticles in the enhanced soil structure are enveloped with cementitious substances, while smaller soil particles coalesce to form aggregates that fill inter-particle pores, cultivating a denser and more stable improved soil structure and augmenting the dynamic characteristics of the improvement investment.

Identifiers

PMID37880291
PMCPMC10600188
OpenAlexW4387948667

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.