Evidence map›Paper›PMID 36171239›Full record

ArticleScientific reports2022

A novel method for estimating subresolution porosity from CT images and its application to homogeneity evaluation of porous media.

Li Zhuang, Hyu-Soung Shin, Sun Yeom, Chuyen Ngoc Pham, Young-Jae Kim

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Li ZhuangKorea Institute of Civil Engineering and Building Technology, Goyang, Republic of Korea.
Hyu-Soung ShinKorea Institute of Civil Engineering and Building Technology, Goyang, Republic of Korea. hyushin@kict.re.kr.
Sun YeomKorea Institute of Civil Engineering and Building Technology, Goyang, Republic of Korea.
Chuyen Ngoc PhamKorea Institute of Civil Engineering and Building Technology, Goyang, Republic of Korea.
Young-Jae KimKorea Institute of Civil Engineering and Building Technology, Goyang, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We propose a new method, i.e., the statistical phase fraction (SPF) method, to estimate the total porosity and spatial distribution of local porosities from subresolution pore-dominated X-ray microtomography images of porous materials. The SPF method assumes that a voxel in a CT image is composed of either a single or a maximum of three pure phases of matter (solid, liquid and air). Gaussian function (GF) fitting is conducted on the basis that the summation of the area of each GF curve is equal to the total area covered by the CT histogram. The volume fraction of each phase corresponding to each GF is calculated based on the mean value of the GF, the area of the GF, and the CT numbers for pure phases. The SPF method is verified on three different types of components containing only air and solid phases, i.e., alumina ceramic and two sintered lunar regolith simulants with relatively homogenous and inhomogeneous microstructures. The estimated porosities of a total of 15 specimens (the total porosity ranges from 0 to 51%) via the SPF method show an average error of 3.11% compared with the ground truth. Spatial distribution of local porosities in the defined representative element volume is investigated for homogeneity evaluation. Results show that the local porosity inhomogeneity in the sintered FJS-1 specimens is more prominent than that in the sintered KLS-1 specimens.

Indexed as

Aluminum OxideCeramicsPorosityTomography, X-Ray ComputedAluminum Oxide

Identifiers

PMID36171239
PMCPMC9519865

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.