Evidence map›Paper›PMID 36984240›Full record

ArticleMaterials (Basel, Switzerland)2023

Compressive Strength of Corrugated Paperboard Packages with Low and High Cutout Rates: Numerical Modelling and Experimental Validation.

Lajos Fehér, Damian Mrówczyński, Renáta Pidl, Péter Böröcz

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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.

Lajos FehérDepartment of Applied Mechanics, Széchenyi István University, Egyetem tér 1, 9026 Győr, Hungary.ORCID 0000-0002-6349-1420
Damian MrówczyńskiResearch and Development Department, Femat Sp. z o.o., Wagrowska 2, 61-369 Poznań, Poland.ORCID 0000-0001-8735-3607
Renáta PidlDepartment of Applied Mechanics, Széchenyi István University, Egyetem tér 1, 9026 Győr, Hungary.ORCID 0000-0002-8617-1761
Péter BöröczDepartment of Logistics and Forwarding, Széchenyi István University, Egyetem tér 1, 9026 Győr, Hungary.ORCID 0000-0002-7432-7271

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The finite element method is a widely used numerical method to analyze structures in virtual space. This method can be used in the packaging industry to determine the mechanical properties of corrugated boxes. This study aims to create and validate a numerical model to predict the compression force of corrugated cardboard boxes by considering the influence of different cutout configurations of sidewalls. The types of investigated boxes are the following: the width and height of the boxes are 300 mm in each case and the length dimension of the boxes varied from 200 mm to 600 mm with a 100 mm increment. The cutout rates were 0%, 4%, 16%, 36%, and 64% with respect to the total surface area of sidewalls of the boxes. For the finite element analysis, a homogenized linear elastic orthotropic material model with Hill plasticity was used. The results of linear regressions show very good estimations to the numerical and experimental box compression test (BCT) values in each tested box group. Therefore, the numerical model can give a good prediction for the BCT force values from 0% cutout to 64% cutout rates. The accuracy of the numerical model decreases a little when the cutout rates are high. Based on the results, this paper presents a numerical model that can be used in the packaging design to estimate the compression strength of corrugated cardboard boxes.

Indexed as

box compression testcompression forcecutoutfinite element methodnumerical modelpaperboard packaging

Identifiers

PMID36984240
PMCPMC10054506

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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.