Evidence map›Paper›PMID 39000828›Full record

ArticleSensors (Basel, Switzerland)2024

Integration of Finite Element Analysis and Laboratory Analysis on 3D Models for Methodology Calibration.

Sara Gonizzi Barsanti, Rosa De Finis, Riccardo Nobile

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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

3 authors.

Sara Gonizzi BarsantiDepartment of Engineering, University of Campania Luigi Vanvitelli, 81100 Caserta, Italy.ORCID 0000-0002-7650-1616
Rosa De FinisDepartment of Engineering of Innovation, University of Salento, 73100 Lecce, Italy.ORCID 0000-0002-7972-345X
Riccardo NobileDepartment of Engineering of Innovation, University of Salento, 73100 Lecce, Italy.ORCID 0000-0003-0024-0496

Funding

PRIN: PROGETTI DI RICERCA DI RILEVANTE INTER- 497 ESSE NAZIONALE - Bando 2022 PNRR: low-coSt tools and machIne learniNg for prEdiction in 498 heRitaGe wood mechanical decaY - SINERGY P20224YMW9
6 · The paper itself

Abstract

To better address mechanical behavior, it is necessary to make use of modern tools through which it is possible to run predictions, simulate scenarios, and optimize decisions. sources integration. This will increase the capability of detecting material modifications that forerun damage and/or to forecast the stage in the future when very likely fatigue is initiating and propagating cracks. Early warning outcomes obtained by the synergetic implementation of NDE-based protocols for studying mechanical and fatigue and fracture behavior will enhance the preparedness toward economically sustainable future damage control scenarios. Specifically, these early warning outcomes will be developed in the form of retopologized models to be used coupled with FEA. This paper presents the first stage of calibration and the combination of a system of different sensors (photogrammetry, laser scanning and strain gages) for the creation of volumetric models suitable for the prediction of failure of FEA software. The test objects were two components of car suspension to which strain gauges were attached to measure its deformation under cyclic loading. The calibration of the methodology was carried out using models obtained from photogrammetry and experimental strain gauge measurements.

Indexed as

3D modelscalibrationFEAintegration of sensorsNDT sensorsstructural analysis

Identifiers

PMID39000828
PMCPMC11243940

What OpenQuestion holds

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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.