Evidence map›Paper›PMID 40442150›Full record

ArticleScientific reports2025

Machine tool FEM model correction assisted by dynamic evolution sequence.

Weihao Lin, Peng Zhong, Xindi Wei, Li Zhu, Xuanlong Wu

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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
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0citing papers in PubMed
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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.

Weihao LinState Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian, 116024, People's Republic of China.
Peng ZhongState Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian, 116024, People's Republic of China.
Xindi WeiState Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian, 116024, People's Republic of China.
Li ZhuState Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian, 116024, People's Republic of China. zhuli@mail.dlut.edu.cn.
Xuanlong WuState Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian, 116024, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the simulation analysis of large-scale industrial instruments such as machine tools, in order to ensure simulation accuracy, model parameter correction is necessary. This research presents a machine tool model correction method assisted by the dynamic evolution sequence (DES). The method first introduces a dynamic evolution method to generate a uniformly distributed sequence, replacing the traditional sequence used in Kriging surrogate models, and constructing a more accurate Kriging surrogate model for machine tools. Moreover, replacing the random sequence with a dynamic evolution sequence enhances the search space coverage of the heterogeneous comprehensive learning particle swarm optimization (HCLPSO) algorithm. The results of numerical examples demonstrate that the finite element model, corrected using the proposed method, accurately predicts the true displacement responses of the machine tool. This method offers a new solution for addressing large-scale machine tool static model correction problems.

Indexed as

Dynamic evolutionHeterogeneous comprehensive learning particle swarm optimizationKriging surrogate modelsLow-discrepancy sequenceMachine tool FEM modelModel correction

Identifiers

PMID40442150
PMCPMC12122679

What OpenQuestion holds

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Registered trials

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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.