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3 2023

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Application of Taguchi methods (doe) in composite engineering

100%

Lesiuk G. , Zielonka P. , Olaleye K. , Soogabbe J. , Lafarga A. F.

Journal of TransLogistics

2023

tom Vol. 19

51-61

In the paper, a design of experiment (DOE) in terms of the Taguchi method was used for the optimization of the manufacturing process. This approach makes it possible to do fewer experiments while still getting the desired outcomes. This research programme will use this tool to optimize the resin casting process by monitoring manufacturing parameters like temperature, curing time, and flameretardant concentration. Thus, this study aims to determine the ideal set of parameters for the resin casting of composite materials. Based on experimental results, it was possible to find crucial factors and their influence on the fracture strength of resin for composite manufacturing systems.

Acoustic emission with machine learning in fracture of composites: preliminary study

100%

Smolnicki M. , Duda S. , Stabla P. , Zielonka P. , Lesiuk G.

2023

tom Vol. 23, no. 4

art. e254, 1--18

In this paper, preliminary studies on the failure analysis of hybrid composite materials utilizing acoustic emission and machine learning are presented. The main purpose of this study was to analyze the possibilities of using machine learning techniques as a way to better cluster the data obtained from acoustic emission. In this paper, we focus on data preparation, feature extraction (Laplacian score), determination of cluster number (Caliński-Harabasz, Silhouette, and Davies-Bouldin), and testing three clustering techniques, namely K-means, fuzzy C-means, and spectral clustering. The dataset was obtained by testing fber metal laminates-composites consisting of metal and composite layers. Two experimental tests were realized on pre-cracked rectangular specimens-one with loading in mode I and one with loading in mode II (DCB-double cantilever beam and ENF-end-notch fexural test). Elastic waves were recorded during these tests via an acoustic emission system. Preliminary studies show that the proposed method can be used successfully to cluster data obtained in this way. The obtained dataset was split into 3 clusters (for the ENF test) and 5 clusters (DCB test). In the next stages of the research campaign, based on the presented results, we intend to change the approach to semi-supervised by running additional single cause damage tests to enhance the achieved results and enable easier damage recognition.

Combined experimental–numerical mode I fracture characterization of the pultruded composite bars

86%

Smolnicki M. , Duda S. , Zielonka P. , Stabla P. , Lesiuk G. , Lopes C. C. C.

2023

tom Vol. 23, no. 3

art. no. e146, 2023

In this paper, pultruded GFRP bars are investigated to determine their fracture properties. The double cantilever beam test (DCB) is used to assess fracture behavior under mode I loading conditions. However, due to the presence of the R-curve effect (variable fracture energy dependent on the length of the crack), it is necessary to introduce a nonstandard approach to determine fracture properties. The mixed experimental–numerical approach is proposed to deal with this issue. Numerical simulations were carried out in Simulia Abaqus, and with Python scripting it was possible to generate models and obtain R-curve for the material. The numerical model built based on the experimental results has very good agreement with it (force–displacement and delamination length–time characteristics) which allows the use of the mentioned model in the analysis of more complex structures. Acoustic emission analysis was introduced as an auxiliary technique. The delamination obtained from both the numerical model and the experiment complies with the registered acoustic emission events. The proposed method can be used in preparing a material model for other composite materials, which display the presence of the R-curve effect.