scholarly journals Managing Data Using Neighbor Replication on Triangular-Grid Structure

Author(s):  
Ali Mamat ◽  
M. Mat Deris ◽  
J. H. Abawajy ◽  
Suhaila Ismail
2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Kong Fanxiao ◽  
Yao Huazhong ◽  
Xie Weidong

In recent years, many scholars have conducted in-depth and extensive research on the mechanical properties, preparation methods, and structural optimization of grid structural materials. In this paper, the structural characteristics of composite intelligent grid are studied by combining theoretical analysis with experiments. According to the existing conditions in the laboratory, the equilateral triangular grid structure experimental pieces were prepared. In this paper, principal component analysis combined with nearest neighbor method was used to detect the damage of composite plates. On this basis, the multiobjective robustness optimization of the structure is carried out based on artificial intelligence algorithm, which makes the structure quality and its sensitivity to uncertain parameters lower. Particle swarm optimization (PSO) is used in neural network training. The damage characteristics of different grid structures, different impact positions, and different impact energies were studied. The results show that the structural damage types, areas, and propagation characteristics are very different when the structure is impacted at different positions, which verifies that the grid structure has a good ability to limit the damage diffusion and shows that the grid structure has a good ability to resist damage.


Author(s):  
Mustafa Mat Deris ◽  
Jemal H. Abawajy ◽  
David Taniar ◽  
Ali Mamat

2013 ◽  
Vol E96.B (1) ◽  
pp. 309-312 ◽  
Author(s):  
Euisin LEE ◽  
Soochang PARK ◽  
Hosung PARK ◽  
Sang-Ha KIM

Materials ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5281
Author(s):  
Mateusz Kozioł ◽  
Piotr Szperlich ◽  
Bartłomiej Toroń ◽  
Piotr Olesik ◽  
Marcin Jesionek

This paper shows a piezoelectric response from an innovative sensor obtained by casting epoxy-SbSI (antimony sulfoiodide) nanowires nanocomposite to a grid structure printed using a fuse deposition modeling (FDM) method. The grid is shown to be a support structure for the nanocomposite. The applied design approach prospectively enables the formation of sensors with a wide spectrum of shapes and a wide applicability. The voltage signal obtained as a result of the piezoelectric effect reached 1.5V and 0.5V under a maximum static stress of 8.5 MPa and under a maximum dynamic stress of 22.3 kPa, respectively. These values are sufficient for potential application in sensor systems. The effect of a systematic increase in the voltage signal with subsequent cycles was also observed, which similarly allows the use of these sensors in monitoring systems for structures exposed to unfavorable cyclical loads. The obtained results also show that the piezoelectric signal improves with increase in strain rate.


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