scholarly journals Ballistic Impact Performance of SiC Ceramic-Dyneema Fiber Composite Materials

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Kai-Kuang Wu ◽  
Yu-Liang Chen ◽  
Jau-Nan Yeh ◽  
Wei-Lun Chen ◽  
Chia-Shih Lin
Keyword(s):  
Composite Material ◽  
Simulation Analysis ◽  
Fiber Composite ◽  
Areal Density ◽  
Target Plate ◽  
Composite Target ◽  
Impact Performance ◽  
Ballistic Resistance ◽  
Sic Ceramic ◽  
The Relationship

This study investigated the ballistic resistance of a composite target plate fabricated by combining SiC ceramic with the Dyneema fiber. To achieve a light-weight target plate that conforms to the US National Institute of Justice level four (NIJ IV) standards, minimal areal density analysis was conducted to obtain the optimal SiC ceramic-Dyneema fiber thickness combination. This study used energy absorption to analyze the ballistic resistance of the target plates. To drastically reduce experimental costs, most of this work employed ANSYS/LS-DYNA software to conduct finite element numerical simulations. First, ballistic experiments that conformed to NIJ IV standards were conducted to verify the simulation parameter configurations. Subsequently, the correlation function of the relationship between the combined thickness of the composite material and its ballistic resistance was determined through the experimental design, which effectively reduced the simulation analysis time. According to simulation experiments and regression analysis, the equation for the relationship between the combined thickness of the composite material and its ballistic resistance was EAhc,hf=−6276.5+500.6hc+1512.6hf+30.7hchf−8.1hc2−113.6hf2, though there were limitations to its application. From the numerical analysis results, 8.1940 mm SiC ceramic and 6.9637 mm Dyneema fiber were determined to constitute the optimal thickness combination for a composite that features a minimal areal density and which conforms to NIJ IV standards. The combination was verified to be consistent with the numerical simulation analysis results.

scholarly journals Impact Resistance of Epoxy Composites Reinforced with Amazon Guaruman Fiber: A Brief Report

Polymers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 2264
Author(s):  
Raphael H. M. Reis ◽  
Fabio C. Garcia Filho ◽  
Larissa F. Nunes ◽  
Veronica S. Candido ◽  
Alisson C. R. Silva ◽  
...  
Keyword(s):  
Fiber Composite ◽  
Impact Resistance ◽  
Fiber Composites ◽  
Epoxy Composites ◽  
Impact Performance ◽  
Electron Microscopy Analysis ◽  
Ballistic Properties ◽  
Microscopy Analysis ◽  
Izod Impact ◽  
The Impact

Fibers extracted from Amazonian plants that have traditionally been used by local communities to produce simple items such as ropes, nets, and rugs, are now recognized as promising composite reinforcements. This is the case for guaruman (Ischinosiphon körn) fiber, which was recently found to present potential mechanical and ballistic properties as 30 vol% reinforcement of epoxy composites. To complement these properties, Izod impact tests are now communicated in this brief report for similar composites with up to 30 vol% of guaruman fibers. A substantial increase in impact resistance, with over than 20 times the absorbed energy for the 30 vol% guaruman fiber composite, was obtained in comparison to neat epoxy. These results were statistically validated by Weibull analysis, ANOVA, and Tukey’s test. Scanning electron microscopy analysis disclosed the mechanisms responsible for the impact performance of the guaruman fiber composites.

scholarly journals Ultrahigh Ballistic Resistance of Twisted Bilayer Graphene

Crystals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 206
Author(s):  
Qing Peng ◽  
Sheng Peng ◽  
Qiang Cao
Keyword(s):  
Weight Ratio ◽  
High Strength ◽  
Bilayer Graphene ◽  
Energy Propagation ◽  
Dynamic Simulations ◽  
Protective Material ◽  
Impact Performance ◽  
Ballistic Resistance ◽  
Twisted Bilayer Graphene ◽  
The Impact

Graphene is a good candidate for protective material owing to its extremely high stiffness and high strength-to-weight ratio. However, the impact performance of twisted bilayer graphene is still obscure. Herein we have investigated the ballistic resistance capacity of twisted bilayer graphene compared to that of AA-stacked bilayer graphene using molecular dynamic simulations. The energy propagation processes are identical, while the ballistic resistance capacity of the twisted bilayer graphene is almost two times larger than the AA-bilayer graphene. The enhanced capacity of the twisted bilayer graphene is assumed to be caused by the mismatch between the two sheets of graphene, which results in earlier fracture of the first graphene layer and reduces the possibility of penetration.

Influence Parameters Analysis of Forming Quality and System Dynamics Simulation of Vertical Steel Bar Benting

2013 ◽  
Vol 483 ◽  
pp. 280-284
Author(s):  
Xi Jian Zheng ◽  
Xin Zhuo Wang ◽  
Jin Meng Zhang ◽  
Yu Fei Zhu
Keyword(s):  
Simulation Analysis ◽  
Reference Value ◽  
Dynamics Simulation ◽  
Forming Quality ◽  
Steel Bar ◽  
New Process ◽  
Cutting Length ◽  
Bending Radius ◽  
The Relationship

The vertical steel bar bending forming is a kind of new process of bending method. The bending speed, bending radius and clamping length H which is the parameters of vertical steel bar bending machine , is directly affect the quality of bending forming parts. This paper calculated the length of reinforcement before being incised and the springback angle of bending steel bar which obtained the reasonable cutting length and bending Angle; Then based on rigid-flexible virtual prototype technology to build the dynamics model of vertical steel bar bending system. Through simulation analysis ,it obtained the relationship between bending speed, bending radius , clamping length H and forming quality of bending steel bar. In this paper, the analysis method have reference value to the design of similar steel bar bending machines.

Electrical conductivity identification of a carbon fiber composite material plate using a rotating magnetic field and multi-coil eddy current sensor

2018 ◽  
Vol 83 (2) ◽  
pp. 20901 ◽  
Author(s):  
Ahmed Chaouki Lahrech ◽  
Bachir Abdelhadi ◽  
Mouloud Feliachi ◽  
Abdelhalim Zaoui ◽  
Mohammed Naїdjate
Keyword(s):  
Magnetic Field ◽  
Neural Networks ◽  
Electrical Conductivity ◽  
Composite Material ◽  
Carbon Fiber ◽  
Fiber Composite ◽  
Rotating Magnetic Field ◽  
Current Sensor ◽  
Carbon Fiber Composite ◽  
Fiber Composite Material

This paper proposes a contactless method for the identification of the electrical conductivity tensor of a carbon fiber composite materials plate using a rotating magnetic field and multi-coil eddy current sensor. This sensor consists of identical rectangular multi-coil, excited by two-phase sinusoidal current source in order to generate a rotating magnetic field and to avoid the mechanical rotation of the sensor. The fibers orientations, the longitudinal and transverse conductivities in each ply of carbon fiber composite material plate were directly determined with analysis of the impedance variation of each coil as function of its angular position. The inversion process is based on the use of artificial neural networks. The direct calculation associated with artificial neural networks makes use of 3D time-harmonic finite element method based on the A, V–A formulation.

scholarly journals Algorithm and Simulation of Association Rules of Drug Relationship Based on Network Model

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Hui Teng ◽  
Yukun Ma ◽  
Di Teng
Keyword(s):  
Decision Making ◽  
Network Model ◽  
Association Rules ◽  
Association Rule ◽  
Simulation Analysis ◽  
Pharmaceutical Research ◽  
Accurate Analysis ◽  
Systematic Analysis ◽  
Relationship Of ◽  
The Relationship

Studying drug relationships can provide deeper information for the construction and maintenance of biomedical databases and provide more important references for disease treatment and drug development. The research model has expanded from the previous focus on a certain drug to the systematic analysis of the pharmaceutical network formed between drugs. Network model is suitable for the study of the nonlinear relationship of the pharmaceutical relationship by modeling the data learning. Association rule mining is used to find the potential correlations between the various sets of massive data. Therefore, based on the network model, this research proposed an algorithm for drug interaction under improved association rules, which achieved accurate analysis and decision-making of drug relationship. Meanwhile, this research applied the established association rule algorithm to discuss the relationship between Chinese medicine and mental illness medicine and conducted the algorithm research and simulation analysis of the association relationship. The results showed the association rule algorithm based on the network model constructed was better than other association algorithms. It had reliability and superiority in decision-making in improving the drug-drug relationship. It also promoted the rational use of medicines and played a guiding role in pharmaceutical research. This provides scientific research personnel with research basis and research ideas for disease-related diagnosis.

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