• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2017.05a
• /
• pp.933-935
• /
• 2017

This paper deals with the influence of fungi for the thermal protective cork-based exterior insulator which protect a missile system from aerodynamic loads and heating during flight of missile. We consider the adhesion of cork-based composite on the composite motor case which fabricated by filament winding process. We also consider the importance of the requirement analysis for effective, successful system development under given system conditions. In order to develop the basic requirement analysis for the thermal protective cork-based exterior insulator, an experimental requirement analysis was accomplished, and some experimental comparing results, the study for preventing fungi are presented.

• Composites Research
• /
• v.36 no.1
• /
• pp.53-58
• /
• 2023

The PIC design method is assigning different stacking sequences for each shell element through the preliminary FE analysis. In previous study, machine learning was applied to the PIC design method in order to assign the region efficiently, and the training data is labeled by dividing each region into tension, compression, and shear through the preliminary FE analysis results value. However, since buckling is not considered, when buckling occurs, it can't be divided into appropriate loading type. In the present study, it was proposed PIC-NTL (PIC design using novel technique for analyzing load type) which is method for applying a novel technique for analyzing load type considering buckling to the conventional PIC design. The stress triaxiality for each ply were analyzed for buckling analysis, and the representative loading type was designated through the determined loading type within decision area divided into two regions of the same size in the thickness direction of the elements. The input value of the training data and label consisted in coordination of element and representative loading type of each decision area, respectively. A machine learning model was trained through the training data, and the hyperparameters that affect the performance of the machine learning model were tuned to optimal values through Bayesian algorithm. Among the tuned machine learning models, the SVM model showed the highest performance. Most effective stacking sequence were mapped into PIC tube based on trained SVM model. FE analysis results show the design method proposed in this study has superior external loading resistance and energy absorption compared to previous study.

• Korean Journal of Metals and Materials
• /
• v.50 no.9
• /
• pp.697-702
• /
• 2012

In this study, unidirectional and plain woven carbon fiber reinforced magnesium matrix composite laminates were fabricated by the liquid pressing infiltration process, and evolutions of the microstructure and compressive strength of the composite laminates under corrosion were investigated by static immersion tests. In the case of the unidirectional composite laminate, the main microstructural damage during immersion appeared as a form of corrosion induced cracks, which were formed at both CF/Mg interfaces and the interfaces between layers. On the otherhand, wrap/fill interface cracks were mainly formed in the plain woven composite laminate, without any cracks at the CF/Mg interface. The formation of these cracks was considered to be associated with internal thermal residual stress, which was generated during cooling after the fabrication process of these materials. As a consequence of the corrosion induced cracks, the thickness of both laminates increased in directions vertical to the fibers with increasing immersion time. With increasing immersion time, the compressive strengths of both composite laminates also decreased continuously. It was found that the plain woven composite laminates have superior corrosion resistance and stability under a corrosive condition than unidirectional laminates.