• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.4
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• pp.107-113
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• 2022

At present, it is possible to manufacture electrodes down to several micrometers (~ ㎛) using inkjet printing technology owing to the development of precision ejection heads. Inkjet printing technology is also used in the manufacturing of bio-sensors, electronic sensors, and flexible displays. To reduce the difference between the electrode design/simulation performance and actual printing pattern performance, it is necessary to analyze and optimize the processable area of the ink material, which is a fluid. In this study, process optimization was conducted to manufacture an IDE pattern and fabricate an impedance sensor. A total of 25 IDE patterns were produced, with five for each lamination process. Electrode line width and height changes were measured by stacking the designed IDE pattern with a nanoparticle-based conductive ink multilayer. Furthermore, the optimal process area for securing a performance close to the design result was analyzed through impedance and capacitance. It was observed that the increase in the height of stack layer 4 was the lowest at 4.106%, and the increase in capacitance was measured to be the highest at 44.08%. The proposed stacking process pattern, which is optimized in terms of uniformity, reproducibility, and performance, can be efficiently applied to bio-applications such as biomaterial sensing with an impedance sensor.

• Composites Research
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• v.33 no.1
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• pp.13-18
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• 2020

Recently, the fire rescue truck in problem proceed research it for the fast works action and for pass the small road. So we were research for weight reduction. In this study, the (NO. 5) fifth boom of the fire rescue truck have 288 mm(W) × 299 mm(D) × 3,691 mm(L) with a maximum load of 876 kg and the thickness of 3 mm of the Steel Boom. This changing of Steel (STRENX960) to CFRP was weave Carbon Fiber NCF (±45°, 2axis) and then it make the NCF Prepreg. This process was designed based on structural analysis, the effects of NCF Prepreg (±45°) on torsion were identified, and the optimal design was made with Stacking Pattern (b). Stack patterns were optimized for levels equal or higher than existing Steel Boom and CFRP Boom stacked in the UD direction, and finally, the lightening effect on weight of approximately 49.6% of the steel was identified.

• Composites Research
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• v.24 no.1
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• pp.37-44
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• 2011

In this paper, Particle Swarm Optimization(PSO) is applied to the design of the Frequency Selective Surface(FSS) and residual stresses of hybrid radome is predicted. An equivalent circuit model with Square Loops arrays was derived and then PSO was applied for acquiring the optimized geometrical parameters with proper resonant frequency. Residual stresses occur in the FSS embedded composite structures after cocuring and have a great influence on the strength of the FSS embedded composite structures. They also effect transmission quality because of delamination. Therefore, the thermal residual stresses of FSS embedded composite structures were analyzed using finite element analysis with considering the effects of FSS pattern, and composite stacking sequence.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.1
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• pp.1-13
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• 2024

This study assessed the efficacy of improving the accuracy of reservoir water level prediction models by employing automated machine learning models and efficient cross-validation methods for time-series data. Considering the inherent complexity and non-linearity of time-series data related to reservoir water levels, we proposed an optimized approach for model selection and training. The performance of twelve models was evaluated for the Obong Reservoir in Gangneung, Gangwon Province, using the TPOT (Tree-based Pipeline Optimization Tool) and four cross-validation methods, which led to the determination of the optimal pipeline model. The pipeline model consisting of Extra Tree, Stacking Ridge Regression, and Simple Ridge Regression showed outstanding predictive performance for both training and test data, with an R² (Coefficient of determination) and NSE (Nash-Sutcliffe Efficiency) exceeding 0.93. On the other hand, for predictions of water levels 12 hours later, the pipeline model selected through time-series split cross-validation accurately captured the change pattern of time-series water level data during the test period, with an NSE exceeding 0.99. The methodology proposed in this study is expected to greatly contribute to the efficient generation of reservoir water level predictions in regions with high rainfall variability.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.2
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• pp.123-130
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• 2013

In this paper, the delamination and failures in frequency selected surface(FSS) caused by residual stresses in the FSS embedded hybrid composites due to the difference between the coefficients of thermal expansion of components and the transmission characteristic changes due to deformation of FSS patterns by residual stresses were studied. FSS may have different electromagnetic characteristics depending on the type of element, design variables, and arrangement. Design variables of dipole FSS were determined using PSO(Particle Swarm Optimization) to obtain the transmission characteristic for the target resonant frequency. Subsequently, the design variables of other types of N-pole(tripole, cross dipole, and Jerusalem cross) were determined based on the dimensions of the dipole for the comparisons of residual stresses of FSS embedded composite structures and transmission characteristics. In addition, effects of FSS pattern, and stacking sequence of composite laminates were considered.