• 한국소음진동공학회논문집
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• 제16권9호
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• pp.919-925
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• 2006

An accurate mathematical model for complex stiffness of the pneumatic spring would be necessary for an efficient design of a pneumatic spring used in vibration isolation tables for precision instruments such as optical devices or nano-scale equipments. A diaphragm, often employed for prevention of air leakage, plays a significant role of complex stiffness element as well as the pressurized air itself Therefore, effects of the diaphragm need to be included in the dynamic model for a more faithful description of dynamic behavior of pneumatic spring. But the complex stiffness of diaphragm is difficult to predict In an analytical way, since it is a rubber membrane of complicated shape in itself. Moreover, the diaphragm should be expandable in response to pressurization inside a chamber, which makes direct measurement of complex stiffness of diaphragm extremely difficult. In our earlier research, the complex stiffness of diaphragm was indirectly measured, which was just to eliminate the theoretical stiffness of pressurized air from the measured complex stiffness of the pneumatic spring. In order to reflect complex stiffness of inflated diaphragm on the total stiffness at the initial design or design improvement stage, however. it is required to be able to predict beforehand. In this paper, how to predict the complex stiffness of inflated rubber diaphragm by commercial FE codes (e.g. ABAQUS) will be discussed and the results will be compared with the indirectly measured values.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.844-849
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• 2006

Accurate modeling of complex dynamic stiffness of the pneumatic springs is crucial for an efficient design of vibration isolation tables for precision instruments such as optical devices or nano-technology equipments. Besides pressurized air itself, diaphragm made of rubber materials, essentially employed for prevention of air leakage, plays a significant contribution to the total complex stiffness. Therefore, effects of the diaphragm should be taken care of precisely. The complex stiffness of an inflated diaphragm is difficult to predict or measure, since it is always working together with the pressurized air. In our earlier research, the complex stiffness of a diaphragm was indirectly estimated simply by subtracting stiffness of the pressurized air from measurement of the total complex stiffness for a single chamber pneumatic spring. In order to reflect dynamic stiffness of inflated diaphragm on the total stiffness at the initial design or design improvement stage, however, it is required to be able to predict beforehand. In this presentation, how to predict the complex stiffness of inflated rubber diaphragm by commercial FE codes(e.g. ABAQUS) will be discussed and the results will be compared with the indirectly measured values.

• Advances in nano research
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• 제16권6호
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• pp.623-638
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• 2024

This study investigates the thermal post-buckling behavior of concrete eccentric annular sector plates reinforced with graphene oxide powders (GOPs). Employing the minimum total potential energy principle, the plates' stability and response under thermal loads are analyzed. The Haber-Schaim foundation model is utilized to account for the support conditions, while the transform differential quadrature method (TDQM) is applied to solve the governing differential equations efficiently. The integration of GOPs significantly enhances the mechanical properties and stability of the plates, making them suitable for advanced engineering applications. Numerical results demonstrate the critical thermal loads and post-buckling paths, providing valuable insights into the design and optimization of such reinforced structures. This study presents a machine learning algorithm designed to predict complex engineering phenomena using datasets derived from presented mathematical modeling. By leveraging advanced data analytics and machine learning techniques, the algorithm effectively captures and learns intricate patterns from the mathematical models, providing accurate and efficient predictions. The methodology involves generating comprehensive datasets from mathematical simulations, which are then used to train the machine learning model. The trained model is capable of predicting various engineering outcomes, such as stress, strain, and thermal responses, with high precision. This approach significantly reduces the computational time and resources required for traditional simulations, enabling rapid and reliable analysis. This comprehensive approach offers a robust framework for predicting the thermal post-buckling behavior of reinforced concrete plates, contributing to the development of resilient and efficient structural components in civil engineering.

• 한국산학기술학회논문지
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• 제17권7호
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• pp.42-48
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• 2016

본 논문에서는 플라이백 DC-DC 컨버터에 사용되는 출력전압 정보를 보다 정확하게 감지하는 피크검출기를 집적회로로 설계하였다. 제안하는 피크검출기의 회로는 하나의 op-amp와 세 개의 트랜지스터로 이루어져 있다. 제안하는 회로는 단순한 구조로 이루어져 있기 때문에 제안하는 회로는 출력전압을 감지하는 과정에서 지연시간을 최소화 할 수 있다. 회로에서 op-amp와 몇 개의 트랜지스터를 사용함으로써, 제안하는 피크검출기가 종래의 커패시터와 다이오드로 설계된 피크검출기를 대신해 칩의 집적화가 가능해지고, 플라이백 컨버터의 모듈을 구성하는 소자가 트랜지스터로 대체되고 칩의 면적이 줄어들어 가격을 줄일 수 있다. 제안하는 회로는 0.35 um CMOS 공정을 이용하여 칩으로 제작하여 측정하였고, 칩 측정결과 모의실험결과와 잘 일치함을 보였다. 시뮬레이션 결과 사인파의 입력신호를 출력신호가 최대 0.3 ~ 3.1 %의 오차 범위 내에서 피크전압을 유지하는 것을 확인하였다. 칩 측정결과 모의실험결과와 잘 일치함을 보였다. 제안하는 회로의 결과를 통하여 종래의 피크검출기 회로의 좋지 않은 레귤레이션을 향상시키기 위하여 높은 플라이백 컨버터의 동작을 보일 수 있다. 플라이백 컨버터의 출력전압을 정확하게 감지하여 안정적인 컨버터 동작을 할 수 있을 것으로 사료된다.