• 제목/요약/키워드: Smart structure

검색결과 1,815건 처리시간 0.031초

고출력 LED 패키지의 열 전달 개선을 위한 금속-실리콘 병렬 접합 구조의 특성 분석 (Heat Conduction Analysis of Metal Hybrid Die Adhesive Structure for High Power LED Package)

  • 임해동;최봉만;이동진;이승걸;박세근;오범환
    • 한국광학회지
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    • 제24권6호
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    • pp.342-346
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    • 2013
  • 고출력 LED 패키지의 방열 특성 향상을 위하여, 다이 접합부에 실리콘 접착제와 금속 패턴의 병렬 접합 구조를 적용하여 열 유동 해석을 수행하였다. 그 결과, LED 칩에서 발생한 열은 주로 금속 패턴 구조물을 통해 기판으로 효과적으로 전달되고 있으나, 패턴 구조물의 크기에 따라 효율의 차이가 있음을 확인하였고, 그 효과를 정량화하기 위해 정규화 길이를 도입하여 칩과 금속 패턴 구조물의 면적에 따른 열 저항을 비교하였다. 정규화 길이가 길어지면 금속 패턴 구조물에 의한 열 우회 경로가 칩에 고르게 분포하여 열 저항이 감소하였으며, 그 값은 단순 병렬 열 저항 이론 값보다 다소 큰 수치로 수렴하지만, 충분한 열 저항 개선 효과를 얻을 수 있었다.

직조 형태의 지능형 연성 복합재료를 이용한 쉘 구동기의 제작 (Fabrication of Shell Actuator using Woven Type Smart Soft Composite)

  • 한민우;송성혁;추원식;이경태;이재원;안성훈
    • 한국정밀공학회지
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    • 제30권1호
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    • pp.39-46
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    • 2013
  • Smart material such as SMA (Shape Memory Alloy) has been studied in various ways because it can perform continuous, flexible, and complex actuation in simple structure. Smart soft composite (SSC) was developed to achieve large deformation of smart material. In this paper, a shell actuator using woven type SSC was developed to enhance stiffness of the structure while keeping its deformation capacity. The fabricated actuator consisted of a flexible polymer and woven structure which contains SMA wires and glass fibers. The actuator showed various actuation motions by controlling a pattern of applied electricity because the SMA wires are embedded in the structure as fibers. To verify the actuation ability, we measured its maximum end-edge bending angle, twisting angle, and actuating force, which were $103^{\circ}$, $10^{\circ}$, and 0.15 N, respectively.

Intelligent design of retaining wall structures under dynamic conditions

  • Yang, Haiqing;Koopialipoor, Mohammadreza;Armaghani, Danial Jahed;Gordan, Behrouz;Khorami, Majid;Tahir, M.M.
    • Steel and Composite Structures
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    • 제31권6호
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    • pp.629-640
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    • 2019
  • The investigation of retaining wall structures behavior under dynamic loads is considered as one of important parts for designing such structures. Generally, the performance of these structures is under the influence of the environment conditions and their geometry. The aim of this research is to design retaining wall structures based on smart and optimal systems. The use of accuracy and speed to assess the structures under different conditions is one of the important parts sought by designers. Therefore, optimal and smart systems are able to have better addressing these problems. Using numerical and coding methods, this research investigates the retaining wall structure design under different dynamic conditions. More than 9500 models were constructed and considered for modelling design. These designs include height and thickness of the wall, soil density, rock density, soil friction angle, and peak ground acceleration (PGA) variables. Accordingly, a neural network system was developed to establish an appropriate relationship between data to obtain safety factor (SF) of retaining walls under different seismic conditions. Different parameters were analyzed and the effect of each parameter was assessed separately. According to these analyses, the structure optimization was performed to increase the SF values. The optimal and smart design showed that under different PGA conditions, the structure performance can be appropriately improved while utilization of the initial (or basic) parameters leads to the structure failure. Therefore, by increasing accuracy and speed, smart methods could improve the retaining structure performance in controlling the wall failure. The intelligent design process of this study can be applied to some other civil engineering applications such as slope stability.

Modeling and fast output sampling feedback control of a smart Timoshenko cantilever beam

  • Manjunath, T. C.;Bandyopadhyay, B.
    • Smart Structures and Systems
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    • 제1권3호
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    • pp.283-308
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    • 2005
  • This paper features about the modeling and design of a fast output sampling feedback controller for a smart Timoshenko beam system for a SISO case by considering the first 3 vibratory modes. The beam structure is modeled in state space form using FEM technique and the Timoshenko beam theory by dividing the beam into 4 finite elements and placing the piezoelectric sensor/actuator at one location as a collocated pair, i.e., as surface mounted sensor/actuator, say, at FE position 2. State space models are developed for various aspect ratios by considering the shear effects and the axial displacements. The effects of changing the aspect ratio on the master structure is observed and the performance of the designed FOS controller on the beam system is evaluated for vibration control.

Vibration response of smart concrete plate based on numerical methods

  • Taherifar, Reza;Chinaei, Farhad;Faramoushjan, Shahram Ghaedi;Esfahani, Mohammad Hossein Nasr;Esfahani, Shabnam Nasr;Mahmoudi, Maryam
    • Smart Structures and Systems
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    • 제23권4호
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    • pp.387-392
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    • 2019
  • This research deals with the vibration analysis of embedded smart concrete plate reinforced by zinc oxide (ZnO). The effective material properties of structure are considered based on mixture rule. The elastic medium is simulated by orthotropic visco-Pasternak medium. The motion equations are derived applying Sinusoidal shear deformation theory (SSDT). The differential quadrature (DQ) method is applied for calculating frequency of structure. The effects of different parameters such as volume percent of ZnO, boundary conditions and geometrical parameters on the frequency of system are shown. The results are compared with other published works in the literature. Results indicate that the ZnO have an important role in frequency of structure.

Using artificial intelligence to solve a smart structure problem

  • Kaiwen, Liu;Jun, Gao;Ruizhe, Qiu
    • Structural Engineering and Mechanics
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    • 제85권3호
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    • pp.393-406
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    • 2023
  • Smart structures are those structure that could adopt some behavior to prevent instability in their responses. The recognition of stability deterioration has been performed through rigid mathematical formulations in control theory and unpredicted results could not be addressed in control systems since they are able to only work under their predefined condition. On the other hand, incorporating all affecting parameters could result in high computational cost and delay time in the response of the systems. Artificial intelligence (AI) method has shown to be a promising methodology not only in the computer science by at everyday life and in engineering problems. In the present study, we exploit the capabilities of artificial intelligence method to obtain frequency response of a smart structure. In this regard, a comprehensive development of equations is presented using Hamilton' principle and first order shear deformation theory. The equations were solved by numerical methods and the results are used to train an artificial neural network (ANN). It is demonstrated that ANN modeling could provide accurate results in comparison to the numerical solutions and it take less time than numerical solution.

스마트 TMD 제어를 위한 강화학습 알고리즘 성능 검토 (Performance Evaluation of Reinforcement Learning Algorithm for Control of Smart TMD)

  • 강주원;김현수
    • 한국공간구조학회논문집
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    • 제21권2호
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    • pp.41-48
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    • 2021
  • A smart tuned mass damper (TMD) is widely studied for seismic response reduction of various structures. Control algorithm is the most important factor for control performance of a smart TMD. This study used a Deep Deterministic Policy Gradient (DDPG) among reinforcement learning techniques to develop a control algorithm for a smart TMD. A magnetorheological (MR) damper was used to make the smart TMD. A single mass model with the smart TMD was employed to make a reinforcement learning environment. Time history analysis simulations of the example structure subject to artificial seismic load were performed in the reinforcement learning process. Critic of policy network and actor of value network for DDPG agent were constructed. The action of DDPG agent was selected as the command voltage sent to the MR damper. Reward for the DDPG action was calculated by using displacement and velocity responses of the main mass. Groundhook control algorithm was used as a comparative control algorithm. After 10,000 episode training of the DDPG agent model with proper hyper-parameters, the semi-active control algorithm for control of seismic responses of the example structure with the smart TMD was developed. The simulation results presented that the developed DDPG model can provide effective control algorithms for smart TMD for reduction of seismic responses.

임시교실용 모듈러 건축물의 품질기준 마련을 위한 특성비교 (Comparison of Characteristics for Establishing Quality Standards of Modular Buildings for Temporary Classrooms)

  • 이종성;박재웅;임군수;김종;한민철;한천구
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2023년도 봄 학술논문 발표대회
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    • pp.83-84
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    • 2023
  • Wall structure smart modular is a building construction method where modules are manufactured in a factory and assembled on-site. This method is gaining popularity in the construction industry as it reduces construction time and mitigates risks such as material supply and labor costs. Wall structure smart modular is necessary as it provides comfortable temporary classroom space during renovation and remodeling of aging school buildings. The structure and characteristics of each type of temporary classroom modular were compared, and wall structure modular showed superior performance in terms of height and weight competitiveness compared to mixed structures. With these advantages, wall structure modular can ensure economic efficiency and recyclability as a temporary classroom. In the future, we aim to compare and analyze the standards such as inter-floor noise and heat transfer coefficient for wall structure and mixed structures.

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