• Title/Summary/Keyword: Energy Element

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Numerical Analysis of Laboratory Heating Experiment on Granite Specimen (화강암의 실내 가열실험에 대한 수치해석적 검토)

  • Dong-Joon, Youn;Changlun, Sun;Li, Zhuang
    • Tunnel and Underground Space
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    • v.32 no.6
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    • pp.558-567
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    • 2022
  • The evolution of temperature and thermal stress in a granite specimen is studied via heating experiment in the context of a high-level radioactive waste repository. A heating condition based on the decay-induced heat is applied to a cubic granite specimen to measure the temperature and stress distributions and their evolution over time. The temperature increases quickly due to heat conduction along the heated surfaces, but a significant amount of thermal energy is also lost through other surfaces due to air convection and conduction into the loading machine. A three-dimensional finite element-based model is used to numerically reproduce the experiment, and the thermo-mechanical coupling behavior and modeling conditions are validated with the comparison to the experimental results. The most crucial factors influencing the heating experiment are analyzed and summarized in this paper for future works.

Optimised neural network prediction of interface bond strength for GFRP tendon reinforced cemented soil

  • Zhang, Genbao;Chen, Changfu;Zhang, Yuhao;Zhao, Hongchao;Wang, Yufei;Wang, Xiangyu
    • Geomechanics and Engineering
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    • v.28 no.6
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    • pp.599-611
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    • 2022
  • Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.

Effects of metal dopant content on mechanical properties of Ti-Cu-N films

  • Hyun S. Myung;Lee, Hyuk M.;Kim, Sang S.;Jeon G. Han
    • Proceedings of the Korean Institute of Surface Engineering Conference
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    • 2001.11a
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    • pp.37-37
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    • 2001
  • TiN coatings were applied for VarIOUS application fields, because of a good wear-resistance and a high hardness. Typically, TiN thin films show the hardness of 25GPa and friction coefficient of 0.6. However, in many field, one is looking for a more improved tool which has low friction coefficient and high wear resistance. The main motivation of this study is to characterize the influence of copper dopant content on TiN thin films. Ti-Cu-N thin films were deposited onto D2 steel substrates by PVD processing with various magnetron current densities (Cu contents). In this work, we synthesized titanium nitride films similar with reported typical titanium nitride films and synthesized Ti-Cu-N thin films with the addition of elemental copper which is measured improved hardness more than pure TiN films with copper content variables. This films has preferred oriented films of (111) direction. In addition, It was found that there is a strong correlation between content of various metal and film characteristics such as preferred orientation, grain size, hardness and friction coefficient and so, in future study, improved mechanical properties of TiN films can be controlled by change in target current density. The Ti-Cu-N film will show apparent hardness improvement and mechanical properties enhancement, when doping element is added onto TiN thin films. Film structure, chemical composition, mechanical properties were investigated by means of X-ray diffraction(XRD), scanning electron microscopy(SEM), transmission electron microscopy (TEM), energy dispersive spectroscopy(EDS), wear resistance tester and nanohardness tester.

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Operating Voltage Prediction in Mobile Semiconductor Manufacturing Process Using Machine Learning (기계학습을 활용한 모바일 반도체 제조 공정에서 동작 전압 예측)

  • Inhwan Baek;Seungwoo Jang;Kwangsu Kim
    • Journal of the Semiconductor & Display Technology
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    • v.22 no.1
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    • pp.124-128
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    • 2023
  • Semiconductor engineers have long sought to enhance the energy efficiency of mobile semiconductors by reducing their voltage. During the final stages of the semiconductor manufacturing process, the screening and evaluation of voltage is crucial. However, determining the optimal test start voltage presents a significant challenge as it can increase testing time. In the semiconductor manufacturing process, a wealth of test element group information is collected. If this information can be controlled to predict the test voltage, it could lead to a reduction in testing time and increase the probability of identifying the optimal voltage. To achieve this, this paper is exploring machine learning techniques, such as linear regression and ensemble models, that can leverage large amounts of information for voltage prediction. The outcomes of these machine learning methods not only demonstrate high consistency but can also be used for feature engineering to enhance accuracy in future processes.

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A Review on "Kidney" Functional System in Korean Medicine : From the Perspective of Molecular Physiology (한의학 신(腎) 기능계에 관한 분자생리학적 고찰)

  • Miso S., Park;Junghyo, Cho;Wangjung, Hur;Horyong, Yoo
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.36 no.5
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    • pp.169-174
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    • 2022
  • In Korean medicine, the "five viscera" theory develops into the theory of homeostasis, in which the dynamic equilibrium state of the yin yang and five elements in the body maintain the balance of the physiological functions. The "five viscera" of the "five elements" can also be referred to as the "functional system," a conceptual system that includes all functional interactions mediated by the organ as well as the organ itself. Nowadays, the structure and function of the organs and tissues in the body are being re-examined, and there is now enough evidence that organs, structures, and their functions that belong to the same "element" are all connected in terms of energy metabolism. The functional system of the "kidney" includes the kidney itself, as well as other components that belong to "water" of the five elements such as bladder, bone, ear, essence, memory, and fear. The authors will discuss the latest findings in science and medicine to expand the understanding of the "Kidney" functional system to the level of molecular physiology.

Seismic retrofit of steel structures with re-centering friction devices using genetic algorithm and artificial neural network

  • Mohamed Noureldin;Masoum M. Gharagoz;Jinkoo Kim
    • Steel and Composite Structures
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    • v.47 no.2
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    • pp.167-184
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    • 2023
  • In this study, a new recentering friction device (RFD) to retrofit steel moment frame structures is introduced. The device provides both self-centering and energy dissipation capabilities for the retrofitted structure. A hybrid performance-based seismic design procedure considering multiple limit states is proposed for designing the device and the retrofitted structure. The design of the RFD is achieved by modifying the conventional performance-based seismic design (PBSD) procedure using computational intelligence techniques, namely, genetic algorithm (GA) and artificial neural network (ANN). Numerous nonlinear time-history response analyses (NLTHAs) are conducted on multi-degree of freedom (MDOF) and single-degree of freedom (SDOF) systems to train and validate the ANN to achieve high prediction accuracy. The proposed procedure and the new RFD are assessed using 2D and 3D models globally and locally. Globally, the effectiveness of the proposed device is assessed by conducting NLTHAs to check the maximum inter-story drift ratio (MIDR). Seismic fragilities of the retrofitted models are investigated by constructing fragility curves of the models for different limit states. After that, seismic life cycle cost (LCC) is estimated for the models with and without the retrofit. Locally, the stress concentration at the contact point of the RFD and the existing steel frame is checked being within acceptable limits using finite element modeling (FEM). The RFD showed its effectiveness in minimizing MIDR and eliminating residual drift for low to mid-rise steel frames models tested. GA and ANN proved to be crucial integrated parts in the modified PBSD to achieve the required seismic performance at different limit states with reasonable computational cost. ANN showed a very high prediction accuracy for transformation between MDOF and SDOF systems. Also, the proposed retrofit showed its efficiency in enhancing the seismic fragility and reducing the LCC significantly compared to the un-retrofitted models.

Analysis of Damping Performance of Hysteretic Dampers of Buckling restrained Braced Type According to eccentricity of school buildings with Torsional irregularities (비틀림 비정형을 가지는 학교건물의 편심율에 따른 좌굴방지가새형 이력댐퍼의 제진성능분석)

  • Kim, Yu-Seong;Lee, Joon-Ho;Kim, Gee-Chul
    • Journal of Korean Association for Spatial Structures
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    • v.23 no.2
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    • pp.37-44
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    • 2023
  • In the case of a school building, even though it is a regular structure in terms of plan shape, if the masonry infill wall acts as a lateral load resisting element, it can be determined as a torsionally irregular building. As a result, the strength and ductility of the structure are reduced, which may cause additional earthquake damage to the structure. Therefore, in this study, a structure similar to a school building with torsional irregularity was selected as an example structure and the damping performance of the PC-BRB was analyzed by adjusting the eccentricity according to the amount of masonry infilled wall. As a result of nonlinear dynamic analysis after seismic reinforcement, the torsional irregularity of each floor was reduced compared to before reinforcement, and the beams and column members of the collapse level satisfied the performance level due to the reduction of shear force and the reinforcement of stiffness. The energy dissipation of PC-BRB was similar in the REC-10 ~ REC-20 analytical models with an eccentricity of 20% or less. REC-25 with an eccentricity of 25% was the largest, and it is judged that it is effective to combine and apply PC-BRB when it has an eccentricity of 25% or more to control the torsional behavior.

Thermal Design of High Power Semiconductor Using Insulated Metal Substrate (Insulated Metal Substrate를 사용한 고출력 전력 반도체 방열설계)

  • Bongmin Jeong;Aesun Oh;Sunae Kim;Gawon Lee;Hyuncheol Bae
    • Journal of the Microelectronics and Packaging Society
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    • v.30 no.1
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    • pp.63-70
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    • 2023
  • Today, the importance of power semiconductors continues to increase due to serious environmental pollution and the importance of energy. Particularly, SiC-MOSFET, which is one of the wide bandgap (WBG) devices, has excellent high voltage characteristics and is very important. However, since the electrical properties of SiC-MOSFET are heatsensitive, thermal management through a package is necessary. In this paper, we propose an insulated metal substrate (IMS) method rather than a direct bonded copper (DBC) substrate method used in conventional power semiconductors. IMS is easier to process than DBC and has a high coefficient of thermal expansion (CTE), which is excellent in terms of cost and reliability. Although the thermal conductivity of the dielectric film, which is an insulating layer of IMS, is low, the low thermal conductivity can be sufficiently overcome by allowing a process to be very thin. Electric-thermal co-simulation was carried out in this study to confirm this, and DBC substrate and IMS were manufactured and experimented for verification.

Impact Absorption Performance of Multi-layered Composite Structures based on Material-Structure Optimization (소재-구조 최적화 기반 다층-복합재료구조 충격흡수성능)

  • Kim, Byung-Jo;Kim, Tae-Won
    • Composites Research
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    • v.22 no.3
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    • pp.66-73
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    • 2009
  • Total thickness, areal density and mass moment of inertia of materials are important material factors for structural characteristics. In this work, a material-structural optimization was performed up to the maximum ballistic limit of multi-layered composite structures under high impact velocity followed by the investigation of the influence of these factors on an impact absorption performance. A unified model combined with Florence's and Awerbuch-Bonder's models was used in optimizing the multi-layered composite structure consisting of CMC, rubber, aluminum and Al-foam. Total thickness, areal density and mass moment of inertia were used for the optimization constraint. As shown in the results, the ballistic limit determined from a newly developed unified model was closely similar to the finite clement analysis. Additionally, the ballistic limit and impact absorption energy obtained by the optimized structure were improved approximately 16.8% and 26.7%, respectively comparing with a not optimized multi-layered structure.

Performance-based plastic design of buckling-restrained braced frames with eccentric configurations

  • Elnaz Zare;Mohammad Gholami;Esmail Usefvand;Mojtaba Gorji Azandariani
    • Earthquakes and Structures
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    • v.24 no.5
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    • pp.317-331
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    • 2023
  • The buckling-restrained braced frames with eccentric configurations (BRBFECs) are stable cyclic behavior and high energy absorption capacity. Furthermore, they have an architectural advantage for creating openings like eccentrically braced frames (EBFs). In the present study, it has been suggested to use the performance-based plastic design (PBPD) method to calculate the design base shear of the BRBFEC systems. Moreover, in this study, to reduce the required steel material, it has been suggested to use the performance-based practical design (PBPD) method instead of the force-based design (FBD) method for the design of this system. The 3-, 6-, and 9-story buildings with the BRBFEC system were designed, and the finite element models were modeled. The seismic performance of the models was investigated using two suits of ground motions representing the maximum considered earthquake (MCE) and design basis earthquake (DBE) seismic hazard levels. The results showed that the models designed with the suggested method, which had lower weights compared to those designed with the FBD method, had a desirable seismic performance in terms of maximum story drift and ductility demand under earthquakes at both MCE and DBE seismic hazard levels. This suggests that the steel weights of the structures designed with the PBPD method are about 13% to 18% lesser than the FBD method. However, the residual drifts in these models were higher than those in the models designed with the FBD method. Also, in earthquakes at the DBE hazard level, the residual drifts in all models except the PBPD-6s and PBPD-9s models were less than the allowable reparability limit.