• 제목/요약/키워드: Network diameter

검색결과 286건 처리시간 0.029초

The effect of thickness and translucency of polymer-infiltrated ceramic-network material on degree of conversion of resin cements

  • Barutcigil, Kubilay;Buyukkaplan, Ulviye Sebnem
    • The Journal of Advanced Prosthodontics
    • /
    • 제12권2호
    • /
    • pp.61-66
    • /
    • 2020
  • PURPOSE. The aim of the present study was to determine the degree of conversion of light- and dual-cured resin cements used in the cementation of all-ceramic restorations under different thicknesses of translucent (T) and high-translucent (HT) polymer-infiltrated ceramic-network (PICN) material. MATERIALS AND METHODS. T and HT PICN blocks were prepared at 0.5, 1.0, 1.5, and 2.0 mm thicknesses (n=80). Resin cement samples were prepared with a diameter of 6 mm and a thickness of 100 ㎛. Light-cured resin cement was polymerized for 30 seconds, and dual-cure resin cement was polymerized for 20 seconds (n=180). Fourier transform infrared spectroscopy (FTIR) was used for degree of conversion measurements. The obtained data were analyzed with ANOVA and Tukey HSD, and independent t-test. RESULTS. As a result of FTIR analysis, the degree of conversion of the light-cured resin cement prepared under 1.5- and 2.0-mm-thick T and HT ceramics was found to be lower than that of the control group. Regarding the degree of conversion of the dual-cured resin cement group, there was no significant difference from the control group. CONCLUSION. Within the limitation of present study, it can be concluded that using of dual cure resin cement can be suggested for cementation of PICN material, especially for thicknesses of 1.5 mm and above.

X-Hypercubes의 연결성과 그 응용 (Conncetiveity of X-Hypercubes and Its Applications)

  • 권경희
    • 한국정보처리학회논문지
    • /
    • 제1권1호
    • /
    • pp.92-98
    • /
    • 1994
  • Hypercubes와 유사한 구조를 가진 X-hypercubes는 hypercubes와 같은수의 node와 edge를 갖고 있다.그러나 node들을 연결한는 방법을 약간 바꾸어 줌으로써 X-hypercubes내의 node들간의 통신시의 delay는 hypercubes 의 그것보다 훨씬 적어지는 것을 기대할 수 있다. 본 논문에서는 X-hypercubes를 새롭게 정의함으로써 두 node들 간의 연결에 관한 조건들을 명확히 해준다.이 정의에 대한 응용으로서,본 논문은 hypercubes 를 X-hypercubes로 그리고 X-hypercubes 를 hypercubes로 embedding시키는 algorthm을 보여준다.이는 이들 두 network에서 운용되는 program 들이 최소한 overhead만으로써 서로 호완될 수 있음을 말해준다.또한 본 논문은 hypercubes 에서의 bitionic merge sort를 simulate함으로써,X-hypercubes에서 운용될 수 있는 bitonic merge sort도 보여주고 있다.

  • PDF

차량 간 통신환경에서의 무선네트워크 성능 측정 및 분석 (An Evaluation of the Performance of Wireless Network in Vehicle Communication Environment)

  • 김승천
    • 한국통신학회논문지
    • /
    • 제36권10A호
    • /
    • pp.816-822
    • /
    • 2011
  • 본 논문은 모바일 컨버전스를 위해서는 가장 필요하다고 보이는 대중적인 무선통신 방법인 IEEE802.11 무선랜의 성능이 이동성을 가지는 환경에서 어떠한지를 실제로 측정하고 성능을 분석해본다. 성능 분석을 위해서는 기존의 IEEE802.11b/g와 차량간 통신(V2V) 환경에 적합하게 설계된 IEE802.11p에 대해서 성능을 측정하여 분석하였다. 본 논문에서는 기존의 IEEE802.11b/g는 V2I, IEEE802.11p는 V2I와 V2V에서 실험을 진행하였다. 따라서 각각 자동차의 주행속도를 점차 증가시켜 실험을 진행하였으며, 그에 따른 통신반경, 링크접속시간, 데이터 전송속도, 지연시간을 측정하였다. 또한 무선 채널에 512, 1024, 1518 byte의 부하를 가지게 함으로써, 주위에 통신량이 많고 적은 상황에 따른 성능도 확인하였다. 결론을 통해서는 분석된 내용을 기반으로 향후 연구 내용을 논한다.

확장성 있는 Peer-to-Peer 서비스 제공을 위한 분산적 피어 선택 기법 (A Distributed Peer Selection Method for Supporting Scalable Peer-to-Peer Services)

  • 박재성
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
    • /
    • 제2권11호
    • /
    • pp.471-474
    • /
    • 2013
  • 본 논문에서는 효율적인 peer-to-peer(P2P) 네트워크의 토폴로지 구축을 위해 참여 피어의 용양과 데이터 소스까지의 홉 수를 고려한 분산적 부모 피어 선택 기법을 제안한다. 이를 위해 우선 각 피어가 부모 피어로 선정될 확률을 결정하기 위해 피어의 용양과 거리를 결합하는 방안을 제시하고 각 피어가 분산적으로 관리하는 이웃피어의 상태 정보를 이용하여 확률적으로 부모 피어를 선택하는 방안을 제시한다. 모의실험을 통해 제안 기법은 용양이 큰 피어가 보다 많은 자식 피어들을 지원하게 함으로써 타 기법들에 비해 동일 환경에서 P2P 네트워크의 지름과 네트워크 구성의 효율성 측면에서 우수함을 정량적으로 검증하였다.

A Monochromatic Soft X-ray Generation from Femtosecond Laser-produced Plasma with Aluminum

  • Son, Joon-Gon;Hwang, Byung-Jun;Seo, Okkyun;Kim, Jae Myung;Noh, Do Young;Ko, Do-Kyeong
    • Journal of the Korean Physical Society
    • /
    • 제73권12호
    • /
    • pp.1834-1839
    • /
    • 2018
  • A tabletop ultrafast soft x-ray has been generated from the laser-produce plasma with a femtosecond pulsed Ti:Sapphire laser. The estimated total flux of Al $K{\alpha}$ is of $2.2{\times}10^9photons/sec$ in $4{\pi}$ radian and the parameters related to the optical performance were obtained. The tungsten/silicon multilayer, flat quartz and bent thallium acid phthalate (TLAP) crystal were used for monochromatization of soft x-ray to refine the aluminum $K{\alpha}$ radiation and compared the respective value of $E/{\Delta}E$. To estimate the size of the x-ray source beam generated by a fs laser, the approximation using the FWHM obtained from the x-ray beam scan near the focal point was discussed, and the size of the diameter was about $9.76{\mu}m$.

반응표면법-역전파신경망을 이용한 AA5052 판재 점진성형 공정변수 모델링 및 유전 알고리즘을 이용한 다목적 최적화 (Modeling of AA5052 Sheet Incremental Sheet Forming Process Using RSM-BPNN and Multi-optimization Using Genetic Algorithms)

  • 오세현;샤오샤오;김영석
    • 소성∙가공
    • /
    • 제30권3호
    • /
    • pp.125-133
    • /
    • 2021
  • In this study, response surface method (RSM), back propagation neural network (BPNN), and genetic algorithm (GA) were used for modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goal of optimization is to determine the maximum forming angle and minimum surface roughness, while varying the production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model and BPNN model to model the variations in the forming angle and surface roughness based on variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process the GA. The results showed that RSM and BPNN can be effectively used to control the forming angle and surface roughness. The optimized Pareto front produced by the GA can be utilized as a rational design guide for practical applications of AA5052 in the ISF process

Machine learning techniques for prediction of ultimate strain of FRP-confined concrete

  • Tijani, Ibrahim A.;Lawal, Abiodun I.;Kwon, S.
    • Structural Engineering and Mechanics
    • /
    • 제84권1호
    • /
    • pp.101-111
    • /
    • 2022
  • It is widely known that axially loaded fiber-reinforced polymer (FRP) confined concrete presents significant and enhanced mechanical properties with reference to the unconfined concrete. Therefore, to predict the mechanical behavior of FRP-confined concrete two quantities-peak strength and ultimate strain are required. Despite the significant advances, the determination of the ultimate strain of FRP-confined concrete is one of the most challenging problems to be resolved. This is often attributed to our persistence in desiring the conventional methods as the sole technique to examine this phenomenon and the complex nature of the ultimate strain of FRP-confined concrete. To bridge the research gap, this study adopted two machine learning (ML) techniques-artificial neural network (ANN) and Gaussian process regression (GPR)-to analyze observations obtained from 627 datasets of FRP-confined concrete circular and non-circular sections under axial loading test. Besides, the techniques are also used to predict the ultimate strain of FRP-confined concrete. Seven parameters namely width/diameter of the specimens, corner radius ratio, the strength of concrete, FRP elastic modulus, FRP thickness, FRP tensile rupture strain, and the axial strain of unconfined concrete-are the input parameters used to predict the ultimate strain of FRP-confined concrete. The results of the current study highlight the merit of using AI techniques in structural engineering applications given their extraordinary ability to comprehend multidimensional phenomena of FRP-confined concrete structures with ease, low computational cost, and high performance over the existing empirical models.

Using ANN to predict post-heating mechanical properties of cementitious composites reinforced with multi-scale additives

  • Almashaqbeh, Hashem K.;Irshidat, Mohammad R.;Najjar, Yacoub
    • Smart Structures and Systems
    • /
    • 제29권2호
    • /
    • pp.337-350
    • /
    • 2022
  • This paper focuses on predicting the post-heating mechanical properties of cementitious composites reinforced with multi-scale additives using the Artificial Neural Network (ANN) approach. A total of four different feed-forward ANN models are developed using 261 data sets collected from 18 published sources. The models are optimized using 12 input parameters selected based on a comprehensive literature review to predict the residual compressive strength, the residual flexural strengths, elastic modulus, and fracture energy of heat-damaged cementitious specimens. Furthermore, the ANN is employed to predict the impact of several variables including; the content of polypropylene (PP) microfibers and carbon nanotubes (CNTs) used in the concrete, mortar, or paste mix design, length of PP fibers, the average diameter of CNTs, and the average length of CNTs. The influence of the studied parameters is investigated at different heating levels ranged from 25℃ to 800℃. The results demonstrate that the developed ANN models have a strong potential for predicting the mechanical properties of the heated cementitious composites based on the mixing ingredients in addition to the heating conditions.

Probabilistic bearing capacity assessment for cross-bracings with semi-rigid connections in transmission towers

  • Zhengqi Tang;Tao Wang;Zhengliang Li
    • Structural Engineering and Mechanics
    • /
    • 제89권3호
    • /
    • pp.309-321
    • /
    • 2024
  • In this paper, the effect of semi-rigid connections on the stability bearing capacity of cross-bracings in steel tubular transmission towers is investigated. Herein, a prediction method based on the hybrid model which is a combination of particle swarm optimization (PSO) and backpropagation neural network (BPNN) is proposed to accurately predict the stability bearing capacity of cross-bracings with semi-rigid connections and to efficiently conduct its probabilistic assessment. Firstly, the establishment of the finite element (FE) model of cross-bracings with semi-rigid connections is developed on the basis of the development of the mechanical model. Then, a dataset of 7425 samples generated by the FE model is used to train and test the PSO-BPNN model, and the accuracy of the proposed method is evaluated. Finally, the probabilistic assessment for the stability bearing capacity of cross-bracings with semi-rigid connections is conducted based on the proposed method and the Monte Carlo simulation, in which the geometric and material properties including the outer diameter and thickness of cross-sections and the yield strength of steel are considered as random variables. The results indicate that the proposed method based on the PSO-BPNN model has high accuracy in predicting the stability bearing capacity of cross-bracings with semi-rigid connections. Meanwhile, the semi-rigid connections could enhance the stability bearing capacity of cross-bracings and the reliability of cross-bracings would significantly increase after considering semi-rigid connections.

절리암반내 지하수 유동해석을 위한 대표체적법, 비대표체적법 및 절리망 해석법의 비교 연구 (A Comparative Study on the REV, non-REV and Joint Network Methods for Analysis of Groundwater Flow in Jointed Rock Masses)

  • 문현구
    • 한국지반공학회논문집
    • /
    • 제15권5호
    • /
    • pp.217-228
    • /
    • 1999
  • 본 논문에서는 절리암반에서 발생하는 지하수 유동과 굴착된 지하공동으로의 지하수 유입량을 해석하는 대표체적법, 비대표체적법 및 절리망 해석법을 소개하고 절리의 수와 공동의 직경을 변화시키면서 각 해석법의 특징과 결과를 비교하였다. 선처리 과정으로서 다수의 절리가 서로 교차하는 절리암반의 등가 수리전도계수를 산정하는 이론과 계산 과정(일명, 순차적 해석)이 소개되었다. 유한요소망과 절리도 및 순차적 해석을 이용하여 445개 요소 각각의 등가 수리전도계수를 계산하였으며 절리암반의 비균질 수리전도성과 대표물성 결정에 관해 논의하였다. 대표체적법에서는 대표물성을 통해 절리암반의 균질화가 이루어졌으며 따라서 절리밀도, 공동의 직경 및 수리전도대비의 증가에 따른 지하수 유입량의 증가도 규칙적이며 일관성 있는 경향을 보였다. 비대표체적법에서는 암반의 비균질성이 요소 단위로 해석에 반영됨으로써 유입량의 변화 양상은 불규칙하였으나 특성 치수가 증가함에 따라 대표체적법의 결과에 접근하는 경향을 보였다. 절리망 해석은 절리밀도, 공동크기 및 절리망과 공동의 교차 여부 등에 가장 민감하게 반응하였으나 해석결과의 신뢰도가 개별 절리에 관한 자료에 너무 의존하게 되는 단점이 있다. 제한된 범위에서 수집될 수밖에 없는 현장 절리자료의 불확실성을 감안할 때 대표체적법과 비대표체적법이 실질적으로 더 합리적인 해석방법으로 인식되었다.

  • PDF