• Journal of the Optical Society of Korea
• /
• 제17권3호
• /
• pp.237-241
• /
• 2013

This paper presents an efficient evolutionary method to optimize the gain ripple of multi-pumps photonic crystal fiber Raman amplifier using the Fuzzy Adaptive Modified PSO (FAMPSO) algorithm. The original PSO has difficulties in premature convergence, performance and the diversity loss in optimization as well as appropriate tuning of its parameters. The feasibility and effectiveness of the proposed hybrid algorithm is demonstrated and results are compared with the PSO algorithm. It is shown that FAMPSO has a high quality solution, superior convergence characteristics and shorter computation time.

• 한국복합재료학회:학술대회논문집
• /
• 한국복합재료학회 1999년도 추계학술발표대회 논문집
• /
• pp.63-67
• /
• 1999

This paper presents the optimization of CFRP laminated rectangular plates using fuzzy theory. In optimization, thickness of CFRP lamina and fiber angle are taken as design variables, and total thickness of the plates is minimized under Tsai-Hill failure criterion. The uncertainties are entered by introducing fuzzy material strengths and then the objective and constraints are represented by a membership function of their own according to the intersection method. Various design results are presented for the CFRP laminated composites plates.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2007년도 제38회 하계학술대회
• /
• pp.1558-1559
• /
• 2007

This study is an application field by using optical fiber. The system to measure sBs from optical fiber is designed, So it can be used as a temperature sensor. by using frequency shift, resulting from temperature changes. the frequency shift is checked by changing temperature from $25^{\circ}C$ to $69^{\circ}C$ with chamber in the laboratory and using 40Km optical fiber. It's also measured by varying the length of optical fiber The program to do the real-time monitoring and analyze the measured data is created to find accurate frequency. It can be used as an optical fiber sensor, which is capable of measuring temperature and distance by using sBs.

• 감성과학
• /
• 제12권1호
• /
• pp.77-86
• /
• 2009

자동차는 첨단공업 기술이 고도로 집적되어 있는 인간-기계 시스템(man machine system)이다. 자동차에 대한 새로운 감성요구를 실현하기 위해서는 인체와 오랜 시간 접촉해 있는 시트 표피재의 분석이 반드시 필요하다. 본 연구에서는 자동차 시트 표피재의 역학적 특성과 감성을 고려한 고급감을 예측하여 고감성 내장 표피재 개발에 기여하고자 한다. 감성용어는 Softness(유연한), Elasticity(탱글탱글한), Volume(풍성한), Stickiness (끈끈한)를 설정하였으며, 이와 대응하는 표피재의 역학적 특성 치를 측정하였다. 피혁의 특성평가에 의한 결과로 resilience, bending moment, thickness와 friction 값을 얻을 수 있었으며, 이러한 역학적 특성 치를 softness, elasticity, volume, stickiness 값으로 변화하기 위해 fuzzy logic을 사용하였다. 또한 Fuzzy logic의 결과인 Softness, Elasticity, Volume, Stickiness 값으로 피혁의 고급감을 예측하기 위한 신경망 모델(Neural network)을 구성하였다. 즉, 자동차 표피재 중 피혁의 4가지 물리량으로 인간의 감성인 표피재의 고급감을 예측하여 고감성 자동차 시트 표피재의 개발을 위한 예측 모델의 가능성을 평가하였다.

• KSBB Journal
• /
• 제15권1호
• /
• pp.14-21
• /
• 2000

본 연구는 조류의 고농도 배양을 통하여 축산폐수로부터 질소, 인등의 영양염류를 효과적으로 제거하여 환경오염을 감소시키는 것을 목적으로 한다. 이를 위하여 조류성장의 환경적 요소인 질소/인 농도비에 대한 질소와 인의 제거효율 분석 실험을 통하여 질적 질소/인 농도비를 결정하였다. 고농도 조류 배양을 위한 광도의 균일한 공급을 위하여 광섬유를 이용한 광생물반응기를 공정에 적용하였다. 제안된 광섬유를 이용한 광생물반응기는 광원으로부터 반응기 전체로 효과적인 광전달을 수행하는 것을 확인하였다. 조류 배양에서 조류의 성장과 질소, 인의 제거를 표현하기 위해서 구조적 속도식 모델을 제시하였다. 유전알고리즘을 이용한 자기구성퍼지 제어기를 구성하여 반연속식 폐수처리공정의 제어를 수행하였다. 구성된 퍼지 제어기는 폐수의 유입량 조절을 통하여 질소의 농도를 주어진 설정치로 유지되도록 운전하였다. 실험 결과에 의해 자기구성 퍼지 제어기는 원하는 질소의 농도를 잘 유지함은 물론 조류의 성장을 증진시킴을 알 수 있었다.

• Structural Engineering and Mechanics
• /
• 제22권6호
• /
• pp.665-683
• /
• 2006

The strength behaviors of Fiber Reinforced Plastics (FRP) Composites can be greatly influenced by the properties of constitutive materials, the laminate structures, and load conditions etc, accompanied by many uncertainty factors. So the reliability study on FRP is an important subject of research. Many achievements have been made in reliability studies based on the probability theory, but little has been done on the roles played by fuzzy variables. In this paper, a fuzzy reliability model for FRP laminates is established first, in which the loads are considered as random variables and the strengths as fuzzy variables. Then a numerical model is developed to assess the fuzzy reliability. The Monte Carlo simulation method is utilized to compute the reliability of laminas under the maximum stress criterion. In the second part of this paper, a generalized fuzzy reliability model (GFRM) is proposed. By virtue of the fact that there may exist a series of states between the failure state and the function state, a fuzzy assumption for the structure state together with the probabilistic assumption for strength parameters is adopted to construct the GFRM of composite materials. By defining a generalized limit state function, the problem is converted to the conventional reliability formula that enables the first-order reliability method (FORM) applicable in calculating the reliability index. Several examples are worked out to show the validity of the models and the efficiency of the methods proposed in this paper. The parameter sensitivity analysis shows that some of the mean values of the strength parameters have great influence on the laminated composites' reliability. The differences resulting from the application of different failure criteria and different fuzzy assumptions are also discussed. It is concluded that the GFRM is feasible to use, and can provide an effective and synthetic method to evaluate the reliability of a system with different types of uncertainty factors.

• Computers and Concrete
• /
• 제19권2호
• /
• pp.133-142
• /
• 2017

Two-stage concrete (TSC), also known as pre-placed aggregate concrete, is characterized by its unique placement technique, whereby the coarse aggregate is first placed in the formwork, then injected with a special grout. Despite its superior sustainability and technical features, TSC has remained a basic concrete technology without much use of modern chemical admixtures, new binders, fiber reinforcement or other emerging additions. In the present study, an experimental database for TSC was built. Different types of cementitious binders (single, binary, and ternary) comprising ordinary portland cement, fly ash, silica fume, and metakaolin were used to produce the various TSC mixtures. Different dosages of steel fibres having different lengths were also incorporated to enhance the mechanical properties of TSC. The database thus created was used to develop fuzzy logic models as predictive tools for the grout flowability and mechanical properties of TSC mixtures. The performance of the developed models was evaluated using statistical parameters and error analyses. The results indicate that the fuzzy logic models thus developed can be powerful tools for predicting the TSC grout flowability and mechanical properties and a useful aid for the design of TSC mixtures.

• Smart Structures and Systems
• /
• 제19권2호
• /
• pp.127-136
• /
• 2017

Fiber reinforced polymer (FRP) has received widespread attention in the field of civil engineering because of its superior durability and corrosion resistance. This article presents the damage mechanisms of a novelty composite called carbon nanofiber modified flax fiber polymer (CNF-modified FFRP). The ability of acoustic emission (AE) to detect damage evolution for different configurations of specimens under uniaxial tension was examined, and some useful AE characteristic parameters were obtained. Test results shows that the mechanical properties of modified composites are associated with the CNF content and the evenness of CNF dispersed in the epoxy matrix. Various damage mechanisms was established by means of scanning electron microscope images. The fuzzy c-means clustering were proposed to classify AE events into groups representing different generation mechanisms. The classifiers are constructed using the traditional AE features -- six parameters from each burst. Amplitude and peak-frequency were selected as the best cluster-definition features from these AE parameters. After comprehensive comparison, a correlation between these AE events classes and the damage mechanisms observed was proposed.

• Computers and Concrete
• /
• 제32권1호
• /
• pp.27-44
• /
• 2023

The current study targets to apply the adaptive neuro-fuzzy inference system (ANFIS) for the estimation of the shear resistance offered by the externally bonded fiber-reinforced polymer (EB-FRP) U-jackets. A total of 202 groups of data cumulated from previous investigations, were employed for the development and evaluation of the ANFIS model. A relative appraisal between the ANFIS predictions and the results of experiments has shown that the assessments by current ANFIS model are in good concurrence with the latter. In addition, assessment of the accuracy of the ANFIS model was done by relating the ANFIS predictions with the forecasts of eight extensively used design guidelines. Based on the examination of various performance measures, it has been derived that the adequacy of the ANFIS model is better than the available guidelines. A parametric investigation has additionally been done to reconnoiter the influence of individual parameters as well as their combined effects on the shear contribution of EB-FRP. Based on the observations made from the parametric study, it has been witnessed that the ANFIS model has incorporated the effect of different parameters more competently than the considered design guidelines.

• Advances in nano research
• /
• 제12권5호
• /
• pp.515-527
• /
• 2022

The application of fibers in concrete obviously enhances the properties of concrete, also the application of natural fibers in concrete is raising due to the availability, low cost and environmentally friendly. Besides, predicting the mechanical properties of concrete in general and shear strength in particular is highly significant in concrete mixture with fiber nanocomposite reinforced concrete (FRC) in construction projects. Despite numerous studies in shear strength, determining this strength still needs more investigations. In this research, Adaptive Neuro-Fuzzy Inference System (ANFIS) have been employed to determine the strength of reinforced concrete with fiber. 180 empirical data were gathered from reliable literature to develop the methods. Models were developed, validated and their statistical results were compared through the root mean squared error (RMSE), determination coefficient (R²), mean absolute error (MAE) and Pearson correlation coefficient (r). Comparing the RMSE of PSO (0.8859) and ANFIS (0.6047) have emphasized the significant role of structural parameters on the shear strength of concrete, also effective depth, web width, and a clear depth rate are essential parameters in modeling the shear capacity of FRC. Considering the accuracy of our models in determining the shear strength of FRC, the outcomes have shown that the R² values of PSO (0.7487) was better than ANFIS (2.4048). Thus, in this research, PSO has demonstrated better performance than ANFIS in predicting the shear strength of FRC in case of accuracy and the least error ratio. Thus, PSO could be applied as a proper tool to maximum accuracy predict the shear strength of FRC.