• 한국농공학회지
• /
• 제16권3호
• /
• pp.3533-3538
• /
• 1974

This study was attempted in order to search for physical properties of sail cement. In this study, soil samples were specified according to soil particle analysis and used for compaction, strength, abrasion, absorption tests respectively according to different cement contents. Cement content sused in each treatment were 6%, 8%, 10% and 12% of total weight of soil-consent mixture. In the test, compressise strengths of the specimens were measured at the following ages; 3 days, 7-days, 14-days, 21-days and 28-days. Abrasion and absorption tests of the specimens were carried out at the 7-days age only. The results obtained from the tests are summarized as follows; 1. As the cement contents were in creased, the compressive strengths of soil-cement were almost proportionally increased. 2. The Compressive strength of soil-cement was not always proporportional to ages. The gradient of compressive strength of the soil-cement was steeper as the cement content was rucreased. 3. As the cement content was increased, the amount of the weight loss of the samples due to the abrasion was decreased remarkably, giving no abrasion for about 8% of the cement content. 4. As the cement content was increased, the absorption ratio of the specimens was not changed remarkably.

• 대한기계학회논문집B
• /
• 제30권11호
• /
• pp.1131-1138
• /
• 2006

Aerodynamic shape design of a partial admission turbine using CFD has been performed. Two step approaches are adopted in this study. Firstly, two-dimensional blade shape is optimized using CFD and genetic algorithm. Initially, the turbine cascade shape is represented by four design parameters. By controlling the design parameters as variables, the non-gradient search is analyzed for obtaining the maximum efficiency. The final two-dimensional blade proved to have a more blade power than the initial blade. Secondly, the three-dimensional CFD analysis including the nozzle, rotor and stator has been conducted. To avoid a heavy computational load due to an unsteady calculation, the frozen rotor method is implemented in steady calculation. The frozen rotor method can detect a variation of the flow-field dependent upon the blade's circumferential position relative to the nozzle. It gives a better idea of wake loss mechanism starting from the lip of the nozzle than the mixing plane concept. Finally, the combination of two and three dimensional design method of the partial admission turbine in this study has proven to be a robust tool in development phase.

• 한국소음진동공학회논문집
• /
• 제18권2호
• /
• pp.185-191
• /
• 2008

Optimal damping layout of the constrained viscoelastic damping layer on beam is identified with temperatures by using a gradient-based numerical search algorithm. An optimal design problem is defined in order to determine the constrained damping layer configuration. A finite element formulation is introduced to model the constrained layer damping beam. The four-parameter fractional derivative model and the Arrhenius shift factor are used to describe dynamic characteristics of viscoelastic material with respect to frequency and temperature. Frequency-dependent complex-valued eigenvalue problems are solved by using a simple re-substitution algorithm in order to obtain the loss factor of each mode and responses of the structure. The results of the numerical example show that the proposed method can reduce frequency responses of beam at peaks only by reconfiguring the layout of constrained damping layer within a limited weight constraint.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2006년도 춘계학술대회논문집
• /
• pp.1235-1242
• /
• 2006

Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the nonlinear dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature with fewer parameters than conventional spring-dashpot models. However the identification procedure of the four-parameter is very time-consuming one. An efficient identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured FRFs coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment. A numerical example shows that the proposed method is efficient and robust in identifying the viscoelastic material parameters of fractional derivative model.

• 정보처리학회논문지B
• /
• 제14B권5호
• /
• pp.377-382
• /
• 2007

본 논문에서는 방사 기저함수 네트워크의 파라미터를 전 영역에서 최적화하는 학습 알고리즘을 제안한다. 기존의 학습 알고리즘들은 지역 최적화만을 수행하기 때문에 성능의 한계가 있고 최종 결과가 초기 네트워크 파라미터 값에 크게 의존하는 단점이 있다. 본 논문에서 제안하는 하이브리드 모의 담금질 기법은 모의 담금질 기법의 전 영역 탐색 능력과 경사 기반 학습 알고리즘의 지역 최적화 능력을 조합하여 전 파라미터 영역에서 해를 찾을 수 있도록 한다. 제안하는 기법을 함수 근사화 문제에 적용하여 기존의 학습 알고리즘에 비해 더 좋은 학습 및 일반화 성능을 보이는 네트워크 파라미터를 찾을 수 있으며, 초기 파라미터 값의 영향을 크게 줄일 수 있음을 보인다.

• 한국재난관리표준학회지
• /
• 제4권1호
• /
• pp.49-55
• /
• 2011

본 연구는 철근 콘크리트 구조물의 새로운 자동화 최적설계 알고리즘을 제시하였다. 기존의 주철근과 콘크리트 단면사이즈 등의 국한된 최적설계 범위를 벗어나 철근의 부착길이, 매입길이, 콘크리트 커버두께 등 세부설계사항까지 모두 고려한 실무에 적합한 효용성 높은 설계알고리즘을 제시함으로써 앞으로 실무분야에 많은 기여를 할 수 있다고 보여 진다.

• 천문학회보
• /
• 제44권1호
• /
• pp.70.3-70.3
• /
• 2019

Understanding how the filamentary structure affects the formation of the prestellar cores and stars is a key issue to challenge. We use the Heterodyne Array Receiver Program (HARP) of the James Clerk Maxwell Telescope (JCMT) to obtain molecular line mapping data for two prestellar cores in different environment, L1544 in filamentary cloud and L694-2 in a small cloud isolated. Observing lines are $^{13}CO$ and $C^{18}O$ (3-2) line to find possible flow motions along the filament, $^{12}CO$ (3-2) to search for any radial accretion (or infalling motions) toward the cores of gas material from their surrounding regions, and $HCO^+$ (4-3) lines to find at which density and which region in the core gases start to be in gravitational collapse. In the 1st moment maps of $^{13}CO$ and $C^{18}O$, velocity gradient patterns implying the flow of material were found at the cores and its surrounding filamentary clouds. The infall asymmetry patterns of HCO+ and $^{13}CO$ line profiles were detected to be good enough to analyze the infalling motions toward the cores. We will report further analysis results on core formation in the filamentary cloud at this meeting.

• Structural Engineering and Mechanics
• /
• 제84권5호
• /
• pp.605-618
• /
• 2022

Glass fiber reinforced polymer (GFRP) elastic gridshells consist of long continuous GFRP tubes that form elastic deformations. In this paper, a method for the form-finding of gridshell structures is presented based on the interpretable machine learning (ML) approaches. A comparative study is conducted on several ML algorithms, including support vector regression (SVR), K-nearest neighbors (KNN), decision tree (DT), random forest (RF), AdaBoost, XGBoost, category boosting (CatBoost), and light gradient boosting machine (LightGBM). A numerical example is presented using a standard double-hump gridshell considering two characteristics of deformation as objective functions. The combination of the grid search approach and k-fold cross-validation (CV) is implemented for fine-tuning the parameters of ML models. The results of the comparative study indicate that the LightGBM model presents the highest prediction accuracy. Finally, interpretable ML approaches, including Shapely additive explanations (SHAP), partial dependence plot (PDP), and accumulated local effects (ALE), are applied to explain the predictions of the ML model since it is essential to understand the effect of various values of input parameters on objective functions. As a result of interpretability approaches, an optimum gridshell structure is obtained and new opportunities are verified for form-finding investigation of GFRP elastic gridshells during lifting construction.

• 한국공간구조학회논문집
• /
• 제24권2호
• /
• pp.83-90
• /
• 2024

Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks and extreme gradient boosting algorithms present good prediction performance.

• 전자공학회논문지
• /
• 제50권6호
• /
• pp.212-220
• /
• 2013

최근 사용자의 생체 신호 정보를 기반으로 사용자 인지향상을 위하여, 상황에 적합한 서비스를 제공하기 위한 인간-컴퓨터/기계 상호작용 (Human computer/machine interaction: HCI/HMI) 시스템이 급격하게 증가하고 있는 추세이다. 이와 같이 인간-컴퓨터/기계 상호작용 기반의 효과적인 사용자 인지향상 시스템을 개발하기 위해서는 사용자의 명시적 의도 파악과 더불어 사용자의 묵시적 의도 파악이 중요하다. 사람의 시각 운동 이론에 따르면, 사람의 안구운동 정보와 동공 반응은 사람의 의도와 행동에 대하여 많은 량의 정보를 제공한다. 이에 본 논문에서는 사용자의 묵시적 의도를 판별하기 위하여, 피험자에게 제공되는 자극영상의 관심(흥미) 영역 (area of interest: AOI) 내에서의 안구운동 패턴인 응시 시간/횟수, 동공 응답 패턴의 동공크기와 동공의 크기변화인 기울기 정보를 분석하는 새로운 접근 방법을 제안한다. 제안하는 모델은 항행적 의도 발생, 정보적 의도발생, 정보적 의도 소멸과 같은 세 가지 유형으로 인간의 묵시적 의도를 식별한다. 여기서 항행적 의도란 주어진 자극영상 내에서 무언가 흥미로운 것을 찾는 행위를 말하며, 이에 반해 정보적 의도는 특정 위치에서 특정 객체는 찾는 행위를 의미한다. 본 연구에서는 사용자 안구운동 패턴과 동공분석 정보 기반으로 서로 다른 묵시적 의도인 항행적 의도, 정보적 의도 발생, 그리고 정보적 의도 소멸 사이에서 그 천이를 감지할 수 있는 계층적 SVM (hierarchical support vector machine: H-SVM)을 이용하였다.