• Earthquakes and Structures
• /
• 제22권4호
• /
• pp.401-419
• /
• 2022

A novel hybrid extreme machine learning-multiverse optimizer (ELM-MVO) framework is proposed to predict the liquefaction phenomenon in seismically excited tunnel lining inside the sand lens. The MVO is applied to optimize the input weights and biases of the ELM algorithm to improve its efficiency. The tunnel located inside the liquefied sand lens is also evaluated under various near- and far-field earthquakes. The results demonstrate the superiority of the proposed method to predict the liquefaction event against the conventional extreme machine learning (ELM) and artificial neural network (ANN) algorithms. The outcomes also indicate that the possibility of liquefaction in sand lenses under far-field seismic excitations is much less than the near-field excitations, even with a small magnitude. Hence, tunnels designed in geographical areas where seismic excitations are more likely to be generated in the near area should be specially prepared. The sand lens around the tunnel also has larger settlements due to liquefaction.

• 유통과학연구
• /
• 제11권3호
• /
• pp.5-11
• /
• 2013

Purpose - Going concern is one of fundamental concepts in accounting and auditing and sometimes the assessment of a company's going concern status that is a tough process. Various going concern prediction models' based on statistical and data mining methods help auditors and stakeholders suggested in the previous literature. Research design - This paper employs a data mining approach to prediction of going concern status of Iranian firms listed in Tehran Stock Exchange using Particle Swarm Optimization. To reach this goal, at the first step, we used the stepwise discriminant analysis it is selected the final variables from among of 42 variables and in the second stage; we applied a grid-search technique using 10-fold cross-validation to find out the optimal model. Results - The empirical tests show that the particle swarm optimization (PSO) model reached 99.92% and 99.28% accuracy rates for training and holdout data. Conclusions - The authors conclude that PSO model is applicable for prediction going concern of Iranian listed companies.

• Nuclear Engineering and Technology
• /
• 제53권7호
• /
• pp.2104-2125
• /
• 2021

This paper presents the verification and validation (V&V) of a calculation module for isotope inventory prediction to control the back-end cycle of spent nuclear fuel (SNF). The calculation method presented herein was implemented in a two-step code system of a lattice code STREAM and a nodal diffusion code RAST-K. STREAM generates a cross section and provides the number density information using branch/history depletion branch calculations, whereas RAST-K supplies the power history and three history indices (boron concentration, moderator temperature, and fuel temperature). As its primary feature, this method can directly consider three-dimensional core simulation conditions using history indices of the operating conditions. Therefore, this method reduces the computation time by avoiding a recalculation of the fuel depletion. The module for isotope inventory calculates the number densities using the Lagrange interpolation method and power history correction factors, which are applied to correct the effects of the decay and fission products generated at different power levels. To assess the reliability of the developed code system for back-end cycle analysis, validation study was performed with 58 measured samples of pressurized water reactor (PWR) SNF, and code-to-code comparison was conducted with STREAM-SNF, HELIOS-1.6 and SCALE 5.1. The V&V results presented that the developed code system can provide reasonable results with comparable confidence intervals. As a result, this paper successfully demonstrates that the isotope inventory prediction code system can be used for spent nuclear fuel analysis.

• 한국분무공학회지
• /
• 제1권3호
• /
• pp.37-50
• /
• 1996

Computational fluid dynamics was used to optimize an A/C duct. Three dimensional flow analysis in an automotive A/C duct was performed computationally using various turbulence models and compared numerical predictions such as outlet flow split, surface pressure distribution along the duct to experimental data. Additionally, we studied the effect of location variation of 2nd branch on exit flow ratio and could find optimal location of 2nd branch. The design of an A/C duct was modeled and calculated to enhance the airflow distribution in each outlet using the STAR-CD computational fluid dynamics software. In results, modified $k-\varepsilon$ turbulence model allows a successful prediction of static pressure distribution particulary at around strong curvature but little improvement flow split. In the future, adoption of CFD to design an A/C duct with modified $k-\varepsilon$ model will bring benefits of producing more accurate prediction, and also give designers more detail information much more than now.

• 한국생산제조학회지
• /
• 제8권2호
• /
• pp.126-136
• /
• 1999

We studied on crack growth retardation in single overloading condition. Crack tip branching which as the second mechanism on crack growth retardation was examined. Crack tip branching was observed to kinked type and forked type. It was found that the branching angle range was from 25 to 53 degree. The variations of crack driving force with branching angle were calculated with finite element method The variation of {{{{ KAPPA _I}}}}, {{{{ KAPPA _II}}}} and total crack driving force(K) were examined respectively So {{{{ KAPPA _I}}}}, {{{{ KAPPA _II}}}} and K mean to mode I, II and total crack driving force. Present model(Willenborg's model) for crack growth retardation prediction was modified to take into consideration the effects of crack tip branching When we predicted retardation with modified model. it was confirmed that predicted and experimental results coincided with well each other.

• Computers and Concrete
• /
• 제33권1호
• /
• pp.1-11
• /
• 2024

Aggressive environmental conditions, and especially the acidic effects of sulfate ion penetration, have reduced the lifetime of concrete structures in some areas, especially coastal and marine areas. In this research, at first, samples made of type II and V cement were kept in a solution of magnesium sulfate (MgSO₄) for a period of 90 and 180 days, the change of appearance. Field Emission Scanning Electron Microscopy (FE-SEM) and X-Ray Diffraction (XRD), were used to analyze the microstructure and the complex mineral composition of the concrete after exposure to corrosive environments. Then solving the differential equation governing the sulfate ion penetration, which is based on the second Fick law, it has been tried to determine the concentration of sulfate ions inside the concrete. In the following, an attempt has been made to improve the prediction of sulfate ion concentration in concrete by using Crank's penetration equation. At the same time, the coefficient in the Crank's solution have been optimized by using the Particle Swarm Optimization (PSO algorithm). The comparison between the results shows that the values obtained from Crank's relation are closer to the experimental results than the equation obtained from Fick's second law and shows a more accurate prediction.

• 정보처리학회논문지A
• /
• 제19A권2호
• /
• pp.77-84
• /
• 2012

프로세서의 성능을 효율적으로 증가시키기 위한 기법 중 하나로 명령어 수준의 병렬성을 높이는 추론적 수행(Speculative execution)이 사용되고 있다. 추론적 수행 기법의 효율성을 결정하는 가장 중요한 핵심 요소는 분기 예측기의 정확도이다. 하지만, 높은 예측율을 보장하는 복잡한 구조의 분기 예측기를 최근 주목 받고 있는 3차원 구조 멀티코어 프로세서에 적용하는데 있어서는 발열 현상이 큰 장애요소가 될 것으로 예측된다. 본 논문에서는 3차원 구조 멀티코어 프로세서에서 발생할 수 있는 분기 예측기의 높은 발열 문제를 해결하기 위해 두 가지 기법을 제시하고, 이에 대한 효율성을 상세하게 분석하고자 한다. 첫번째 기법은 분기 예측기의 온도가 임계 온도 이상으로 올라가는 경우 분기 예측기의 동작을 일시적으로 정지시키는 동적 온도 관리 기법이고, 두번째 기법은 3차원 구조 멀티코어 프로세서의 각 층 별로 온도를 고려하여 서로 다른 복잡도를 지닌 분기 예측기를 차등 배치하는 기법이다. 두 가지 기법 중에서 복잡도를 고려한 차등 배치 기법은 평균 $87.69^{\circ}C$의 온도를 나타내는 반면, 동적 온도 관리 기법은 평균 $89.64^{\circ}C$의 온도를 나타내었다. 그리고, 각 층에서 발생하는 온도 변화율을 각 기법에 대하여 비교한 결과, 동적 온도 관리 기법의 온도 변화율은 평균 $17.62^{\circ}C$을 나타내었고 복잡도 차등 배치 기법의 온도 변화율은 평균 $11.17^{\circ}C$을 나타내었다. 이러한 온도 분석을 통하여 3차원 멀티코어 프로세서에서 분기 예측기의 온도를 제어하였을 경우, 복잡도 차등 배치 기법을 적용하는 것이 더 효율적임을 알 수 있다. 성능적인 측면을 분석한 결과, 동적 온도 관리 기법은 해당 기법을 적용하지 않았을 경우보다 평균 27.66%의 성능하락을 나타내었지만, 복잡도 차등 배치 기법은 평균 3.61%의 성능 하락만을 나타내었다.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2008년도 추계종합학술대회 B
• /
• pp.289-292
• /
• 2008

본 논문에서는 OpenRISC 프로세서의 성능 및 전력 소모 개선을 위해 동적 분기예측 기법, 사원 집합연관 캐시 구조, ODC를 이용한 클럭 게이팅 기법을 제안한다. 동적 분기 예측 기법은 분기 명령에 대해 다음에 실행될 명령에 대한 예측 주소를 저장하는 BTB를 사용하였다. 사원 집합연관 캐시는 네 개의 메모리 블록을 한 개의 캐시 블록에 사상되는 구조로 되어있어 직접사상 캐시에 비해 접근 실패율이 낮다. ODC를 이용한 클럭게이팅 기법은 논리합성 개념인 무관조건의 입출력 ODC조건을 찾아 클럭 게이팅 로직을 삽입함으로써 동적 소비전력을 줄일 수 있다. 테스트 프로그램을 이용하여 제안한 기법들을 적용한 OpenRISC 프로세서의 성능을 측정한 결과, 기존 프로세서 대비실행시간이 8.9% 향상 되었고, 삼성 $0.18{\mu}m$ 라이브러리를 이용하여 동적 전력을 측정한 결과, 기존 프로세서 대비 소비전력을 13.9% 이상 감소하였다.

• Smart Structures and Systems
• /
• 제22권4호
• /
• pp.413-424
• /
• 2018

The factors affecting the shear strength of the angle shear connectors in the steel-concrete composite beams can play an important role to estimate the efficacy of a composite beam. Therefore, the current study has aimed to verify the output of shear capacity of angle shear connector according to the input provided by Support Vector Machine (SVM) coupled with Firefly Algorithm (FFA). SVM parameters have been optimized through the use of FFA, while genetic programming (GP) and artificial neural networks (ANN) have been applied to estimate and predict the SVM-FFA models' results. Following these results, GP and ANN have been applied to develop the prediction accuracy and generalization capability of SVM-FFA. Therefore, SVM-FFA could be performed as a novel model with predictive strategy in the shear capacity estimation of angle shear connectors. According to the results, the Firefly algorithm has produced a generalized performance and be learnt faster than the conventional learning algorithms.

• 한국정보과학회논문지:시스템및이론
• /
• 제26권7호
• /
• pp.847-862
• /
• 1999

본 논문에서는 유한버퍼의(finite-buffered) 동기화된(synchronous) 큐잉모델(queueing model)을 이용하여 명령어들간의 병렬성, 분기명령의 빈도수, 분기예측(branch prediction)의 정확도, 캐쉬미스 등의 파라미터들을 고려하여 프로세서의 명령어 실행율을 예측하며 캐쉬의 성능과 파이프라인 성능간의 관계를 분석할 수 있는 새로운 해석적 모델을 제안하였다. 해석적 모델은 모델의 타당성을 검증하기 위해서 시뮬레이션을 수행하여 얻은 결과와 비교하였다. 해석적 모델과 시뮬레이션을 비교한 결과 대부분 10% 오차 내에서 일치하였다. 본 연구를 통하여 얻은 해석적 모델을 사용하면 시뮬레이션에서는 드러나지 않는 성능제약의 원인에 대한 명확한 규명이 가능하기 때문에 성능향상을 위한 설계자료를 얻을 수 있으며, 시스템 성능 밸런스를 위한 캐쉬와 비순차이슈 파이프라인 성능간의 관계에 대한 정확한 분석이 가능하다.Abstract This research presents a novel analytic model to predict the instruction execution rate of superscalar processors using the queuing model with finite-buffer size and synchronous operation mode. The proposed model is also able to analyze the performance relationship between cache and pipeline. The proposed model takes into account various kinds of architectural parameters such as instruction-level parallelism, branch probability, the accuracy of branch prediction, cache miss, and etc.. To prove the correctness of the model, we performed extensive simulations and compared the results with the analytic model. Simulation results showed that the proposed model can estimate the average execution rate accurately within 10% error compared to simulation results. The proposed model can explain the causes of performance bottleneck which cannot be uncovered by the simulation method only. The model is also able to show the effect of the cache miss on the performance of out-of-order issue superscalar processors, which can provide an valuable information in designing a balanced system.