• Structural Engineering and Mechanics
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• 제87권2호
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• pp.151-164
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• 2023

The latest earthquake's costly repairs and economic disruption were brought on by excessive residual drift. Self-centering systems are one of the most efficient ways in the current generation of seismic resistance system to get rid of and reduce residual drift. The mechanics and behavior of the self-centering system in response to seismic forces were impacted by a number of important factors. The amount of post-tensioning (PT) force, which is often employed for the standing posture after an earthquake, is the first important component. The energy dissipater element is another one that has a significant impact on how the self-centering system behaves. Using the damper as a replaceable and affordable tool and fuse in self-centering frames has been recommended to boost energy absorption and dampening of structural systems during earthquakes. In this research, the self-centering steel moment frame connections are equipped with cushion flexural dampers (CFDs) as an energy dissipator system to increase energy absorption, post-yielding stiffness, and ease replacement after an earthquake. Also, it has been carefully considered how to reduce permanent deformations in the self-centering steel moment frames exposed to seismic loads while maintaining adequate stiffness, strength, and ductility. After confirming the FE model's findings with an earlier experimental PT connection, the behavior of the self-centering connection using CFD has been surveyed in this study. The FE modeling takes into account strands preloading as well as geometric and material nonlinearities. In addition to contact and sliding phenomena, gap opening and closing actions are included in the models. According to the findings, self-centering moment-resisting frames (SF-MRF) combined with CFD enhance post-yielding stiffness and energy absorption with the least amount of permeant deformation in a certain CFD thickness. The obtained findings demonstrate that the effective energy dissipation ratio (β), is increased to 0.25% while also lowering the residual drift to less than 0.5%. Also, this enhancement in the self-centering connection with CFD's seismic performance was attained with a respectable moment capacity to beam plastic moment capacity ratio.

• 한국시뮬레이션학회논문지
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• 제30권1호
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• pp.103-112
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• 2021

최근 정보통신기술의 발달에 따른 공공 자전거 시스템 운영 사례가 증가하고 있다. 대도시의 공공 자전거 시스템은 시민에 대한 공공성과 편리성을 모두 확보해야하기 때문에, 도입부터 운영까지 다양한 이슈에 대한 분석이 필요하다. 또한, 최근 라스트 마일 수단으로 각광받고 있는 개인 모빌리티 사업과의 공존을 위한 다양한 시나리오 역시 대비할 필요가 있다. 본 논문은 공공 자전거 시스템의 효율적 운영 관리를 위한 시뮬레이션 모델을 제안한다. 특히, 제안한 방법은 공공 자전거 시스템의 일반적인 구조와 행태를 모델링 하여 다른 도시에 쉽게 활용할 수 있는 형태로 개발하였고, 컴포넌트 기반의 모델 구성으로 향후 모델의 수정 및 확장이 용이하도록 개발하였다. 본 논문에서는 제안된 방법의 사례로 세종시 공공 자전거 시뮬레이션을 수행하였다. 세종시 공공 자전거 시스템의 데이터를 적용하여 시뮬레이션 결과를 도출하고, 도출된 결과를 세종시 실데이터와 비교하여 검증하였다. 검증된 모델을 이용하여, 세종시에 적합한 공공 자전거 서비스를 설계하고 분석할 수 있는 도구로 활용될 수 있을 것으로 기대한다.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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• pp.440-443
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• 2001

As inter-network traffics grows rapidly, the router systems as a network component becomes to be capable of not only wire-speed packet processing but also plentiful programmability for quality services. A network processor technology is widely used to achieve such capabilities in the high-end router. Although providing two such capabilities, the network processor can't support a deep packet processing at nominal wire-speed. Considering QoS may result in performance degradation of processing packet. In order to achieve foster processing, one chipset of network processor is occasionally not enough. Using more than one urges to consider a problem that is, for instance, an out-of-order delivery of packets. This problem can be serious in some applications such as voice over IP and video services, which assume that packets arrive in order. It is required to develop an effective packet processing mechanism leer using more than one network processors in parallel in one linecard unit of the router system. Simulation analysis is also needed for verifying the mechanism. We propose the packet processing mechanism consisting of more than two NPs in parallel. In this mechanism, we use a load-balancing algorithm that distributes the packet traffic load evenly and keeps the sequence, and then verify the algorithm with simulation analysis. As a simulation tool, we use DEVSim++, which is a DEVS formalism-based hierarchical discrete-event simulation environment developed by KAIST. In this paper, we are going to show not only applicability of the DEVS formalism to hardware modeling and simulation but also predictability of performance of the load balancer when implemented with FPGA.

• 대한기계학회논문집A
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• 제37권9호
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• pp.1133-1140
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• 2013

컴퓨터 해석모델은 물리현상을 바탕으로 단순화된 모델을 구축하고 해를 구하는 유용한 도구이나, 많은 경우 단순화 가정 또는 입력변수 정보의 미비나 불확실성으로 인해 실제와 차이가 발생한다. 본 연구에서는 이러한 문제에 대해 베이지안 확률이론을 이용하여 실측데이터를 통해 해석모델을 보정하는 방법을 소개하고 이를 파이로 작동기구의 탄소성 압착 문제에 적용한다. 파이로 작동기구는 고에너지의 재료를 원격으로 폭발시켜 작동하는 장치로 그 작동의 신속한 계산을 위해서 단순한 수학모델을 구축하고 실험데이터를 토대로 미지의 입력변수를 확률적으로 보정하였다. 이 때, 확률적 추정을 위해서는 현대적 계산통계기법의 하나인 Markov Chain Monte Carlo 기법을 이용하였으며, 최종적으로 그 결과를 압착거동해석에 활용하여 작동기구의 신뢰도를 평가하였다.

• 소음진동
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• 제7권2호
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• pp.319-329
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• 1997

Wigner-Ville distribution has been recognized as a useful tool and applied to various types of mechanical noise and vibration signals, but its limitation which mainly comes from the cross-talk has not been well addressed. The cross-talk takes place for a signal with multiple components, simply because the Wigner-Ville distribution is a bilinear transform. The cross-talk often causes a negative value in the distribution. This cannot be accepted for the Wigner- Ville distribution, because it is an expression of power. Smoothing the Wigner-Ville distribution by convoluting it wih a window, is most commonly used to reduce the cross-talk. There can be infinite number of distributions depending on the windows. In this paper, we attempted to develop a distribution which is the best or the optimal in reducing the cross-talk. This could be possible by employing the ambiguity function. For a general signal, however it is difficult to express the ambiguity function as a mathematically closed form. This requires an appropriate modeling to make such expression possible. We approximated the Wigner-Ville distribution as a sum of linear segments. In the ambiguity function domain, the legitimate components are reflected as linear lines passing through the origin. Every lines has its own length and slope. But, the cross-talk is widely distributed in the ambiguity function plane. Based on this realization, we proposed a two-dimensional window which is in fact 'rotating window', that can eliminate cross-talk component. The rotating window is examined numerically and is found to have a better performance in reducing the cross-talk than conventional windows, the Gaussian window.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.155-155
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• 2019

The Agricultural Policy/Environmental eXtender (APEX) models have been developed for assessing agricultural management efforts and their effects on soil and water at the field scale as well as more complex multi-subarea landscapes, whole farms, and watersheds. National Academy of Agricultural Sciences, Wanju, Korea, has modified a key component of APEX application, named APEX-Paddy for simulating water quality with considering appropriate paddy management practices, such as puddling and flood irrigation management. Calibration and validation are an anticipated step before any model application. Simple techniques are essential to assess whether or not a parameter should be adjusted for calibration. However, very few study has been done to evaluate the ability of APEX-Paddy to simulate the impact of multiple management scenarios on nutrients loss. In this study, the observation data from experimental fields at Iksan in South Kora was used in calibration and evaluation process during 2013-2015. The APEX auto- calibration tool (APEX-CUTE) was used for model calibration and sensitivity analysis. Four quantitative statistics, the coefficient of determination ($R^2$),Nash-Sutcliffe(NSE),percentbias(PBIAS)androotmeansquareerror(RMSE)were used in model evaluation. In this study, the hydrological process of the modified model, APEX-Paddy, is being calibrated and tested in predicting runoff discharge rate and nutrient yield. Field-scale calibration and validation processes are described with an emphasis on essential calibration parameters and direction regarding logical sequences of calibration steps. This study helps to understand the calibration and validation way is further provided for applications of APEX-Paddy at the field scales.

• 한국BIM학회 논문집
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• 제11권1호
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• pp.21-30
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• 2021

Reinforcing bars, a major component of the pre-fab structure, adheres to the existing on-site assembly method and attempts to develop and commercialize the technology of the pre-assembly method, but the effect is insignificant. Welded Wire / Bar Mat (WBM) has various advantages such as commercialization of rebar through machine manufacturing to improve workability, but it is different from the existing design and the construction method is different from the previous one. Therefore, to maximize the advantages of WBM and improve productivity, manufacturing, transportation, and construction from the design stage should be considered based on BIM from the initial design stage. In this paper, the concept of the design support system for the WBM was established based on the use of BIM in concrete reinforcement and the preliminary research on the WBM. WBM conversion design was performed for the existing prefabricated members, and based on this, the exchange format and system of the master prefabricated model with the WBM design data were set up. As a result of the pilot test, it was found that the traditional reinforcing bar information extracted from the master prefab model has transmitted 100% accurately. As for the WBM information, 100% of the information on the straight reinforcement was transmitted and represented, and the information on the bent reinforcement was found to have a 90% recall in the master BIM tool.

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.89-94
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• 2023

Cloud-based technology is used in different organizations around the world for various purposes. Using this technology, the service providers provide the service mainly SaaS, PaaS and while the cloud service consumer consumes the services by paying for the service they used or accessed by the principle of "pay per use". The customer of the services can get any services being at different places or locations using different machines or electronic devices. Under the conditions of being well organized and having all necessary infrastructures, the services can be accessed suitably. The identified problem in this study is that cloud providers control and monitor the system or tools by ignoring the calculation and consideration of various faults made from the cloud provider side during service delivery. There are currently problems with ignoring the consumer or client during the monitoring and mentoring system for cloud services consumed at the customer or client level by SLA provisions. The new framework was developed to address the above-mentioned problems. The framework was developed as a unified modeling language. Eight basic components are used to develop the framework. For this research, the researcher developed a prototype by using a selected cloud tool to simulate and java programming language to write a code as well as MySQL to store data during SLA. The researcher used different criteria to validate the developed framework i.e. to validate SLA that is concerned with a cloud service provider, validate what happened when the request from the client-side is less than what is specified in SLA and above what is specified in SLA as well as implementing the monitoring mechanism using the developed Monitoring component. The researcher observed that with the 1st and 3rd criteria the service level agreement was violated and this indicated that if the Service level agreement is monitored or managed only by cloud service prover, there is a violation of LSA. Therefore, the researcher recommended that the service level agreement be managed by both cloud service providers and service consumers in the cloud computing environment.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1244-1244
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from mastitic and healthy cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from mastitic and healthy cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA and FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference, thereby providing a useful means for spectroscopy-based clinic applications.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1042-1042
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.