• Earthquakes and Structures
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• 제12권3호
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• pp.321-332
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• 2017

The reverse fault is a dangerous geological hazard faced by buried steel pipelines. Permanent ground deformation along the fault trace will induce large compressive strain leading to buckling failure of the pipe. A hybrid pipe-shell element based numerical model programed by INP code supported by ABAQUS solver was proposed in this study to explore the strain performance of buried X80 steel pipeline under reverse fault displacement. Accuracy of the numerical model was validated by previous full scale experimental results. Based on this model, parametric analysis was conducted to study the effects of four main kinds of parameters, e.g., pipe parameters, fault parameters, load parameter and soil property parameters, on the strain demand. Based on 2340 peak strain results of various combinations of design parameters, a semi-empirical model for strain demand prediction of X80 pipeline at reverse fault crossings was proposed. In general, reverse faults encountered by pipelines are involved in 3D oblique reverse faults, which can be considered as a combination of reverse fault and strike-slip fault. So a compressive strain demand estimation procedure for X80 pipeline crossing oblique-reverse faults was proposed by combining the presented semi-empirical model and the previous one for compression strike-slip fault (Liu 2016). Accuracy and efficiency of this proposed method was validated by fifteen design cases faced by the Second West to East Gas pipeline. The proposed method can be directly applied to the strain based design of X80 steel pipeline crossing oblique-reverse faults, with much higher efficiency than common numerical models.

• Structural Engineering and Mechanics
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• 제43권1호
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• pp.127-145
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• 2012

One of the most important and challenging steps in seismic vulnerability and performance assessment of highway bridges is the determination of the bridge component damage parameters and their corresponding limit states. These parameters are very essential for defining bridge damage state as well as determining the performance of highway bridges under a seismic event. Therefore, realistic damage limit states are required in the development of reliable fragility curves, which are employed in the seismic risk assessment packages for mitigation purposes. In this article, qualitative damage assessment criteria for ordinary highway bridges are taken into account considering the critical bridge components in terms of proper engineering demand parameters (EDPs). Seismic damage of bridges is strongly related to the deformation of bridge components as well as member internal forces imposed due to seismic actions. A simple approach is proposed for determining the acceptance criteria and damage limit states for use in seismic performance and vulnerability assessment of ordinary highway bridges in Turkey constructed after the 1990s. Physical damage of bridge components is represented by three damage limit states: serviceability, damage control, and collapse prevention. Inelastic deformation and shear force demand of the bent components (column and cap beam), and superstructure displacement are the most common causes for the seismic damage of the highway bridges. Each damage limit state is quantified with respect to the EDPs: i.e. curvature and shear force demand of RC bent components and superstructure relative displacement.

• Structural Engineering and Mechanics
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• 제70권3호
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• pp.289-301
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• 2019

Hysteretic energy is defined as energy dissipated through inelastic deformations during a ground motion by the system. It includes frequency content and duration of ground motion as two remarkable parameters, while these characteristics are not seen in displacement spectrum. Since maximum displacement individually cannot be the appropriate criterion for damage assessment, hysteretic energy has been evaluated in this research as a more comprehensive seismic demand parameter. An innovative methodology has been proposed to establish a new equivalent linear model to estimate hysteretic energy spectrum for bilinear SDOF models under two different sets of earthquake excitations. Error minimization has been defined in the space of equivalent linearization concept, which resulted in equivalent damping and equivalent period as representative parameters of the linear model. Nonlinear regression analysis was carried out for predicting these equivalent parameter as a function of ductility. The results also indicate differences between seismic demand characteristics of far-field and near-field ground motions, which are not identified by most of previous equations presented for predicting seismic energy. The main advantage of the proposed model is its independency on parameters related to earthquake and response characteristics, which has led to more efficiency as well as simplicity. The capability of providing a practical energy based seismic performance evaluation is another outstanding feature of the proposed model.

• 산업경영시스템학회지
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• 제19권37호
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• pp.31-40
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• 1996

The amount of safety stock is decided from various information such as the forecasted demand, the lead time, the size of the order quantity and the desired service level. There are two cases to consider the problem of setting safety stock when both the demand in a period and the lead time are characterized as random variables: the first case is the parameters of the demand and lead time distributions are known, the second case is they are unknown and must be estimated. The objective of this study is to present the procedure for setting safety stocks in the case the parameters of the demand and lead time distributions are unknown and must be estimated. In this study, a simple exponential smoothing model is used. to generate the estimates of demand in each period and a discrete distribution of the lead time is developed from historical data, and the optimal service level is used which determined to consider both of a backorder and lost sale.

• Structural Engineering and Mechanics
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• 제23권2호
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• pp.177-193
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• 2006

Determining the hysteretic energy demand and dissipation capacity and level of damage of the structure to a predefined earthquake ground motion is a highly non-linear problem and is one of the questions involved in predicting the structure's response for low-performance levels (life safe, near collapse, collapse) in performance-based earthquake resistant design. Neural Network (NN) analysis offers an alternative approach for investigation of non-linear relationships in engineering problems. The results of NN yield a more realistic and accurate prediction. A NN model can help the engineer to predict the seismic performance of the structure and to design the structural elements, even when there is not adequate information at the early stages of the design process. The principal aim of this study is to develop and test multi-layered feedforward NNs trained with the back-propagation algorithm to model the non-linear relationship between the structural and ground motion parameters and the hysteretic energy demand in steel moment resisting frames. The approach adapted in this study was shown to be capable of providing accurate estimates of hysteretic energy demand by using the six design parameters.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1990년도 춘계공동학술대회논문집; 한국과학기술원; 28 Apr. 1990
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• pp.125-139
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• 1990

This paper presents a forecasting method for domestic demand of electric home appliances. Because of lack of data, some popular methods such as time series analysis may not be appropriate to forecast such a demand domestically. We suggest a systematic and practical method by considering structural parameters and variables which determine the actual demand. We use this model to forecast the demand of color TV. Since the parameters in our model may be variant according to the change of economic environment, our model leads the user to develop a dynamic model to be used in the well-known System Dynamics Approach.

• ETRI Journal
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• 제44권4호
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• pp.624-640
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• 2022

Taxi-demand forecasting and hotspot prediction can be critical in reducing response times and designing a cost effective online taxi-booking model. Taxi demand in a region can be predicted by considering the past demand accumulated in that region over a span of time. However, other covariates-like neighborhood influence, sociodemographic parameters, and point-of-interest data-may also influence the spatiotemporal variation of demand. To study the effects of these covariates, in this paper, we propose three models that consider different covariates in order to select a set of independent variables. These models predict taxi demand in spatial units for a given temporal resolution using linear and ensemble regression. We eventually combine the characteristics (covariates) of each of these models to propose a robust forecasting framework which we call the combined covariates model (CCM). Experimental results show that the CCM performs better than the other models proposed in this paper.

• 한국전산유체공학회지
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• 제17권2호
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• pp.65-70
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• 2012

The droplet ejection behavior from drop-on-demand printhead are investigated numerically in terms of the non-dimensional parameters. The numerical simulation is performed using a volume-of-fluid model. It is important to eject droplet within the printability range, where the droplet is ejected in stable manner without satellite droplets. Generally, the printability range has been determined by Z number, which is the inverse of Oh number. However, it is found that the ejection of droplets with same Z number can exhibit different behavior depending on the value of Ca and We number. Therefore, it is insufficient to determine the printability range only with Z number. Instead, other non-dimensional parameters, such as Ca and We number, should be considered comprehensively.

• Earthquakes and Structures
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• 제2권1호
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• pp.25-42
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• 2011

This paper discusses a mechanical model for the vulnerability assessment of old masonry building aggregates that takes into account the uncertainties inherent to the building parameters, to the seismic demand and to the model error. The structural capacity is represented as an analytical function of a selected number of geometrical and mechanical parameters. Applying a suitable procedure for the uncertainty propagation, the statistical moments of the capacity curve are obtained as a function of the statistical moments of the input parameters, showing the role of each one in the overall capacity definition. The seismic demand is represented by response spectra; vulnerability analysis is carried out with respect to a certain number of random limit states. Fragility curves are derived taking into account the uncertainties of each quantity involved.

• 산업경영시스템학회지
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• 제17권31호
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• pp.59-72
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• 1994

This paper deals with ordering policies of consumable goods which have large demand rates in a multi-level distribution system. The system we are concerned consists of one Central Distribution Center(CDC) and N non-identical Regional Distribution Centers(RDCs) which have different demand rates, minimum fillrates, leadtimes, etc. The customer demand on the RDC is stationary poisson and the RDCs demand on the CDC is superposition of Q-stage Erlang distributions. We approximate the RDCs and CDC demand distribution to nomal in order to enhance the efficiency of algorithm. The relevant costs include a fixed ordering cost and inventory holding cost, and backorder cost. The objective is to find a continuous-review ordering policy that minimizes the expected average costs under constraints of minimum fill rates of RDCs and maximum allowable mean delay of CDC. We developed an algorithm for determining the optimal ordering policies of the CDC and the RDCs. We verified and compared the performance of the algorithm through the simulation using the algorithm result as the input parameters.