• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.88-96
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• 2010

This paper presents a two-phase quantitative framework to aid the decision making process for effective selection of an efficient freight logistics hub from 8 alternatives in Thailand on the North-South economic corridor. Phase 1 employs both multiple regression and Pearson Feature selection to find the important criteria, as defined by logistics hub score, and to reduce number of criteria by eliminating the less important criteria. The result of Pearson Feature selection indicated that only 5 of 15 criteria affected the logistics hub score. Moreover, Genetic Algorithm (GA) was constructed from original 15 criteria data set to find the relationship between logistics criteria and freight logistics hub score. As a result, the statistical tools are provided the same 5 important criteria, affecting logistics hub score from GA, and data mining tool. Phase 2 performs the fuzzy stochastic AHP analysis with the five important criteria. This approach could help to gain insight into how the imprecision in judgment ratios may affect their alternatives toward the best solution and how the best alternative may be identified with certain confidence. The main objective of the paper is to find the best alternative for selecting freight logistics hub under proper criteria. The experimental results show that by using this approach, Chiang Mai province is the best place with the confidence interval 95%.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1069-1078
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• 2018

Demand response (DR) programs give opportunity to consumers to manage their electricity bills. Besides, distribution system operator (DSO) is interested in using DR programs to obtain technical and economic benefits for distribution network. Since small consumers have difficulties to individually take part in the electricity market, an entity named demand response provider (DRP) has been recently defined to aggregate the DR of small consumers. However, implementing DR programs face challenges to fairly allocate benefits and payments between DRP and DSO. This paper presents a procedure for modeling the interaction between DRP and DSO based on a bilevel programming model. Both DSO and DRP behave from their own viewpoint with different objective functions. On the one hand, DRP bids the potential of DR programs, which are load shifting and load curtailment, to maximize its expected profit and on the other hand, DSO purchases electric power from either the electricity market or DRP to supply its consumers by minimizing its overall cost. In the proposed bilevel programming approach, the upper level problem represents the DRP decisions, while the lower level problem represents the DSO behavior. The obtained bilevel programming problem (BPP) is converted into a single level optimizing problem using its Karush-Kuhn-Tucker (KKT) optimality conditions. Furthermore, point estimate method (PEM) is employed to model the uncertainties of the power demands and the electricity market prices. The efficiency of the presented model is verified through the case studies and analysis of the obtained results.

• Tunnel and Underground Space
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• v.30 no.1
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• pp.15-28
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• 2020

In this study, a procedure was introduced to estimate strength and deformation modulus of the 3-D discrete fracture network(DFN) systems using the distinct element method(DEM). Fracture entities were treated as non-persistent square planes in the DFN systems. Systematically generated fictitious fractures having similar mechanical characteristics of intact rock were combined with non-persistent real fractures to create polyhedral blocks in the analysis domain. Strength and deformation modulus for 10 m cube domain of various deterministic and stochastic 3-D DFN systems were estimated using the DEM to explore the applicability of suggested method and to examine the effect of fracture geometry on strength and deformability of DFN systems. The suggested procedures were found to effective in estimating anisotropic strength and deformability of the 3-D DFN systems.

• Tunnel and Underground Space
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• v.26 no.3
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• pp.166-180
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• 2016

The present study numerically simulated the CO2 injection into the saline aquifer of CO2CRC Otway pilot project and the resulting hydrological-mechanical coupled process in the storage site by TOUGH-FLAC simulator. A three-dimensional numerical model was generated using the stochastic geological model which was established based on well log and core data. It was estimated that the CO2 injection of 30,000t over a period of 200 days increased the pressure near the injection point by 0.5 MPa at the most. The pressure increased rapidly and tended to approach a certain value at an early stage of the injection. The hydrological and mechanical behavior observed from the CO2 flow, effective stress change and stress-strength ratio revealed that the CO2 injection into the saline aquifer under the given condition would not have significant effects on the mechanical safety of the storage site and the hydrological state around the adjacent fault.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.817-826
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• 2002

Many researchers have been tried to forecast the future as analyzing data characteristics and the forecasting methodology may be divided into two cases of deterministic and stochastic techniques. However, the understanding data characteristics may be very important for model construction and forecasting. In the sense of this view, recently, the deterministic method known as nonlinear dynamics has been studied in many fields. This study uses the geometrical methodology suggested by Poincare for analyzing nonlinear dynamic systems and we apply the methodology to understand the characteristics of known systems and hydrologic data, and determines the possibility of forecasting according to the data characteristics. Say, we try to understand the data characteristics as constructing Poincare map by using Poincare section and could conjecture that the data sets are linear or nonlinear and an appropriate model.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.461-480
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• 2010

This paper analyses the data collected from the $2^{nd}$ Jindo Bridge, a cable-stayed bridge in Korea that is a structural health monitoring (SHM) international test bed for advanced wireless smart sensors network (WSSN) technology. The SHM system consists of a total of 70 wireless smart sensor nodes deployed underneath of the deck, on the pylons, and on the cables to capture the vibration of the bridge excited by traffic and environmental loadings. Analysis of the data is performed in both the time and frequency domains. Modal properties of the bridge are identified using the frequency domain decomposition and the stochastic subspace identification methods based on the output-only measurements, and the results are compared with those obtained from a detailed finite element model. Tension forces for the 10 instrumented stay cables are also estimated from the ambient acceleration data and compared both with those from the initial design and with those obtained during two previous regular inspections. The results of the data analyses demonstrate that the WSSN-based SHM system performs effectively for this cable-stayed bridge, giving direct access to the physical status of the bridge.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.54-61
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• 2019

Recently, IITS (intelligent integrated transportation system) has been important topic in Smart City related industry. As a main objective of IITS, prevention of traffic jam (due to car accidents) has been attempted with help of advanced sensor and communication technologies. Studies show that car accident has certain correlation with some factors including characteristics of location, weather, driver's behavior, and time of day. We concentrate our study on observing auto correlativity of car accidents in terms of time of day. In this paper, we performed the ARIMA tests including ADF (augmented Dickey-Fuller) to check the three factors determining auto-regressive, stationarity, and lag order. Summary on forecasting of hourly car crash counts is presented, we show that the traffic accident data obtained in Korea can be applied to ARIMA model and present a result that traffic accidents in Korea have property of being recurrent daily basis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.109-116
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• 2015

This paper is concerned with the single vendor single buyer integrated production inventory problem. To make this problem more practical, space restriction and lead time proportional to lot size are considered. Since the space for the inventory is limited in most practical inventory system, the space restriction for the inventory of a vendor and a buyer is considered. As product's quantity to be manufactured by the vendor is increased, the lead time for the order is usually increased. Therefore, lead time for the product is proportional to the order quantity by the buyer. Demand is assumed to be stochastic and the continuous review inventory policy is used by the buyer. If the buyer places an order, then the vendor will start to manufacture products and the products will be transferred to the buyer with equal shipments many times. The mathematical formulation with space restriction for the inventory of a vendor and a buyer is suggested in this paper. This problem is constrained nonlinear integer programming problem. Order quantity, reorder points for the buyer, and the number of shipments are required to be determined. A Lagrangian relaxation approach, a popular solution method for constrained problem, is developed to find lower bound of this problem. Since a Lagrangian relaxation approach cannot guarantee the feasible solution, the solution method based on the Lagrangian relaxation approach is proposed to provide with a good feasible solution. Total costs by the proposed method are pretty close to those by the Lagrangian relaxation approach. Sensitivity analysis for space restriction for the vendor and the buyer is done to figure out the relationships between parameters.

• Earthquakes and Structures
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• v.13 no.2
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• pp.151-164
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• 2017

This article aims to investigate the possible retrofitting of a deficient building with soft story failure mode by connecting it to an adjacent building which is designed based on current code with friction dampers at all floors. Low cost and high performance reliability along with significant energy dissipation pertaining to stable hysteretic loops may be considered in order to choose the proper damper for connecting adjacent buildings. After connecting two neighbouring floors by friction dampers, the sliding forces of dampers at various stories are set in two arrangements: uniform sliding force and then variable sliding force. In order to account for the stochastic nature of the seismic events, incremental dynamic analyses are employed prior and after the installation of the friction dampers at the various floors. Based on these results, fragility curves and mean annual rate of exceedance of serviceability and ultimate limit states are obtained. The results of this study show that the collapse mode of the deficient building can affect the optimum arrangement of sliding forces of friction dampers at Collapse Prevention (CP) performance level. In particular, the Immediate Occupancy (IO) performance level is not tangible to the sliding force arrangement and it depends solely on sliding force value. Generally it can be claimed that this rehabilitation scheme can turn the challenge of pounding two adjacent buildings into the opportunity of dissipating a large amount of the seismic input energy by the friction dampers, thus improving significantly the poor seismic performance of the deficient structure.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.97-103
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• 2018

In this paper, the estimation method for the power signal harmonics is proposed by using the time-varying optimal finite impulse response (FIR) filter. To estimate the magnitude and phase-angle of the harmonic components, the time-varying optimal FIR filter is designed for the state space representation of the noisy power signal which the magnitude and phase is considered as a stochastic process. Since the time-varying optimal FIR filter used in the proposed method does not use any priori information of the initial condition and has FIR structure, the proposed method could overcome the demerits of Kalman filter based method such as poor estimation and divergence problem. Due to the FIR structure, the proposed method is more robust against to the model uncertainty than the Kalman filter. Moreover, the proposed method gives more general solution than the time-invariant optimal FIR filter based harmonic estimation method. To verify the performance and robustness of the proposed method, the proposed method is compared with time-varying Kalman filter based method through simulation.