• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.4
• /
• pp.120-128
• /
• 2017

More people travel oversea as the economic size of Korea is getting larger and more new jobs are requested to be created by the society. To respond to these trend and request, Incheon International Airport Corporation (IIAC) is about to expand its processing capability with a new terminal; 54 million passengers to 72 million. IIAC is also introducing new strategies such as open innovation (OI) and creating shared value (CSV). With these changes, IIAC faces new challenges of restructuring its business and organization with new ideas. Most organizations including IIAC are becoming more dependent on external resources to keep their competitive advantages under the turbulence of global business environmental changes. Therefore, they focus on the OI paradigm which is reported as a convincing strategy to improve competitiveness in terms of budget and time-to-market. OI is to quickly react to the rapidly changing business environment and is adopted to support startup incubation. In the previous research with IIAC, three major tasks were defined; utilizing the IIAC brand power for external vendors, building a technology road-map, and introducing a collaboration support system. This paper deals with the collaboration system as proposed in the previous research. We focused on the collaboration process for startup incubation. Cases were studied; the K-startup model by the government, a university model to explore youth startups, and a R&D institute model to study professional startups. Based on the case studies, we defined an IIAC model and proposed issues to take care of. The model is distinguished from the other studied models since IIAC is a prospective customer of new technology.

• International Journal of Reliability and Applications
• /
• v.2 no.3
• /
• pp.209-240
• /
• 2001

Computer-based simulation and analysis is used extensively in engineering for a variety of tasks. Despite the steady and continuing growth of computing power and speed, the computational cost of complex high-fidelity engineering analyses and simulations limit their use in important areas like design optimization and reliability analysis. Statistical approximation techniques such as design of experiments and response surface methodology are becoming widely used in engineering to minimize the computational expense of running such computer analyses and circumvent many of these limitations. In this paper, we compare and contrast five experimental design types and four approximation model types in terms of their capability to generate accurate approximations for two engineering applications with typical engineering behaviors and a wide range of nonlinearity. The first example involves the analysis of a two-member frame that has three input variables and three responses of interest. The second example simulates the roll-over potential of a semi-tractor-trailer for different combinations of input variables and braking and steering levels. Detailed error analysis reveals that uniform designs provide good sampling for generating accurate approximations using different sample sizes while kriging models provide accurate approximations that are robust for use with a variety of experimental designs and sample sizes.

• Coupled systems mechanics
• /
• v.9 no.5
• /
• pp.433-454
• /
• 2020

In-place analysis for offshore platforms is essentially required to make proper design for new structures and true assessment for existing structures. The structural integrity of platform components under the maximum and minimum operating loads of environmental conditions is required for risk assessment and inspection plan development. In-place analyses have been executed to check that the structural member with all appurtenances robustness and capability to support the applied loads in either storm condition or operating condition. A nonlinear finite element analysis is adopted for the platform structure above the seabed and the pile-soil interaction to estimate the in-place behavior of a typical fixed offshore platform. The analysis includes interpretation of dynamic design parameters based on the available site-specific data, together with foundation design recommendations for in-place loading conditions. The SACS software is utilized to calculate the natural frequencies of the model and to obtain the response of platform joints according to in-place analysis then the stresses at selected members, as well as their nodal displacements. The directions of environmental loads and water depth variations have important effects on the results of the in-place analysis behavior. The result shows that the in-place analysis is quite crucial for safe design and operation of offshore platform and assessment for existing offshore structures.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.3
• /
• pp.559-564
• /
• 2010

The GMDH(Group Method of Data Handling) algorithm can be used to predict the complex nonlinear systems. The traditional GMDH algorithm produces the prdicted output of the system model in the output layer through the input layer and the intermediate layers as the prescribed process. The outputs of each layer are produced only by the outputs of the former layer. However, in the traditional GMDH algorithm, though the optimal structure of each layer is derived, the overall structure may not be derived optimally. To overcome this problem, GMDH prediction model which has the overall optimal structure is constructed by feeding back the error between the predicted output and the real output. This can make the prediction more precise. The capability improvement of the proposed algorithm compared to the traditional algorithm is verified through computer simulation.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.12 no.3
• /
• pp.437-445
• /
• 1999

This paper presents a simple modification technique of finite element model for dynamic analysis of linear/nonlinear structural system subjected to multiple support excitation. For the sake of verification of the proposed method, dynamic responses obtained by the present technique for a couple of linear and nonlinear structural systems were compared with those by a general-purpose structural analysis software which can deal with the multi-support analysis. The method presented in this paper is expected to be used for multiple support excitation analysis by means of a computer code without the capability of modeling the non-synchronous support motion.

• Journal of Power Electronics
• /
• v.16 no.2
• /
• pp.643-653
• /
• 2016

The conventional methods used to evaluate battery state-of-charge (SOC) cannot accommodate the chemistry nonlinearities, measurement inaccuracies and parameter perturbations involved in estimation systems. In this paper, an impedance-based equivalent circuit model has been constructed with respect to a LiFePO₄ battery by approximating the electrochemical impedance spectrum (EIS) with RC circuits. The efficiencies of approximating the EIS with RC networks in different series-parallel forms are first discussed. Additionally, the typical hysteresis characteristic is modeled through an empirical approach. Subsequently, a methodology incorporating an H-infinity observer designated for open-circuit voltage (OCV) observation and a hysteresis model developed for OCV-SOC mapping is proposed. Thereafter, evaluation experiments under FUDS and UDDS test cycles are undertaken with varying temperatures and different current-sense bias. Experimental comparisons, in comparison with the EKF based method, indicate that the proposed SOC estimator is more effective and robust. Moreover, test results on a group of Li-ion batteries, from different manufacturers and of different chemistries, show that the proposed method has high generalization capability for all the three types of Li-ion batteries.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.49 no.6
• /
• pp.305-311
• /
• 2000

This paper presents a hybrid algorithm for solving optimal power flow(OPF) in order to enhance a systems capability to cope with outages, which is based on combined application of evolutionary computation and local search method. The efficient algorithm combining main advantages of two methods is as follows : Firstly, evolutionary computation is used to perform global exploitation among a population. This gives a good initial point of conventional method. Then, local methods are used to perform local exploitation. The hybrid approach often outperforms either method operating alone and reduces the total computation time. The objective function of the security constrained OPF is the minimization of generation fuel costs and real power losses. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). In OPF considering security, the outages are selected by contingency ranking method(contingency screening model). The OPF considering security, the outages are selected by contingency ranking method(contingency screening model). The method proposed is applied to IEEE 30 buses system to show its effectiveness.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.12
• /
• pp.3868-3888
• /
• 2022

A widely used social networking service like Twitter has the ability to disseminate information to large groups of people even during a pandemic. At the same time, it is a convenient medium to share irrelevant and unverified information online and poses a potential threat to society. In this research, conventional machine learning algorithms are analyzed to classify the data as either non-rumor data or rumor data. Machine learning techniques have limited tuning capability and make decisions based on their learning. To tackle this problem the authors propose a deep learning-based Rumor Detection Neural Network model to predict the rumor tweet in real-world events. This model comprises three layers, AttCNN layer is used to extract local and position invariant features from the data, AttBi-LSTM layer to extract important semantic or contextual information and HPOOL to combine the down sampling patches of the input feature maps from the average and maximum pooling layers. A dataset from Kaggle and ground dataset #gaja are used to train the proposed Rumor Detection Neural Network to determine the veracity of the rumor. The experimental results of the RDNN Classifier demonstrate an accuracy of 93.24% and 95.41% in identifying rumor tweets in real-time events.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2568-2574
• /
• 2005

Control architecture of the action based robot engineering can be divided into two types of deliberate type - and reactive type- controller. Typical deliberate type, slow in reaction speed, is well suited for the realization of the higher intelligence with its capability to forecast on the basis of environmental model according to time flow, while reactive type is suitable for the lower intelligence as it fits to the realization of speedy reactive action by inputting the sensor without a complete environmental model. Looking at the environments in the application areas in which robots are actually used, we can see that they have been mostly covered by the uncertain and unknown dynamic changes depending on time and place, the previously known knowledge being existed though. It may cause, therefore, any deterioration of the robot performance as well as further happen such cases as the robots can not carry out their desired performances, when any one of these two types is solely engaged. Accordingly this paper aims at suggesting Goal-oriented Geometric Model(GGM) Based Intelligent System Architecture which leads the actions of the robots to perform their jobs under variously changing environment and applying the suggested system structure to the navigation issues of the robots. When the robots do perform navigation in human life changing in a various manner with time, they can appropriately respond to the changing environment by doing the action with the recognition of the state. Extending this concept to cover the highest hierarchy without sticking only to the actions of the robots can lead us to apply to the algorithm to perform various small jobs required for the carrying-out of a large main job.

• Nuclear Engineering and Technology
• /
• v.54 no.3
• /
• pp.803-810
• /
• 2022

The small modular liquid-metal fast reactor (SMFR) is an important component of advanced nuclear systems. SMFRs exhibit relatively low breeding capability and constraint space for control rod installation. Consequently, control rods are deeply inserted at beginning and are withdrawn gradually to compensate for large burnup reactivity loss in a long lifetime. This paper is committed to investigating the impact of control rod compensation operation on core neutronics characteristics. This paper presents a whole core fine depletion model of long lifetime SMFR using OpenMC and the influence of depletion chains is verified. Three control rod position schemes to simulate the compensation process are compared. The results show that the fine simulation of the control rod compensation process impacts significantly the fuel burnup distribution and absorber consumption. A control rod equivalent position scheme proposed in this work is an optimal option in the trade-off between computation time and accuracy. The control position is crucial for accurate power distribution and void feedback coefficients in SMFRs. The results in this paper also show that the pin level power distribution is important due to the heterogeneous distribution in SMFRs. The fuel burnup distribution at the end of core life impacts the worth of control rods.