• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1902-1912
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• 2024

This paper presents results from system-level modeling of a water-based reactor cavity cooling system using RELAP5-3D. The computational model is benchmarked with experimental data from a half-scale RCCS test facility at Argonne National Laboratory. The model prediction is first compared with a two-phase oscillatory baseline experimental case where mixed accuracy is obtained. The model shows reasonable prediction of mass flow rate, pressure, and temperature but significant overprediction of void fraction. The model prediction is then compared with a fault case where the inlet of the risers is gradually reduced using a throttling valve. As the valve is closed, the model is able to predict some major flow phenomena observed in the experiment such as the dampening of oscillations, the reintroduction of oscillations, as well as boiling, flashing, and geysering in the risers. However, the timeline of these events are not well captured by the model. The model is also used to investigate the evolution of flow regime in the chimney. This work highlights that the semi-empirical constitutive relations used in RELAP-3D could have a strong influence on the accuracy of the model in two-phase oscillatory flows.

• International Journal of Automotive Technology
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• v.7 no.4
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• pp.459-468
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• 2006

The objective of this paper is the development of the forward-looking dynamic simulation model of a hybrid electric vehicle(HEV) for a fuel economy study. The specification of the vehicle is determined based on two factors, engine peak power to curb weight ratio and specific engine power. The steady state efficiency models of the powertrain components are explained in detail. These include a spark ignition direct injection(SIDI) engine, an integrated starter alternator(ISA), and an infinitely variable transmission(IVT). The paper describes the integration of these models into a forward facing dynamic simulation diagram using the AMESim environment. Appropriate vehicle and driver models have been added and described. The controller was designed in Simulink and was combined with the physical powertrain model by the co-simulation interface. Finally, the simulation results of the HEV are compared with those of a baseline vehicle in order to demonstrate the fuel economy potential. Results for the vehicle speed error and the fuel economy over standard driving cycles are illustrated.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.104-110
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• 2016

Dense local image descriptors like SIFT are fruitful for capturing salient information about image, shown to be successful in various image-related tasks when formed in bag-of-words representation (i.e., histograms). In this paper we consider to utilize these dense local descriptors in the object tracking problem. A notable aspect of our tracker is that instead of adopting a point estimate for the target model, we account for uncertainty in data noise and model incompleteness by maintaining a distribution over plausible candidate models within the Bayesian framework. The target model is also updated adaptively by the principled Bayesian posterior inference, which admits a closed form within our Dirichlet prior modeling. With empirical evaluations on some video datasets, the proposed method is shown to yield more accurate tracking than baseline histogram-based trackers with the same types of features, often being superior to the appearance-based (visual) trackers.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2004.10a
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• pp.108-111
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• 2004

Structural dynamic characteristics and aeroelastic stability of a small-scale bearingless rotor system have been investigated. A flexbeam is one of the most important component of bearingless hub system. It must have sufficient torsional flexibility as well as baseline stiffness in order to produce feathering motion. In the present paper, a cross-shaped composite flexbeam has been proposed for a guarantee of torsional flexibility and flapwise and lagwise bending stiffness. One dimensional elastic beam model was used for the construction of a structural model. Equivalent isotropic sectional stiffness was used in the blade model, and the flexbeam was regarded as anisotropic; which has ten independent stiffness quantities. CAMRAD II has been used for the analysis of structural dynamic characteristics of the bearingless rotor system. Rotational natural frequencies and aeroelastic stability at hovering have been investigated. Analysis result shows that the cross-shaped flexbeam has the rotational natural frequency tuning capacity.

• Speech Sciences
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• v.10 no.3
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• pp.263-277
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• 2003

One of major problems in speech recognition is performance degradation due to the mismatch between the training and test environments. Recently, Stereo-based Piecewise LInear Compensation for Environments (SPLICE), which is frame-based bias removal algorithm for cepstral enhancement using stereo training data and noisy speech model as a mixture of Gaussians, was proposed and showed good performance in noisy environments. In this paper, we propose several methods to improve the conventional SPLICE. First we apply Cepstral Mean Subtraction (CMS) as a preprocessor to SPLICE, instead of applying it as a postprocessor. Secondly, to compensate residual distortion after SPLICE processing, two-stage SPLICE is proposed. Thirdly we employ phonetic information for training SPLICE model. According to experiments on the Aurora 2 database, proposed method outperformed the conventional SPLICE and we achieved a 50% decrease in word error rate over the Aurora baseline system.

• Environmental Engineering Research
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• v.10 no.6
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• pp.316-327
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• 2005

Constructed wetlands provide several benefits that are not solely limited to storm water management and are becoming common in storm water management. In this research, four recently constructed wetlands underwent in situ and laboratory water sampling to determine their efficiency in removing storm water pollutants over a 5-month period. From the sampling results, it was determined that each of the wetlands was able to reduce the concentration of pollutants in the stormwater. To aid in the assessment of the wetlands against each other, a model was developed to determine the extent of removal of stormwater pollutants over the length of the wetland. The results from this model complimented the data collected from the field. Improvements, such as increased amounts of vegetation were recommended for the wetlands with the aim of increasing the effectiveness. Further investigations into the wetlands will allow for better understanding of the wetland's performance.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.196-202
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• 2024

The ability to understand given environments and plan a sequence of actions leading to goal state is crucial for personal service robots. With recent advancements in deep learning, numerous studies have proposed methods for state representation in planning. However, previous works lack explicit information about relationships between objects when the state observation is converted to a single visual embedding containing all state information. In this paper, we introduce graph-based state representation that incorporates both object and relationship features. To leverage these advantages in addressing the task planning problem, we propose a Graph Neural Network (GNN)-based subgoal prediction model. This model can extract rich information about object and their interconnected relationships from given state graph. Moreover, a search-based algorithm is integrated with pre-trained subgoal prediction model and state transition module to explore diverse states and find proper sequence of subgoals. The proposed method is trained with synthetic task dataset collected in simulation environment, demonstrating a higher success rate with fewer additional searches compared to baseline methods.

• Structural Engineering and Mechanics
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• v.91 no.6
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• pp.591-606
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• 2024

This article proposes a new methodology for identifying beam damage based on changes in modal parameters using the Double Stage Extended Improved Particle Swarm Optimization (DSEIPSO) technique. A finite element code is first developed in MATLAB to model an ideal beam structure based on classical beam theory. An experimental study is then performed on a laboratory-scale beam, and the modal parameters are extracted. An improved version of the PSO algorithm is employed to update the finite element model based on the experimental measurements, representing the real structure and forming the baseline model for all further damage detection. Subsequently, structural damages are introduced in the experimental beam. The DSEIPSO algorithm is then utilized to optimize the objective function, formulated using the obtained mode shapes and the natural frequencies from the damaged and undamaged beams to identify the exact location and extent of the damage. Experimentally obtained resultsfrom a simple cantilever beam are used to validate the effectiveness of the proposed method. The illustrated results show the effectiveness of the proposed method for structural damage detection in the SHM field.

• Phonetics and Speech Sciences
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• v.8 no.4
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• pp.103-113
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• 2016

This paper aims to propose articulatory features as novel predictors for automatic pronunciation assessment of English produced by Korean learners. Based on the distinctive feature theory, where phonemes are represented as a set of articulatory/phonetic properties, we propose articulatory Goodness-Of-Pronunciation(aGOP) features in terms of the corresponding articulatory attributes, such as nasal, sonorant, anterior, etc. An English speech corpus spoken by Korean learners is used in the assessment modeling. In our system, learners' speech is forced aligned and recognized by using the acoustic and pronunciation models derived from the WSJ corpus (native North American speech) and the CMU pronouncing dictionary, respectively. In order to compute aGOP features, articulatory models are trained for the corresponding articulatory attributes. In addition to the proposed features, various features which are divided into four categories such as RATE, SEGMENT, SILENCE, and GOP are applied as a baseline. In order to enhance the assessment modeling performance and investigate the weights of the salient features, relevant features are extracted by using Best Subset Selection(BSS). The results show that the proposed model using aGOP features outperform the baseline. In addition, analysis of relevant features extracted by BSS reveals that the selected aGOP features represent the salient variations of Korean learners of English. The results are expected to be effective for automatic pronunciation error detection, as well.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.95-97
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• 2005

Communication, Ocean, and Meteorological Satellite (COMS) to be launched in year 2008 will be the first Korean multi-purpose geostationary satellite aiming at three major missions, i.e.: communication, ocean, and meteorological applications. The development of systems for the meteorological mission sponsored by the Korea Meteorological Administration (KMA) consists of payloads, ground system, and data processing system. The program called COMS Meteorological Data Processing System (CMDPS) has been initiated for the development of data processing system. The primary objective ofCMDPS is to derive the level-2 environmental products from geo-Iocated and calibrated level 1.5 COMS data. Preliminary design for the level-2 data processing system consists of 16 baseline products and will be refined by end of 3rd project year. Also considered for the development are the necessary initial information such as land use and digital elevation map, algorithms for the vicarious calibration and procedures for the calibration monitoring, and radiative transfer model. Here, we briefly introduce the overall development strategy, flow chart for the intended baseline products, a few preliminary algorithm results and future plans.