• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2D
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• pp.103-110
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• 2012

This study presents O/D based emission estimation model and methodology under cold- and hot-start conditions. Contrasting with existing link-based model, new model is able to estimate cold-start emissions with actual traffic characteristics. The results of the case study with new model show similar amount of emission with existing model under hot-start conditions, but five times much more than existing model under cold-start conditions. The annual social benefit estimated by this model is 56.2 hundred million won, which is 48% higher than the result from existing model. It means current green transportation policies are undervalued in terms of air quality improvement. Therefore, New model is expected to improve the objectivity of air quality evaluation results regarding green transportation policies and be applied in various transportation-environment policies.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2297-2310
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• 2022

A condensation heat transfer model is essential to accurately predict the performance of the passive containment cooling system (PCCS) during an accident in an advanced light water reactor. However, most of existing models tend to predict condensation heat transfer very well for a specific range of thermal-hydraulic conditions. In this study, a new correlation for condensation heat transfer coefficient (HTC) is presented using machine learning technique. To secure sufficient training data, a large number of pseudo data were produced by using ten existing condensation models. Then, a neural network model was developed, consisting of a fully connected layer and a convolutional neural network (CNN) algorithm, DenseNet. Based on the hold-out cross-validation, the neural network was trained and validated against the pseudo data. Thereafter, it was evaluated using the experimental data, which were not used for training. The machine learning model predicted better results than the existing models. It was also confirmed through a parametric study that the machine learning model presents continuous and physical HTCs for various thermal-hydraulic conditions. By reflecting the effects of individual variables obtained from the parametric analysis, a new correlation was proposed. It yielded better results for almost all experimental conditions than the ten existing models.

• Steel and Composite Structures
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• v.49 no.1
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• pp.109-123
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• 2023

Headed studs welded to steel beams and embedded within the concrete of deck slabs are vital components of modern composite floor systems, where safety and economy depend on the accurate predictions of the stud shear resistance. The multitude of existing deck profiles and the complex behavior of studs in deck slab ribs makes developing accurate and reliable mechanical or empirical design models challenging. The paper addresses this issue by presenting a machine learning (ML) model developed from the natural gradient boosting (NGBoost) algorithm capable of producing probabilistic predictions and a database of 464 push-out tests, which is considerably larger than the databases used for developing existing design models. The proposed model outperforms models based on other ML algorithms and existing descriptive equations, including those in EC4 and AISC 360, while offering probabilistic predictions unavailable from other models and producing higher shear resistances for many cases. The present study also showed that the stud shear resistance is insensitive to the concrete elastic modulus, stud welding type, location of slab reinforcement, and other parameters considered important by existing models. The NGBoost model was interpreted by evaluating the feature importance and dependence determined with the SHapley Additive exPlanations (SHAP) method. The model was calibrated via reliability analyses in accordance with the Eurocodes to ensure that its predictions meet the required reliability level and facilitate its use in design. An interactive open-source web application was created and deployed to the cloud to allow for convenient and rapid stud shear resistance predictions with the developed model.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.04a
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• pp.11-16
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• 1989

This paper presents a fatigue reliability model for the reliability-based evaluation of remaining fatigue life of existing rail-road bridges. It is demonstrated that the simple fatigue reliability model based on the Weibull distribution of fatigue life can be extended by incorporating various effects due to the rate of the train-traffic increase and in-service Inspections. The paper also suggests the system fatigue reliability analysis using an approximate formulation and 2nd-order bound solutions. The application of the proposed model to existing rail-road brdiges based on field load tests shows that it may be practically used for the assessment of fatigue reliability, remaining life, and in-service inspection scheduling of existing rail-road bridges.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.91-97
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• 2019

In automatic map generalization, the formalization of cartographic principles is important. This study proposes and evaluates the selection method for road network generalization that analyzes existing maps using reverse engineering and formalizes the selection rules for the road network. Existing maps with a 1:5,000 scale and a 1:25,000 scale are compared, and the criteria for selection of the road network data and the relative importance of each network object are determined and analyzed using $T{\ddot{o}}pfer^{\prime}s$ Radical Law as well as the logistic regression model. The selection model derived from the analysis result is applied to the test data, and road network data for the 1:25,000 scale map are generated from the digital topographic map on a 1:5,000 scale. The selected road network is compared with the existing road network data on the 1:25,000 scale for a qualitative and quantitative evaluation. The result indicates that more than 80% of road objects are matched to existing data.

• Korean Journal of Hydrosciences
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• v.4
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• pp.33-49
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• 1993

The Purpose of this study is to classify existing hysteresis models and to discuss a possibility of a new type of the hysteresis model. The existing hysteresis models are classified into three types: the interpolation model, the scaling model and the domain model, of which only domain model is to simulate hysteresis curves based on the theoretical approach, It is useful to develop a hysteresis model that requires only one branch of hysteresis curves for the model calibration because obtaining hysteresis curves by experiments is expensive and time-concept by many investigators, however their models are not successful to accurately simulate real data of Rubicon Sandy Loam and Dune Sand. There is a possibility that a new model is based on the dependent domain concept considering the weighting factor, $P_a$($\theta$), which accounts for the pore blockage effect against air entry. Conclusively, a new model where the weighting factor $P_a$($\theta$) in Model III-1 (Mualem, 1984) reduces to a known variable through an appropriate method is an alternative model which required only one branch of main curves for the model calibration.

• Selected Papers of The Society of Naval Architects of Korea
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• v.2 no.1
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• pp.129-139
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• 1994

This paper describes a design model for the conceptual design of ships. Existing design models have problems such that their operating mode of batch versions cannot reflect the design procedures in reality. Reliability of the results is low because the performance estimations are based mainly on empirical formulas. To improve the problems of existing design models, a new design model has been developed. The new model consists of an interactive user interface, a database of main engines, a database of particulars of existing ships, and ten modules for performance estimations. To develop such a user-oriented system, the concept of graphical user interface (GUI) is adopted.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.44-53
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• 2008

An interacting multiple model (IMM) estimation algorithm based on the mixing of the predicted state estimates is proposed in this paper for a right continuous jump-linear system model different from the left-continuous system model used to develop the existing IMM algorithm. The difference lies in the modeling of the mode switching time. Performance of the proposed algorithm is compared numerically with that of the existing IMM algorithm for noisy system identification. Based on the numerical analysis, the proposed algorithm is applied to target tracking with a large sampling period for performance comparison with the existing IMM.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1531-1539
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• 2020

Searching for portable baggage through the system before boarding an airplane at an airport is important because it prevents many risks. In addition to these dangerous items, personal and confidential information leaks are occurring at airports through data storage devices. In the airport search system, there is a need for a system that searches not only dangerous items but also devices that can leak data. In this paper, we proposed a model that searches for a data storage device by improving the existing model. A comparative evaluation was conducted using existing algorithms. As a result, it was confirmed that the performance of the proposed model is 74 in the training data and 46.73 in the test data, which is superior to the existing model.

• Geomechanics and Engineering
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• v.20 no.2
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• pp.103-112
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• 2020

The dynamic response of crossing tunnels under heavy-haul train loads is still not fully understood. In this study, based on the case of a high-speed tunnel underneath an existing heavy-haul railway tunnel, a model experiment was performed to research the dynamic response characteristics of crossing tunnels. It is found that the under-crossing changes the dynamic response of the existing tunnel and surrounding rock. The acceleration response of the existing tunnel enhances, and the dynamic stress of rock mass between crossing tunnels decreases after the excavation. Both tunneling and the excitation of heavy-haul train loads stretch the tunnel base, and the maximum tensile strain is 18.35 µε in this model test. Then, the measured results were validated by numerical simulation. Also, a parametric study was performed to discuss the influence of the relative position between crossing tunnels and the advanced support on the dynamic behavior of the existing tunnel, where an amplifying coefficient of tunnel vibration was introduced to describe the change in acceleration due to tunneling. These results reveal the dynamic amplifying phenomenon of the existing tunnel during the new tunnel construction, which can be referred in the dynamic design of crossing tunnels.