• Smart Structures and Systems
• /
• v.10 no.4_5
• /
• pp.375-391
• /
• 2012

This paper reports the structural health monitoring benchmark study results for the Canton Tower using Bayesian methods. In this study, output-only modal identification and finite element model updating are considered using a given set of structural acceleration measurements and the corresponding ambient conditions of 24 hours. In the first stage, the Bayesian spectral density approach is used for output-only modal identification with the acceleration time histories as the excitation to the tower is unknown. The modal parameters and the associated uncertainty can be estimated through Bayesian inference. Uncertainty quantification is important for determination of statistically significant change of the modal parameters and for weighting assignment in the subsequent stage of model updating. In the second stage, a Bayesian model updating approach is utilized to update the finite element model of the tower. The uncertain stiffness parameters can be obtained by minimizing an objective function that is a weighted sum of the square of the differences (residuals) between the identified modal parameters and the corresponding values of the model. The weightings distinguish the contribution of different residuals with different uncertain levels. They are obtained using the Bayesian spectral density approach in the first stage. Again, uncertainty of the stiffness parameters can be quantified with Bayesian inference. Finally, this Bayesian framework is applied to the 24-hour field measurements to investigate the variation of the modal and stiffness parameters under changing ambient conditions. Results show that the Bayesian framework successfully achieves the goal of the first task of this benchmark study.

• Nuclear Engineering and Technology
• /
• v.47 no.2
• /
• pp.204-211
• /
• 2015

Probabilistic safety assessment (PSA) has had a significant role in quantitative decision-making by finding design and operational vulnerabilities and evaluating cost-benefit in improving such weak points. In particular, it has been widely used as the core methodology for risk-informed applications (RIAs). Even though the nature of PSA seeks realistic results, there are still "conservative" aspects. One of the sources for the conservatism is the assumptions of safety analysis and the estimation of failure frequency. Surveillance, diagnosis, and prognosis (SDP), utilizing massive databases and information technology, is worth highlighting in terms of its capability for alleviating the conservatism in conventional PSA. This article provides enabling techniques to solidify a method to provide time- and condition-dependent risks by integrating a conventional PSA model with condition monitoring and prognostics techniques. We will discuss how to integrate the results with frequency of initiating events (IEs) and probability of basic events (BEs). Two illustrative examples will be introduced: (1) how the failure probability of a passive system can be evaluated under different plant conditions and (2) how the IE frequency for a steam generator tube rupture (SGTR) can be updated in terms of operating time. We expect that the proposed model can take a role of annunciator to show the variation of core damage frequency (CDF) depending on operational conditions.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.22 no.2
• /
• pp.76-82
• /
• 2018

In this present study, in order to update the finite element model considering the boundary conditions, a method has been proposed. The conventional finite element model updating method, updates the finite element model by using the dynamic characteristics (natural frequency, mode shape) which can be estimated from the ambient vibration test. Therefore, prediction of the static response of an actual structure is difficult. Furthermore, accurate estimation of the physical properties is relatively hard. A novel method has been proposed to overcome the limitations of conventional method. Initially, the proposed method estimates the rotational spring constant of a finite element model using the deflection of structure and the rotational displacement of support measurements. The final updated finite element model is constructed by estimating the material properties of the structure using the finite element model with updated rotational spring constant and the dynamic characteristics of the structure. The proposed finite element model updating method is validated through numerical simulation and compared with the conventional finite element model updating method.

• Journal of the Korea Computer Graphics Society
• /
• v.25 no.2
• /
• pp.11-18
• /
• 2019

In this paper, we propose a framework that can perform acceleration collision detection efficiently by using a cone based collision area in a particle-based system which requires collision detection with many objects. Three conditions determine particle and cone-based collision regions: 1) If there is a cone position within the radius of the adjacent particle, 2) In the case where the position of the adjacent particle exists in the cone area, 3) When adjacent particles exist between two vectors forming a cone area. As a result, it is defined that when the above conditions are all satisfied, the particle and the region of a cone have collided. In this paper, we automatically update the area of the cone, which is the collision detection area, according to the particle movement. Determine the direction and length of the cone based on the position and velocity of the particle to calculate the dynamic change of the cone. Collision detection is performed quickly using only the particles in the finally calculated area. The acceleration method proposed in this paper is simple to implement because it is executed with a closed form equation instead of explicitly creating the tree data structure, and collision inspection performance is improved in all results.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2003.05a
• /
• pp.181-186
• /
• 2003

The satellite navigation system is widely used for identifying a user's position regardless of weather or geographic conditions and also make effect on new technology of marine LBS(Location Based Service), which has the technology of geographic information such as the ENC. Generally, there are conceivable systems of marine LBS such as ECDIS, or ECS that use the ENC itself with powerful processor in installed type on ships bridge. Since the ENC is relatively heavy structure with dummy format for data transfer between different systems, we should reduce the ENC to small and compact size in order to use it in mobile platform. In this paper, we assumed that the mobile system like PDA, or Webpad can be used for small capability of mobile platform. However, the ENC should be updated periodically by update profile data produced by HO. If we would reduce the ENC without a consideration of update, we could not get newly updated data furthermore. As summary, we studied considerations for ENC reduction with update capability. It will make the ENC be useful in many mobile platforms for various applications.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_4
• /
• pp.1889-1900
• /
• 2022

Roads are an essential factor in the physical functioning of modern society. The spatial information of the road has much longer update cycle than the traffic situation information, and it is necessary to generate the information faster and more accurately than now. In this study, as a way to achieve that goal, the Pan-sharpening technique was applied to satellite images of Kompsat 3 and 3A to improve spatial resolution. Then, the data were used for road extraction using the semantic segmentation technique, which has been actively researched recently. The acquired Kompsat 3/3A pan-sharpened images were trained by putting it into a U-Net based segmentation model along with Massachusetts road data, and the applicability of the images were evaluated. As a result of training and verification, it was found that the model prediction performance was maintained as long as certain conditions were maintained for the input image. Therefore, it is expected that the possibility of utilizing satellite images such as Kompsat satellite will be even higher if rich training data are constructed by applying a method that minimizes the impact of surrounding environmental conditions affecting models such as shadows and surface conditions.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.10 no.6 s.52
• /
• pp.19-28
• /
• 2006

Most conventional model updating methods must use mathematical objective function with experimental modal matrices and analytical system matrices or must use information about the gradient or higher derivatives of modal properties with respect to each updating parameter. Therefore, most conventional methods are not appropriate for complex structural system such as bridge structures due to stability problem in inverse analysis with ill-conditions. Sometimes, moreover, the updated model may have no physical meaning. In this paper, a new FE model updating method based on a hybrid optimization technique using genetic algorithm (GA) and Holder-Mead simplex method (NMS) is proposed. The performance of hybrid optimization technique on the nonlinear problem is demonstrated by the Goldstein-Price function with three local minima and one global minimum. The influence of the objective function is evaluated by the case study of a simulated 10-dof spring-mass model. Through simulated case studies, finally, the objective function is proposed to update mass as well as stiffness at the same time. And so, the proposed hybrid optimization technique is proved to be an efficient method for FE model updating.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.8
• /
• pp.667-675
• /
• 2013

This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.15 no.4
• /
• pp.273-280
• /
• 2012

The numerical simulation using the Lattice Boltzmann Method in the field of computational fluid dynamics becomes wider in the engineering applications because of its simplicity of update rules compared to the conventional Navier-Stokes solvers. Here, a two-dimensional D2Q9 LB model is numerically tested with a few new computational treatment on the free surface. The single relaxation time is applied under the gravitational field where applied only in the higher density fluid because of its big density difference. At the free surface, the reconstruction techniques in combination with boundary conditions is adopted in order to get some distribution function coming into the fluid site from the air one, and surface tension, early stable test for the gravitional field is considered in it. With the implementation of the gravitational profile, conserving the overall mass and grid dependency are observed during the calculations and freesurface advance track is well captured with an experiment.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.60 no.6
• /
• pp.13-20
• /
• 2018

Universal Soil Loss Equation (USLE) has been widely used to estimate potential soil loss because USLE is a simple and reliable method. The rainfall erosivity factor (R factor) explains rainfall characteristics. R factors, cited in the Bulletin on the Survey of the Erosion of Topsoil of the Ministry of Environment in the Republic of Korea, are too outdated to represent current rainfall patterns in the Republic of Korea. Rainfall datasets at one minute intervals from 2013 to 2017 were collected from fifty rainfall gauge stations to update R factors considering current rainfall condition. The updated R factors in this study were compared to the previous R factors which were calculated using the data from 1973 to 1996. The coefficient of determination between the updated and the previous R factors shows 0.374, which means the correlation is not significant. Therefore, it was concluded that the previous R factors might not explain current rainfall conditions. The other remarkable result was that regression equations using annual rainfall data might be inappropriate to estimate reasonable R factors because the correlation between annual rainfall and the R factors was generally unsatisfy.