• Structural Engineering and Mechanics
• /
• v.17 no.2
• /
• pp.267-279
• /
• 2004

This paper presents an improved Monte Carlo simulation for the probabilistic determination of initial cable forces of cable-stayed bridges under dead loads using the response surfaces method. A response surface (i.e. a quadratic response surface without cross-terms) is used to approximate structural response. The use of the response surface eliminates the need to perform a deterministic analysis in each simulation loop. In addition, use of the response surface requires fewer simulation loops than conventional Monte Carlo simulation. Thereby, the computation time is saved significantly. The statistics (e.g. mean value, standard deviation) of the structural response are calculated through conventional Monte Carlo simulation method. By using Monte Carlo simulation, it is possible to use the existing deterministic finite element code without modifying it. Probabilistic analysis of a truss demonstrates the proposed method' efficiency and accuracy; probabilistic determination of initial cable forces of a cable-stayed bridge under dead loads verifies the method's applicability.

• Journal of Electrochemical Science and Technology
• /
• v.10 no.3
• /
• pp.276-283
• /
• 2019

Nitinol is an alloy of nickel and titanium. Nitinol is one of the shape memory alloys(SMA) that are restored to a remembered form, changing the crystal structure at a given temperature. Because of these unique features, it is used in medical devices, high precision sensors, and aerospace industries. However, the conventional method of mechanical machining for nitinol has problems of thermal and residual stress after processing. Therefore, the electrochemical machining(ECM), which does not produce residual stress and thermal deformation, has emerged as an alternative processing technique. In addition, to replace the existing experimental planning methods, this study used deep neural network(DNN), which is the basis for AI. This method was shown to be more useful than conventional method of design of experiments(RSM, Taguchi, Regression) by applying deep neural network(DNN) to electrochemical machining(ECM) and comparing root mean square errors(RMSE). Comparison with actual experimental values has shown that DNN is a more useful method than conventional method. (DOE - RSM, Taguchi, Regression). The result of the machining was accurately and efficiently predicted by applying electrochemical machining(ECM) and deep neural network(DNN) to the shape memory alloy(SMA), which is a hard-mechinability material.

• Journal of the Korean Society of Safety
• /
• v.32 no.2
• /
• pp.92-97
• /
• 2017

This study deals with new application method of the connecting tuned mass damper (CTMD) system for efficient vibration control of adjacent twin structures which have the same dynamic properties such as natural frequency and damping characteristics to each other. In the existing research, the vibration control of the twin structures has a limit to the application of the conventional damper-connection method of the twin structures. Due to the same frequency characteristics leading to the equally vibrating behaviors, it is impossible to apply the conventional connection method of the adjacent structures. In order to overcome these limitations induced by the symmetry of the dynamic characteristics, we propose a new CTMD-based control system that adopts the conventional connection configuration but unbalances the symmetric system by arranging the control device asymmetrically and then can finally achieve the efficient control performance. In order to demonstrate the applicability of the proposed system, numerical simulations of the optimally designed proposed system have been performed in comparison with the optimal design results of the existing independent single tuned mass damper (STMD) control system and the another optimal control system previously proposed by the same author, hereafter called CTMD-OsTMD. The comparative results of the control performances among STMD, CTMD-OsTMD and the proposed CTMD systems verified that the newly proposed control system can be a control-efficient and cost-effective system for vibration suppression of the two adjacent twin structures.

• Journal of Korean Society of Transportation
• /
• v.29 no.4
• /
• pp.125-138
• /
• 2011

The highway visibility reduction caused by fog is one of the major elements of traffic accidents. Though the fog warning systems can lead drivers into safe driving by letting them aware dangerous situations in advance, the optical sensors, such as fog sensor, has been extremely costly. Through recent studies, it is delivered that visibility measurements have become obtainable with relatively cheap cameras and their functionality is as similar as a driver' visual sense. Those measurements however require additional signs or ROI, so it is still costly and unable to utilize the conventional images from the existing systems. This study proposes a new method to detect the visibility in real time based on the conventional images from the existing CCTV cameras. The proposed method builds a road model and extracts and applies vehicle movements and visible lines - those highlight easy and quick visibility measurements. The proposed method has advantages of both (1) having possible day and night visibility measurements similar to drivers' visual sense and (2) being easily applied to the existing CCTV system without additional devices. This paper presents field experiments using images acquired from the Central Inland Expressway and discusses future research directions.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2008.04a
• /
• pp.602-607
• /
• 2008

A technique for reliability-based design optimization(RBDO) is developed based on the Bayesian approach, which can deal with the epistemic uncertainty arising due to the limited number of data. Until recently, the conventional RBDO was implemented mostly by assuming the uncertainty as aleatory which means the statistical properties are completely known. In practice, however, this is not the case due to the insufficient data for estimating the statistical information, which makes the existing RBDO methods less useful. In this study, a Bayesian reliability is introduced to take account of the epistemic uncertainty, which is defined as the lower confidence bound of the probability distribution of the original reliability. In this case, the Bayesian reliability requires double loop of the conventional reliability analyses, which can be computationally expensive. Kriging based dimension reduction method(KDRM), which is a new efficient tool for the reliability analysis, is employed to this end. The proposed method is illustrated using a couple of numerical examples.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.4
• /
• pp.1-7
• /
• 1998

This paper describes a meshless of element-free method based on fuzzy knowledge processing. To efficiently simulate complicated physical phenomena with dynmics and non-linear ploblem using computational mechanics, special method is required such as parallel processing or adaptive analysis techniques. However, the conventional finite element method is too complicated to be employed in the above cases. In order to reduce the above complexity of the conventional finite element analysis systms, the so called meshles finite elements as an input information have been stuided. Node is generated if its distance form existing node points is similar to the node spacing fuction at the point. The node spacing function is well controlled by the fuzzy knowledge processing Practical performances of the present system are demonstrated through several three-dimensional(3D) problems.

• Journal of Mechanical Science and Technology
• /
• v.17 no.10
• /
• pp.1552-1562
• /
• 2003

In this paper, we propose a new PIV methodology for obtaining a velocity field from a sequence of multiple image data based on a least-square principle (also known as MQD; minimum quadratic difference) for the grey level difference between two neighboring frames of image data. We investigated both the accuracy of the result and the time consumption in the computation. It turns out that the proposed method is not only accurate but fast compared with the conventional correlation PIV techniques. Our method is applied to the spin-up flows and the results show that the method can be a good substitution for the conventional algorithms employed in the existing commercial codes.

• Structural Monitoring and Maintenance
• /
• v.1 no.3
• /
• pp.323-338
• /
• 2014

In this study a new innovative method of earthquake-resistant strengthening of reinforced concrete structures is presented for the first time. Strengthening according to this new method consists of the construction of steel fiber ultra-high-strength concrete jackets without conventional reinforcement which is usually applied in the construction of conventional reinforced concrete jackets. An innovative solution is proposed also for the first time that ensures a satisfactory seismic performance of existing reinforced concrete structures, strengthened by using composite materials. The weak point of the use of such materials in repairing and strengthening of old R/C structures is the area of beam-column joints. According to the proposed solution, the joints can be strengthened with a steel fiber ultra-high-strength concrete jacket, while strengthening of columns can be achieved by using CFRPs. The experimental results showed that the performance of the subassemblage strengthened with the proposed mixed solution was much better than that of the subassemblage retrofitted completely with CFRPs.

• Proceedings of the KIEE Conference
• /
• 1998.07b
• /
• pp.575-577
• /
• 1998

In this paper, we propose a hybrid target tracking algorithm which combine the conventional Kalman filter algorithm and the fuzzy neural network. Conventional methods are degraded in the presence of uncertanties and the environmental noise. These problems can be resolved by the proposed method. The training data for the proposed target tracker is obtained by the off-line simulation. Unlike other target trackers usging fuzzy inference system, our method can be easily integrated into the existing system. A numerical simulation is included to show the effectiveness and the feasibility of the proposed method.

• Nuclear Engineering and Technology
• /
• v.40 no.5
• /
• pp.375-386
• /
• 2008

Conventional static reliability analysis methods are inadequate for modeling dynamic interactions between components of a system. Various techniques such as dynamic fault tree, dynamic Bayesian networks, and dynamic reliability block diagrams have been proposed for modeling dynamic systems based on improvement of the conventional modeling methods. In this paper, we review these methods briefly and introduce dynamic nodes to the existing reliability graph with general gates (RGGG) as an intuitive modeling method to model dynamic systems. For a quantitative analysis, we use a discrete-time method to convert an RGGG to an equivalent Bayesian network and develop a software tool for generation of probability tables.