• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.565-574
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• 2022

The infrastructures such as offshore, bridges, power plant, oil and gas piping and aircraft operate in a harsh environment during their service life. Structural integrity of engineering components used in these industries is paramount for the reliability and economics of operation. Two regression models based on the concept of Gaussian process regression (GPR) and Minimax probability machine regression (MPMR) were developed to predict stress intensity factor range (𝚫K). Both GPR and MPMR are in the frame work of probability distribution. Models were developed by using the fatigue crack growth data in MATLAB by appropriately modifying the tools. Fatigue crack growth experiments were carried out on Eccentrically-loaded Single Edge notch Tension (ESE(T)) specimens made of API 5L X65 Grade steel in inert and corrosive environments (2.0% and 3.5% NaCl). The experiments were carried out under constant amplitude cyclic loading with a stress ratio of 0.1 and 5.0 Hz frequency (inert environment), 0.5 Hz frequency (corrosive environment). Crack growth rate (da/dN) and stress intensity factor range (𝚫K) values were evaluated at incremental values of loading cycle and crack length. About 70 to 75% of the data has been used for training and the remaining for validation of the models. It is observed that the predicted SIF range is in good agreement with the corresponding experimental observations. Further, the performance of the models was assessed with several statistical parameters, namely, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Coefficient of Efficiency (E), Root Mean Square Error to Observation's Standard Deviation Ratio (RSR), Normalized Mean Bias Error (NMBE), Performance Index (ρ) and Variance Account Factor (VAF).

• Smart Structures and Systems
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• v.25 no.2
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• pp.135-153
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• 2020

There has been a sustained interest towards the non-contact structural displacement measurement by means of videogrammetric technique. On the way forward, one of the major concerns is the spurious image drift induced by temperature variation. This study therefore carries out an investigation into the temperature effect of videogrammetric technique, focusing on the exploration of the mechanism behind the temperature effect and the elimination of the temperature-caused measurement error. 2D videogrammetric measurement tests under monotonic or cyclic temperature variation are first performed. Features of measurement error and the casual relationship between temperature variation and measurement error are then studied. The variation of the temperature of digital camera is identified as the main cause of measurement error. An excellent linear relationship between them is revealed. After that, camera parameters are extracted from the mapping between world coordinates and pixels coordinates of the calibration targets. The coordinates of principle point and focal lengths show variations well correlated with temperature variation. The measurement error is thought to be an outcome mainly attributed to the variation of the coordinates of principle point. An approach for eliminating temperature-caused measurement error is finally proposed. Correlation models between camera parameters and temperature are formulated. Thereby, camera parameters under different temperature conditions can be predicted and the camera projective matrix can be updated accordingly. By reconstructing the world coordinates with the updated camera projective matrix, the temperature-caused measurement error is eliminated. A satisfactory performance has been achieved by the proposed approach in eliminating the temperature-caused measurement error.

• Journal of the Korea institute for structural maintenance and inspection
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• v.5 no.1
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• pp.169-175
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• 2001

Bridge load rating calculations provide a basis for determining the safe load capacity of bridge. Load rating requires engineering judgement in determining a rating value that is applicable to maintaining the safe use of the bridge and arriving at posting and permit decisions. Load testing is an effective means in calculating the rating value of bridge. In Korea, load carrying capacity of bridge is modified by response modification factor that is determined from comparisons of measured values and analysis results. The response modification factor may be corrupted by vehicle location error that is defined as the gap of test vehicle location between load testing and analysis. In this study, the effects of vehicle location error to structural response and response modification factor are investigated, and a new method for evaluating response modification factor is proposed. The random data analysis shows that the proposed method is less sensitive to vehicle location error than the present method.

• Computational Structural Engineering
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• v.35 no.4
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• pp.27-33
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• 2022

• Journal of the Earthquake Engineering Society of Korea
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• v.23 no.1
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• pp.83-88
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• 2019

Structural analysis remains as an essential part of any integrated civil engineering system in today's rapidly changing computing environment. Even with enormous advancements in capabilities of computers and mobile tools, enhancing computational efficiency of algorithms is necessary to meet the changing demands for quick real time response systems. The finite element method is still the most widely used method of computational structural analysis; a robust, reliable and automated finite element structural analysis module is essential in a modern integrated structural engineering system. To be a part of an automated finite element structural analysis, an efficient adaptive mesh generation scheme based on R-H refinement for the mesh and error estimates from representative strain values at Gauss points is described. A coefficient that depends on the shape of element is used to correct overly distorted elements. Two simple case studies show the validity and computational efficiency. The scheme is appropriate for nonlinear and dynamic problems in earthquake engineering which generally require a huge number of iterative computations.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.1
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• pp.11-20
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• 1993

Sensitivity information is required in the optimal design process. In structural optimization, sensitivity calculation is a bottleneck due to its complexities and expensiveness. Various schemes have been proposed for the calculation. Analytic and finite difference methods are the most popular at the present time. However, they have advantages and disadvantages in different ways. Semi-anayltic method has been suggested to overcome the difficulties. In spite of the excellency, the semi-analytic method has been found to possess numerical error quite much with respect to shape variables. In this research, the error from each method is evaluated and compared using a shape variable. A two-dimensional beam is selected for an example since it has mathematical solution. An efficient method is suggested for the structural optimization which utilizes finite element method.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1121-1137
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• 2015

This study presents probabilistic-based damage identification technique for highlighting damage in metallic structures. This technique utilizes distributed piezoelectric transducers to generate and monitor the ultrasonic Lamb wave with narrowband frequency. Diagnostic signals were used to define the scatter signals of different paths. The energy of scatter signals till different times were calculated by taking root mean square of the scatter signals. For each pair of parallel paths an error function based on the energy of scatter signals is introduced. The resultant error function then is used to estimate the probability of the presence of damage in the monitoring area. The presented method with an autofocusing feature is applied to aluminum plates for method verification. The results identified using both simulation and experimental Lamb wave signals at different central frequencies agreed well with the actual situations, demonstrating the potential of the presented algorithm for identification of damage in metallic structures. An obvious merit of the presented technique is that in addition to damages located inside the region between transducers; those who are outside this region can also be monitored without any interpretation of signals. This novelty qualifies this method for online structural health monitoring.

• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.469-476
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• 2005

Performance of a force-torque sensor is affected significantly by an error signal that is included in the sensor signal. The error sources may be classified mainly into two categories: one is a structural error due to inaccuracy of sensor body, and the other is a noise signal existing in sensed information. This paper presents a principle of 6-axis force-torque sensor briefly, a double-hole structure to be able to improve a structural error, and then a signal conditioning to reduce the effect of a noise signal. The validity of the proposed method is investigated through experimental study, which shows that SIN ratio is improved significantly in our experimental setup, and the sensor can be implemented cheaply with reasonable performance.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.452-459
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• 1999

In this study, error estimates using the stress projecting scheme and adaptive nodal generation procedure in the element-free Galerkin(EFG) method are proposed. The essence of proposed error estimates is to use the difference between the values of the projected stress and these given directly by the EFG solution. The stress projection can be obtained simply by taking product of shape function based on a different domain of influence with the stresses at nodes. An adaptive procedure based on error estimates is discussed in this paper. By use of background integration cell, adding node scheme at high error norm area is proposed. To demonstrate the performance of proposed scheme, the convergence behavior is investigated for several examples

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.211-219
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• 2023

The structural health of a pipeline is usually assessed by visual inspection. In addition to the fact that this method is expensive and time consuming, inspection of the whole structure is not possible due to limited access to some points. Therefore, adopting a damage detection method without the mentioned limitations is important in order to increase the safety of the structure. In recent years, vibration-based methods have been used to detect damage. These methods detect structural defects based on the fact that the dynamic responses of the structure will change due to damage existence. Therefore, the location and extent of damage, before and after the damage, are determined. In this study, fuzzy genetic algorithm has been used to monitor the structural health of the pipeline to create a fuzzy automated system and all kinds of possible failure scenarios that can occur for the structure. For this purpose, the results of an experimental model have been used. Its numerical model is generated in ABAQUS software and the results of the analysis are used in the fuzzy genetic algorithm. Results show that the system is more accurate in detecting high-intensity damages, and the use of higher frequency modes helps to increase accuracy. Moreover, the system considers the damage in symmetric regions with the same degree of membership. To deal with the uncertainties, some error values are added, which are observed to be negligible up to 10% of the error.