• Smart Structures and Systems
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• v.4 no.6
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• pp.759-777
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• 2008

A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.4
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• pp.425-433
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• 2001

A correlation between fatigue damage and acousto-ultrasonic (AU) parameters has been obtained from signals acquired during fatigue loading of the single-lap joints of a carbon-fiber reinforced plastic (CFRP) laminates and A16061 plate. The correlation showed an analogy to those representing the stiffness reduction $(E/E_0)$ of polymer matrix composites by the accumulation of fatigue damage. This has been attributed to the transmission characteristics of acoustic wave energy through bonded joints with delamination-type defects and their influence on the change of spectral content of AU signals. Another correlation between fatigue cycles and the spectral magnitude of acoustic emission (AE) signals has also been found during the final stage of fatigue loading. Both AU and AE can be applied almost in real-time to monitor the evolution of damage during fatigue loading.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07a
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• pp.32-35
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• 2002

The work focuses on the development of a Cu lead-frame with a single-sided adhesive tape for cost reduction and reliability improvement of LOC (lead on chip) package products, which are widely used for the plastic-encapsulation of memory chips. Most of memory chips are assembled by the LOC packaging process where the top surface of the chip is directly attached to the area of the lead-frame with a double-sided adhesive tape. However, since the lower adhesive layer of the double-sided adhesive tape reveals the disparity in the coefficient of thermal expansion from the silicon chip by more than 20 times, it often causes thermal displacement-induced damage of the IC pattern on the active chip surface during the reliability test. So, in order to solve these problems, in the resent work, the double-sided adhesive tape is replaced by a single-sided adhesive tape. The single-sided adhesive tape does net include the lower adhesive layer but instead, uses adhesive materials, which are filled in clear holes of the base film, just for the attachment of the lead-frame to the top surface of the memory chip. Since thermal expansion of the adhesive materials can be accommodated by the base film, memory product packaged using the lead-flame with the single-sided adhesive tape is shown to have much improved reliability. Author allied this invention to the Korea Patent Office for a patent (4-2000-00097-9).

• Radiation Oncology Journal
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• v.3 no.1
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• pp.1-8
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• 1985

To determine the dose·survival and repair characteristics of the jejunal crypt cells, experimental study was carried out using total 70 mice. Single or split irradiations of 1,100 to 2,200 rad were delivered to whole bodies of $C_{57}$ BL mice, using a cesium 137 animal irradiator and those mice were sacrificed after 90 hours. The number of regenerating crypts per jejunal circumference was counted by a jejunal crypt cell assay technique and dose·response curve was measured. The results were as follows : 1. The average number of jejunal crypts per circumference in control group was 140. In a single irradiation group, the number of regenerated jejunal crypts was, 125, 56, 2 in each subgroup of 1,100 rad, 1,400 rad and 1,800 rad respectively. In split irraiation group, it was 105,44,2 in each subgroup of 1,400rad 1,800rad and 2,200rad respectively. 2. Mean lethal dose of mouse jejunal crypt cell was 167 and 169 rad respectively in a single and split irradiation. 3. Repair dose of sublethal damage was 280 rad. 4. Sublethal damage was completely repaired within 4 hours between the split dose of irradiation.

• Structural Engineering and Mechanics
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• v.30 no.6
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• pp.699-712
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• 2008

The effectiveness of wavelet transform in detecting delamination damages in multilayered composite beams and plates is studied here. The damaged composite beams and plates are modeled in finite element software ABAQUS and the first few mode shapes are obtained. The mode shapes of the damaged structures are then wavelet transformed. It is observed that the distribution of wavelet coefficients can identify the damage location of beams and plates by showing higher values of wavelet coefficients at the position of damage. The effectiveness of the method is studied for different boundary conditions, damage location and size for single as well as multiple delaminations in composite beams and plates. It is observed that both discrete wavelet transform (DWT) and continuous wavelet transform (CWT) can detect the presence and location of the damaged region from the mode shapes of the structures. DWT may be used to approximately evaluate the size of the delamination area, whereas, CWT is efficient to detect smaller delamination areas in composites.

• Journal of Mechanical Science and Technology
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• v.14 no.9
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• pp.978-984
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• 2000

The aim of this study is to investigate the ductile fracture behaviour under Mode I loading using SA533B pressure vessel steel. Experiments consist of the Round Notch Bar Test (RNB), Single Edge Crack Bending Test (SECB), and V-Notch Bar Test (VNB). Results from the RNB test were used to tune the damage modelling constant. The other tests were performed to acquire the J-resistance curves and to confirm the damage constants. Microstructural observation includes the measurement of crack profile to obtain the roughness parameter. Finally, simulation using Rousellier Ductile Damage Theory (RDDT) was carried out with 4-node quadrilateral element ($L_c=0.25\;mm$). For the crack advance, the failed element removal technique was adopted with a ${\beta}$ criterion. In conclusion, the predicted simulation using RDDT showed a good agreement with the experimental results. A trial using a roughness parameter was made for a new evaluation of J-resistance curve, which is more conservative than the conventional one.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.6
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• pp.258-269
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• 1999

It is important to evaluate fatigue damage of in-service material in respect to assure safety and remaining fatigue life in structure and mechanical components under cyclic load . Fatigue damage is represented by mathematical modelling with crack growth rate da/dN and cycle ration N/Nf and is detected by X-ray diffraction and ultrasonic wave method etc. But this is estimated generally by single parameter but influenced by many test conditions The characteristics of it indicates fatigue damage has complex fracture mechanism. Therefore, in this study we propose that back-propagation neural networks on the basis of ration of X-ray half-value breath B/Bo, fractal dimension Df and fracture mechanical parameters can construct artificial intelligent networks estimating crack growth rate da/dN and cycle ratio N/Nf without regard to stress amplitude Δ $\sigma$.

• Wind and Structures
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• v.3 no.1
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• pp.23-40
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• 2000

In the early morning hours of February 23rd, 1998, seven large tornadoes ravaged central Florida. A total of 42 people were killed and millions of dollars of damage was done. A strip mall and other commercial structures sustained considerable damage and several residential areas were completely destroyed. Based on field observations, the paper examines the causes and sequence of structural failure for the masonry single family homes. Wind speeds are estimated based on the observed damage, and compared to the meteorological data. Finally, recommendations are given that could help to eliminate or reduce similar failures in the future. It was found that with simple, cost effective measures, most if not all of the damage could have been prevented.

• Structural Monitoring and Maintenance
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• v.5 no.4
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• pp.507-519
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• 2018

In this paper, damage assessment in wind-turbine towers using vibration-based artificial neural networks (ANNs) is numerically investigated. At first, a vibration-based ANNs algorithm is designed for damage detection in a wind turbine tower. The ANNs architecture consists of an input, an output, and hidden layers. Modal parameters of the wind turbine tower such as mode shapes and frequencies are utilized as the input and the output layer composes of element stiffness indices. Next, the finite element model of a real wind-turbine tower is established as the test structure. The natural frequencies and mode shapes of the test structure are computed under various damage cases of single and multiple damages to generate training patterns. Finally, the ANNs are trained using the generated training patterns and employed to detect damaged elements and severities in the test structure.

• Smart Structures and Systems
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• v.23 no.1
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• pp.15-29
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• 2019

This paper addresses the problem of damage detection in suspension bridge hangers, with an emphasis on the modal flexibility method. It aims at evaluating the capability and the accuracy of the modal flexibility method to detect and locate single and multiple damages in suspension bridge hangers, with different level of severity and various locations. The study is conducted numerically and experimentally on a laboratory suspension bridge mock-up. First, the covariance-driven stochastic subspace identification is used to extract the modal parameters of the bridge from experimental data, using only output measurements data from ambient vibration. Then, the method is demonstrated for several damage scenarios and compared against other classical methods, such as: Coordinate Modal Assurance Criterion (COMAC), Enhanced Coordinate Modal Assurance Criterion (ECOMAC), Mode Shape Curvature (MSC) and Modal Strain Energy (MSE). The paper demonstrates the relative merits and shortcomings of these methods which play a significant role in the damage detection ofsuspension bridges.