Junkyeong Kim

Identification of new dinucleotide‐repeat polymorphisms in factor VIII gene using fluorescent PCR

Summary.  Haemophilia A is an X‐linked inherited bleeding disorder. Linkage diagnosis using polymorphic markers in the factor VIII gene is used to archive the carrier detection and prenatal diagnosis. The objective of this study was to establish the allele frequency and heterozygosity rate (HR) of two new intragenic markers (Intron 1 and 24) and other markers (Intron 13 and 22) using fluorescent PCR. Five hundred unrelated healthy women were screened and haemophilic family was studied for carrier detection and prenatal diagnosis. We observed five different alleles of Intron 1, 10 of Intron 24, nine of Intron 13 and six of Intron 22. The observed HR for Intron 1, 24, 13 and 22 were 34.0, 35.2, 53.0 and 42.6%, while the expected HR were 33.6, 36.3, 50.1 and 44.3%, respectively. Heterozygosity rate with the combined use of all four intragenic markers was 76.6% (383/500). In prenatal diagnosis of a haemophilic family, a pregnant woman was heterozygous with three intragenic (Intron 1, 13 and 22) and one extragenic St14 VNTR (DXS52) markers. She was considered to be a carrier, and she carried a male foetus by AMXY PCR and chromosome analysis of amniocytes. Foetus did not have mutant haplotype as his uncle, suggesting a normal male status. Our study demonstrates the utility of two new intragenic markers in FVIII gene for carrier detection and prenatal diagnosis of haemophilic families.

Integrating embedded piezoelectric sensors with continuous wavelet transforms for real-time concrete curing strength monitoring

It is highly necessary to evaluate strength development during the curing process to ensure the quality of concrete in construction using concrete. In particular, curing strength monitoring at early age is very important to reduce the construction cost and time, because it can provide the information required for the decision-making to safely progress to the next process. In this study, a guided wave-based non-destructive curing strength gain monitoring method that can be used even for early-age concrete is proposed. A steel plate-type piezoelectric sensor module was embedded in the concrete media at the same time as concrete placement to measure the signal from early-age concrete. The guided wave signals were measured continuously using the pitch-catch method at regular intervals. The wavelet transform process was performed to improve the quality of the signal. The guided waves velocity of each measurement time was varied by extracting the time of flight. The wave velocity hysteresis curve according to the curing age was traced to analyse the variation patterns. Finally, a specific equation to estimate the curing strength without destructive test was derived using regression analysis based on the wave velocity hysteresis and the results from the compression test.

Artificial Neural Network-Based Early-Age Concrete Strength Monitoring Using Dynamic Response Signals

Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process.

Advanced Fatigue Crack Detection Using Nonlinear Self-Sensing Impedance Technique for Automated NDE of Metallic Structures

This article reports the application of a nonlinear impedance technique under a low-frequency vibration to detect contact-type structural defects such as fatigue cracks. If the contact-type damage is developed within the structure due to the low-frequency dynamic load, the vibration can cause a nonlinear fluctuation of the structural impedance because of the contact acoustic nonlinearity (CAN). This nonlinear effect can lead to amplitude modulation and phase modulation of the current flow. The nonlinear characteristics of the structural impedance can be extracted by observing the coupled electromechanical impedance of a piezoelectric active sensor and utilizing nonlinear wave modulation spectroscopy. Experimentally, a low-frequency vibration was applied to a notched coupon at a certain natural frequency by a shaker, so that a nonlinear fatigue crack can be artificially formed at the notch tip. Then, the nonlinear features are extracted based on a self-sensing impedance measurement from a host structure under a low-frequency vibration. The damage metric was established based on the nonlinear fluctuation of the impedance due to the CAN.

Development of Embedded EM Sensors for Estimating Tensile Forces of PSC Girder Bridges

The tensile force of pre-stressed concrete (PSC) girders is the most important factor for managing the stability of PSC bridges. The tensile force is induced using pre-stressing (PS) tendons of a PSC girder. Because the PS tendons are located inside of the PSC girder, the tensile force cannot be measured after construction using conventional NDT (non-destructive testing) methods. To monitor the induced tensile force of a PSC girder, an embedded EM (elasto-magnetic) sensor was proposed in this study. The PS tendons are made of carbon steel, a ferromagnetic material. The magnetic properties of the ferromagnetic specimen are changed according to the induced magnetic field, temperature, and induced stress. Thus, the tensile force of PS tendons can be estimated by measuring their magnetic properties. The EM sensor can measure the magnetic properties of ferromagnetic materials in the form of a B (magnetic density)-H (magnetic force) loop. To measure the B-H loop of a PS tendon in a PSC girder, the EM sensor should be embedded into the PSC girder. The proposed embedded EM sensor can be embedded into a PSC girder as a sheath joint by designing screw threads to connect with the sheath. To confirm the proposed embedded EM sensors, the experimental study was performed using a down-scaled PSC girder model. Two specimens were constructed with embedded EM sensors, and three sensors were installed in each specimen. The embedded EM sensor could measure the B-H loop of PS tendons even if it was located inside concrete, and the area of the B-H loop was proportionally decreased according to the increase in tensile force. According to the results, the proposed method can be used to estimate the tensile force of unrevealed PS tendons.

Prestressing Loss Management for PSC Girder Tendon Based on EM Sensing

In this paper, an EM sensing based prestressing force estimation method is proposed, in which it can estimate tensile force of PS tendon for PSC girder. The PSC girder has more improved performance than the general concrete girder by introducing the prestressing to the concrete. Thus the PSC girder bridge is widely constructed due to its high performance and low cost. However, the prestressing force has not been managed nevertheless it is major factor for the maintenance of the PSC girder bridge. The prestressing force was just measured during construction using jacking device and after that, it can not be managed. For this reason, this paper proposes a tensile force estimation method of PS tendon based on EM sensor. The permeability of ferroelectric material is changed according to the induced stress to the material, in which it can be measured using EM sensor. To measure the permeability of PS tendon, the EM sensor was fabricated and verified by performing the MTS test. The test was performed using 7-wire steel tendon under the 0, 40, 80, 120, 160, 200 KN of tensile force. The permeability of PS tendon was gradually decreased according to the increasement of tensile force. The regression method was used to find the relation between permeability and stress. As a result, the permeability has linear relation with the tensile force of PS tendon and the pre-stressing force can be estimated by the derived estimation equation.

A study on MFL based wire rope damage detection

Non-destructive testing on wire rope is in great demand to prevent safety accidents at sites where many heavy equipment using ropes are installed. In this paper, a research on quantification of magnetic flux leakage (MFL) signals were carried out to detect damages on wire rope. First, a simulation study was performed with a steel rod model using a finite element analysis (FEA) program. The leakage signals from the simulation study were obtained and it was compared for parameter: depth of defect. Then, an experiment on same conditions was conducted to verify the results of the simulation. Throughout the results, the MFL signal was quantified and a wire rope damage detection was then confirmed to be feasible. In further study, it is expected that the damage characterization of an entire specimen will be visualized as well.

A Study on Weight Estimation of Moving Vehicles using Bridge Weigh-in-Motion Technique

In this study, the estimation of axial load and total axial load was conducted using Bridge Weigh-in-Motion(BWIM) technique which generally consists of devices for measuring the strain induced in the bridge by the vehicles. axle detectors for collecting information on vehicle velocity and axle spacing. and data acquisition equipment. Vehicle driving test for the development of the BWIM system is necessary but it needs much cost and time. In addition, it demands various driving conditions for the test. Thus, we need a numerical-simulation method for resolving the cost and time problems of vehicle driving tests, and a way of measuring bridge response according to various driving conditions. Using a bridge model reflecting the dynamic characteristic contributes to increased accuracy in numerical simulation. In this paper, we conduct a numerical simulation which reflects the dynamic characteristic of a bridge using the Bridge Weigh-in-Motion technique, and suggest overload vehicle enforcement technology.

Embedded EM Sensor for Tensile Force Estimation of PS tendon of PSC Girder

In this paper, an embedded EM sensor was researched to estimate prestressing force of PS tendon in PSC girder. Recent methodologies for managing prestressing force loss were staying on verifying a applying prestressing force under construction, namely the loss management can not be controlled after construction. To estimate the tensile force of PS tendon during lifetime of PSC girder, this research proposed a bobbin-type embedded EM sensor that can be embedded in PSC girder is designed and fabricated considering the shape properties of anchorage zone and sheath. To verify the proposed sensor, a small PSC girder test was performed. The embedded EM sensor was connected to a sheath and anchor block, and the concrete was poured. After curing, the change of the permeability of PS tendon under tensile forces of 200, 710, 1070, 1300kN was measured using embedded EM sensor. The permeability of PS tendon had decreased according to the increment of applied tensile force. Also it is confirmed that the change of permeability due to applied tensile force could resolve the applied tensile force values. As a result, proposed embedded EM sensor could be embed into the PSC girder and it could be used to estimate the tensile force variation during lifetime of PSC girder.

Early-age concrete strength estimation based on piezoelectric sensor using artificial neural network

Recently, novel methods to estimate the strength of concrete have been reported based on numerous NDT methods. Especially, electro-mechanical impedance technique using piezoelectric sensors are studied to estimate the strength of concrete. However, the previous research works could not provide the general information about the early-age strength important to manage the quality of concrete and/or the construction process. In order to estimate the early-age strength of concrete, the electro-mechanical impedance method and the artificial neural network(ANN) is utilized in this study. The electro-mechanical impedance varies with the mechanical properties of host structures. Because the strength development is most influential factor among the change of mechanical properties at early-age of curing, it is possible to estimate the strength of concrete by analyzing the change of E/M impedance. The strength of concrete is a complex function of several factors like mix proportion, temperature, elasticity, etc. Because of this, it is hard to mathematically derive equations about strength of concrete. The ANN can provide the solution about early-age strength of concrete without mathematical equations. To verify the proposed approach, a series of experimental studies are conducted. The impedance signals are measured using embedded piezoelectric sensors during curing process and the resonant frequency of impedance is extracted as a strength feature. The strength of concrete is calculated by regression of strength development curve obtained by destructive test. Then ANN model is established by trained using experimental results. Finally the ANN model is verified using impedance data of other sensors.