Korea Atomic Energy Research Institute (“KAERI”) has been developing various studies related to the nuclear fuel cycle. Among them, KAERI was focusing on the pyroprocess, which recycles some useful elements white reducing the volume and toxicity of spent nuclear fuel (SNF). Pyroprocess involves the handling of SNF, which cannot be handled directly by the facility worker. Therefore, SNF is handled and processed through remote handling device within a shielded facility such as a hot cell. Nuclear Facilities with such hot cells are called nuclear fuel cycle facilities, and unlike other facilities, heating, ventilating, and air conditioning (HVAC) system are particularly important in nuclear fuel cycle facilities to maintain the atmosphere in the hot cell and remove radioactive materials. In addition, due to the nature of the pyroprocess, which uses molten salt, corrosion is a problem in air atmosphere, so the process can only be carried out in an inert gas atmosphere. KAERI has a nuclear fuel cycle facility called the Irradiation Material Examination Facility (IMEF), and has built and operated the ACPF inside the IMEF, which operates an inert atmosphere hot cell for the demonstration of the pyroprocess. For efficient process development of the pyroprocess, it is necessary to put the developed equipment into the hot cell, which is a radiationcontrolled area, after sufficient verification in a mock-up facility. For this purpose, the ACPF mock-up facility, which simulates the system, space, and remote handling equipment of the ACPF, is operated separately in the general laboratory area. The inert gas conditioning system of the ACPF consists of very complex piping, blowers, and valves, requires special attention to maintenance. In addition, if there is a small leak in the piping within these valves or piping, radioactive materials can be directly exposed to facility workers, so continuous monitoring and maintenance are required to prevent accident. In this study, the applicability of acoustic emission technology and ultrasonic technology for leak detection in the inert gas conditioning system of ACPF mock-up facility was investigated. For this purpose, new bypass pipes and valves were installed in the existing system to simulate the leakage of pipes and valves. Acoustic emission sensors are attached directly to pipes or valves to detect signals, while ultrasonic sensors are installed at a distance to detect signals. The optimal parameters of each technology to effectively suppress background noise were derived and, and the feasibility of identifying normal and abnormal scenarios in the system was analyzed.

The acoustic emission (AE) method as a passive non-destructive monitoring technique is proposed for real-time monitoring of mechanical degradation in underground structures, such as deep geological disposal of high-level nuclear waste (HLW). This study investigates the low-frequency characteristics of AE signals emitted during the fracturing of meter-scale concrete specimens; uniaxial compression tests (UCT) in a lab scale and Goodman jack (GJ) tests in a 1.3 m-long concrete block were conducted while acquiring the AE signals using low-frequency AE sensors. The results indicate a sharp increase in AE energy emission at approximately 60% and 80% of the yield stresses in the UCT and GJ tests, respectively. The collected AE signals were primarily found in two frequency bands: the 4-28 kHz range and the 56-80 kHz range. High-frequency AE signals were captured more as the stress increased in the GJ tests, which was in contrast to the UCT tests. Furthermore, the AE signals obtained from the Goodman jack tests tended to lower RA values than the UCT results. This study presents unique experimental data with low-frequency AE sensors under different loading conditions, which provides insights into field-scale AE monitoring practices.

The underground environment has an advantage to minimize the external influences because it is isolated space with surrounded rock medium. Therefore, underground rock has been used recently as the target for a disposal system of spent fuel with high-level radioactive. The disposal system mainly consists of natural barrier (i.e., surrounded rock medium) and engineered barrier (i.e., concrete lining, plug, backfill, canister, and buffer). In particular, the engineered barrier is important for long-term storage because it has to preferentially block the leakage of radioactive nuclide. Non-destructive technologies (NDT) have been utilized to monitor the state of disposal system for considering the limitation in deep depth conditions such as limited environment for direct damage inspection. Acoustic emission (AE) monitoring technique is an effective method to monitor the damage (crack) magnitude, history (i.e., crack evolution), and location using high-frequency elastic waves. To apply the AE monitoring method in the disposal system, the characteristics of damaged materials should be considered. The concrete lining has multi-failure behavior (i.e., brittle and ductile) resulted from composition as cement and reinforcing steel bar. Therefore, it important to investigate the AE characteristics according to the failure level of reinforced concrete for damage monitoring of the disposal systems. In this study, the four-point bending tests were carried out to measure the AE signals from the cracking of reinforce concrete specimens in laboratory. The test specimens were prepared with different strength. After the experiment, the AE characteristics were analyzed using the AE parameters with loading and failure state in the curve of time-stress. This study will be helpful for damage monitoring using AE technique in the field of high-level radioactive disposal system.

The acoustic emission (AE) is proposed as a feasible method for the real-time monitoring of the structural damage evolution in concrete materials that are typically used in the storage of nuclear wastes. However, the characteristics of AE signals emitted from concrete structures subjected to various environmental conditions are poorly identified. Therefore, this study examines the AE characteristics of the concrete structures during uniaxial compression, where the storage temperature and immersion conditions of the concrete specimens varied from 15℃ to 75℃ and from completely dry to water-immersion, respectively. Compared with the dry specimens, the water-immersed specimens exhibited significantly reduced uniaxial compressive strengths by approximately 26%, total AE energy by approximately 90%, and max RA value by approximately 70%. As the treatment temperature increased, the strength and AE parameters, such as AE count, AE energy, and RA value, of the dry specimens increased; however, the temperature effect was only minimal for the immersed specimens. This study suggests that the AE technique can capture the mechanical damage evolution of concrete materials, but their AE characteristics can vary with respect to the storage conditions.

Deep geologic disposal of high-level nuclear wastes (HLW) requires intensive monitoring instrumentations to ensure long-term security. Acoustic emission (AE) method is considered as an effective method to monitor the mechanical degradation of natural rock and man-made concrete structures. The objectives of this study are (a) to identify the AE characteristics emitted from concretes as concrete materials under different types of loading, (b) to suggest AE parametric criteria to determine loading types and estimate the failure stage, and finally (c) to examine the feasibility of using AE method for real-time monitoring of geologic disposal system of HLW. This study performs a series of the mechanical experiments on concrete samples simultaneously with AE monitoring, including the uniaxial compression test (UCT), Brazilian tensile test (BTT) and punch through shear test (PTST). These mechanical tests are chosen to explore the effect of loading types on the resulting AE characteristics. This study selects important AE parameters which includes the AE count, average frequency (AF) and RA value in the time domain, and the peak frequency (PF) and centroid frequency in the frequency domain. The result reveals that the cumulative AE counts, the maximum RA value and the moving average PF show their potentials as indicators to damage progress for a certain loading type. The observed trends in the cumulative AE counts and the maximum RA value show three unique stages with an increase in applied stress: the steady state stage (or crack initiation stage; < 70% of yield stress), the transition stage (or damage progression stage; 70–90% of yield stress) and the rising stage (or failure stage; > 90% of yield stress). In addition, the moving average PF of PTST in the early damage stage appears to be particularly lower than that of UCT and BTT. The loading in BTT renders distinctive responses in the slope of the maximum RA–cumulative AE count (or tan ). The slope value shows less than 0.25 when the stress is close to 30% of BTT, 60% of UCT and 75% of PTST and mostly after 90% of yield stress, the slope mostly decreases than 0.25 in all tests. This study advances our understanding on AE responses of concrete materials with well-controlled laboratoryscale experimental AE data, and provides insights into further development of AE-base real-time diagnostic monitoring of structures made of rocks and concretes.

밸브의 내부 누설 현상은 밸브의 내부 부품의 손상에 의해 발생하며 배관 시스템의 사고와 운전정지를 일으키는 주요 요인이 다. 본 연구는 버터플라이형 밸브의 내부 누설에 따라 배관계에서 발생하는 음향방출 신호를 이용하여 배관 가동 중 실시간 누설 진단의 가능성을 검토하였다. 이를 위해 밸브의 작동 모드별로 측정한 시간영역의 AE 원시신호를 취득하였으며 이로부터 구축한 데이터셋은 데 이터 기반의 인공지능 알고리즘에 적용하여 밸브의 내부 누설 유무를 진단하는 모델을 생성하였다. 누설 유무진단을 분류의 문제로 정의 하여 SVM 기반의 머신러닝과 CNN 기반의 딥러닝 분류 알고리즘을 적용하였다. 데이터의 특징 추출에 기반한 SVM 분류 모델의 경우, 이 진분류 모델에서 구축된 모델에 따라 83~90%의 정확도를 나타냈으며, 다중 클래스인 경우 분류 정확도가 66%로 감소하였다. 반면, CNN 기반의 다중 클래스 분류 모델의 경우 99.85%의 분류 정확도를 얻을 수 있었다. 결론적으로 밸브 내부 누설 진단을 위한 SVM 분류모델은 다중 클래스의 정확도 향상을 위해 적절한 특징 추출이 필요하며, CNN 기반의 분류모델은 프로세서의 성능 저하만 없다면 누설진단과 밸브 개도 분류에 효율적인 접근방법임을 확인하였다.

In this study, the well-known non-destructive acoustic emission (AE) and electrical resistivity methods were employed to predict quantitative damage in the silo structure of the Wolsong Low and Intermediate Level Radioactive Waste Disposal Center (WLDC), Gyeongju, South Korea. Brazilian tensile test was conducted with a fully saturated specimen with a composition identical to that of the WLDC silo concrete. Bi-axial strain gauges, AE sensors, and electrodes were attached to the surface of the specimen to monitor changes. Both the AE hit and electrical resistance values helped in the anticipation of imminent specimen failure, which was further confirmed using a strain gauge. The quantitative damage (or damage variable) was defined according to the AE hits and electrical resistance and analyzed with stress ratio variations. Approximately 75% of the damage occurred when the stress ratio exceeded 0.5. Quantitative damage from AE hits and electrical resistance showed a good correlation (R = 0.988, RMSE = 0.044). This implies that AE and electrical resistivity can be complementarily used for damage assessment of the structure. In future, damage to dry and heated specimens will be examined using AE hits and electrical resistance, and the results will be compared with those from this study.

Evaluating the quantitative damage to rocks through acoustic emission (AE) has become a research focus. Most studies mainly used one or two AE parameters to evaluate the degree of damage, but several AE parameters have been rarely used. In this study, several data-driven models were employed to reflect the combined features of AE parameters. Through uniaxial compression tests, we obtained mechanical and AE-signal data for five granite specimens. The maximum amplitude, hits, counts, rise time, absolute energy, and initiation frequency expressed as the cumulative value were selected as input parameters. The result showed that gradient boosting (GB) was the best model among the support vector regression methods. When GB was applied to the testing data, the root-mean-square error and R between the predicted and actual values were 0.96 and 0.077, respectively. A parameter analysis was performed to capture the parameter significance. The result showed that cumulative absolute energy was the main parameter for damage prediction. Thus, AE has practical applicability in predicting rock damage without conducting mechanical tests. Based on the results, this study will be useful for monitoring the near-field rock mass of nuclear waste repository.

To estimate weld quality of the resistance spot-welding, the acoustic emission features are investigated from the total acoustic emission signal at the single-spot weld. Typically, the resistance spot welding process consists of several stages: set-down of the electrodes, squeeze, current flow, forging, hold time, and lift-off. Various types of acoustic emission response corresponding to each stage can be separately analyzed by using back-propagation neural network classifier and wavelet transform technique. The presented machine learning results provide a validation for using back-propagation neural network and wavelet transform technique as a valuable insights into the resistance spot-welding process. Especially, a wavelet transform technique is demonstrated and the plots are very powerful in the recognition of the acoustic emission features

In this study, carbon/epoxy composite DCB(double cantilever beam) specimens based on K-means clustering and wavelet transform analyses are presented. For the fracture Mode I, the fiber orientation θ = [0 ]24 and θ = [±45]12 both shown up stable crack growth in DCB testing. For the fiber orientation θ = [0 ]24 , the continuous type AE signal showed at central frequency 130～270kHz, which means that matrix micro cracking was occurred. The Burst type AE signal was occurred at central frequency 200～300kHz due to fiber bridging and fiber breaking. Other burst type AE signals were occurred at central frequency 130～180kHz with very high amplitude due to fiber bridging. For the fiber orientation θ = [±45]12 , the burst type signal showed at central frequency 220～300kHz, which means that fiber breaking was occurred. Mixed type of burst and continuous signals were captured at central frequency 250～480kHz due to fiber friction.

This is a study on the distribution of acoustic emission parameters during a burst test for a type-II CNG vehicle fuel tank. A resonant AE sensor with a central frequency of 150 kHz was attached to the composite materials in the center of the fuel tank. The pressure was increased from 30 to 100% of the expected burst pressure and was maintained for 10 minutes at each level. Damage at 70% of expected burst pressure occurred by various damage mechanisms including fiber breakage and delamination, while that of below 60% only occurred by matrix crack initiation and growth. The count, duration and rise time of the AE signal at 60% of the expected burst pressure are distributed below 500, 5000 μs and 300 μs, respectively. Then, at above 70% they increased with pressure by superimposing of individual AE signal generated at a nearby place. These results confirmed that the analysis of the distribution of AE parameters is an effective tool for estimating damage of a CNG fuel tank.

This study deals with the high frequency induction hardening (HF at 850℃, 120kHz & 50kW condition) SM45C steel. (1) The HF specimen, which was tempered at 150℃, did not show any tempering effect. A brittle fracture occurred at rounded area of the tensile specimen. AE (acoustic emission) amplitude distribution showed between 45dB and 60dB. (2) A slip and fracture occurred at the hole area of the HF specimen which was tempered at 300℃. As they pass the yield point, the AE energy is increased intermittently and AE amplitude distribution exists between 70dB and 85dB. In addition, after imposing the maximum tensile load, AE signals showed high amplitude and energy distribution. The AE amplitude showed between 45dB and 70dB. (3) A brittle fracture occurred at HF specimen which was tempered at 450℃ as if it is torn in the direction of 45° on parallel area over the both sides of the tensile specimen, which lead to several peak appeared in AE energy. It was found that the AE amplitude was relatively low and the AE energy was high.

This study investigated tensile deformation of the stress aging heat-treated SM45C steel which are aging temperature at 250℃ and 300℃; aging time at 1 hour and, 3 hours; applied load at 300N and 400N by using an acoustic emission techniques (AEs). A signal processing technology is applied to evaluate an AE source characterization of different AE measurement systems DiSP & PCI-2. In this study, most suitable aging condition appeared at 250℃, 3 hours and 300N. But in cases of 250℃, 3 hours, 400N and 300℃, 3 hours, 400N conditions, yield load decreased compare to other conditions according to the over-aging phenomena. On the other hand, when arranged via AE amplitude results by K-means clustering pattern recognition of AE raw signals, tendency of signal strength appeared non-heat treatment condition, 'Class 1 < Class 2 < Class 3'; optimal condition, 'Class 3 < Class 2'; over-aging condition, 'Class 3 < Class 2 < Class 1'. This is judged by emitting a lot of AE energy when material causes plastic deformation because ductility increases on factor by over-aging phenomenon.

This study is deal with the high frequency induction hardening (HF at 850℃, 120kHz & 50kW condition) SM45C steel. (1) The HF specimen which was tempered at 150℃, did not appear any tempering effect. A brittle fracture occurred at rounded area of the tensile specimen. AE amplitude distribution showed between 45~60dB. (2) The HF specimen which was tempered at 300℃, slip and fracture occurred at the hole area of the tensile specimen. As it passes the yield point, the AE energy increased intermittently and AE amplitude distribution showed between 70~85dB. In addition, after the maximum tensile load, it showed high amplitude and energy distribution. The AE amplitude showed between 45~70dB. (3) The HF specimen which was tempered at 450℃, a brittle fracture occurred as if it is torn in the direction of 45℃ on parallel area over the both sides of the tensile specimen, which led to several peak to be appeared in AE energy. It was found that the AE amplitude was relatively low and the AE energy was high.