• 지질공학
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• 제28권3호
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• pp.349-365
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• 2018

The strain and acoustic emission (AE) signals of Pocheon granite were measured during uniaxial compression tests to investigate microcrack formation and damage. Crack closure, initiation, and damage stresses of each sample were determined through an analysis of the crack volumetric strain and stiffness. The samples experienced four damage stages according to stress levels: stage 1 = crack closure stage; stage 2 = elastic stage; stage 3 = crack initiation stage; stage 4 = crack damage stage. At least 75% of all AE signals occurred in stages 3 and 4, and different AE parameters were detected in the four stress stages. Rise time, count, energy, and duration clearly showed a tendency to gradually increase with the damage stress stage. In particular, the rise time, energy, and duration increased by at least 95% in stage 4 as compared with stage 1. However, the maximum amplitude showed a smaller increase, and the average frequency decreased slightly at higher stages. These results indicate that as the degree of rock damage increases, the crack size grows larger. The crack types corresponding to the AE signals were determined using the relationship between RA (Rise time / Amplitude) values and average frequencies. Tension cracking was dominant in all stress stages. Shear cracking was rare in stages 1 and 2, but increased in stages 3 and 4. These results are consistent with previous studies that reported cracking begins after samples have already been damaged. Our study shows that the state of rock damage can be investigated solely through an analysis of AE parameters when rocks are under compressive stress. As such, this methodology is suitable for understanding and monitoring the stress state of bedrock.

• Smart Structures and Systems
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• 제30권6호
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• pp.601-612
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• 2022

The prediction of structural mechanical behaviors is vital important to early perceive the abnormal conditions and avoid the occurrence of disasters. Especially for underground engineering, complex geological conditions make the structure more prone to disasters. Aiming at solving the problems existing in previous studies, such as incomplete consideration factors and can only predict the continuous performance, the deep attention fused temporal convolution network (DATCN) is proposed in this paper to predict the spatial mechanical behaviors of structure, which integrates both the temporal effect and spatial effect and realize the cross-time prediction. The temporal convolution network (TCN) and self-attention mechanism are employed to learn the temporal correlation of each monitoring point and the spatial correlation among different points, respectively. Then, the predicted result obtained from DATCN is compared with that obtained from some classical baselines, including SVR, LR, MLP, and RNNs. Also, the parameters involved in DATCN are discussed to optimize the prediction ability. The prediction result demonstrates that the proposed DATCN model outperforms the state-of-the-art baselines. The prediction accuracy of DATCN model after 24 hours reaches 90 percent. Also, the performance in last 14 hours plays a domain role to predict the short-term behaviors of the structure. As a study case, the proposed model is applied in an underwater shield tunnel to predict the stress variation of concrete segments in space.

• 한국수자원학회논문집
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• 제51권11호
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• pp.1011-1020
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• 2018

본 연구에서는 미급수지역의 주요 수원인 지하수위 현황을 이용한 가뭄 모니터링 기법을 개발하기 위해 256개의 국가지하수관측망 관측 자료를 이용하여 관측소별, 월별 수위분포를 핵밀도함수로 추정하였다. 추정된 누적분포함수를 이용하여 월별 지하수위의 분위수를 구하고, 분위수를 정규화 하여 표준지하수지수(SGI)를 산정하였다. 관측소별로 산정된 SGI는 티센망을 이용하여 167개 시군별 SGI로 변환하였다. SGI의 범위에 따른 가뭄등급을 설정하여 시군별 지하수 가뭄 정도를 모니터링 할 수 있는 기법을 제시하였다. 이를 통해 계측이 이루어지지 않는 미급수지역의 지하수가뭄상황을 국가지하수관측망을 활용해 간접적으로 판단할 수 있도록 하였다.

• Geomechanics and Engineering
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• 제14권5호
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• pp.459-466
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• 2018

By conducting uniaxial loading cycle tests on the coal rock with outburst proneness, the dilatation characteristics at different loading rates were investigated. Under uniaxial loading and unloading, the lateral deformation of coal rock increased obviously before failure, leading to coal dilatation. Moreover, the post-unloading recovery of the lateral deformation was rather small, suggesting the onset of an accelerated failure. As the loading rate increased further, the ratio of the stress at the dilatation critical point to peak-intensity increased gradually, and the pre-peak volumetric deformation decreased with more severe post-peak damage. Based on the laboratory test results, the lateral deformation of the coals at different depths in the #1302 isolated coal pillars, Yangcheng Coal Mine, was monitored using wall rock displacement meter. The field monitoring result indicates that the coal lateral displacement went through various distinct stages: the lateral displacement of the coals at the depth of 2-6 m went through an "initial increase-stabilize-step up-plateau" series. When the coal wall of the working face was 24-18 m away from the measuring point, the coals in this region entered the accelerated failure stage; as the working face continued advancing, the lateral displacement of the coals at the depth over 6 m increased steadily, i.e., the coals in this region were in the stable failure stage.

• 한국응급구조학회지
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• 제27권1호
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• pp.79-90
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• 2023

Purpose: The study attempted to improve the health promotion behavior of university students by identifying the factors that affect health promotion behavior and by checking depression, anxiety, and stress levels of university students after the COVID-19 pandemic. Methods: We collected data using a structured questionnaire targeting 170 university students in C-province between December 1 and December 31, 2022. Results: Health promotion behavior had a significantly negative correlation with Depression (r=-.361, p<.001), Anxiety (r=-.191, p=.012), and Stress (r=-.301, p<.001), respectively. The influencing factors of health promotion behavior are gender (r=0.184, p<.001) and depression (r=-0.303, p<.001); the explanatory power is accounted for 15%. Conclusion: A practical method with counseling programs and mental health support services for early detection of risk groups by periodically monitoring the depression state of university students requires practicing health promotion behavior. Therefore, active support and attention should be provided to manage the mental health of university students.

• Smart Structures and Systems
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• 제14권2호
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• pp.209-224
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• 2014

With more and more built long-term structural health monitoring (SHM) systems, it has been considered to apply monitored data to learn the reliability of bridges. In this paper, based on a long-term SHM system, especially in which the sensors were embedded from the beginning of the construction of the bridge, a method to calculate the localized reliability around an embedded sensor is recommended and implemented. In the reliability analysis, the probability distribution of loading can be the statistics of stress transferred from the monitored strain which covered the effects of both the live and dead loads directly, and it means that the mean value and deviation of loads are fully derived from the monitored data. The probability distribution of resistance may be the statistics of strength of the material of the bridge accordingly. With five years' monitored strains, the localized reliabilities around the monitoring sensors of a bridge were computed by the method. Further, the monitored stresses are classified into two time segments in one year period to count the loading probability distribution according to the local climate conditions, which helps us to learn the reliability in different time segments and their evolvement trends. The results show that reliabilities and their evolvement trends in different parts of the bridge are different though they are all reliable yet. The method recommended in this paper is feasible to learn the localized reliabilities revealed from monitored data of a long-term SHM system of bridges, which would help bridge engineers and managers to decide a bridge inspection or maintenance strategy.

• 터널과지하공간
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• 제15권1호
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• pp.1-8
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• 2005

지금까지 국내에서 적용된 내공변위 계측은 수동식 시스템 혹은 계측 정밀도가 떨어지는 방법들로서 운영중인 터널에 적용하는데 한계가 있는 것으로 평가되어 최근 국내에 도입되고 있는 자동화 내공변위 계측 시스템들을 비교 분석하고 앞으로 운영중인 지하공간과 터널에의 적용성에 대해 검토하였다. 1. 광섬유 센서를 이용한 Sofo는 국내에서 터널 라이닝의 응력 측정에는 활용된 바가 있으나 아직 터널의 내공변위와 지중 변위의 측정에 적용된 실적이 없으며 앞으로 계측 자료의 신뢰도 및 시스템의 경제성 등에 대한 충분한 검토가 요구되고 있다. 2. 각도센서와 변위센서를 이용한 TPMS는 현재 국내에서 운영중인 터널인 천안-논산간 고속도로 차령터널과 지하철 터널 및 공동구 등에서 적용중이다. 3. BCS는 두 개의 각도 센서를 한 조로 이용하는 점이 TPMS와 다른 점으로서 거의 TPMS와 같은 특성을 지니고 있다. 앞으로 센서의 정밀도가 개선될 필요가 있으며 현장에서 아주 정밀한 교류 입력 전위차를 취득하는 데는 어려움도 있어 자동화 계측 가능여부가 검증되어야 할 것으로 본다. 앞으로 터널 시공 현장에 자동계측 시스템의 검증을 위하여 TPMS 및 BCS 등을 설치 및 운영하고 기술적인 문제를 보완함으로써 이를 시공중인 주계측 단면과 운영중인 터널에 적용하여야 할 것으로 본다.

• Journal of Animal Science and Technology
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• 제66권1호
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• pp.31-56
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• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• 한국미생물생명공학회:학술대회논문집
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• 한국미생물생명공학회 2000년도 Proceedings of 2000 KSAM International Symposium and Spring Meeting
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• pp.94-99
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• 2000

Bioluminescence is being used as a prevailing reporter of gene expression in microorganisms and mammalian cells. Bacterial bioluminescence draws special attention from environmental biotechnologists since it has many advantageous characteristics, such as no requirement of extra substractes, highly sensitive, and on-line measurability. Using bacterial bioluminescence as a reporter of toxicity has replaced the classical toxicity monitoring technology of using fish or daphnia with a cutting-edge technology. Fusion of bacterial stress promoters, which control the transcription of stress genes corresponding to heat-shock, DNA-, or oxidative-damaging stress, to the bacterial lux operon has resulted in the development of novel toxicity biosensors with a short measurement time, enhanced sensitivity, and ease and convenient usage. Therefore, these recombinant bioluminescent bacteria are expected to induce bacterial bioluminescence when the cells are exposed to stressful conditions, including toxic chemicals. We have used these recombinant bioluminescent bacteria in order to develop toxicity biosensors in a continuous, portable, or in-situ measurement from for air, water, and soil environments. All the data obtained from these toxicity biosensors for these environments were found to be repeatable and reproducible, and the minimum detection level of toxicity was found to be ppb (part per billion) levels for specific chemicals.

• Geomechanics and Engineering
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• 제25권1호
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• pp.49-58
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• 2021

The resistance of soil to the tractive force of flowing water is one of the essential parameters for the stability of the soil when directly exposed to the movement of water such as in rivers and ocean beds. Biopolymers, which are new to sustainable geotechnical engineering practices, are known to enhance the mechanical properties of soil. This study addresses the surface erosion resistance of river-sand treated with several biopolymers that originated from micro-organisms, plants, and dairy products. We used a state-of-the-art erosion function apparatus with P-wave reflection monitoring. Experimental results have shown that biopolymers significantly improve the erosion resistance of soil surfaces. Specifically, the critical shear stress (i.e., the minimum shear stress needed to detach individual soil grains) of biopolymer-treated soils increased by 2 to 500 times. The erodibility coefficient (i.e., the rate of increase in erodibility as the shear stress increases) decreased following biopolymer treatment from 1 × 10-2 to 1 × 10-6 times compared to that of untreated river-sands. The scour prediction calculated using the SRICOS-EFA program has shown that a height of 14 m of an untreated surface is eroded during the ten years flow of the Nakdong River, while biopolymer treatment reduced this height to less than 2.5 m. The result of this study has demonstrated the possibility of cross-linked biopolymers for river-bed stabilization agents.