• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.2999-3029
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• 2024

To improve the predictive capability of a nuclear thermal hydraulic safety analysis code by developing a better constitutive equation for individual phenomenon has been the general research direction until now. This paper proposes a new method to directly use complex experimental data obtained from integral effect test (IET) to improve constitutive models holistically and simultaneously. The method relies on the sensitivity of a simulation result of IET data to the multiple constitutive equations utilized during the simulation, and the sensitivity of individual model determines the direction of modification for the constitutive model. To develop a robust and generalized method, a clustering algorithm using an artificial neural network, sample space size determination using non-parametric statistics, and sampling method of Latin hypercube sampling are used in a combined manner. The value of the proposed methodology is demonstrated by applying the method to the ATLAS DSP-05 IET experiment. A sensitivity of each observation parameter to the constitutive models is analyzed. The new methodology suggested in the study can be used to improve the code prediction results of complex IET data by identifying the direction for constitutive equations to be modified.

• International Journal of Computer Science & Network Security
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• v.24 no.10
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• pp.154-158
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• 2024

Billions of the objects around us are transformed to the IoT device by connecting them with the internet and control in that way of collecting and sharing data. Privacy is required to keep the data save from the security attacks in internet of things. Computer vision is used for monitoring the people. Computer vision algorithms, application and tools are primarily used in IOT for human movement's analysis. Traditional system and algorithms are unable to detect the human in a perfect manner. Use of the thermal camera is degraded the movements of human detection. In this paper we propose a new IoT system that is combined with the latest feature of computer vision to detect the position using computer vision. It is a useful technology that helps to keep an eye on your house and office. It will alert you if anybody enters your home or office and do any harm at your place. For that purpose, the credit card size Raspberry PI card will be used. Histogram of oriented gradient (HOG) algorithm is used to detect the person in the image.

• Food Science of Animal Resources
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• v.40 no.4
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• pp.588-600
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• 2020

The effect of age (22, 30, 38, and 46 days) on Beijing duck breast myosin gels was investigated. The results showed that the water holding capacity (WHC) and gel strength were markedly improved at the age of 30 days. Differential scanning calorimetry suggested that the myosin thermal ability increased at the age of 30 and 38 days (p<0.05). A compact myosin gel network with thin cross-linked strands and small regular cavities formed at the age of 30 days, which was resulted from the higher content of hydrophobic interactions and disulfide bonds. Moreover, the surface hydrophobicity of myosin extracted from a 30-day-old duck breast decreased significantly under temperature higher than 80℃ (p<0.05). This study illustrated that myosin extracted from a 30-day-old duck's breast enhanced and stabilized the WHC, thermal stability and molecular forces within the gel system. It concluded that age is an essential influencing factor on the myosin thermal stability and gel quality of Beijing duck due to the transformation of fibrils with different myosin character.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.62-68
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• 2016

The feeder cable assembly is an automotive part used for telecommunication. If it malfunctions, the control and safety of the automobile can be put at risk. ALT (Accelerated Life Testing) is a testing process for products in which they are subjected to conditions (stress, strain, temperatures, etc.) in excess of their normal service parameters in an attempt to uncover faults and potential modes of failure in a short amount of time. Failure is caused by defects in the design, process, quality, or application of the part, and these defects are the underlying causes of failure or which initiate a process leading to failure. Thermal shock occurs when a thermal gradient causes different parts of an object to expand by different amounts. Thermal shock testing is performed to determine the ability of parts and components to withstand sudden changes in temperature. In this research, the main causes of failure of the feeder cable assembly were snapping, shorting and electro-pressure resistance failure. Using the Coffin-Manson model for ALT, the normal conditions were from Tmax = $80^{\circ}C$ to Tmin = $-40^{\circ}C$, the accelerated testing conditions were from Tmax = $120^{\circ}C$ to Tmin = $-60^{\circ}C$, the AF (Acceleration Factor) was 2.25 and the testing time was reduced from 1,000 cycles to 444 cycles. Using the Bxlife test, the number of samples was 5, the required life was B0.04%.10years, in the acceleration condition, 747 cycles were obtained. After the thermal shock test under different conditions, the feeder cable assembly was examined by a network analyzer and compared with the Weibull distribution modulus parameter. The results obtained showed good results in acceleration life test mode. For the same reliability rate, the testing time was decreased by a quarter using ALT.

• Tunnel and Underground Space
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• v.19 no.3
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• pp.203-212
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• 2009

The prediction of near field behavior around an underground high-level radioactive waste repository is important for the repository design as well as the safety assessment. In this study, a sensitivity analysis for seven parameters consisted of design parameters and material properties was carried out using a three-dimensional finite difference code. From the sensitivity analysis, it was found that the effects of borehole spacing, tunnel spacing, cooling time and rock thermal conductivity were more significant than the other parameters. For getting a statistical distribution of buffer and rock temperatures around the repository, an artificial neural network, backpropagation, was applied. The reliability of the trained neural network was tested with the cases with randomly chosen input parameters. When the parameter variation is within ${\pm}10%$, the prediction from the network was found to be reliable with about a 1% error. It was possible to calculate the temperature distribution for many cases quickly with the trained neural network. The buffer and rock temperatures showed a normal distribution with means of $98^{\circ}C$ and $83.9^{\circ}C$ standard deviations of $3.82^{\circ}C$ and $3.67^{\circ}C$, respectively. Using the neural network, it was also possible to estimate the required change in design parameters for reducing the buffer and rock temperatures for $1^{\circ}C$.

• Geomechanics and Engineering
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• v.16 no.4
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• pp.363-373
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• 2018

The evaluation of Thermo-Hydro-Mechanical (THM) coupling behavior is important for the development of underground space for various purposes. For a high-level radioactive waste repository excavated in a deep underground rock mass, the accurate prediction of the complex THM behavior is essential for the long-term safety and stability assessment. In order to develop reliable THM analysis techniques effectively, an international cooperation project, Development of Coupled models and their Validation against Experiments (DECOVALEX), was carried out. In DECOVALEX-2015 Task B2, the in situ THM experiment that was conducted at Horonobe Underground Research Laboratory(URL) by Japan Atomic Energy Agency (JAEA), was modeled by the research teams from the participating countries. In this study, a THM coupling technique that combined TOUGH2 and FLAC3D was developed and applied to the THM analysis for the in situ experiment, in which rock, buffer, backfill, sand, and heater were installed. With the assistance of an artificial neural network, the boundary conditions for the experiment could be adequately implemented in the modeling. The thermal, hydraulic, and mechanical results from the modeling were compared with the measurements from the in situ THM experiment. The predicted buffer temperature from the THM modelling was about $10^{\circ}C$ higher than measurement near by the overpack. At the other locations far from the overpack, modelling predicted slightly lower temperature than measurement. Even though the magnitude of pressure from the modeling was different from the measurements, the general trends of the variation with time were found to be similar.

• KIEAE Journal
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• v.14 no.4
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• pp.119-125
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• 2014

This study investigated the effects of pipe network materials and distance on system performance utilizing unused energy sources in large-scale horticulture facility. For this, the modeling was performed with a 100 m long and 100 m wide rectangular shaped glass house having an area of 1ha ($10,000m^2$) using EnergyPlus software. The heat sources considered were air source, geothermal heat, power plant waste heat, sea water heat, and river water. The temperature variation of the fluid with regard to pipe material and distance from the heat source and the resultant heat pump electricity consumptions were calculated. It turned out that the fluid temperature reaching the heat pump increased as the distance from the heat source increased in case of sea water and river water, which have higher temperatures than the surrounding soil, improving the heat pump efficiency. It was vice versa in case of the power plant waste heat. In addition, pipe material of PVC showed the smallest effect on the system performance variation due to the lowest thermal conductivity, compared to PB and HDPE.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.459-466
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• 2006

Numerical values of thermodynamic properties such as temperature, pressure, dryness, volume, enthalpy and entropy are required in numerical analysis on evaluating the thermal performance. But the steam table itself cannot be used without modelling. From this point of view the neural network with function approximation characteristics can be an alternative. the multi-layer neural networks were made for saturated vapor region and superheated vapor region separately. For saturated vapor region the neural network consists of one input layer with 1 node, two hidden layers with 10 and 20 nodes each and one output layer with 7 nodes. For superheated vapor region it consists of one input layer with 2 nodes, two hidden layers with 15 and 25 nodes each and one output layer with 3 nodes. The proposed model gives very successful results with ${\pm}0.005%$ of percentage error for temperature, enthalpy and entropy and ${\pm}0.025%$ for pressure and specific volume. From these successful results, it is confirmed that the neural networks could be powerful method in function approximation of the steam table.

• Composites Research
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• v.28 no.2
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• pp.70-74
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• 2015

In this paper, carbon nanotubes (CNTs) and micro glass bubbles (GBs) have been incorporated into a polyamide6 (PA6) matrix to impart thermoelectric properties. The spaces created in the matrix by GBs allows the formation of "segregated" CNT network. The tightly bound CNT network, if controlled properly, can serve as a conductive path for electron transport, while prohibiting phonon transport, which would provide an ideal configuration for thermoelectric applications. The CNTs and GBs were dispersed in a nylon-formic acid solution using horn sonication followed by coagulation in deionized water, and nanocomposite panels were fabricated using a hot press. The performance of nanocomposite panels was evaluated from thermal and electrical conductivities and Seebeck coefficient, and a thermoelectric figure of merit as high as 0.016 was achieved.

• Smart Structures and Systems
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• v.6 no.8
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• pp.939-951
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• 2010

A low-cost wireless sensor network (WSN) solution with highly expandable super and simple nodes was developed. The super node was designed as a sensing unit as well as a receiving terminal with low energy consumption. The simple node was designed to serve as a cheaper alternative for large-scale deployment. A 12-bit ADC inputs and DAC outputs were reserved for sensor boards to ease the sensing integration. Vibration and thermal field tests of the Chi-Lu Bridge were conducted to evaluate the WSN's performance. Integral acceleration, temperature and tilt sensing modules were constructed to simplify the task of long-term environmental monitoring on this bridge, while a star topology was used to avoid collisions and reduce power consumption. We showed that, given sufficient power and additional power amplifier, the WSN can successfully be active for more than 7 days and satisfy the half bridge 120-meter transmission requirement. The time and frequency responses of cables shocked by external force and temperature variations around cables in one day were recorded and analyzed. Finally, guidelines on power characterization of the WSN platform and selection of acceleration sensors for structural health monitoring applications were given.