• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.197-198
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• 2021

The temperature and humidity inside concrete affects the depth of carbonation. In this study, the temperature and humidity inside concrete were predicted by the numerical method under the boundary conditions of ambient temperature, humidity, solar radiation, and wind. Using the results of the thermal humidity analysis, diffusion of carbon dioxide and the reaction of cement hydration products were calculated for carbonation depth.

• Corrosion Science and Technology
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• v.10 no.3
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• pp.87-94
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• 2011

The typical corrosion prevention method inside the steel upper box girder in a suspension bridge involves the use of paints. However, in an effort to reduce environmental impact and cost, the suspension portion of the Yeongjong Bridge, Korea utilizes dehumidification systems to control humidity and prevent corrosion inside its box girder. Maintaining a uniform humidity distribution at the proper level inside the box girder is critical to the successful corrosion control. In this study, the humidity and the resultant atmospheric corrosivity inside the box girder of the Yeongjong Bridge was monitored. The corrosion rate of the steel inside the box girder was obtained using thin-film electrical resistance (TFER) corrosion sensors. Time-of-wetness (TOW) measurements and the deposition rates of atmospheric pollutants such as $Cl^{-}$ and $SO_{x}$ were also obtained. Classification of the atmospheric corrosivity inside the box girder was evaluated according to ISO 9223. As a result, no corrosion was found in the upper box girder, indicating that the dehumidification system used in the Yeongjong Bridge is an effective corrosion control method.

• Journal of Conservation Science
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• v.29 no.4
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• pp.311-320
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• 2013

The showcase has insufficient temperature control, but it has excellent humidity control. The annual average temperature and relative humidity inside the showcase was $18.8^{\circ}C$ and 60.3%, respectively, and the showcase showed lower temperature and higher humidity than the exhibition room. The temperature inside the showcase appeared with high variation according to the seasons, while relative humidity was ranging from 59% to 61% regardless of the seasons. The showcase showed high temperature and humidity likewise the exhibition room in summer. In addition, lowering of temperature was elevated relative humidity according to the operation of air conditioner in summer. A moisture problem occurred because the temperature and humidity differences between the exhibition room and showcase were large according to the operation of air conditioner in winter. PI for temperature and relative humidity inside the showcase is 18.0%, and it means conservation environment for exhibition is unsuitable. In particular, continuous management of temperature and humidity inside the showcase is required because PI in the summer and winter is less than 1.0%.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.5
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• pp.93-99
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• 2017

A model was developed using Artificial Neural Networks (ANNs) based on Principal Component Analysis (PCA), to accurately predict the air humidity inside an experimental greenhouse located in Daegu (latitude $35.53^{\circ}N$, longitude $128.36^{\circ}E$, and altitude 48 m), South Korea. The weather parameters, air temperature, relative humidity, solar radiation, and carbon dioxide inside and outside the greenhouse were monitored and measured by mounted sensors. Through the PCA of the data samples, three main components were used as the input data, and the measured inside humidity was used as the output data for the ALYUDA forecaster software of the ANN model. The Nash-Sutcliff Model Efficiency Coefficient (NSE) was used to analyze the difference between the experimental and the simulated results, in order to determine the predictive power of the ANN software. The results obtained revealed the variables that affect the inside air humidity through a sensitivity analysis graph. The measured humidity agreed well with the predicted humidity, which signifies that the model has a very high accuracy and can be used for predictions based on the computed $R^2$ and NSE values for the training and validation samples.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.10a
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• pp.83-84
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• 2016

Surplus water inside a concrete other than moisture that is used for hydration of the cement affects the physical properties of the concrete (modulus of elasticity, compressive strength, drying shrinkage, and creep) by drying. Changes in temperature and humidity inside a concrete has correlation with the movement speed and reaction rate of deterioration factors such as carbon dioxide and chloride ions. In this study, comparison was performed between temperature and relative humidity inside the concrete and meteorological data for exposure environment through measurement at the site for two years. Surface temperature of the concrete (depth 1cm) was measured higher by 6℃ during the summers, while it was measured lower by 2℃ during the winters due to solar radiation, wind, and radiation cooling. As for relative humidity, change was large in the depth of 1cm, while more than 85% was maintained in the depth of 10cm.

• International Journal of Highway Engineering
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• v.7 no.3 s.25
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• pp.23-30
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• 2005

Predicting distribution and variation of humidity inside concrete is essential to improve curing quality of concrete at field. The concrete humidity is predicted by numerical analysis using surface humidity as boundary condition. However, ambient humidity has been used instead of the surface humidity because the surface humidity could not be ccurately measured. Because it is hard to accurately measure the surface humidity, owever, the ambient humidity has been used instead of the surface humidity in the numerical analysis. In this paper, a methodology to accurately measure the surface humidity is suggested, and the ambient humidity and the humidity at the surface and inside the concrete measured by a series of laboratory tests are presented. The cause of low concrete humidity immediately after placement was investigated by a separately performed test. A surface humidity prediction model was developed using the measured humidity, and consequently validated through an additional test.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.135-135
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• 2017

Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.

• Journal of Environmental Health Sciences
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• v.43 no.1
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• pp.87-94
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• 2017

Objectives: This study was conducted to determine the impact of aquariums on indoor air quality for improving humidity and reducing indoor air pollutants. Methods: An air-conditioning chamber was used to determine humidity increase by aquarium volume at three different temperatures ($20^{\circ}C$, $25^{\circ}C$, $30^{\circ}C$). Humidity increase was measured for 21 hours ($20^{\circ}C$) and 12 hours ($25^{\circ}C$, $30^{\circ}C$) while placing five different volume of aquarium in the chamber. Concentrations of several volatile organic compounds and formaldehyde were measured after a known amount was injected into the chamber with and without an aquarium. Results: The humidity inside the chamber increased when the aquarium was inside the chamber. Humidity change was similar at $20^{\circ}C$, $25^{\circ}C$, and $30^{\circ}C$, but slightly higher at higher temperatures. The bigger the aquarium volume, the higher was the humidity increase that occurred. Humidity increase by the aquarium was sufficient to increase indoor humidity in winter and negligible in summer. Concentrations of some water-soluble indoor air pollutants and formaldehyde were decreased with the aquarium inside the chamber. Conclusions: An aquarium could increase indoor humidity in winter, while the humidity increase is negligible in summer. An aquarium could decrease some water-soluble indoor air pollutants, including formaldehyde. This result implies that an aquarium may have positive effects on indoor environmental quality.

• Journal of Bio-Environment Control
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• v.18 no.3
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• pp.200-207
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• 2009

This study was conducted to analyze the variations of air temperature, relative humidity and pressure in a low pressure chamber for plant growth. The low pressure chamber was composed of an acrylic cylinder, a stainless plate, a mass flow controller, an elastomer pressure controller, a read-out-box, a vacuum pump, and sensors of air temperature, relative humidity, and pressure. The pressure leakage in the low pressure chamber was greatly affected by the material and connection method of tubes. The leakage rate in the low pressure chamber with the welding of the stainless tubes and a plate decreased by $0.21kPa{\cdot}h^{-1}$, whereas the leakage in the low pressure chamber with teflon tube and rubber O-ring was given by $1.03kPa{\cdot}h^{-1}$. Pressure in the low pressure chamber was sensitively fluctuated by the air temperature inside the chamber. An elastomer pressure controller was installed to keep the pressure in the low pressure chamber at a setting value. However, inside relative humidity at dark period increased to saturation level.. Two levels (25 and 50kPa) of pressure and two levels (500 and 1,000sccm) of mass flow rate were provided to investigate the effect of low pressure and mass flow rate on relative humidity inside the chamber. It was concluded that low setting value of pressure and high mass flow rate of mixed gas were the effective methods to control the pressure and to suppress the excessive rise of relative humidity inside the chamber.

• Journal of the Korean Society of Costume
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• v.63 no.5
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• pp.102-114
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• 2013

This study performed the evaluation of skin temperature, heart rate, humidity and temperature inside clothing, and subjective sensation to estimate the physiological responses of the human body and its feeling of comfort for developing value-added dox fabric. Experiments were performed on five healthy adult women whose average age was 21, at climate chamber in which temperature, relative humidity and air current were set up below $28{\pm}5^{\circ}C$, $50{\pm}10%$, 0.2m/s, respectively. Two kinds of clothes were used for the experiments: 100% cotton and dox clothes. The clothes were identical in size and form, and the attire consisted of long-sleeved shirts, long trousers, and socks. The experiment was performed for 30 minutes using ergometer. The results are as follows. 1) It showed low skin temperature of forearm, breast, back, forehead and lower leg in exercise, but high skin temperature of them in recovery. However skin temperature of thigh and foot increased from rest to recovery. 2) It showed significant difference (p<0.001, p<0.01) in average skin temperature between cotton and dox clothes. Cotton clothes had a higher average skin temperature compared to dox. Not only was there a significant difference in temperature inside clothing (p<0.001), this was also the case with humidity inside the clothing (p<0.001).