• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.729-737
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• 2013

The environmental load of concrete pavement can be categorized by temperature and moisture loads, which mean temperature distribution, and drying shrinkage and creep in the concrete slab. In this study, a method calculating the environmental load essential to mechanistic design of airport concrete pavement was developed. First, target area and design slab thickness were determined. And, the concrete temperature distribution with slab depth was predicted by a pavement temperature prediction program to calculate equivalent linear temperature difference. The concrete drying shrinkage was predicted by improving an existing model to calculate differential shrinkage equivalent linear temperature difference considering regional relative humidity. In addition, the stress relaxation was considered in the drying shrinkage. Eventually, the equivalent linear temperature difference due to temperature and the differential shrinkage equivalent linear temperature difference due to moisture were combined into the total equivalent linear temperature difference as terminal environmental load. The environmental load of eight civilian and two military airports which represent domestic regional weather conditions were calculated and compared by the method developed in this study to show its application.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.264-276
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• 2021

Background: Salt marshes provide a variety of ecosystem services; however, they are vulnerable to human activity, water level fluctuations, and climate change. Analyses of the relationships between plant communities and environmental conditions in salt marshes are expected to provide useful information for the prediction of changes during climate change. In this study, relationships between the current vegetation structure and environmental factors were evaluated in the tidal flat at the southern tip of Ganghwa, Korea, where salt marshes are well-developed. Results: The vegetation structure in Ganghwa salt marshes was divided into three groups by cluster analysis: group A, dominated by Phragmites communis; group B, dominated by Suaeda japonica; and group C, dominated by other taxa. As determined by PERMANOVA, the groups showed significant differences with respect to altitude, soil moisture, soil organic matter, salinity, sand, clay, and silt ratios. A canonical correspondence analysis based on the percent cover of each species in the quadrats showed that the proportion of sand increased as the altitude increased and S. japonica appeared in soil with a relatively high silt proportion, while P. communis was distributed in soil with low salinity. Conclusions: The distributions of three halophyte groups differed depending on the altitude, soil moisture, salinity, and soil organic matter, sand, silt, and clay contents. Pioneer species, such as S. japonica, appeared in soil with a relatively high silt content. The P. communis community survived under a wider range of soil textures than previously reported in the literature; the species was distributed in soils with relatively low salinity, with a range expansion toward the sea in areas with freshwater influx. The observed spatial distribution patterns may provide a basis for conservation under declining salt marshes.

• Journal of Ecology and Environment
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• v.38 no.4
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• pp.493-503
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• 2015

This study analyzed how spatial distribution of Himantormia lugubris is affected by the microenvironment in the Antarctic Specially Protected Area (ASPA) No. 171 located in the Barton Peninsula of King George Island that belongs to the maritime Antarctic. In order to determine the population structure of H. lugubris growing in Baekje Hill within ASPA No. 171, we counted the individuals of different size groups after dividing the population into 5 growth stages according to mean diameter as follows: ≤ 1 cm, 1-3 cm, 3-5 cm, 5-10 cm, and ≥ 10 cm. The count of H. lugubris individuals in each growth stage was converted into its percentage with respect to the entire population, which yielded the finding that stages 1 through 5 accounted for 32.8%, 25.3%, 15.9%, 22.5%, and 3.5%, respectively. This suggests that the population of H. lugubris in ASPA No. 171 has a stable reverse J-shaped population structure, with the younger individuals outnumbering mature ones. The mean density of H. lugubris was 17.6/0.25 m², mean canopy cover 13.3%, and the mean dry weight 37.8 g/0.25 m². It began to produce spore in the sizes over 3 cm, and most individuals measuring 5-10 cm were adults with sexually mature apothecia. The spatial distribution of H. lugubris was highly heterogeneous. The major factors influencing its distribution and performance were found to be the period covered by snow, wind direction, moisture, size of the substrate, and canopy cover of Usnea spp. Based on these factors, we constructed a prediction model for estimating the spatial distribution of H. lugubris. Conclusively, the major factors for the spatial distribution of H. lugubris were snow, wind, substrate and the competition with Usnea spp. These results are important for understanding of the distribution in the maritime Antarctic and evolution of H. lugubris that claims a unique life history and ecological niche.

• International Journal of Concrete Structures and Materials
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• v.6 no.3
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• pp.177-186
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• 2012

The temperature distributions of concrete structures strongly depend on the value of thermal conductivity of concrete. However, the thermal conductivity of concrete varies according to the composition of the constituents and the temperature and moisture conditions of concrete, which cause difficulty in accurately predicting the thermal conductivity value in concrete. For this reason, in this study, back-propagation neural network models on the basis of experimental values carried out by previous researchers have been utilized to effectively account for the influence of these variables. The neural networks were trained by 124 data sets with eleven parameters: nine concrete composition parameters (the ratio of water-cement, the percentage of fine and coarse aggregate, and the unit weight of water, cement, fine aggregate, coarse aggregate, fly ash and silica fume) and two concrete state parameters (the temperature and water content of concrete). Finally, the trained neural network models were evaluated by applying to other 28 measured values not included in the training of the neural networks. The result indicated that the proposed method using a back-propagation neural algorithm was effective at predicting the thermal conductivity of concrete.

• Journal of the Korean Wood Science and Technology
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• v.28 no.1
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• pp.18-27
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• 2000

Even the same materials are assembled in flush door skin panel, warping is not simply prevented under the changes of environmental conditions since wood and wood-based material have large variations in their physical and mechanical properties. The parameters such as linear movement coefficient(LMC), modulus of elasticity (MOE), required to predict warping could be estimated by oven drying method and dynamic method instead of American Society for Testing Materials(ASTM) procedure. The relationship between warping and LMC was curvilinear, while it between warping and MOE was linear. LMC had a larger effect on warping than MOE. Material propensity of skin panel such as hardboard and plywood showed normal distributions. The variation of material properties, however, was much larger in plywood than in hardboard. Monte Carlo simulation also indicated that rejection ratio of flush door due to the occurrence of warping could be predicted with consideration of the relationship of warping and parameters of probability distribution of MOE, LMC, and moisture content.

• Journal of the Korea Concrete Institute
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• v.14 no.1
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• pp.118-125
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• 2002

Hydration is the main reason for the growth of the material properties. An exact parameter to control the chemical and physical process is not the time, but the degree of hydration. Therefore, it is reasonable that development of all material properties and the formation of microstructure should be formulated in terms of degree of hydration. Mathematical formulation of degree of hydration is based on combination of reaction rate functions. The effect of moisture conditions as well as temperature on the rate of reaction is considered in the degree of hydration model. This effect is subdivided into two contributions: water shortage and water distribution. The former is associated with the effect of W/C ratio on the progress of hydration. The water needed for progress of hydration do not exist and there is not enough space for the reaction products to form. The tatter is associated with the effect of free capillary water distribution in the pore system. Physically absorption layer does not contribute to progress of hydration and only free water is available for further hydration. In this study, the effects of chemical composition of cement, W/C ratio, temperature, and moisture conditions on the degree of hydration are considered. Parameters that can be used to indicate or approximate the real degree of hydration are liberated heat of hydration, amount of chemically bound water, and chemical shrinkage, etc. Thus, the degree of heat liberation and adiabatic temperature rise could be determined by prediction of degree of hydration.

• Journal of Biosystems Engineering
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• v.42 no.3
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• pp.190-198
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• 2017

Purpose: A thin-layer drying equation was developed to analyze the drying processes of soybeans (white and black beans) and investigate drying conditions by verifying the suitability of existing grain drying equations. Methods: The drying rates of domestic soybeans were measured in a drying experiment using air at a constant temperature and humidity. The drying rate of soybeans was measured at two temperatures, 50 and $60^{\circ}C$, and three relative humidities, 30, 40 and 50%. Experimental constants were determined for the selected thin layer drying models (Lewis, Page, Thompson, and moisture diffusion models), which are widely used for predicting the moisture contents of grains, and the suitability of these models was compared. The suitability of each of the four drying equations was verified using their predicted values for white beans as well as the determination coefficient ($R^2$) and the root mean square error (RMSE) of the experiment results. Results: It was found that the Thompson model was the most suitable for white beans with a $R^2$ of 0.97 or greater and RMSE of 0.0508 or less. The Thompson model was also found to be the most suitable for black beans, with a $R^2$ of 0.97 or greater and an RMSE of 0.0308 or less. Conclusions: The Thompson model was the most appropriate prediction drying model for white and black beans. Empirical constants for the Thompson model were developed in accordance with the conditions of drying temperature and relative humidity.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.34-38
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• 2003

A mathematical model was developed for estimating the mechanical interrelation between characteristics of soil and main design factors of a tracked vehicle, and predicting the tractive performance of the tracked vehicle. Based on the mathematical model, a computer simulation program (TPPMTV) was developed in the study. The model considered the continuous change in tension for the whole track of a tracked vehicle, the analysis of shape and tension of the track segment between sprocket and first roadwheel, and the side thrust on both sides of grouser by the active earth pressure theory in predicting the tractive performance of a tracked vehicle. Also, the model contained not only sinkage depth of the track but the pressure distribution under the track in analyzing the side thrust. The effectiveness of the developed model was verified by performing the draw bar pull tests with a tracked vehicle reconstructed for test in loam soil with moisture content of 18.92％. The predicted drawbar pulls by the model were well matched to the measured ones. Such results implied that the model developed in the study could estimate the drawbar pulls well at various soil conditions, and would be very useful as a simulation tool for designing a tracked vehicle and predicting its tractive performance.

• 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.

• Atmosphere
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• v.32 no.3
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• pp.235-246
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• 2022

A large number of MJO skill metrics and process-oriented MJO simulation metrics have been developed by previous studies including the MJO Working Group and Task Force. To assess models' successes and shortcomings in the MJO simulation, a standardized set of diagnostics with the additional set of dynamics-oriented diagnostics are applied. The Global Coupled (GC) model developed for the operation of the climate prediction system is used with the comparison between the GC2 and GC3.1. Two GC models successfully capture three-dimensional dynamic and thermodynamic structure as well as coherent eastward propagation from the reference regions of the Indian Ocean and the western Pacific. The low-level moisture convergence (LLMC) ahead of the MJO deep convection, the low-level westerly and easterly associated with the coupled Rossby-Kelvin wave and the upper-level divergence are simulated successfully. The GC3.1 model simulates a better three-dimensional structure of MJO and thus reproduces more realistic eastward propagation. In GC2, the MJO convection following the LLMC near and east of the Maritime Continent is much weaker than observation and has an asymmetric distribution of both low and upper-level circulation anomalies. The common shortcomings of GC2 and GC3.1 are revealed in the shorter MJO periods and relatively weak LLMC as well as convective activity over the western Indian Ocean.