• Title/Summary/Keyword: soil variables

Search Result 526, Processing Time 0.027 seconds

Normalized Subgrade Analytical Model Considering Stress-Dependency and Modulus Degradation (응력의존성 및 탄성계수 감쇠특성을 고려한 노상토의 정규화 해석모델)

  • Kim, Ji-Hwan;Kang, Beong-Joon;Lee, Jun-Hwan;Kweon, Gi-Chul
    • Journal of the Korean Geotechnical Society
    • /
    • v.24 no.4
    • /
    • pp.37-46
    • /
    • 2008
  • Application of resilient modulus, representing mechanical behavior of pavement materials, has become general concept for pavement design, analysis and maintenance after '86 AASHTO selected it as a basic input property of subgrade. It is known that resilient modulus of domestic subgrade soil is affected greatly by material factors, such as water content and dry weight unit, and stress components, such as deviatoric stress and confining stress, while effects of loading frequency and loading repeat were regarded negligible. If design based on resilient modulus is to be successfully implemented, design input variables of relevant models should be able to reflect local conditions. In this study, generalized mechanical model for subgrade is proposed. Model parameters are estimated from test results. Verification of the model was performed through finite element analysis using the proposed model, which showed good agreement with measured results of pavement deflections.

J2-bounding Surface Plasticity Model with Zero Elastic Region (탄성영역이 없는 J2-경계면 소성모델)

  • Shin, Hosung;Oh, Seboong;Kim, Jae-min
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.43 no.4
    • /
    • pp.469-476
    • /
    • 2023
  • Soil plasticity models for cyclic and dynamic loads are essential in non-linear numerical analysis of geotechnical structures. While a single yield surface model shows a linear behavior for cyclic loads, J2-bounding surface plasticity model with zero elastic region can effectively simulate a nonlinearity of the ground response with the same material properties. The radius of the yield surface inside the boundary surface converged to 0 to make the elastic region disappear, and plastic hardening modulus and dilatancy define plastic strain increment. This paper presents the stress-strain incremental equation of the developed model, and derives plastic hardening modulus for the hyperbolic model. The comparative analyses of the triaxial compression test and the shallow foundation under the cyclic load can show stable numerical convergence, consistency with the theoretical solution, and hysteresis behavior. In addition, plastic hardening modulus for the modified hyperbolic function is presented, and a methodology to estimate model variables conforming 1D equivalent linear model is proposed for numerical modeling of the multi-dimensional behavior of the ground.

Free vibration analysis of Bi-Directional Functionally Graded Beams using a simple and efficient finite element model

  • Zakaria Belabed;Abdeldjebbar Tounsi;Abdelmoumen Anis Bousahla;Abdelouahed Tounsi;Mohamed Bourada;Mohammed A. Al-Osta
    • Structural Engineering and Mechanics
    • /
    • v.90 no.3
    • /
    • pp.233-252
    • /
    • 2024
  • This research explores a new finite element model for the free vibration analysis of bi-directional functionally graded (BDFG) beams. The model is based on an efficient higher-order shear deformation beam theory that incorporates a trigonometric warping function for both transverse shear deformation and stress to guarantee traction-free boundary conditions without the necessity of shear correction factors. The proposed two-node beam element has three degrees of freedom per node, and the inter-element continuity is retained using both C1 and C0 continuities for kinematics variables. In addition, the mechanical properties of the (BDFG) beam vary gradually and smoothly in both the in-plane and out-of-plane beam's directions according to an exponential power-law distribution. The highly elevated performance of the developed model is shown by comparing it to conceptual frameworks and solution procedures. Detailed numerical investigations are also conducted to examine the impact of boundary conditions, the bi-directional gradient indices, and the slenderness ratio on the free vibration response of BDFG beams. The suggested finite element beam model is an excellent potential tool for the design and the mechanical behavior estimation of BDFG structures.

The NCAM Land-Atmosphere Modeling Package (LAMP) Version 1: Implementation and Evaluation (국가농림기상센터 지면대기모델링패키지(NCAM-LAMP) 버전 1: 구축 및 평가)

  • Lee, Seung-Jae;Song, Jiae;Kim, Yu-Jung
    • Korean Journal of Agricultural and Forest Meteorology
    • /
    • v.18 no.4
    • /
    • pp.307-319
    • /
    • 2016
  • A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

Estimation of High Resolution Sea Surface Salinity Using Multi Satellite Data and Machine Learning (다종 위성자료와 기계학습을 이용한 고해상도 표층 염분 추정)

  • Sung, Taejun;Sim, Seongmun;Jang, Eunna;Im, Jungho
    • Korean Journal of Remote Sensing
    • /
    • v.38 no.5_2
    • /
    • pp.747-763
    • /
    • 2022
  • Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

A Studs on Farmers Syndrome and Its Risk Factors of Vinylhouse Workers and Evaluation of Risk Factors of Vinylhouse Works (일부 농촌지역 비닐하우스 농사자들의 작업환경 및 농부증 실태와 관련요인평가)

  • Lee, Jung-Jeung
    • Journal of agricultural medicine and community health
    • /
    • v.29 no.1
    • /
    • pp.101-119
    • /
    • 2004
  • Objectives: In order to estimate risk factors affecting the health of vinylhouse workers and harmful environments in vinylhouse working. Methods: The investigator performed questionnaires and laboratory examinations on 102 vinylhouse workers and 69 farmers in 7 myoens (Korean subcounties). one eup (a Korean town), Goryeong-gun, Gyeongsangbuk-do between April 8 and 18, 2004 (for 11 days), and measured the heavy metal in the air and the soil, temperature, humidity, air current, harmful gases in vinylhouses. Results: Even in cloudy days, the temperature in vinylhouses in daylight was $33.4^{\circ}$ and the temperature difference between inside and outside vinylhouses was around $16^{\circ}$. Oxygen concentration was similar inside and outside vinylhouses, while carbon dioxide concentration was lower inside than outside vinylhouses. Carbon monoxide was not detected. In the air inside vinylhouses, cadmium was not detected. Lean concentration in the soil was lower inside vinylhouses than outside vinylhouses at surface, while cadmium concentration was similar inside and outside vinylhouses in the soil except some areas. Out of male vinylhouse workers. 16.4---- were positive farmer's syndrome and 49.2---- were suspicious, while out of females, 41.5---- were positive and 46.3---- were suspicious. Out of male farmers, 30.4---- were positive farmer's syndrome, while out of female farmers, 60.0---- were positive and 28.3---- were suspicious. There was no difference between vinylhouse workers and farmers in the distribution of hypertension and abnormal liver function, while diabetes mellitus was more common in farmers than in vinylhouse workers. Vinylhouse working, sex, and hours of farming per day were selected as significant variables affecting farmer's syndrome in this study, and the rate of positive farmer's syndrome was rather lower in vinylhouse workers than in farmers. Females were higher than males in the rate, and those who farmed at least 10 hours per day were higher in the rate than those who farmed less than 10 hours per day. Out of the vinylhouse workers, no differences were found between the distribution of farmer's syndrome and farming-related variables such as the total period of farming, the size of farm land, the mean farming hours per day, the number of family members who farm together, the frequency of scattering agricultural chemicals. In addition, there were no differences between the distribution and the wearing masks and protectors and personal sanitation among those who scattered agricultural chemicals by themselves. There were no differences found in blood lean concentration, urinary cadmium concentration, serum cholinesterase, and hemoglobin according to the distribution of farmer's syndrome. In the vinylhouse workers, females were higher than males in the rate of farmer's syndrome, and those who farmed at least 10 hours per day were higher in the rate than those who farmed less than 10 hours per day. Meanwhile, the rate was lower in those who slept at least 8 hours a day than in those who slept less than 8 hours. Conclusions: In conclusion, the physical environments inside vinylhouses were harmful, but no significant difference was found in harmfulness of the chemical environments. The chronic diseases such as farmer's syndrome. hypertension, diabetes, and dyshepatia were not common in the vinylhouse workers than in the farmers. Meanwhile, farmer's syndrome was more common in the vinylhouse workers who worked longer and slept less.

  • PDF

Analysis of Significance between SWMM Computer Simulation and Artificial Rainfall on Rainfall Runoff Delay Effects of Vegetation Unit-type LID System (식생유니트형 LID 시스템의 우수유출 지연효과에 대한 SWMM 전산모의와 인공강우 모니터링 간의 유의성 분석)

  • Kim, Tae-Han;Choi, Boo-Hun
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.48 no.3
    • /
    • pp.34-44
    • /
    • 2020
  • In order to suggest performance analysis directions of ecological components based on a vegetation-based LID system model, this study seeks to analyze the statistical significance between monitoring results by using SWMM computer simulation and rainfall and run-off simulation devices and provide basic data required for a preliminary system design. Also, the study aims to comprehensively review a vegetation-based LID system's soil, a vegetation model, and analysis plans, which were less addressed in previous studies, and suggest a performance quantification direction that could act as a substitute device-type LID system. After monitoring artificial rainfall for 40 minutes, the test group zone and the control group zone recorded maximum rainfall intensity of 142.91mm/hr. (n=3, sd=0.34) and 142.24mm/hr. (n=3, sd=0.90), respectively. Compared to a hyetograph, low rainfall intensity was re-produced in 10-minute and 50-minute sections, and high rainfall intensity was confirmed in 20-minute, 30-minute, and 40-minute sections. As for rainwater run-off delay effects, run-off intensity in the test group zone was reduced by 79.8% as it recorded 0.46mm/min at the 50-minute point when the run-off intensity was highest in the control group zone. In the case of computer simulation, run-off intensity in the test group zone was reduced by 99.1% as it recorded 0.05mm/min at the 50-minute point when the run-off intensity was highest. The maximum rainfall run-off intensity in the test group zone (Dv=30.35, NSE=0.36) recorded 0.77mm/min and 1.06mm/min in artificial rainfall monitoring and SWMM computer simulation, respectively, at the 70-minute point in both cases. Likewise, the control group zone (Dv=17.27, NSE=0.78) recorded 2.26mm/min and 2.38mm/min, respectively, at the 50-minutes point. Through statistical assessing the significance between the rainfall & run-off simulating systems and the SWMM computer simulations, this study was able to suggest a preliminary design direction for the rainwater run-off reduction performance of the LID system applied with single vegetation. Also, by comprehensively examining the LID system's soil and vegetation models, and analysis methods, this study was able to compile parameter quantification plans for vegetation and soil sectors that can be aligned with a preliminary design. However, physical variables were caused by the use of a single vegetation-based LID system, and follow-up studies are required on algorithms for calibrating the statistical significance between monitoring and computer simulation results.

Verification of International Trends and Applicability in the Republic of Korea for a Greenhouse Gas Inventory in the Grassland Biomass Sector (초지 바이오매스 부문 온실가스 인벤토리 구축을 위한 국제 동향과 국내 적용 가능성 평가)

  • Sle-gee Lee;Jeong-Gwan Lee;Hyun-Jun Kim
    • Journal of The Korean Society of Grassland and Forage Science
    • /
    • v.43 no.4
    • /
    • pp.257-267
    • /
    • 2023
  • The grassland section of the greenhouse gas inventory has limitations due to a lack of review and verification of biomass compared to organic carbon in soil while grassland is considered one of the carbon storages in terrestrial ecosystems. Considering the situation at internal and external where the calculation of greenhouse gas inventory is being upgraded to a method with higher scientific accuracy, research on standards and methods for calculating carbon accumulation of grassland biomass is required. The purpose of this study was to identify international trends in the calculation method of the grassland biomass sector that meets the Tier 2 method and to conduct a review of variables applicable to the Republic of Korea. Identify the estimation methods and access levels for grassland biomass through the National Inventory Report in the United Nations Framework Convention on Climate Change and type the main implications derived from overseas cases. And, a field survey was conducted on 28 grasslands in the Republic of Korea to analyse the applicability of major issues. Four major international issues regarding grassland biomass were identified. 1) country-specific coefficients by land use; 2) calculations on woody plants; 3) loss and recovery due to wildfire; 4) amount of change by human activities. As a result of field surveys and analysis of activity data available domestically, it was found that there was a significant difference in the amount of carbon in biomass according to use type classification and climate zone-soil type classification. Therefore, in order to create an inventory of grassland biomass at the Tier 2 level, a policy and institutional system for making activity data should develop country-specific coefficients for climate zones and soil types.

Impacts of Three-dimensional Land Cover on Urban Air Temperatures (도시기온에 작용하는 입체적 토지피복의 영향)

  • Jo, Hyun-Kil;Ahn, Tae-Won
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.37 no.3
    • /
    • pp.54-60
    • /
    • 2009
  • The purpose of this study is to analyze the impacts of three-dimensional land cover on changing urban air temperatures and to explore some strategies of urban landscaping towards mitigation of heat build-up. This study located study spaces within a diameter of 300m around 24 Automatic Weather Stations(AWS) in Seoul, and collected data of diverse variables which could affect summer energy budgets and air temperatures. The study also selected reflecting study objectives 6 smaller-scale spaces with a diameter of 30m in Chuncheon, and measured summer air temperatures and three-dimensional land cover to compare their relationships with results from Seoul's AWS. Linear regression models derived from data of Seoul's AWS revealed that vegetation volume, greenspace area, building volume, building area, population density, and pavement area contributed to a statistically significant change in summer air temperatures. Of these variables, vegetation and building volume indicated the highest accountability for total variability of changes in the air temperatures. Multiple regression models derived from combinations of the significant variables also showed that both vegetation and building volume generated a model with the best fitness. Based on this multiple regression model, a 10% increase of vegetation volume decreased the air temperatures by approximately 0.14%, while a 10% increase of building volume raised them by 0.26%. Relationships between Chuncheon's summer air temperatures and land cover distribution for the smaller-scale spaces also disclosed that the air temperatures were negatively correlated to vegetation volume and greenspace area, while they were positively correlated to hardscape area. Similarly to the case of Seoul's AWS, the air temperatures for the smaller-scale spaces decreased by 0.32% ($0.08^{\circ}C$) as vegetation volume increased by 10%, based on the most appropriate linear model. Thus, urban landscaping for the reduction of summer air temperatures requires strategies to improve vegetation volume and simultaneously to decrease building volume. For Seoul's AWS, the impact of building volume on changing the air temperatures was about 2 times greater than that of vegetation volume. Wall and rooftop greening for shading and evapotranspiration is suggested to control atmospheric heating by three-dimensional building surfaces, enlarging vegetation volume through multilayered plantings on soil surfaces.

A stratified random sampling design for paddy fields: Optimized stratification and sample allocation for effective spatial modeling and mapping of the impact of climate changes on agricultural system in Korea (농지 공간격자 자료의 층화랜덤샘플링: 농업시스템 기후변화 영향 공간모델링을 위한 국내 농지 최적 층화 및 샘플 수 최적화 연구)

  • Minyoung Lee;Yongeun Kim;Jinsol Hong;Kijong Cho
    • Korean Journal of Environmental Biology
    • /
    • v.39 no.4
    • /
    • pp.526-535
    • /
    • 2021
  • Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.