• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2008년도 춘계 학술발표회 초청강연 및 논문집
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• pp.1466-1483
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• 2008

This paper discusses the development of an up-to-date computerized CPT (Cone Penetration Test) based soil engineering classification system to provide geotechnical engineers with a handy tool for their daily design activities. Five CPT soil engineering classification systems are incorporated in this effort. They include the probabilistic region estimation and fuzzy classification methods, both developed by Zhang and Tumay, the Schmertmann, the Douglas and Olsen, and the Robertson et al. methods. In the probabilistic region estimation method, a conformal transformation is used to determine the soil classification index, U, from CPT cone tip resistance and friction ratio. A statistical correlation is established between U and the compositional soil type given by the Unified Soil Classification System (USCS). The soil classification index, U, provides a soil profile over depth with the probability of belonging to different soil types, which more realistically and continuously reflects the in-situ soil characterization, which includes the spatial variation of soil types. The CPT fuzzy classification on the other hand emphasizes the certainty of soil behavior. The advantage of combining these two classification methods is realized through implementing them into visual basic software with three other CPT soil classification methods for friendly use by geotechnical engineers. Three sites in Louisiana were selected for this study. For each site, CPT tests and the corresponding soil boring results were correlated. The soil classification results obtained using the probabilistic region estimation and fuzzy classification methods are cross-correlated with conventional soil classification from borings logs and three other established CPT soil classification methods.

• 한국토양비료학회지
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• 제49권1호
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• pp.93-114
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• 2016

As a means of improving Korean Soil Classification System, we have reviewed Australian Soil Classification System by comparing Soil Taxonomy and FAO/WRB Classification System. Australian Soil Classification System is composed of 14 of Order, 87 of Sub-order, 556 of Great-group, 2,451 of Sub-group, and 7,276 of Family. Interestingly, soil order has the Anthroposols which is not classified with Soil Taxonomy, and the classification for some of soils is based on soil texture abruption horizon and soil structure. Seven of 14 soil orders are classified with an old version based on soil color rather than morphological characteristics. The distribution scale of Australian soil order is the largest in Tenosols, and followed by Kandosols, Rudosols, Sodosols and Vertisols in Australia.

• 한국토양비료학회지
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• 제48권5호
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• pp.535-541
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• 2015

Korean soil classification system is based on the US soil taxonomy. This study aimed to understand and inform the soil taxonomy of 2010 and 2014 US soil classification systems. Ingwan series belonged to anthropogenic soil was classified to coarse loamy over sandy, mixed, mesic family of Aquic Udorthents based on the soil taxonomy of 2010 and coarse loamy over sandy, mixed, mesic family of Anthroportic Udorthents based on the soil taxonomy of 2014. An anthropogenic soil is increasing in Korea. Considering the domestic relationship depending on US soil taxonomy, it is important to be well-informed of the taxonomy and apply the updated taxonomy system properly to the domestic soil classification. This study of defining the anthropogenic soil will provide useful information on soil management and its utilization.

• Geomechanics and Engineering
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• 제37권3호
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• pp.263-277
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• 2024

Artificial Neural Networks (ANNs) are artificial learning algorithms that provide successful results in solving many machine learning problems such as classification, prediction, object detection, object segmentation, image and video classification. There is an increasing number of studies that use ANNs as a prediction tool in soil classification. The aim of this research was to understand the role of hyperparameter optimization in enhancing the accuracy of ANNs for soil type classification. The research results has shown that the hyperparameter optimization and hyperparamter optimized ANNs can be utilized as an efficient mechanism for increasing the estimation accuracy for this problem. It is observed that the developed hyperparameter tool (HyperNetExplorer) that is utilizing the Covariance Matrix Adaptation Evolution Strategy (CMAES), Genetic Algorithm (GA) and Jaya Algorithm (JA) optimization techniques can be successfully used for the discovery of hyperparameter optimized ANNs, which can accomplish soil classification with 100% accuracy.

• 한국토양비료학회지
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• 제50권6호
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• pp.520-529
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• 2017

In Korea, the largest agricultural lands are paddy fields which have poor infiltration and drainage properties. Recently, Korean government pursuits cultivating upland crops in paddy fields to reduce overproduced rice in Korea. In order to succeed this policy, it is critical to set criteria suitability classification for upland crops cultivating in paddy field soils. The objective of this study was developing guideline of suitability classification for sesame cultivation in paddy field soils. Yields of sesame cultivated in paddy field soils and soil properties were investigated at 40 locations at nationwide scale. Soil properties such as topography, soil texture, soil moisture contents, slope, and drainage level were investigated. The guideline of suitability classification for sesame was determined by multi-regression method. As a result, sesame yields had the greatest correlation with topography, soil moisture content, and slope. Since sesame is sensitive to excessive soil moisture content, paddy fields with well drained, slope of 7-15% and mountain foot or hill were best suit for cultivating sesame. Sesame yields were greater with less soil moisture contents. Based on these results, area of best suitable paddy field land for sesame was 161,400 ha, suitable land was 62,600 ha, possible land was 331,600 ha, and low productive land was 1,075,500 ha. Compared to existing suitability classification, the new guideline of classification recommended smaller area of best or suitable areas to cultivate sesame. This result may suggest that sesame cultivation in paddy field can be very susceptible to soil moisture contents.

• 대한토목학회논문집
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• 제28권5C호
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• pp.293-301
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• 2008

지반을 대상으로 하는 일련의 활동에서 지층의 구성에 관한 정보는 필수적인 요소이다. 일반적으로 시추를 통해 지층 구성을 알 수 있으나, 배출되는 작업수와 슬라임, 굴진속도, SPT 시료 등을 참고하여 작성되는 다소 경험적인 면이 있다. 더욱이 최근 시추장비의 고성능화로 인해 얇은 토사층의 경우 구분이 점점 어려워지고 있는 것이 현실이다. 피에조콘관입시험은 주로 점토층을 대상으로 시행되었으나 최근 모래층 및 실트층으로 사용이 확대되고 있는 실정이다. 연속적인 데이터를 확보할 수 있다는 이점이 있어 흙분류에 적용하기 위한 연구가 많이 진행되었고 다양한 도표가 제안되어 사용되고 있다. 하지만, 국내에서는 이에 대한 검증 없이 적용하고 있는 것이 현실이며, 이에 대한 검증을 바탕으로 국내지반과 현실에 맞는 새로운 흙분류 시스템의 개발이 필요한 실정이다. 본 연구에서는 국내 17개 지역에서 수행된 피에조콘 관입시험 결과와 채취된 시료들에 대한 흙분류 결과를 데이터베이스화하였고, 피에조콘 결과를 이용하도록 제안된 국 내외 흙분류차트 7종류들의 국내지반에 대한 적용성을 토질 종류별로 검토하였다. 또한 종합적으로 국내지반의 흙분류에 가장 적합한 흙분류차트와 사용 변수들을 도출하였고 선정된 도표의 영역별 설명과 국내 기술자들에게 익숙한 통일분류결과와의 상관성에 대하여 고찰하였다.

• 한국초전도ㆍ저온공학회논문지
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• 제23권3호
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• pp.26-31
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• 2021

Advanced classification of Cs contaminated soil by using a magnetic force-assisted selection pipe was investigated. A selection pipe is a device that sort particles depending on their particle size, based on the relationship between buoyancy, drag, and gravity force acting on the particles. Radioactive cesium is concentrated in small-particle size soil components with a large specific surface area. Hence, the volume of the Cs contaminated soil can be reduced by recycling the large-particle size soil components with low radioactive concentration. One of the problems of the selection pipe was that the radioactive concentration of the stayed soil in the selection pipe exceeds 8000 Bq/kg, which is the standard value of recycling of Cs contaminated soil, due to low classification accuracy. In this study, magnetic fields were applied to the lab-scale selection pipe from upper side to improve the classification accuracy and to reduce the radioactive concentration of the stayed soil.

• 한국지하수토양환경학회지:지하수토양환경
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• 제15권6호
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• pp.122-127
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• 2010

Constructing the national inventory that can be used as a tool to identify and assess existing or potential contamination is necessary for efficiently managing the soil and groundwater contamination. In order to start this construction, the first step is how we define and classify potential contamination sources of soil and groundwater. After selecting the basic classification model of contamination sources from developed countries, we suggested the classification and list of the potential contamination sources of soil and groundwater which are appropriate for specific conditions of South Korea. In addition, we investigated several databases to confirm the existence of available data sources and then examined established attribute data through chemical accident response information system (CARIS) and water information system (WIS) in National Institute of Environmental Research and mine geographic information system (MGIS) in Mine Reclamation Corporation. All sorts of attribute data in the existing databases can be utilized as significant assessment factors for determining the management priority of potential contamination sources in the future. Therefore, it is required the expanded investigation of additional database sources and the continual modification so that the classification system of potential contamination sources can be improved.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2002년도 봄 학술발표회 논문집
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• pp.133-138
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• 2002

Several well-known soil classification charts, like made by Robertson(1986,1990), Olsen(1981), existed already. In Korea, Lee Sun-Jae(1997) made new classification chart based on Unified Soil Classification System with locality In this study, 6 classification charts were applied respective area. Even exact decision is impossible which one is correct, this study can give useful guideline.

• 한국토양비료학회지
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• 제46권6호
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• pp.536-541
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• 2013

In Soil Taxonomy system, anthropogenic soils are still classified as Entisols since the International Classification Committee for Anthropogenic Soils is in the process of classifying anthropogenic soils as new orders. In reality, it is difficult to characterize anthropogenic soils because Soil Taxonomy (ST) system does not distinguish between natural and anthropogenic Entisols. On the other hand, World Reference Base for soil resources (WRB) considers human impacts on soils and contains an independent category of anthropogenic soils, which makes easier to understand anthropogenic soil characteristics than Soil Taxonomy system. A remodeled paddy field (Gasan) was selected to classify by ST and WRB. Soil samples were taken to analyze chemical and physical properties. Based on the results of the analyses, the ST system classified Gasan as coarse loamy, mixed, mesic, Aquic Udorthents while the WRB did as Stagnic Urbic Technosols (Oxyaquic, Arenic). As a conclusion, the WRB classification information of the anthropogenic provides more detail characteristics of the anthropogenic soils.