Journal of Korean Tunnelling and Underground Space Association
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v.11
no.4
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pp.327-351
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2009
Laboratory tests are performed in this paper to investigate the brittle failure characteristics of over-stressed rocks taken in deep depth. Also, numerical simulation performed using that the so-called CWFS(Cohesion Weakening Frictional Strengthening) model is known to predict brittle failure phenomenon reasonably well. The most typical rock types of Korean peninsula - granite and gneiss - were used for testing. Results of uniaxial compression tests showed that the crack initiation stress was about 41 % to 42% of the uniaxial compressive strength regardless of rock types, where as, the crack damage stress of granite was about 75%, and that of gneiss was about 97%. Through the damage-controlled test, strength parameters of each rock were obtained as a function of damage degree. After the peak, the crack damage stress and the maximum stress were decreased, The cohesion was decreased and the friction angle was increased with increase of rock damage. Before reaching the peak, the elastic modulus was slightly increased, while decreased after the peak. Poisson's ratio was increased as the damage of rock proceeds. Comparison of uniaxial compression tests and damage-controlled tests shows the crack initiation stress estimated from the damage-controlled test fluctuated within the range of crack initiation stress obtained from the uniaxial compression test; the crack damage stress was less than that estimated from the uniaxial compression test. In order to predict the critical depth that brittle failure occurs, numerical simulations using the CWFS model were performed for an example site. Material parameters obtained from the laboratory tests mentioned above were used for CWFS simulation. Comparison between the critical depth predicted from the numerical simulation using the CWFS model and that predicted by using the damage index proposed by Martin et al.(l999), showed that critical depth cannot be reasonably predicted by the currently used damage index except for circular tunnels. A modified damage index was proposed by the author which takes the shape of tunnels other than circular into account.
Kyeong-Tae Kim;Hyun-Jung Lee;Whee-Moon Kim;Won-Kyong Song
Korean Journal of Environment and Ecology
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v.37
no.4
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pp.289-301
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2023
Forests within watersheds are essential in maintaining ecosystems and are the central infrastructure for constructing an ecological network system. However, due to indiscriminate development projects carried out over past decades, forest fragmentation and land use changes have accelerated, and their original functions have been lost. Since a forest's structural pattern directly impacts ecological processes and functions in understanding forest ecosystems, identifying and analyzing change patterns is essential. Therefore, this study analyzed structural changes in the forest landscape according to the time-series land cover changes using the FRAGSTATS model for the dam watershed of the Geum River upstream. Land cover changes in the dam watershed of the Geum River upstream through land cover change detection showed an increase of 33.12 square kilometers (0.62%) of forests and 67.26 square kilometers (1.26%) of urbanized dry areas and a decrease of 148.25 square kilometers (2.79%) in agricultural areas from the 1980s to the 2010s. The results of no-sampling forest landscape analysis within the watershed indicated landscape percentage (PLAND), area-weighted proximity index (CONTIG_AM), average central area (CORE_MN), and adjacency index (PLADJ) increased, and the number of patches (NP), landscape shape index (LSI), and cohesion index (COHESION) decreased. Identification of structural change patterns through a moving window analysis showed the forest landscape in Sangju City, Gyeongsangbuk Province, Boeun County in Chungcheongbuk Province, and Jinan Province in Jeollabuk Province was relatively well preserved, but fragmentation was ongoing at the border between Okcheon County in Chungcheongbuk Province, Yeongdong and Geumsan Counties in Chungcheongnam Province, and the forest landscape in areas adjacent to Muju and Jangsu Counties in Jeollabuk Province. The results indicate that it is necessary to establish afforestation projects for fragmented areas when preparing a future regional forest management strategy. This study derived areas where fragmentation of forest landscapes is expected and the results may be used as basic data for assessing the health of watershed forests and establishing management plans.
A series of laboratory tests (physical and mechanical index and engineering design) were conducted on undisturbed granite soils of CW and RS weathering grades in Korea. From these testes it can be concluded that most of physical and mechanical index values are very sensitive to change in weathering grade from CW to RS. Engineering design tests indicate that the unconfined compressive strength and the shear strength parameters are significantly reduced and that the soil becomes ductile and plastic with increasing weathering and saturation. It was found that weathered granite soils have the special characteristics when water saturated: (i) they significantly lose their shear strength(especially cohesion) and unconfined compressive strength, (ii) they are fragile and their grains break down in water as observed in grain size analysis.
This study was conducted to construct a hypothetical model of depression in Korean adolescent women and validate the fit of the model to the empirical data. The data were collected from 345 high school girls in Seoul, from May 1 to June 30, 1998. The instruments were the Body Mass Index, Physical Satisfaction Scale, Family Adaptatibility and Cohesion Evaluation Scale III, Family Satisfaction Scale, CES-D and School Adptation Scale. The data were analyzed using descriptive statistics with the pc -SAS program. The Linear Structural Relationship(LISREL) modeling process was used to find the best fit model which would predict the causal relationships among the variables. The overall fit of the hypothetical model to the data was moderate [X$^2$=69.6(df=17, p=.000), GFI =0.95, AGFI=0.90, RMR=0.087, NNFI=0.86, NFI=0.90]. The predictable variables, especially menstrual symptoms, physical symptoms and family function, had a significant direct effect on depression. but school life adaptation did not have a significant direct effect. These variables explained 18.1% of the total variance.
Peatland is distributed in China widely, and organic matters in soil frequently induce problems in the construction and maintenance of highway engineering due to the high permeability and compressibility. In this paper, a selected site of Dali-Lijiang expressway was surveyed in China. A numerical model was built to predict the settlement of the foundation of the selected section employing the soft soil creep (SSC) model in PLAXIS 8.2. The model was subsequently verified by the result of field observance. Consequently, the parameters of 17 types of soils from different regions in China with organic contents varying from 1.1-74.9% were assigned to the numerical model to study the settlement characteristics. The calculated results showed that the duration of primary consolidation and proportion of primary settlement in the total settlement decreased with increasing organic content. Two empirical equations, for total consolidation settlement and secondary settlement, were proposed using multiple linear regression based on the calculated results from the numerical models. The analysis results of the significances of certain soil parameters demonstrated that the natural compression index, secondary compression index, cohesion and friction angle have significant linear relevance with both the total settlement and secondary settlement, while the initial coefficient of permeability exerts significant influence on the secondary settlement only.
Magazine of the Korean Society of Agricultural Engineers
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v.31
no.1
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pp.82-95
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1989
This study was carried out for the stability analysis of earth dam by the variation of compaction density. The test samples were taken from five kinds of soil used for banking material and the degree of compaction for this samples were chosen 100, 95, 90, 85, and 80 percent. The stability problems were analysed by the settlement and camber( extra banking) of dam, strength parameter and dam slope, and coefficient of permeability and seapage flow through dam body. The results of the stability analysis of earth dam are as follows. 1. The more the fine particle increases and lower the compaction degree becomes, the lower the preconsolidation load becomes but the compression index becomes higher. 2. Sixty to eighty percent of settlement of dam occurs during the construction period and the settlement ratio after completion of dam is inversly proportional to the degree of compaction. 3. The camber of dam has heigher value in condition that it has more fine particle(N) and heigher dam height(H) with the relation of H= e(aN-bH-e). 4. The cohesion(C) decreases in proportion to compaction degree(D) and fine particle(N) with the relation of C= aD+ bN-c, but the internal friction angle is almost constant regardless of change of degree of compaction. 5. In fine soil, strength parameter from triaxial compression test is smaller than that from direct shear test but, they are almost same in coarse soil regardless of the test method. 6. The safety factor of the dam slope generally decreases in proportion to cohesion and degree of compaction but, in case of coarse soil, it is less related to the degree of compaction and is mainly afected by internal friction angle. 7. Soil permeability(K) decreases by the increases of the degree of compaction and fine particle with relation of K=e(a-bl)-cN) 8. The more compaction thickness is, the less vertical permeability (Kv) is but the more h6rzontal permeability (KH) is, and ratio of Kv versus KH is largest in range from 85 to 90 percent of degree of corn paction. 9. With the compaction more than 85 percent and coefficient of permeability less than ${\alpha}$X 10-$^3$cm/sec, the earth dam is generally safe from the piping action.
Alzabeebee, Saif;Zuhaira, Ali Adel;Al-Hamd, Rwayda Kh. S.
Geomechanics and Engineering
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v.28
no.4
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pp.397-404
/
2022
Accurate prediction of the undrained shaft resistance is essential for robust design of bored piles in undrained condition. The undrained shaft resistance is calculated using the undrained adhesion factor multiplied by the undrained cohesion of the soil. However, the available correlations to predict the undrained adhesion factor have been developed using simple regression techniques and the accuracy of these correlations has not been thoroughly assessed in previous studies. The lack of the assessment of these correlations made it difficult for geotechnical engineers to select the most accurate correlation in routine designs. Furthermore, limited attempts have been made in previous studies to use advanced data mining techniques to develop simple and accurate correlation to predict the undrained adhesion factor. This research, therefore, has been conducted to fill these gaps in knowledge by developing novel and robust correlation to predict the undrained adhesion factor. The development of the new correlation has been conducted using the multi-objective evolutionary polynomial regression analysis. The new correlation outperformed the available empirical correlations, where the new correlation scored lower mean absolute error, mean square error, root mean square error and standard deviation of measured to predicted adhesion factor, and higher mean, a20-index and coefficient of correlation. The correlation also successfully showed the influence of the undrained cohesion and the effective stress on the adhesion factor. Hence, the new correlation enhances the design accuracy and can be used by practitioner geotechnical engineers to ensure optimized designs of bored piles in undrained conditions.
This study investigates the influence of nano-silica and basalt fiber content, curing duration, and freeze-thaw cycles on the static and dynamic properties of soil specimens. A comprehensive series of tests, including Unconfined Compressive Strength (UCS), static triaxial, and dynamic triaxial tests, were conducted. Additionally, scanning electron microscopy (SEM) analysis was employed to examine the microstructure of treated specimens. Results indicate that a combination of 1% fiber and 10% nano-silica yields optimal soil enhancement. The failure patterns of specimens varied significantly depending on the type of additive. Static triaxial tests revealed a notable reduction in the brittleness index (IB) with the inclusion of basalt fibers. Specimens containing 10% nano-silica and 1% fiber exhibited superior shear strength parameters and UCS. The highest cohesion and friction angle were obtained for treated specimens with 10% nano-silica and 1% fiber, 90 kPa and 37.8°, respectively. Furthermore, an increase in curing time led to a significant increase in UCS values for specimens containing nano-silica. Additionally, the addition of fiber resulted in a decrease in IB, while the addition of nano-silica led to an increase in IB. Increasing nano-silica content in stabilized specimens enhanced shear modulus while decreasing the damping ratio. Freeze-thaw cycles were found to decrease the cohesion of treated specimens based on the results of static triaxial tests. Specimens treated with 10% nano-silica and 1% fiber experienced a reduction in shear modulus and an increase in the damping ratio under freeze-thaw conditions. SEM analysis reveals dense microstructure in nano-silica stabilized specimens, enhanced adhesion of soil particles and fibers, and increased roughness on fiber surfaces.
In this work, Integral photography with variable focusing lens arrays is proposed. We fabricate two-dimensional liquid crystal lens arrays using cohesion of UV curable polymer and lithography. Applied voltage to the cell alters the effective refractive index of the liquid crystal layer and results in a change of the focal length. By adjusting the focal length, synchronized elemental image array for real or virtual mode is integrated in front of or behind the lens array.
It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.
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