Monopiles, used as one foundation option for offshore wind turbines, are usually subjected to great cyclic lateral loads due to wind and wave. In this study, model pile load tests were performed using calibration chamber and three model piles with different pile lengths in order to investigate the behavior of laterally cyclic loaded piles driven into sand. Model test results show that the first loading cycle generates a bigger displacement than the following ones, and the permanent displacement of piles by one loading cycle decreases with increasing the number of cycles. 1-way cyclic loading causes the permanent displacement in the same direction as cyclic loading, whereas 2-way cyclic loading causes the permanent displacement in the reverse direction of initial loading. It is also observed that the permanent displacement of piles due to cyclic lateral loads increases with decreasing relative density of soil and with increasing the magnitude of cyclic loads. However, it is insensitive to the earth pressure ratio of soil and embedded pile length. In addition, based on the model pile load test results, equations for estimation of the permanent lateral displacement and rotation angle of piles due to 1-way cyclic lateral loads are proposed.
KSCE Journal of Civil and Environmental Engineering Research
/
v.28
no.3C
/
pp.179-186
/
2008
Pressuremeter test estimates the deformational properties of soil from the relationship between applied pressure and the displacement of cavity wall. It is general to utilize the reloading curve for the estimation of deformational properties of soil because the initial loading curve can be affected by the disturbance caused by boring. On the other hand, the instrumental resolution or the variation of measured data makes it hard to estimate the maximum shear modulus from pressuremeter test results. This study suggested the methodology estimating the maximum shear modulus from pressuremeter test directly, based on the curve fitting of reloading curve. In addition, the difference was taken into account between the stress state around the probe in reloading and that of the in-situ state. Pressuremeter tests were conducted for 15 cases using a large calibration chamber, together with a number of reference tests. The maximum shear moduli taken from suggested method were compared with those from empirical correlation and bender element test.
Journal of the Korea institute for structural maintenance and inspection
/
v.28
no.3
/
pp.1-9
/
2024
This study proposes a multi-scale template matching technique with image pyramids (TMI) to measure structural dynamic displacement using a vision sensor under atmospheric turbulence conditions and evaluates its displacement measurement performance. To evaluate displacement measurement performance according to distance, the three-story shear structure was designed, and an FHD camera was prepared to measure structural response. The initial measurement distance was set at 10m, and increased with an increment of 10m up to 40m. The atmospheric disturbance was generated using a heating plate under indoor illuminance condition, and the image was distorted by the optical turbulence. Through preliminary experiments, the feasibility of displacement measurement of the feature point-based displacement measurement method and the proposed method during atmospheric disturbances were compared and verified, and the verification results showed a low measurement error rate of the proposed method. As a result of evaluating displacement measurement performance in an atmospheric disturbance environment, there was no significant difference in displacement measurement performance for TMI using an artificial target depending on the presence or absence of atmospheric disturbance. However, when natural targets were used, RMSE increased significantly at shooting distances of 20 m or more, showing the operating limitations of the proposed technique. This indicates that the resolution of the natural target decreases as the shooting distance increases, and image distortion due to atmospheric disturbance causes errors in template image estimation, resulting in a high displacement measurement error.
Cho, Wonhee;Lim, Wontaek;Kim, Eun-Sook;Lim, Jong-Hwan;Ko, Dongwook W.
Korean Journal of Agricultural and Forest Meteorology
/
v.22
no.3
/
pp.215-231
/
2020
Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R2) and root mean square error (RMSE). The final model performed very well, with 0. 98 R2 and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.
1. Purpose Rural tourism is made by individuals with different characteristics, needs and wants. It is important to have information on the characteristics and preferences of the consumers of the different types of existing rural accommodation. The stud aims to identify the determinants of consumer preference by type of accommodations. 2. Methodology 2.1 Sample Data were collected from 1000 people by telephone survey with three-stage stratified random sampling in seven metropolitan areas in Korea. Respondents were chosen by sampling internal on telephone book published in 2006. We surveyed from four to ten-thirty 0'clock afternoon so as to systematic sampling considering respondents' life cycle. 2.2 Two-step cluster Analysis Our study is accomplished through the use of a two-step cluster method to classify the accommodation in a reduced number of groups, so that each group constitutes a type. This method had been suggested as appropriate in clustering large data sets with mixed attributes. The method is based on a distance measure that enables data with both continuous and categorical attributes to be clustered. This is derived from a probabilistic model in which the distance between two clusters in equivalent to the decrease in log-likelihood function as a result of merging. 2.3 Multinomial Logit Analysis The estimation of a Multionmial Logit model determines the characteristics of tourist who is most likely to opt for each type of accommodation. The Multinomial Logit model constitutes an appropriate framework to explore and explain choice process where the choice set consists of more than two alternatives. Due to its ease and quick estimation of parameters, the Multinomial Logit model has been used for many empirical studies of choice in tourism. 3. Findings The auto-clustering algorithm indicated that a five-cluster solution was the best model, because it minimized the BIC value and the change in them between adjacent numbers of clusters. The accommodation establishments can be classified into five types: Traditional House, Typical Farmhouse, Farmstay house for group Tour, Log Cabin for Family, and Log Cabin for Individuals. Group 1 (Traditional House) includes mainly the large accommodation establishments, i.e. those with ondoll style room providing meals and one shower room on family tourist, of original construction style house. Group 2 (Typical Farmhouse) encompasses accommodation establishments of Ondoll rooms and each bathroom providing meals. It includes, in other words, the tourist accommodations Known as "rural houses." Group 3 (Farmstay House for Group) has accommodation establishments of Ondoll rooms not providing meals and self cooking facilities, large room size over five persons. Group 4 (Log Cabin for Family) includes mainly the popular accommodation establishments, i.e. those with Ondoll style room with on shower room on family tourist, of western styled log house. While the accommodations in this group are not defined as regards type of construction, the group does include all the original Korean style construction, Finally, group 5 (Log Cabin for Individuals)includes those accommodations that are bedroom western styled wooden house with each bathroom. First Multinomial Logit model is estimated including all the explicative variables considered and taking accommodation group 2 as base alternative. The results show that the variables and the estimated values of the parameters for the model giving the probability of each of the five different types of accommodation available in rural tourism village in Korea, according to the socio-economic and trip related characteristics of the individuals. An initial observation of the analysis reveals that none of variables income, the number of journey, distance, and residential style of house is explicative in the choice of rural accommodation. The age and accompany variables are significant for accommodation establishment of group 1. The education and rural residential experience variables are significant for accommodation establishment of groups 4 and 5. The expenditure and marital status variables are significant for accommodation establishment of group 4. The gender and occupation variable are significant for accommodation establishment of group 3. The loyalty variable is significant for accommodation establishment of groups 3 and 4. The study indicates that significant differences exist among the individuals who choose each type of accommodation at a destination. From this investigation is evident that several profiles of tourists can be attracted by a rural destination according to the types of existing accommodations at this destination. Besides, the tourist profiles may be used as the basis for investment policy and promotion for each type of accommodation, making use in each case of the variables that indicate a greater likelihood of influencing the tourist choice of accommodation.
Park, Myung-Sook;Jung, Hahn Chul;Lee, Seonju;Ahn, Jae-Hyun;Bae, Sujung;Choi, Jong-Kuk
Korean Journal of Remote Sensing
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v.37
no.5_2
/
pp.1281-1293
/
2021
The recent launch of the GOCI-II enables South Korea to have the world's first capability in deriving the ocean color data at geostationary satellite orbit for about 20 years. It is necessary to develop a consistent long-term ocean color time-series spanning GOCI to GOCI-II mission and improve the accuracy through validation using in situ data. To assess the GOCI-II's early mission performance, the objective of this study is to compare the GOCI-II Chlorophyll-a concentration (Chl-a), Colored Dissolved Organic Matter (CDOM), and remote sensing reflectances (Rrs) through comparison with the GOCI data. Overall, the distribution of GOCI-II Chl-a corresponds with that of the GOCI over the Yellow Sea, Korea Strait, and the Ulleung Basin. In particular, a smaller RMSE value (0.07) between GOCI and GOCI-II over the summer Ulleung Basin confirms the GOCI-II data's reliability. However, despite the excellent correlation, the GOCI-II tends to overestimate Chl-a than the GOCI over the Yellow Sea and Korea Strait. The similar over-estimation bias of the GOCI-II is also notable in CDOM. Whereas no significant bias or error is found for Rrs at 490 nm and 550 nm (RMSE~0), the underestimation of Rrs at 443 nm contributes to the overestimation of GOCI-II Chl-a and CDOM over the Yellow Sea and the Korea Strait. Also, we show over-estimation of GOCI-II Rrs at 660 nm relative to GOCI to cause a possible bias in Total suspended sediment. In conclusion, this study confirms the initial reliability of the GOCI-II ocean color products, and upcoming update of GOCI-II radiometric calibration will lessen the inconsistency between GOCI and GOCI-II ocean color products.
Journal of Korean Society of Coastal and Ocean Engineers
/
v.34
no.2
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pp.37-45
/
2022
A simplified model using the lifetime distribution has been presented to estimate the Mean Residual Life (MRL) of rubble-mound breakwaters, which is not like a stochastic process model based on time-dependent history data to the cumulative damage progress of rubble-mound breakwaters. The parameters involved in the lifetime distribution can be easily estimated by using the upper and lower limits of lifetime and their likelihood that made a judgement by several experts taking account of the initial design lifetime, the past sequences of loads, and others. The simplified model presented in this paper has been applied to the rubble-mound breakwater with TTP armor layer. Wiener Process (WP)-based stochastic model also has been applied together with Monte-Carlo Simulation (MCS) technique to the breakwater of the same condition having time-dependent cumulative damage to TTP armor layer. From the comparison of lifetime distribution obtained from each models including Mean Time To Failure (MTTF), it has found that the lifetime distributions of rubble-mound breakwater can be very satisfactorily fitted by log-normal distribution for all types of cumulative damage progresses, such as exponential, linear, and logarithmic deterioration which are feasible in the real situations. Finally, the MRL of rubble-mound breakwaters estimated by the simplified model presented in this paper have been compared with those by WP stochastic process. It can be shown that results of the presented simplified model have been identical with those of WP stochastic process until any ages in the range of MTT F regardless of the deterioration types. However, a little of differences have been seen at the ages in the neighborhood of MTTF, specially, for the linear and logarithmic deterioration of cumulative damages. For the accurate estimation of MRL of harbor structures, it may be desirable that the stochastic processes should be used to consider properly time-dependent uncertainties of damage deterioration. Nevertheless, the simplified model presented in this paper can be useful in the building of the MRL-based preventive maintenance planning for several kinds of harbor structures, because of which is not needed time-dependent history data about the damage deterioration of structures as mentioned above.
For the calculation of population parameter and estimation of recruitment of a fish population, an application of multiple regression method was used with some statistical inferences. Then, the differences between the calculated values and the true parameters were discussed. In addition, this method criticized by applying it to the statistical data of a population of bigeye tuna, Thunnus obesus of the Indian Ocean. The method was also applied to the available data of a population of Pacific saury, Cololabis saira, to estimate its recuitments. A stock at t year and t+1 year is, $N_{0,\;t+1}=N_{0,\;t}(1-m_t)-C_t+R_{t+1}$ where $N_0$ is the initial number of fish in a given year; C, number o: fish caught; R, number of recruitment; and M, rate of natural mortality. The foregoing equation is $$\phi_{t+1}=\frac{(1-\varrho^{-z}{t+1})Z_t}{(1-\varrho^{-z}t)Z_{t+1}}-\frac{1-\varrho^{-z}t+1}{Z_{t+1}}\phi_t-a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}C_t+a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}R_{t+1}......(1)$$ where $\phi$ is CPUE; a', CPUE $(\phi)$ to average stock $(\bar{N})$ in number; Z, total mortality coefficient; and M, natural mortality coefficient. In the equation (1) , the term $(1-\varrho^{-z}t+1)/Z_{t+1}$s almost constant to the variation of effort (X) there fore coefficients $\phi$ and $C_t$, can be calculated, when R is a constant, by applying the method of multiple regression, where $\phi_{t+1}$ is a dependent variable; $\phi_t$ and $C_t$ are independent variables. The values of Mand a' are calculated from the coefficients of $\phi_t$ and $C_t$; and total mortality coefficient (Z), where Z is a'X+M. By substituting M, a', $Z_t$, and $Z_{t+1}$ to the equation (1) recruitment $(R_{t+1})$ can be calculated. In this precess $\phi$ can be substituted by index of stock in number (N'). This operational procedures of the method of multiple regression can be applicable to the data which satisfy the above assumptions, even though the data were collected from any chosen year with similar recruitments, though it were not collected from the consecutive years. Under the condition of varying effort the data with such variation can be treated effectively by this method. The calculated values of M and a' include some deviation from the population parameters. Therefore, the estimated recruitment (R) is a relative value instead of all absolute one. This method of multiple regression is also applicable to the stock density and yield in weight instead of in number. For the data of the bigeye tuna of the Indian Ocean, the values of estimated recruitment (R) calculated from the parameter which is obtained by the present multiple regression method is proportional with an identical fluctuation pattern to the values of those derived from the parameters M and a', which were calculated by Suda (1970) for the same data. Estimated recruitments of Pacific saury of the eastern coast of Korea were calculated by the present multiple regression method. Not only spring recruitment $(1965\~1974)$ but also fall recruitment $(1964\~1973)$ was found to fluctuate in accordance with the fluctuations of stock densities (CPUE) of the same spring and fall, respectively.
This study was carried out to estimate the effects of breed and environment such as sex, test station, test year, test season, parity, initial and final weight on average daily gain, age at 90kg, backfat thickness, feed efficiency, lean percent and selection index on the basis of the performance data collected from 25,790 pigs of Duroc, Yorkshire and Landrace breeds which were performance-tested at the Korea Swine Testing Station from 1991 to 2002. The results obtained in the study are summarized as follows; 1. The means of the major economic traits were estimated as 959.95${\pm}$0.699g for average daily gain, 138.36${\pm}$0.072days for age at 90kg, 1.41${\pm}$0.001cm for backfat thickness, 2.33${\pm}$0.001 for feed efficiency, 56.71${\pm}$0.018% for lean percent and 221.65${\pm}$0.113 for selection index. 2. The effect of breed was statistically significant for all studied traits. Briefly, Duroc showed the best performance for the average daily gain and age at 90kg. Landrace had the best performances for the backfat thickness and lean meat percent. In feed efficiency and selection index, Yorkshire had a better score than other breeds. 3. The least-squares means of female and male for the traits studied were 923.05${\pm}$1.289g and 974.53${\pm}$0.856g for average daily gain, 139.74${\pm}$0.145days and 137.21${\pm}$0.097days for age at 90kg, 1.49${\pm}$0.002cm and 1.39${\pm}$0.002cm for backfat thickness, 2.43${\pm}$0.002 and 2.28${\pm}$0.002 for feed efficiency, 56.43${\pm}$0.034% and 56.81${\pm}$0.023% for lean percent and 211.37${\pm}$0.194 and 224.61${\pm}$0.129 for selection index. Therefore, males were superior to females for all traits examined. 4. The effect of test station was statistically significant for all traits except for selection index. Performances for age at 90kg, backfat thickness, feed efficiency and lean meat percent collected from Test station 2 were higher than those from Test station 1. However, Test station 1 showed better average daily gain. 5. The initial weight and final weight included as a covariate in this study had a significant influence on average daily gain, age at 90kg, backfat thickness, feed efficiency and selection index. From the absolute values of the estimated regression coefficients, it was inferred that the final weight had greater effect for the investigated traits than the initial weight.
Park, Kyoung-Je;Yoon, Hye-Young;Chun, Se-Jin;Lee, Ho-Sa;Lee, Dong-Hun;Jahng, Deokjin;Lee, Kyu-Ho
Korean Journal of Microbiology
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v.34
no.3
/
pp.154-161
/
1998
To investigate whether the introduced genetic marker is useful to detect the survivalship and activity of the natural bacteria under the stressed conditions, one Gram-negative isolate, KP964 was transformed to the luminous phenotype by transferring luxAB gene. Under the starvation-stress this luminous bacterial culturability (determined by colony-forming-units [CFU] on agar plate) decreased rapidly below the detection limit by 37 days, while its total cell number (determined by AODC) remained almost the same as its initial inocular size. At that time period, the viable cell number was estimated to be 1400 times higher than its CFU number. The bioiuminescence (determined by relative light units [RLU]) produced under the same condition was also monitored and found to decrease more rapidly than the culturability by 5-fold. Under the other stresses, e.g., osmotic shocks, acid shock, and exposure to toxic chemicals, this bacterial strain did not show the reliable correlation between CFU and RLU. These results might not suggest the direct estimation of bioiuminescence from the stressed bacteria be an index of both the survivalship and its activity. However, when the stressed bacterial cells were incubated under the favorable condition by relieving from the existing stress, the potential bioiuminescence (the lag periods before the increase of bioiuminescence, the increase rates of bioiuminescence, and the maximal levels of bioiuminescence) was shown to be highly dependent upon the strengths of the stresses exposed to the bacterial cells. Therefore, analysis of the potential bioiuminescence from the stressed bacteria revealed good relationships with survival as well as activity.
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