• Title/Summary/Keyword: Depth of cover

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Site Characterization using Shear-Wave Velocities Inverted from Rayleigh-Wave Dispersion in Chuncheon, Korea (레일리파 분산을 역산하여 구한 횡파속도를 이용한 춘천시의 부지특성)

  • Jung, JinHoon;Kim, Ki Young
    • Geophysics and Geophysical Exploration
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    • v.17 no.1
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    • pp.1-10
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    • 2014
  • To reveal and classify site characteristics in densely populated areas in Chuncheon, Korea, Rayleigh-waves were recorded at 50 sites including four sites in the forest area using four 1-Hz velocity sensors and 24 4.5-Hz vertical geophones during the period of January 2011 to May 2013. Dispersion curves of the Rayleigh waves obtained by the extended spatial autocorrelation method were inverted to derive shear-wave velocity ($v_s$) models comprising 40 horizontal layers of 1-m thickness. Depths to weathered rocks ($D_b$), shear wave velocities of these basement rocks ($v_s^b$), average velocities of the overburden layer ($\bar{v}_s^s$), and the average velocity to a depth of 30 m ($v_s30$), were then derived from those models. The estimated values of $D_b$, $v_s^b$, $\bar{v}_s^s$, and $v_s30$ for 46 sites at lower altitudes were in the ranges of 5 to 29 m, 404 to 561 m/s, 208 to 375 ms/s, and 226 to 583 m/s, respectively. According to the Korean building code for seismic design, the estimated $v_s30$ indicates that the lower altitude areas in Chuncheon are classified as $S_C$ (very dense soil and soft rock) or $S_D$ (stiff soil). To determine adequate proxies for $v_s30$, we compared the computed values with land cover, lithology, topographic slope, and surface elevation at each of the measurement sites. Due to a weak correlation (r = 0.41) between $v_s30$ and elevation, the best proxy of them, applications of this proxy to Chuncheon of a relatively small area seem to be limited.

Effect of a frontal impermeable layer on the excess slurry pressure during the shield tunnelling in the saturated sand (포화 사질토에서 전방 차수층이 쉴드터널 초과 이수압에 미치는영향)

  • Lee, Yong-Jun;Lee, Sang-Duk
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.13 no.4
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    • pp.347-370
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    • 2011
  • Slurry type shield would be very effective for the tunnelling in a sandy ground, when the slurry pressure would be properly adjusted. Low slurry pressure could cause a tunnel face failure or a ground settlement in front of the tunnel face. Thus, the stability of tunnel face could be maintained by applying an excess slurry pressure that is larger than the active earth pressure. However, the slurry pressure should increase properly because an excessively high slurry pressure could cause the slurry flow out or the passive failure of the frontal ground. It is possible to apply the high slurry pressure without passive failure if a horizontal impermeable layer is located in the ground in front of the tunnel face, but its location, size, and effects are not clearly known yet. In this research, two-dimensional model tests were carried out in order to find out the effect of a horizontal impermeable layer for the slurry shield tunnelling in a saturated sandy ground. In tests slurry pressure was increased until the slurry flowed out of the ground surface or the ground fails. Location and dimension of the impermeable layer were varied. As results, the maximum and the excess slurry pressure in sandy ground were linearly proportional to the cover depth. Larger slurry pressure could be applied to increase the stability of the tunnel face when the impermeable layer was located in the ground above the crown in front of the tunnel face. The most effective length of the impermeable grouting layer was 1.0 ~ 1.5D, and the location was 1.0D above the crown level. The safety factor could be suggested as the ratio of the maximum slurry pressure to the active earth pressure at the tunnel face. It could also be suggested that the slurry pressure in the magnitude of 3.5 ~4.0 times larger than the active earth pressure at the initial tunnel face could be applied if the impermeable layer was constructed at the optimal location.

Ecological Changes of Insect-damaged Pinus densiflora Stands in the Southern Temperate Forest Zone of Korea (I) (솔잎혹파리 피해적송림(被害赤松林)의 생태학적(生態学的) 연구(研究) (I))

  • Yim, Kyong Bin;Lee, Kyong Jae;Kim, Yong Shik
    • Journal of Korean Society of Forest Science
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    • v.52 no.1
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    • pp.58-71
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    • 1981
  • Thecodiplosis japonesis is sweeping the Pinus densiflora forests from south-west to north-east direction, destroying almost all the aged large trees as well as even the young ones. The front line of infestation is moving slowly but ceaselessly norhwards as a long bottle front. Estimation is that more than 40 percent of the area of P. densiflora forest has been damaged already, however some individuals could escapes from the damage and contribute to restore the site to the previous vegetation composition. When the stands were attacked by this insect, the drastic openings of the upper story of tree canopy formed by exclusively P. densiflora are usually resulted and some environmental factors such as light, temperature, litter accumulation, soil moisture and offers were naturally modified. With these changes after insect invasion, as the time passes, phytosociologic changes of the vegetation are gradually proceeding. If we select the forest according to four categories concerning the history of the insect outbreak, namely, non-attacked (healthy forest), recently damaged (the outbreak occured about 1-2 years ago), severely damaged (occured 5-6 years ago), damage prolonged (occured 10 years ago) and restored (occured about 20 years ago), any directional changes of vegetation composition could be traced these in line with four progressive stages. To elucidate these changes, three survey districts; (1) "Gongju" where the damage was severe and it was outbroken in 1977, (2) "Buyeo" where damage prolonged and (3) "Gochang" as restored, were set, (See Tab. 1). All these were located in the south temperate forest zone which was delimited mainly due to the temporature factor and generally accepted without any opposition at present. In view of temperature, the amount and distribution of precipitation and various soil factor, the overall homogeneity of environmental conditions between survey districts might be accepted. However this did not mean that small changes of edaphic and topographic conditions and microclimates can induce any alteration of vegetation patterns. Again four survey plots were set in each district and inter plot distance was 3 to 4 km. And again four subplots were set within a survey plot. The size of a subplot was $10m{\times}10m$ for woody vegetation and $5m{\times}5m$ for ground cover vegetation which was less than 2 m high. The nested quadrat method was adopted. In sampling survey plots, the followings were taken into account: (1) Natural growth having more than 80 percent of crown density of upper canopy and more than 5 hectares of area. (2) Was not affected by both natural and artificial disturbances such as fire and thinning operation for the past three decades. (3) Lower than 500 m of altitude (4) Less than 20 degrees of slope, and (5) Northerly sited aspect. An intensive vegetation survey was undertaken during the summer of 1980. The vegetation was devided into 3 categories for sampling; the upper layer (dominated mainly by the pine trees), the middle layer composed by oak species and other broad-leaved trees as well as the pine, and the ground layer or the lower layer (shrubby form of woody plants). In this study our survey was concentrated on woody species only. For the vegetation analysis, calculated were values of intensity, frequency, covers, relative importance, species diversity, dominance and similarity and dissimilasity index when importance values were calculated, different relative weights as score were arbitrarily given to each layer, i.e., 3 points for the upper layer, 2 for the middle layer and 1 for the ground layer. Then the formula becomes as follows; $$R.I.V.=\frac{3(IV\;upper\;L.)+2(IV.\;middle\;L.)+1(IV.\;ground\;L.)}{6}$$ The values of Similarity Index were calculated on the basis of the Relative Importance Value of trees (sum of relative density, frequency and cover). The formula used is; $$S.I.=\frac{2C}{S_1+S_2}{\times}100=\frac{2C}{100+100}{\times}100=C(%)$$ Where: C = The sum of the lower of the two quantitative values for species shared by the two communities. $S_1$ = The sum of all values for the first community. $S_2$ = The sum of all values for the second community. In Tab. 3, the species composition of each plot by layer and by district is presented. Without exception, the species formed the upper layer of stands was Pinus densiflora. As seen from the table, the relative cover (%), density (number of tree per $500m^2$), the range of height and diameter at brest height and cone bearing tendency were given. For the middle layer, Quercus spp. (Q. aliena, serrata, mongolica, accutissina and variabilis) and Pinus densiflora were dominating ones. Genus Rhodedendron and Lespedeza were abundant in ground vegetation, but some oaks were involved also. (1) Gongju district The total of woody species appeared in this district was 26 and relative importance value of Pinus densiflora for the upper layer was 79.1%, but in the middle layer, the R.I.V. for Quercus acctissima, Pinus densiflora, and Quercus aliena, were 22.8%, 18.7% and 10.0%, respectively, and in ground vegetation Q. mongolica 17.0%, Q. serrata 16.8% Corylus heterophylla 11.8%, and Q. dentata 11.3% in order. (2) Buyeo district. The number of species enumerated in this district was 36 and the R.I.V. of Pinus densiflora for the uppper layer was 100%. In the middle layer, the R.I.V. of Q. variabilis and Q. serrata were 8.6% and 8.5% respectively. In the ground vegetative 24 species were counted which had no more than 5% of R.I.V. The mean R.I.V. of P.densiflora ( totaling three layers ) and averaging four plots was 57.7% in contrast to 46.9% for Gongju district. (3) Gochang-district The total number of woody species was 23 and the mean R.I.V. of Pinus densiflora was 66.0% showing greater value than those for two former districts. The next high value was 6.5% for Q. serrata. As the time passes since insect outbreak, the mean R.I.V. of P. densiflora increased as the following order, 46.9%, 57.7% and 66%. This implies that P. densiflora was getting back to its original dominat state again. The pooled importance of Genus Quercus was decreasing with the increase of that for Pinus densiflora. This trend was contradict to the facts which were surveyed at Kyonggi-do area (the central temperate forest zone) reported previously (Yim et al, 1980). Among Genus Quercus, Quercus acutissina, warm-loving species, was more abundant in the southern temperature zone to which the present research is concerned than the central temperate zone. But vice-versa was true with Q. mongolica, a cold-loving one. The species which are not common between the present survey and the previous report are Corpinus cordata, Beltala davurica, Wisturia floribunda, Weigela subsessilis, Gleditsia japonica var. koraiensis, Acer pseudosieboldianum, Euonymus japonica var. macrophylla, Ribes mandshuricum, Pyrus calleryana var. faruiei, Tilia amurensis and Pyrus pyrifolia. In Figure 4 and Table 5, Maximum species diversity (maximum H'), Species diversity (H') and Eveness (J') were presented. The Similarity indices between districts were shown in Tab. 5. Seeing Fig. 6, showing two-dimensional ordination of polts on the basis of X and Y coordinates, Ai plots aggregate at the left site, Bi plots at lower site, and Ci plots at upper-right site. The increasing and decreasing patterns as to Relative Density and Relative Importance Value by genus or species were given in Fig. 7. Some of the patterns presented here are not consistent with the previously reported ones (Yim, et al, 1980). The present authors would like to attribute this fact that two distinct types of the insect attack, one is the short war type occuring in the south temperate forest zone, which means that insect attack went for a few years only, the other one is a long-drawn was type observed at the temperate forest zone in which the insect damage went on continuously for several years. These different behaviours of infestation might have resulted the different ways of vegetational change. Analysing the similarity indices between districts, the very convincing results come out that the value of dissimilarity index between A and B was 30%, 27% between B and C and 35% between A and C (Table 6). The range of similarity index was obtained from the calculation of every possible combinations of plots between two districts. Longer time isolation between communities has brought the higher value of dissimilarity index. The main components of ground vegetation, 10 to 20 years after insect outbreak, become to be consisted of mainly Genus Lespedeza and Rhododendron. Genus Quercus which relate to the top dorminant state for a while after insect attack was giving its place to Pinus densiflora. It was implied that, provided that the soil fertility, soil moisture and soil depth were good enough, Genus Quercuss had never been so easily taken ever by the resistant speeies like Pinus densiflora which forms the edaphic climax at vast areas of forest land. Usually they refer Quercus to the representative component of the undisturbed natural forest in the central part of this country.

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Memory Organization for a Fuzzy Controller.

  • Jee, K.D.S.;Poluzzi, R.;Russo, B.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1041-1043
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    • 1993
  • Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)+dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].

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Efficacy and Accuracy of Patient Specific Customize Bolus Using a 3-Dimensional Printer for Electron Beam Therapy (전자선 빔 치료 시 삼차원프린터를 이용하여 제작한 환자맞춤형 볼루스의 유용성 및 선량 정확도 평가)

  • Choi, Woo Keun;Chun, Jun Chul;Ju, Sang Gyu;Min, Byung Jun;Park, Su Yeon;Nam, Hee Rim;Hong, Chae-Seon;Kim, MinKyu;Koo, Bum Yong;Lim, Do Hoon
    • Progress in Medical Physics
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    • v.27 no.2
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    • pp.64-71
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    • 2016
  • We develop a manufacture procedure for the production of a patient specific customized bolus (PSCB) using a 3D printer (3DP). The dosimetric accuracy of the 3D-PSCB is evaluated for electron beam therapy. In order to cover the required planning target volume (PTV), we select the proper electron beam energy and the field size through initial dose calculation using a treatment planning system. The PSCB is delineated based on the initial dose distribution. The dose calculation is repeated after applying the PSCB. We iteratively fine-tune the PSCB shape until the plan quality is sufficient to meet the required clinical criteria. Then the contour data of the PSCB is transferred to an in-house conversion software through the DICOMRT protocol. This contour data is converted into the 3DP data format, STereoLithography data format and then printed using a 3DP. Two virtual patients, having concave and convex shapes, were generated with a virtual PTV and an organ at risk (OAR). Then, two corresponding electron treatment plans with and without a PSCB were generated to evaluate the dosimetric effect of the PSCB. The dosimetric characteristics and dose volume histograms for the PTV and OAR are compared in both plans. Film dosimetry is performed to verify the dosimetric accuracy of the 3D-PSCB. The calculated planar dose distribution is compared to that measured using film dosimetry taken from the beam central axis. We compare the percent depth dose curve and gamma analysis (the dose difference is 3%, and the distance to agreement is 3 mm) results. No significant difference in the PTV dose is observed in the plan with the PSCB compared to that without the PSCB. The maximum, minimum, and mean doses of the OAR in the plan with the PSCB were significantly reduced by 9.7%, 36.6%, and 28.3%, respectively, compared to those in the plan without the PSCB. By applying the PSCB, the OAR volumes receiving 90% and 80% of the prescribed dose were reduced from $14.40cm^3$ to $0.1cm^3$ and from $42.6cm^3$ to $3.7cm^3$, respectively, in comparison to that without using the PSCB. The gamma pass rates of the concave and convex plans were 95% and 98%, respectively. A new procedure of the fabrication of a PSCB is developed using a 3DP. We confirm the usefulness and dosimetric accuracy of the 3D-PSCB for the clinical use. Thus, rapidly advancing 3DP technology is able to ease and expand clinical implementation of the PSCB.