• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.4
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• pp.545-560
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• 2019

During EPB TBM tunnelling, an appropriate application of additives such as foam and polymer is an essential factor to secure the stability of TBM as well as tunnelling performance. From the '90s, there have been many studies on the optimal injection of additives worldwidely contrary to the domestic situation. Therefore, in this paper, the foam, which is widely adopted for soil conditioning, was selected as an additive in order to investigate the effect of foam injection on TBM performance through a series of laboratory excavation tests. The excavation experiments were carried out on artificial sandy soil specimens with consideration of the variance of FIR (Foam Injection Ratio), FER (Foam Expansion Ratio) and $C_f$ (Surfactant Concentration), which indicate the amount and quality of the foam. During the tests, torque values were measured, and the workability of conditioned soil was evaluated by comparing the slump values of muck after each experiment. In addition, a weight loss of the replaceable aluminum cutter bits installed on the blade was measured to estimate the degree of abrasion. Finally, the foam injection ratio for the optimal TBM excavation for the typical soil specimen was determined by comparing the measured torque, slump value and abrasion. Note that the foam injection conditions satisfying the appropriate level of machine load, mechanical wear and workability are essential in the EPB TBM operational design.

• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.333-343
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• 2015

This research aims at identifying the goshawk's possible and replaceable breeding ground by using the MaxEnt prediction model which has so far been insufficiently used in Korea, and providing evidence to expand possible protection areas for the goshawk's breeding for the future. The field research identified 10 goshawk's nests, and 23 appearance points confirmed during the 3rd round of environmental research were used for analysis. 4 geomorphic, 3 environmental, 7 distance, and 9 weather factors were used as model variables. The final environmental variables were selected through non-parametric verification between appearance and non-appearance coordinates identified by random sampling. The final predictive model (MaxEnt) was structured using 10 factors related to breeding ground and 7 factors related to appearance area selected by statistics verification. According to the results of the study, the factor that affected breeding point structure model the most was temperature seasonality, followed by distance from mixforest, density-class on the forest map and relief energy. The factor that affected appearance point structure model the most was temperature seasonality, followed by distance from rivers and ponds, distance from agricultural land and gradient. The nature of the goshawk's breeding environment and habit to breed inside forests were reflected in this modeling that targets breeding points. The northern central area which is about $189.5 km^2$(2.55 %) is expected to be suitable breeding ground. Large cities such as Cheongju and Chungju are located in the southern part of Chungcheongbuk-do whereas the northern part of Chungcheongbuk-do has evenly distributed forests and farmlands, which helps goshawks have a scope of influence and food source to breed. Appearance point modeling predicted an area of $3,071 km^2$(41.38 %) showing a wider ranging habitat than that of the breeding point modeling due to some limitations such as limited moving observation and non-consideration of seasonal changes. When targeting the breeding points, a specific predictive area can be deduced but it is difficult to check the points of nests and it is impossible to reflect the goshawk's behavioral area. On the other hand, when targeting appearance points, a wider ranging area can be covered but it is less accurate compared to predictive breeding point since simple movements and constant use status are not reflected. However, with these results, the goshawk's habitat can be predicted with reasonable accuracy. In particular, it is necessary to apply precise predictive breeding area data based on habitat modeling results when enforcing an environmental evaluation or establishing a development plan.