• Explosives and Blasting
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• v.20 no.3
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• pp.59-71
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• 2002

The points of this design case are the planning and excavation method of a new double-tracked railroad tunnel which is approx. 11∼22 meters apart from existing single-tracked railroad tunnel. For the optimum excavation method some needs are required in design stage, such as the reduction of noise and vibration, public resentment, damage of buildings and construction costs. Hence the estimation and application of allowable noise and vibration criterion is important. The ground coefficient (K, n) of this site is determined by field trial blasting. The excavation method is chosen to satisfy the allowable noise and vibration criterion. In addition, in order to ensure the stability of existing single-tracked railroad tunnel, the instrumentation of maintenance level is accompanied during the construction stage. As a result of this design condition, central diaphragm excavation with line drilling and pre-large hole boring blasting is applied to the area within 15 meters apart from existing tunnel. And above 15 meters apart, pre-large hole boring blasting is designed.

• Explosives and Blasting
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• v.41 no.3
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• pp.26-37
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• 2023

In order to determine the amount of explosives that can minimize the vibration generated during tunnel construction using the blasting method, it is necessary to derive the blasting vibration coefficients, K and n, by analyzing the vibration records of trial blasting in the field or under similar conditions. In this study, we aimed to develop a technique that can derive reasonable K and n when trial blasting cannot be performed. To this end, we collected full-scale trial blast data and studied how to predict the blast vibration coefficient (K, n) according to the type of explosive, center cut blasting method, rock origin and type, and rock grade using deep learning (DL). In addition, the correction value between full-scale and borehole trial blasting results was calculated to compensate for the limitations of the borehole trial blasting results and to carry out a design that aligns more closely with reality. In this study, when comparing the available explosive amount according to the borehole trial blasting result equation, the predictions from deep learning (DL) exceed 50%, and the result with the correction value is similar to other blast vibration estimation equations or about 20% more, enabling more economical design.