Tunnel and Underground Space (터널과지하공간)

Korean Society for Rock Mechanics and Rock Engineering (한국암반공학회)
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Development of an Optimized Prediction System of Round Trip Occurrence using Genetic Algorithm

유전자알고리즘을 활용한 최적화된 라운드트립 발생 예측 시스템 개발

  • Received : 2015.12.10
  • Accepted : 2015.12.24
  • Published : 2015.12.31
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Abstract

Round trip activity occurs discretely due to the abrasion of drill bit in the deep drilling project. Round trip has great impact on the drilling performance because it takes more time to change a drill bit as the depth goes deeper. Therefore, a reliable prediction technology of the round trip should be secured for feasibility analysis and effective management of the drilling project. Lee et al. (2013) developed the TOSA (round trip occurrence simulation algorithm) which can analyze the depth and timing of round trip occurrence at each abrasion state of bit. However, TOSA has weakness that it takes long time for simulation because the number of simulation increase exponentially as increasing the number of simulation section. This study developed the TOSA based round trip performance prediction module using genetic algorithm for simulating in a short time and verified simulation results.

대심도 시추공사는 시추비트의 마모로 인해 발생하는 라운드트립(round trip)이 이산적으로 발생된다. 라운드트립은 심도가 깊어질수록 교체에 소요되는 시간이 증가하여 공사 성능에 많은 영향을 끼친다. 따라서 시추 프로젝트의 타당성분석 및 관리 효율화를 위해서는 라운드트립의 신뢰적인 예측기술이 확보되어야 한다. 이승수 등(2013)은 TOSA(round trip occurrence simulation algorithm)을 제시하여 비트의 마모단계별 라운드트립이 발생되는 깊이와 시점을 분석할 수 있는 알고리즘을 제시하였다. 그러나 시뮬레이션 구간의 수가 증가할수록 시뮬레이션 횟수가 기하급수적으로 증가하여 연산시간이 오래 걸린다는 단점을 가지고 있다. 본 연구에서는 유전자 알고리즘을 활용하여 단 시간에 TOSA를 통한 최적화된 라운드트립의 발생을 예측할 수 있는 모듈을 개발하고 검증한 내용에 대하여 소개한다.

Keywords

References

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