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Particle-Mixing Simulations Using DEM and Comparison of the Performance of Mixing Indices

DEM을 이용한 입자 혼합 시뮬레이션과 혼합지수들의 성능 비교

  • 조미경 (동명대학교 게임공학과)
  • Received : 2016.09.23
  • Accepted : 2016.12.22
  • Published : 2017.02.01

Abstract

Mixing of molecular grains having different characteristics is very important in many industries such as the food and pharmaceutical industries. With the development of computer simulations, it is common practice to find the optimal mixing conditions through a simulation before the actual mixing task to estimate the proper level of mixing. Accordingly, there has been an increasing need for a mixing index to measure the mix of particles in the simulation process. Mixing indices, which have been widely used so far, can largely be classified into two types: first is the statistical-based mixing index, which is prepared using the sampling method, and the second is the mixing index that is prepared using all the particles. In this paper, we calculated mixing indices in different ways for the data in the course of mixing the particles using the DEM simulation. Additionally, we compared the performance, advantages, and disadvantages of each mixing index. Therefore, I propose a standard that can be used to select an appropriate mixing index.

식품, 약학 분야 등 많은 산업 분야에서 다른 특징을 가지는 분자 알갱이들을 잘 혼합하는 것은 중요한 작업이다. 컴퓨터 시뮬레이션의 발달로 적정 수준의 혼합 상태를 얻기 위해 먼저 시뮬레이션을 통한 최적의 혼합 조건들을 찾는 작업이 보편화되고 있다. 이에 따라 시뮬레이션 과정에서 혼합 상태를 측정할 수 있는 혼합 지수에 대한 필요성이 증가하고 있다. 현재까지 많이 사용되는 혼합 지수는 두 가지 종류로 분류되는데 첫째는 샘플링을 통한 통계적 기반의 방법이고 두 번째는 전체 입자들을 모두 사용하여 혼합 지수를 계산하는 방법이다. 본 논문에서는 DEM 시뮬레이션으로 입자들을 혼합하는 과정에서 획득한 데이터에 대해 다양한 혼합 지수들을 계산하여 각 혼합 지수들의 성능과 장단점을 비교 분석하였다. 이로써 적절한 혼합지수를 선택하여 사용할 수 있는 실험적 정보를 제시하고자 한다.

Keywords

References

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