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La, Mg 이온교환 ZSM-5 촉매의 제조와 촉매 산강도에 따른 MTO 반응 활성의 검토
김한일,황종현,정태환,정석진 경희대학교 산학협력기술연구원 1997 산학협력기술연구논문집 Vol.3 No.-
The MTO(methanol to olefin) process that aims at the production of olefins from methanol has attracted research interest because of its possiblity as another source of raw material in petrochemical industries. However its reaction path is not only ceased at the point of olefin production but also much amount of by products such as paraffins and aromatics that accelerate carbon deposit are produced. Thus the catalyst deactivation is rapidly progressed. In order to maximize the selectivity from methanol to olefin, alkylation and aromatization should be excluded from reaction path through catalyst and process variables. In this viewpoint, as a solution of the former problem, various metals were substituted on HZSM-5 which is used in commercial MTO process. With NH_3 TPD and activity test, the correlation between reaction products and possibility in control of Bro¨nsted acid site which is reported as the reaction active site was investigated. In this study, ethylene and propylene are the target products because of their wide applicating field.
정영식,정석진 한국전산구조공학회 2000 한국전산구조공학회논문집 Vol.13 No.3
Genetic Algorithms(GA) together with simulated annealing are often called methods of last resorts since they can be applicable to any kind of problems, particularly those to which no sophisticated procedures are applicable or feasible. The design of structures is primarily the process of selecting a section for each member from those available in the market, resulting in the problem of combinatorial nature. Therefore it is usual for the design space to include astronomical number of designs making the search in the space often impossible. In this work, Genetic Algorithms and some related technique are introduced and applied to the design of steel frameworks. In problems with a small number of design variables, GA found true global optima. GA also found true optima for the continuous variable test problems and proved their applicability to structural optimization. For those problems of real size, however, it appears to be difficult to expect GA to find optimum or even near optimum designs. The use of G bit improvement added to ordinary GA has shown much better results and draws attention for further research. 유전자 알고리즘(GA)은 어떠한 유형의 문제에도 적용가능하며 달리 방법이 없는 경우 최후의 수단으로 흔히 사용되는 방법이다. 강구조물 설계란 기본적으로 구조물을 이루는 부재로서 어떤 재료를 선택될 것인지를 결정하는 문제이다. 따라서 천문학적인 숫자의 설계가 존재하며 이들 중 최적의 설계를 탐색하는 것은 대체로 불가능한 일이다. 본 논문에서는 GA와 이와 관련된 여러 가지 기법들을 소개하고 강구조물 최적설계에 이들의 활용을 모색하였다. 작은 설계공간을 가지는 문제에서는 GA로 전역최적설계를 찾을 수 있었다. GA는 또한 연속변수 최적설계 문제에서도 최적설계를 찾았으며 구조물 최적설계에 적용될 수 있음을 보였다. 그러나 규모가 큰 현실문제에서는 GA가 최적 또는 최적에 근접한 설계를 항상 찾을 수 있을 것이라고 기대하기는 어려울 것으로 생각된다. GA에 G bit improvement를 추가하여 수행한 경우에 더 좋은 최적설계 결과를 보여주었으며 앞으로 이 부분의 연구가 활발해 질 것이다.