http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Hossein Riasat Harami (검색결과 1 건)
- 무료
- 기관 내 무료
- 유료
-
Amir Dashti,Farshid Zargari,Hossein Riasat Harami,Amir H. Mohammadi,Zahra Nikfarjam 한국화학공학회 2019 Korean Journal of Chemical Engineering Vol.36 No.10
Predicting the solubility of acid gases in ionic liquids (ILs), has lately appeared as advantageous for natural gas purifying, which is equipped by powerful models considering technical and economic aspects. Important issue in the assessment of ILs for potential utilization in gas sweetening process is estimating the H2S solubility at various temperatures and pressures Experimental measurements are costly and take considerable time and effort. As a result, proposing methods for predicting the behavior of this system over a wide range of conditions is vital. In this regard, molecular dynamics simulation (MD) technique as well as artificial intelligence knowledge of hybrid genetic algorithmadaptive neuro fuzzy inference system (GA-ANFIS) and an empirical polynomial regression (PR) model were employed to estimate the solubility of H2S in [bmim][PF6] IL. Pressure and temperature are considered as the independent input variables and H2S solubility as the dependent output variable. The results of this study reveal that the simple fourthorder PR model and GA-ANFIS have the highest accuracy. As a result of the simplicity and accuracy of PR model, it can be used without any prior knowledge about MD and artificial intelligence (AI). According to the accuracy and precision of model proved by the obtained result, the solubility of H2S in ILs has been estimated. The results show that the PR method is more trustworthy than other models.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
