This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is intro...This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is introduced into the grey time series model to predict future trend of measurement values in chemical process. These predicted measurements are then used in the dynamic model to retrieve the change of fault parameters by model based diagnosis algorithm. In another method, historical data is introduced directly into the dynamic model to retrieve historical fault parameters by model based diagnosis algorithm. These parameters are then predicted by the grey time series model. The two methods are applied to a gravity tank example. The case study demonstrates that the first method is more accurate for fault prediction.展开更多
Chemical stability and reactivity of organic pollutants is dependent to their formation enthalpies. The main objective of this study is to provide simple straightforward strategy for prediction of the formation enthal...Chemical stability and reactivity of organic pollutants is dependent to their formation enthalpies. The main objective of this study is to provide simple straightforward strategy for prediction of the formation enthalpies of wide range organic pollutants only from their structural functional groups. Using such an extended dataset cornprising 1694 organic chemicals from 77 diverse material classes benefits the generalizability and reliability of the study. The new suggested collection of 12 functional groups and a simple linear regression lead to promising statis- tics of R2= 0.958, Q2 =0.956, and AEE= 57 kJ.mo1-1 for the whole dataset. Moreover, unknown experimental formation enthalpies for 27 organic pollutants are estimated by the presented approach. The resultant model needs no technical software/calculations, and thus can be easily applied by a non-specialist user.展开更多
Ammonia, primarily made with Haber-Bosch process developed in 1909 and winning two Nobel prizes, is a promising noncarbon fuel for preventing global warming of 1.5 °C above pre-industrial levels. However,the unde...Ammonia, primarily made with Haber-Bosch process developed in 1909 and winning two Nobel prizes, is a promising noncarbon fuel for preventing global warming of 1.5 °C above pre-industrial levels. However,the undesired characteristics of the process, including high carbon footprint, necessitate alternative ammonia synthesis methods, and among them is chemical looping ammonia production(CLAP) that uses nitrogen carrier materials and operates at atmospheric pressure with high product selectivity and energy efficiency. To date, neither a systematic review nor a perspective in nitrogen carriers and CLAP has been reported in the critical area. Thus, this work not only assesses the previous results of CLAP but also provides perspectives towards the future of CLAP. It classifies, characterizes, and holistically analyzes the fundamentally different CLAP pathways and discusses the ways of further improving the CLAP performance with the assistance of plasma technology and artificial intelligence(AI).展开更多
基金Supported by the Shandong Natural Science Foundation(ZR2013BL008)
文摘This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is introduced into the grey time series model to predict future trend of measurement values in chemical process. These predicted measurements are then used in the dynamic model to retrieve the change of fault parameters by model based diagnosis algorithm. In another method, historical data is introduced directly into the dynamic model to retrieve historical fault parameters by model based diagnosis algorithm. These parameters are then predicted by the grey time series model. The two methods are applied to a gravity tank example. The case study demonstrates that the first method is more accurate for fault prediction.
基金Supported by the "Tehran Naftoon Arya Eng. Co." research committee of Iran
文摘Chemical stability and reactivity of organic pollutants is dependent to their formation enthalpies. The main objective of this study is to provide simple straightforward strategy for prediction of the formation enthalpies of wide range organic pollutants only from their structural functional groups. Using such an extended dataset cornprising 1694 organic chemicals from 77 diverse material classes benefits the generalizability and reliability of the study. The new suggested collection of 12 functional groups and a simple linear regression lead to promising statis- tics of R2= 0.958, Q2 =0.956, and AEE= 57 kJ.mo1-1 for the whole dataset. Moreover, unknown experimental formation enthalpies for 27 organic pollutants are estimated by the presented approach. The resultant model needs no technical software/calculations, and thus can be easily applied by a non-specialist user.
基金supported by the DNL Cooperation Fund,CAS(DNL180402)the support from the University of Wyoming。
文摘Ammonia, primarily made with Haber-Bosch process developed in 1909 and winning two Nobel prizes, is a promising noncarbon fuel for preventing global warming of 1.5 °C above pre-industrial levels. However,the undesired characteristics of the process, including high carbon footprint, necessitate alternative ammonia synthesis methods, and among them is chemical looping ammonia production(CLAP) that uses nitrogen carrier materials and operates at atmospheric pressure with high product selectivity and energy efficiency. To date, neither a systematic review nor a perspective in nitrogen carriers and CLAP has been reported in the critical area. Thus, this work not only assesses the previous results of CLAP but also provides perspectives towards the future of CLAP. It classifies, characterizes, and holistically analyzes the fundamentally different CLAP pathways and discusses the ways of further improving the CLAP performance with the assistance of plasma technology and artificial intelligence(AI).
