Achieving sustainable development while limiting environmental pollution is one of the main enormous challenges for chemical engineering at present. To develop and design a greener alternative to replace or retrofit a current polluted process, it is essential to establish a method for quantitatively evaluating the environmental impact of a chemical process so that its environmental performance can be improved by identifying and discovering the bottlenecks that cause the pollution. In this work, a green degree (GD) method is proposed to quantitatively evaluate the environmental impact of a chemical process and related energygeneration system. Definitions and calculation formulas of green degrees for a substance, a mixture, a stream, and a unit (process) are illustrated. The green degree is an integrated index that includes nine environmental impact categories (including global, air, water, and toxicological effects). Therefore, it is comprehensive for assessing and understanding the environmental performance of a complex multicomponent chemical system. Three illustrative case studies are presented to further describe and verify the applicability of the method: (1) solvent screening by comparing the green degree values of solvents, (2) process route screening for producing methyl methacrylate (MMA), and (3) green degree analysis of the methyl methacrylate process (i-C4 route) by integration with process simulation technology.
in Wiley Online Library (wileyonlinelibrary.com)Vapor-liquid equilibrium (VLE) and liquid-liquid equilibrium (LLE) data of binary and ternary acrylic systems were systematically measured. Subsequently, VLLE phase diagrams of binary systems, tridimensional VLE phase diagrams of methyl acrylate (MA)-methanol (Me)-H 2 O ternary system, and quaternary LLE phase diagrams of MA-Me-H 2 O-methyl acetate (MeOAc) system were constructed. These diagrams clearly demonstrated the effects of temperature on phase equilibrium. The experimental data was fitted by the NRTL and UNIQUAC models, and the best-fitted parameters were used to predict interaction properties of ternary and quaternary mixture. Therefore, the phase equilibrium data were provided as reference for the design of acrylic systems rectification or extraction process. Residue curve was mapped out for MA-Me-H 2 O system through Aspen plus software. Finally, using thermodynamics and residue curve as theoretical basis, two novel separation processes were proposed and applied to the quaternary acrylic systems. V C 2015 American Institute of Chemical Engineers AIChE J, 62: [228][229][230][231][232][233][234][235][236][237][238][239][240] 2016
How to make an accurate evaluation of the quality of pension service has become the most important task. However, in the real world, many customs always forget to rate pension service. They only leave a few short, less semantic, and discontinuous review words below the service. This paper will propose an effective multi-dimension attention convolutional neural networks (MACNNs) model to analyze customer review texts and predict the pension service quality. In MACNN, the emoticon feature, sentiment feature, and word feature can be extracted together to construct feature space. And then attention layer and convolution layer work together to predict the service quality. Compared with the traditional machine learning methods and neural network methods, this method is more objective and accurate to reflect consumers’ real evaluation of pension service.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.