Comprehensive analysis on the economy and energy demand of pressure-swing distillation and pervaporation for separating waste liquid containing multiple components

A large amount of waste liquids containing methanol/acetone/water mixtures are produced in the synthesis of methyl methacrylate(MMA).Under the advocacy of green chemical industry,it is urgent to develop an efficient,economic and energy-saving mixture separation process.Through thermodynamic azeotropic behavior and pressure sensitivity analysis,pressure-swing distillation was determined and the optimal separation pressure of each column in the process was obtained.Due to the composition of waste liquids produced were quite different in MMA production,the pressure-swing distillation separation process was designed to fully achieve the accurate waste liquids treatment.Taking the total annual cost(TAC)as the target,the sequential iteration method was used to optimize the process,and the impact of composition on economy was compared.In order to further realize the energy-saving of the separation process,the pervaporation membrane module was introduced to pretreat the waste liquid in the pressure-swing distillation.The results showed that the TAC of the coupling process was 46% higher than that of the pressure-swing distillation process,and the thermodynamic efficiency was 30% higher.This study provides waste liquid treatment technology for enterprises and analyzes its economic and energy efficiency,which has reference significance for the development of coupled separation technology.

Sequential Similarity Detection Algorithm Based on Image Edge Feature

This paper proposes a new sequential similarity detection algorithm(SSDA), which can overcome matching error caused by grayscale distortion; meanwhile, time consumption is much less than that of regular algorithms based on image feature. The algorithm adopts Sobel operator to deal with subgraph and template image, and regards the region which has maximum relevance as final result. In order to solve time-consuming problem existing in original algorithm, a coarse-to-fine matching method is put forward. Besides, the location correlation keeps updating and remains the minimum value in the whole scanning process, which can significantly decrease time consumption. Experiments show that the algorithm proposed in this article can not only overcome gray distortion, but also ensure accuracy. Time consumption is at least one time orders of magnitude shorter than that of primal algorithm.

Internal structural optimization of hollow fan blade based on sequential quadratic programming algorithm

Several structural design parameters for the description of the geometric features of a hollow fan blade were determined.A structural design optimization model of a hollow fan blade which based on the strength constraint and minimum mass was established based on the finite element method through these parameters.Then,the sequential quadratic programming algorithm was employed to search the optimal solutions.Several groups of value for initial design variables were chosen,for the purpose of not only finding much more local optimal results but also analyzing which discipline that the variables according to could be benefit for the convergence and robustness.Response surface method and Monte Carlo simulations were used to analyze whether the objective function and constraint function are sensitive to the variation of variables or not.Then the robust results could be found among a group of different local optimal solutions.

APPLICATION OF SURROGATE BASED PARTICLE SWARM OPTIMIZATION TO THE RELIABILITY-BASED ROBUST DESIGN OF COMPOSITE PRESSURE VESSELS

A surrogate based particle swarm optimization （SBPSO） algorithm which combines the surrogate modeling technique and particle swarm optimization is applied to the reliability- based robust design （RBRD） of composite pressure vessels. The algorithm and efficiency of SBPSO are displayed through numerical examples. A model for filament-wound composite pressure vessels with metallic liner is then studied by netting analysis and its responses are analyzed by using Finite element method （performed by software ANSYS）. An optimization problem for maximizing the performance factor is formulated by choosing the winding orientation of the helical plies in the cylindrical portion, the thickness of metal liner and the drop off region size as the design variables. Strength constraints for composite layers and the metal liner are constructed by using Tsai-Wu failure criterion and Mises failure criterion respectively. Numerical examples show that the method proposed can effectively solve the RBRD problem, and the optimal results of the proposed model can satisfy certain reliability requirement and have the robustness to the fluctuation of design variables.

A Necessary Condition about the Optimum Partition on a Finite Set of Samples and Its Application to Clustering Analysis

This paper presents another necessary condition about the optimum parti-tion on a finite set of samples. From this condition, a corresponding generalized sequential hao f k-means (GSHKM) clustering algorithm is built and many well-known clustering algorithms are found to be included in it. Under some assumptions the well-known MacQueen's SHKM (Sequential Hard K-Means)algorithm, FSCL (Frequency Sensitive Competitive Learning) algorithm and RPCL (Rival Penalized Competitive Learning) algorithm are derived. It is shown that FSCL in fact still belongs to the kind of GSHKM clustering algth rithm and is more suitable for producing means of K-partition of sample data,which is illustrated by numerical experiment. Meanwhile, some improvements on these algorithms are also given.