Simultaneous optimization of heat-integrated crude oil distillation systems

Crude oil distillation is important in refining industry. Operating variables of distillation process have a critical effect on product output value and energy consumption. However, the objectives of minimum energy consumption and maximum product output value do not coordinate with each other and do not lead to the maximum economic benefit of a refinery. In this paper, a systematic optimization approach is proposed for the maximum annual economic benefit of an existing crude oil distillation system, considering product output value and energy consumption simultaneously. A shortcut model in Aspen Plus is used to describe the crude oil distillation and the pinch analysis is adopted to identify the target of energy recovery. The optimization is a nonlinear programming problem and solved by stochastic algorithm of particle warm optimization.

Optimization of a crude distillation unit using a combination of wavelet neural network and line-up competition algorithm

The modeling and optimization of an industrial-scale crude distillation unit （CDU） are addressed. The main spec- ifications and base conditions of CDU are taken from a crude oil refinery in Wuhan, China. For modeling of a com- plicated CDU, an improved wavelet neural network （WNN） is presented to model the complicated CDU, in which novel parametric updating laws are developed to precisely capture the characteristics of CDU. To address CDU in an economically optimal manner, an economic optimization algorithm under prescribed constraints is presented. By using a combination of WNN-based optimization model and line-up competition algorithm （LCA）, the supe- rior performance of the proposed approach is verified. Compared with the base operating condition, it is validat- ed that the increments of products including kerosene and diesel are up to 20% at least by increasing less than 5% duties of intermediate coolers such as second pump-around （PA2） and third Dump-around （PA3）.

Essential Oil from Inula britannica Extraction with SF-CO_2 and Its Antifungal Activity

The aim of this study was to determine the extraction technique of supercritical fluid carbon dioxide（SF-CO 2） for the essential oil from Inula britannica flowers and its antifungal activities against plant pathogenic fungi for its potential application as botanical fungicide.The effects of factors,including extraction temperature,extraction pressure,SF-CO 2 flow rate,flower powder size,and time on the essential oil yield were studied using the single factor experiment.An orthogonal experiment was conducted to determine the best operating conditions for the maximum extraction oil yield.Adopting the optimum conditions,the maximum yield reached 10.01% at 40°C temperature,30 MPa pressure,60 mesh flower powder size,20 L h-1SF-CO 2 flow rate,and 90 min extraction time.The antifungal activities of I.britannica essential oil using the SF-CO 2 against the most important plant pathogenic fungi were also examined through in vitro and in vivo tests.Sixteen plant pathogenic fungi were inhibited to varying degrees at 1 mg mL-1concentration of the essential oil.The mycelial growth of Gaeumannomyces graminis var.tritici was completely inhibited.The radial growths of Phytophthora capsici and Fusarium monilifome were also inhibited by 83.76 and 64.69%,respectively.In addition,the essential oil can inhibit the spore germination of Fusarium oxysporum f.sp.vasinfectum,Phytophthora capsici,Colletotrichum orbiculare,and Pyricularia grisea,and the corresponding inhibition rates were 98.26,96.54,87.89,and 87.35% respectively.The present study has demonstrated that the essential oil of I.britannica flowers extracted through the SF-CO 2 technique is one potential and promising antifungal agent that can be used as botanical fungicide to protect crops.

Optimization and evaluation of fish oil rnicrocapsules

Fish oil microcapsules were prepared using two natural polysaccharides, alginate and chitosan, as the wall materials. A response surface methodology （RSM） was used to optimize the conditions for fish oil encapsulation efficiency （FOEE）. The FOEE was investigated with respect to three key-variables in the RSM： ratio of inner oil phase to aqueous phase （X1 w/w）; concentration of the aqueous phase （X2, wt%）; and ratio of the aqueous phase to outer oil phase （X3, v/v）. The optimal formulation obtained from the RSM model, i.e., 2.7：1 （X1）, 1.6 wt% （X2）, and 11.5：1 （X3）, gave a FOEE of 28%. The model was validated and the fish oil microcapsules prepared under the optimized conditions were characterized in terms of particle size, polydispersity index （PDI）, zeta potential, surface morphology, and in vitro release. The average droplet size, PDI, and zeta potential were 915 nm, 0.038, and ＋5.2 mV, respectively. The fish oil microcapsules were highly uniform microspheres, and had an accumulative release rate of 77.7% in 270 min in a gastrointestinal model, indicating their potential as an alternative carrier for the controlled release of fish oil. In conclusion, formulating optimal microencapsulation conditions by the RSM can be applied to the microencapsulation of various oil-soluble nutrients for food applications.

Research on the Optimization Approach for Cargo Oil Tank Design Based on the Improved Particle Swarm Optimization Algorithm

Based on the improved particle swarm optimization(PSO) algorithm,an optimization approach for the cargo oil tank design(COTD) is presented in this paper.The purpose is to design an optimal overall dimension of the cargo oil tank(COT) under various kinds of constraints in the preliminary design stage.A non-linear programming model is built to simulate the optimization design,in which the requirements and rules for COTD are used as the constraints.Considering the distance between the inner shell and hull,a fuzzy constraint is used to express the feasibility degree of the double-hull configuration.In terms of the characteristic of COTD,the PSO algorithm is improved to solve this problem.A bivariate extremum strategy is presented to deal with the fuzzy constraint,by which the maximum and minimum cargo capacities are obtained simultaneously.Finally,the simulation demonstrates the feasibility and effectiveness of the proposed approach.