A deep reinforcement learning approach to gasoline blending real-time optimization under uncertainty

The gasoline inline blending process has widely used real-time optimization techniques to achieve optimization objectives,such as minimizing the cost of production.However,the effectiveness of real-time optimization in gasoline blending relies on accurate blending models and is challenged by stochastic disturbances.Thus,we propose a real-time optimization algorithm based on the soft actor-critic(SAC)deep reinforcement learning strategy to optimize gasoline blending without relying on a single blending model and to be robust against disturbances.Our approach constructs the environment using nonlinear blending models and feedstocks with disturbances.The algorithm incorporates the Lagrange multiplier and path constraints in reward design to manage sparse product constraints.Carefully abstracted states facilitate algorithm convergence,and the normalized action vector in each optimization period allows the agent to generalize to some extent across different target production scenarios.Through these well-designed components,the algorithm based on the SAC outperforms real-time optimization methods based on either nonlinear or linear programming.It even demonstrates comparable performance with the time-horizon based real-time optimization method,which requires knowledge of uncertainty models,confirming its capability to handle uncertainty without accurate models.Our simulation illustrates a promising approach to free real-time optimization of the gasoline blending process from uncertainty models that are difficult to acquire in practice.

Research and Practice of Blending Teaching Based on “MOOC + SPOC + Flipped Classroom” for Software Engineering

Based on "MOOC + SPOC + Flipped Classroom", a particular blending teaching pattern adapting to MOOC teaching is proposed to strengthen software engineering students' abilities to study themselves and practice innovatively. Firstly, the process of MOOC development in China is introduced. The distinguishing feature and effect of MOOC teaching are analyzed, followed by the comparison with traditional class. The online Plus offline blending teaching pattern is the combination of online self-study on MOOC before class, seminar study of flipped classroom in class and the summary after class. With the demonstration of a typical case, a progressive strategy is given to implement blending teaching. Finally, the blending teaching pattern is assessed from multiple perspectives, of which both advantages and disadvantages are dissected. Through primary exploration, introducing online study and flipped classroom, blending teaching plays a positive role in software engineering teaching, which means traditional teaching pattern is changed. Meanwhile, students' innovative consciousness and practical ability are inspired. Nevertheless, new problems arise, so that intensive practice and improvement are necessary.

ESTIMATION OF BLENDING RATIO OF TWO-COMPONENT FIBER BUNDLE FROM BUNDLE LOAD-ELONGATION CURVE

In this paper, two methods were developed to assess the blending ratio of two-componentfiber bundles. They were the peak-height method and the slope method. The relationship be-tween blending ratio and testing data was analysed, and the regression curves were obtained bystepwise regression method. It was pointed out that the testing errors of both methods were lessthan two percent. The validities of both methods were verified by experiments, All calculationsof both methods were completed by computer. The blending ratio was ascertained from the test-ing data of bundle fiber strength tester which was made by the authors themselves.

A Method for Crude Oil Selection and Blending Optimization Based on Improved Cuckoo Search Algorithm

Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a crude oil selection and blending optimization model based on the data of crude oil property. The model is a mixed-integer nonlinear programming(MINLP) with constraints, and the target is to maximize the similarity between the blended crude oil and the objective crude oil. Furthermore, the model takes into account the selection of crude oils and their blending ratios simultaneously, and transforms the problem of looking for similar crude oil into the crude oil selection and blending optimization problem. We applied the Improved Cuckoo Search(ICS) algorithm to solving the model. Through the simulations, ICS was compared with the genetic algorithm, the particle swarm optimization algorithm and the CPLEX solver. The results show that ICS has very good optimization efficiency. The blending solution can provide a reference for refineries to find the similar crude oil. And the method proposed can also give some references to selection and blending optimization of other materials.

Multi-objective Design of Blending Fuel by Intelligent Optimization Algorithms

Fuel design is a complex multi-objective optimization problem in which facile and robust methods are urgently demanded.Herein,a complete workflow for designing a fuel blending scheme is presented,which is theoretically supported,efficient,and reliable.Based on the data distribution of the composition and properties of the blending fuels,a model of polynomial regression with appropriate hypothesis space was established.The parameters of the model were further optimized by different intelligence algorithms to achieve high-precision regression.Then,the design of a blending fuel was described as a multi-objective optimization problem,which was solved using a Nelder–Mead algorithm based on the concept of Pareto domination.Finally,the design of a target fuel was fully validated by experiments.This study provides new avenues for designing various blending fuels to meet the needs of next-generation engines.

Intersecting Line of Conical Surface and Smoothly Blending of Two Tubes Whose Axes Are Non-Coplanar

We construct two conical surfaces which take non-coplanar lines as generatrix and rational Bezier curve as ridge-line, and prove that the intersecting line of conical surface has similar properties to Bezier curve. Then, the smoothly blending of two cylinders whose axes are non-coplanar is realized by taking intersecting line of conical surface as axes.

A novel chemical composition estimation model for cement raw material blending process

Raw material blending process is an essential part of the cement production process. The main purpose of the process is to guarantee a certain oxide composition for the raw meal at the outlet of the mill by regulating the four raw materials. But the chemical compositions of raw materials vary from time to time, resulting in difficulties to control the oxide compositions to a predefined value. Therefore, a novel algorithm to estimate the chemical compositions of the raw materials is developed. The paper mainly consists of two parts. In model construction part, a novel constrained least square model is proposed to overcome the deviation introduced by long-term drift of the material components, and the model parameters are estimated with an online strategy. And in validation part, the approach is implemented to two examples including datasets from simulation model and the actual industrial process. The final results show the effectiveness of the proposed method.

Modeling Ocean Chlorophyll Distributions by Penalizing the Blending Technique

Disparities between the in situ and satellite values at the positions where in situ values are obtained have been the main handicap to the smooth modeling of the distribution of ocean chlorophyll. The blending technique and the thin plate regression spline have so far been the main methods used in an attempt to calibrate ocean chlorophyll at positions where the in situ field could not provide value. In this paper, a combination of the two techniques has been used in order to provide improved and reliable estimates from the satellite field. The thin plate regression spline is applied to the blending technique by imposing a penalty on the differences between the satellite and in situ fields at positions where they both have observations. The objective of maximizing the use of the satellite field for prediction was outstanding in a validation study where the penalized blending method showed a remarkable improvement in its estimation potentials. It is hoped that most analysis on primary productivity and management in the ocean environment will be greatly affected by this result, since chlorophyll is one of the most important components in the formation of the ocean life cycle.

Closed-loop scheduling optimization strategy based on particle swarm optimization with niche technology and soft sensor method of attributes-applied to gasoline blending process

Gasoline blending scheduling optimization can bring significant economic and efficient benefits to refineries.However,the optimization model is complex and difficult to build,which is a typical mixed integer nonlinear programming(MINLP)problem.Considering the large scale of the MINLP model,in order to improve the efficiency of the solution,the mixed integer linear programming-nonlinear programming(MILP-NLP)strategy is used to solve the problem.This paper uses the linear blending rules plus the blending effect correction to build the gasoline blending model,and a relaxed MILP model is constructed on this basis.The particle swarm optimization algorithm with niche technology(NPSO)is proposed to optimize the solution,and the high-precision soft-sensor method is used to calculate the deviation of gasoline attributes,the blending effect is dynamically corrected to ensure the accuracy of the blending effect and optimization results,thus forming a prediction-verification-reprediction closed-loop scheduling optimization strategy suitable for engineering applications.The optimization result of the MILP model provides a good initial point.By fixing the integer variables to the MILPoptimal value,the approximate MINLP optimal solution can be obtained through a NLP solution.The above solution strategy has been successfully applied to the actual gasoline production case of a refinery(3.5 million tons per year),and the results show that the strategy is effective and feasible.The optimization results based on the closed-loop scheduling optimization strategy have higher reliability.Compared with the standard particle swarm optimization algorithm,NPSO algorithm improves the optimization ability and efficiency to a certain extent,effectively reduces the blending cost while ensuring the convergence speed.

Feasibility Investigation of Bitumen Properties by Blending of Coal Tar Pitch

There are numerous methods and additives available to improve the durability and quality of road bitumen. A coal tar obtained by coal coking was distilled in a laboratory into fractions of initial boiling point IBP-180℃ (gasoline-like fuel), 180℃ - 360℃ (diesel-like fuel), and >360℃ (residue or coal tar pitch). The coal tar pitch was added into road bitumen by up to 1 - 5 wt% and investigated the alteration of physical and chemical properties. The physico-mechanical properties of coal tar pitch and bitumen blends, as well as the chemical group composition, were determined using standard techniques (MNS) and the SARA method, respectively. Results of 3% coal tar pitch addition into bitumen enhanced ductility by 12.4% and softening point by 1.6℃. We found that blending with bitumen coal tar pitch as a modifier could improve bitumen properties.

Conceptual Blending and Meme Humor on the Internet:The Example of COVID-19 Publicity Posters in Chinese Microblogging

Internet memes,as multimodal cultural products disseminated through the Internet,usually take the form of short videos or images that express humor or satire.The creation and dissemination of humor in memes are both creative and complex,and the successful perception of meme humor reflects humans’universal thinking capacity.Based on the theoretical framework of conceptual blending,this paper selects a set of COVID-19 publicity posters from the official Weibo account of China Guangzhou Fabu(Guangzhou Internet Information Office),analyses the multi-level structure of Internet memes,and explores the dynamic cognitive process in the interpretation of humorous memes to reveal people’s ability to make simultaneous analogies and integration between elements in different mental spaces.

基于Blending-Clustering集成学习的大坝变形预测模型

【目的】变形是反映大坝结构性态最直观的效应量,构建科学合理的变形预测模型是保障大坝安全健康运行的重要手段。针对传统大坝变形预测模型预测精度低、误报率高等问题导致的错误报警现象,【方法】选取不同预测模型和聚类算法集成,构建了一种Blending-Clustering集成学习的大坝变形预测模型,该模型以Blending对单一预测模型集成提升预测精度为核心,并通过Clustering聚类优选预测值改善模型稳定性。以新疆某面板堆石坝变形监测数据为实例分析,通过多模型预测性能比较,对所提出模型的预测精度和稳定性进行全面评估。【结果】结果显示:Blending-Clustering模型将预测模型和聚类算法集成,均方根误差(RMSE)和归一化平均百分比误差(nMAPE)明显降低,模型的预测精度得到显著提高;回归相关系数(R~2)得到提升,模型具备更强的拟合能力;在面板堆石坝上22个测点变形数据集上的预测评价指标波动范围更小,模型的泛化性和稳定性得到有效增强。【结论】结果表明:Blending-Clustering集成预测模型对于预测精度、泛化性和稳定性均有明显提升,在实际工程具有一定的应用价值。

Effect of <i>γ</i>-Valerolactone Blending on Engine Performance, Combustion Characteristics and Exhaust Emissions in a Diesel Engine

γ-valerolactone (GVL) is a C5-cyclic ester that can be produced from biomass providing a potentially renewable fuel for transportation and feedstock for the chemical industry. Experiments were performed with fossil diesel (D), D + biodiesel (BD) and D + BD + GVL blends. A four-cylinder, turbocharged direct injection diesel engine was used for the tests. The engine was coupled to a dynamometer to vary the load. CO, NOx, THC and smoke emissions were measured by using a multi-channel gas analyzer. Combustion characteristics were assessed by in-cylinder pressure data with respect to crank angle and the derived heat release rates. Compared with D, and D + BD blends, addition of GVL had relatively little effect on engine performance and NOx emission, but reduced the exhaust concentration of CO, unburned fuel and smoke significantly. The smoke reduction is particularly notable in view of the very recent suggestion that black carbon is the second most important greenhouse gas in the atmosphere next to carbon dioxide. No diesel engine study with GVL has been reported so far.

Calibrating Remotely Sensed Ocean Chlorophyll Data: An Application of the Blending Technique in Three Dimensions (3D)

In this article, the extension to three dimensions (3D) of the blending technique that has been widely used in two dimensions (2D) to calibrate ocean chlorophyll is presented. The results thus obtained revealed a very high degree of efficiency when predicting observed values of ocean chlorophyll. The mean squared difference between the predicted and observed values of ocean chlorophyll when 3D technique was used fell far below the tolerance level which was set to the difference between satellite and observed in-situ values. The resulting blended field did not only provide better predictions of the in situ observations in areas where bottle samples cannot be obtained but also provided a smooth variation of the distribution of ocean chlorophyll throughout the year. An added advantage is its computational efficiency since data that would have been treated at least four times would be treated only once. With the advent of these results, it is believed that the modelling of the ocean life cycle will become more realistic.

1,1-Dibutoxybutane as a Petroleum Diesel Fuel BlendingComponent and Their Mixture Performance

Effect of 1,1-dibutoxybutane （DBB） addition on petroleum DF （diesel fuel） performance has been studied. The study wasstarted by preparing DBB from decomposition of 1 -butanol on manganese impregnated on activated carbon （Mn/AC） catalyst at 450 ℃ in stainless steel reactor. The product was distilled at 200 ℃ and the residue obtained was analyzed by GC-MS and HSQC NMR toconfirm its structure and purity. The DBB-DF mixtures were prepared at different compositions and determined their excess molarvolume, homogeneity, phase stability, ignition quality, lubricity, cold flow quality, energy content, and viscosity. The addition of DBBinto DF formed a homogeneous mixture and had a good phase stability. The mixtures gave positive excess molar volume values overthe whole concentration ranges. The ignition quality and lubricity of the mixtures increased without lost in cold flow quality. Slightdecreased in viscosity and energy content per mass unit were observed.

The Hole Transport Characteristics of 1,4,5,8,9 and 11-Hexaazatriphenylene-Hexacarbonitrile by Blending

The hole transport characteristics of molecule blends of 1, 4, 5, 8, 9 and 11-hexaazatriphenylene-hexacarbonitrile （HAT-CN）： N,N＇-di（naphthalene-l-yl）-N,N＇-diphenyl-benzidine （NPB） and HAT-CN： 4,4＇-cyclohexylidenebis[N,N- bis（4-methylphenyl）benzenamine] （TAPC） with various NPB and TAPC mixing concentrations （5 90wt%） are studied. When the concentration is in the range of 5-80wt%, it is found that the hole conductions in the two blends are space-charge-limited current （SCLC） with free trap distributions. The current-voltage characteristics of the two blends show SCLC with exponentiM trap distributions at the concentration of 90wt%. The hole mo- bilities of the two blends are very close （10^-4-10^-3 cm2 V^-1 s-X ）, the dependence of electric field and temperature can be described by the modified Poole-Frenkel model. The hole mobility and activation energy of the two blends depending on concentration are similar.

Effect of Blending Ratio on the Properties of Ramie/Polyester Blended Yarn

The effects of the blending ratio on the properties of Ramie/Polyester blended yarns are discussed in this paper. The experimental results show that the elongation of the yarn with the polyester content more than 40% is better than that of others. There is a lowest tenacity of the yarn corresponding to the blending ratio of 50/50 or so. The other properties of the yarn, such as the evenness and hairiness, will be improved with the increasing of the polyester content.

Improved Automotive Fuel Resistance of Natural Rubber/Chlorosulfonated Polyethylene Blends by Blending Epoxidized Natural Polymer

The natural rubber (NR) was mixed with chlorosulfonated polyethylene (CSM), due to the difference of polarity in NR and CSM made this blend incompatible and the third component was used. Epoxidzed natural rubber (ENR) was used as a third component. NR/CSM blended with the blend ratio of 50/50 was prepared by using a two-roll mill and vulcanization in a compression mold at 160°C. The ENR content was varied from 1 to 7 phr. The curing characteristics, morphology, mechanical properties, and automotive fuel swelling were investigated. The results indicated that the cure time of the blend rubbers was shorter as adding ENR. The mechanical properties of the blend rubbers were not affected by ENR content. However, automotive fuel resistance of the blend rubbers was found to increase with adding ENR in rubber blend.

Dynamic management system of ore blending in an open pit mine based on GIS/GPS/GPRS

Using GIS, GPS and GPRS, a dynamic management system of ore blending in an open pit mine has been designed and developed. A linear program was established in a practical application. The system is very good at automatically drawing up a daily production plan of ore blending and monitors and controls the process of mining production in real time. Experiments under real conditions show that the performance of this system is stable and can satisfy production standards of ore blending in open pit mines.

Seamless Multi-Projector Displays Using Nonlinear Edge Blending

The seamless tiled display is an effective realization for the wide field and high-resolution display of media;the technology of edge blending is the core of seamless tiled display system and is also the hot-spot of Digital Light Process (DLP). The paper introduces the technique of edge blending process and puts forward the improved algorithm of edge blending in order to eliminate the edge of the light generated regional integration and achieve seamless connection. The algorithm is the modification of existing fusion algorithm that using two addition parameters p and a, and finally adds Gamma operator to further correction of the pixel brightness. Experimental results show that, the proposed algorithm effectively eliminates the light generated by the edge of the integration region and the image has good transitions, the proposed algorithm reduces the output of the projector color differences by the value of SNR.