水溶性轻质砂芯模性能与应用

以聚乙烯醇(PVAL)水溶液作为基体材料,以模型砂为增强材料,经过热烘干工艺制作了一种水溶性砂芯模材料,着重对水溶性轻质砂芯模的制备工艺特点、力学性能和水溶性能进行研究,并将所制得的水溶性轻质砂芯模成功用于树脂基复合材料结构件的制造中。结果表明,水溶性轻质砂芯模较纯砂芯模(1.60 g/cm~3)轻24%,比金属模具的钢材密度(7.85 g/cm3)轻84.5%;水溶性轻质砂芯模的压缩强度随着温度的升高而降低,当温度为150℃时,轻质砂芯模的压缩强度为4.09 MPa;水溶性轻质砂芯模的各项性能满足复合材料结构件制造的要求。     

Process to Planet Approach to Sustainable Process Design: Multiple Objectives and Byproducts

While standard life cycle assessment methods exclude fundamental process engineering models in its analysis, sustainable process design (SPD) is plagued by the dilemma of boundary selection that results in consideration of incomplete life cycles and shifting of emissions outside the system boundary. The Process to Planet (P2P) framework bridges this gap by combining sustainable process design with environmentally extended input output analysis. This framework extending across multiple scales provides the capability of working with process variables and designing processes at the equipment scale while considering the entire life cycle through the supply chain and economic scale models. This work expands the P2P framework to account for byproducts originating from any unit within the model. The framework is further modified to incorporate an economic objective function, henceforth developing a multiobjective (MO) optimization problem for optimal design of any generic industrial process. The modified P2P framework is demonstrated by application to a corn ethanol manufacturing process case study. The MO problem is solved using the epsilon constraint method to obtain Pareto optimal frontiers that reveal the trade-off between environmental and economic dimensions of the sustainable process design problem. Comparison between commonly practiced conventional SPD and P2P SPD Pareto curves exposes the chance of choosing non optimal solutions if the former method is employed.     

Robust Optimal Operation of Two‐Chamber Microbial Fuel Cell System Under Uncertainty: A Stochastic Simulation Based Multi‐Objective Genetic Algorithm Approach

This investigation is performed to study the optimal operation decision of two‐chamber microbial fuel cell (MFC) system under uncertainty. To gain insight into the mechanism of uncertainty propagation, a Quasi‐Monte Carlo method‐based stochastic analysis is conducted not only to elucidate the effect of each uncertain parameter on the variability of power density output, but also to illustrate the interactive effects of the all uncertain parameters on the performance of MFC. Moreover, a systematic stochastic simulation‐based multi‐objective genetic algorithm framework is proposed to identify a set of Pareto‐optimal robust operation strategies, which is helpful to provide an imperative insight into the relationship between the mean and standard deviation of output power density. The results indicate that (1) the coefficient of variance (COV) value of output power density has a linear relationship with the COV value of each uncertainty parameter as well as all interactive parameters; and (2) a significant performance improvement with respect to both mean and standard deviation of power density is observed by implementing the multi‐objective robust optimization. These results thus validate that the proposed uncertainty analysis and robust optimization framework provide a promising tool for robust optimal design and operation of fuel cell systems under uncertainty.     

Multicriteria Optimization of a High‐Yield Pulping Process

This work deals with the application of a multicriteria optimization technique for the optimization of a jack pine pulping process, which has a large number of input and output variables. The optimization process is mainly comprised of two steps: reduction of the volume of the search space and determination of good compromise solutions. In the first step, the Pareto domain is approximated by a large number of possible solutions. The optimization technique uses the concept of preference, indifference and veto to determine the best solutions. Results show that an optimal solution zone can be defined and zones of decreasing preference can be drawn.     

Development of reactive rotational moulding process

Abstract

A recent revival of industrial interest in rotational moulding of reactive liquid polymers has led to renewed research efforts in this area of polymer processing. This paper describes the design and construction of a reactive liquid polymer feed system for use in reactive rotational moulding. This feed system allows multiple material shots to be added to the mould without the need to stop mould rotation. The paper also describes work to develop a control technique that explores the exploitation of changes in ultrasound signal properties to monitor viscosity during cure in reactive rotational moulding (RRM). Tests have been conducted on dicyclopentadiene (DCPD) in a static off-line rig, to simulate the conditions that are expected during rotational moulding. The signals propagated through the DCPD indicate a rise in ultrasonic velocity during cure, associated with mechanical property changes owing to increased crosslinking. This technique is non-intrusive, and measurements can be obtained real-time for the duration of cure.     

Optimization of styrene acrylonitrile random bulk copolymerization reactors

Bulk polymerization of random styrene‐acrylonitrile (SAN) copolymer using AIBN initiator, in nonisothermal batch reactors is optimized using single and multiple objective functions. The objectives are selected from among: minimization of the reaction time, maximization of the overall monomer conversion, and maximization of the number average molecular weight of the product. Constraints are used for the mole fraction of styrene in the copolymer produced (so as to produce copolymer having desired properties), and on the permissible range of temperature in the reactor. Pareto optimal solutions are obtained for some sample 2‐ and 3‐objective optimization problems. The optimization toolbox of MATLAB with genetic algorithm as the solver is used. Different points in the Pareto set are associated with different optimal temperature histories, a few of which are provided. POLYM. ENG. SCI., 55:2377–2387, 2015. © 2015 Society of Plastics Engineers     

Multiobjective optimization of polymerization reaction of vinyl acetate by genetic algorithm technique with a new replacement criterion

A multiobjective optimization procedure based on genetic algorithm has been developed to determine optimum operational conditions of polymerization reaction. In this article by using a new selection criterion to choose the next generation members with better quality, optimization efficiency is improved and the number of generations to obtain Pareto optimal set reduced. In this proposed method a novel replacement criterion based on ranking level information and proximity of solutions to the Pareto optimal front is used to choose the next generation members. The polymerization of vinyl acetate has been chosen as an example. Two objective functions, which used in this study, are maximization of the weight average molecular weight up to the desired value and minimization of the residual initiator concentration. A Pareto optimal set of objective functions has been obtained by application of a Pareto set filter operator. Furthermore, the influence of genetic algorithm parameters on the efficiency and convergence of genetic algorithm is studied by changing cross over and mutation probabilities. Because of the flexibility and generality of genetic algorithm, this optimization method is a useful technique with lots of potentials in determination of optimum value of operation parameters. POLYM. ENG. SCI., 2008. © 2008 Society of Plastics Engineers     

多型芯径向抽芯注塑模设计

轴套塑件上有12个周向均布的圆孔,注塑生产时需要多型芯径向抽芯。为此设计了一种特殊的轴套注塑模具,论述了模具结构特点和工作原理。该模具利用异型弯销、转盘及滑块完成多型芯径向抽芯,而未采用一般的齿轮-齿条机构或连杆机构,简化了模具结构。采用三脚推管推出塑件,解决了轴套塑件脱模难的问题。模具结构简单紧凑,工作可靠,操作方便,成型塑件质量好。     

Thermal stability and abrasion resistance of polyacrylate/nano-silica hybrid coatings

Polyacrylate (PAE)/nano-silica (SiO₂) hybrids were prepared by an in situ sol–gel process of tetraethyl orthosilicate in the presence of PAE toluene solution. The hybrid coatings were fabricated using a PAE/SiO₂ suspension by the traditional casting. Their intermolecular interaction and morphology, as well as thermal, mechanical, and optical properties, were investigated using Fourier transform infrared spectroscopy, field-emission scanning electron microscope, differential scanning calorimetry and TG/DTA thermogravimetric analysis, coating impact testing, and UV–Vis spectroscopy, respectively. At the same time, their abrasive properties were carried out by abrasion resistance and nanoindentation tests. The results indicate that silica nanoparticles, with diameter about 30 nm, can disperse homogeneously in the PAE matrix, where hydrogen bonds between the PAE and nano-silica are formed. Therefore, homogeneous dispersion of nano-silica particles provides high transparency for the PAE/SiO₂ hybrid coating as the size of nano-silica phase is much smaller than the wavelength (390–770 nm) of visible light. PAE/nano-silica hybrid coatings have increased T _g and thermal stability including the onset decomposition temperature, 10 % weight loss temperature, and char at 700 °C. Additionally, the incorporation of nano-silica particles improves the glossiness of the PAE/nano-silica hybrid coatings and enhances their abrasion resistance and surface hardness. The nano-silica content has obvious effect on the thermal, mechanical, optical, and anti-abrasion properties of PAE/SiO₂ hybrid coatings. With the consideration of all the properties of hybrid coatings, the PAE/SiO₂ hybrid containing 10 phr of nano-silica has the optimal composition. These PAE/nano-silica hybrid coatings have potential applications in high-performance hologram image recording.     

Influence of powder morphology on properties of ceramic injection moulding feedstocks

The powder-binder-mixture is the most critical aspect in the injection moulding processing chain, because the feedstock properties determine the success of the following steps, i.e. excellent flowability in the injecting phase and high green strength during debinding. Therefore, nearly spherical particles which pass each other easily in the feedstock stream are advantageous. The applicable particle size is limited in order to reach high solids loadings which are connected with the specific powder surface. According to this, in this study a very unfavourable powder was introduced into a feedstock. The investigated β-alumina powder consists of plate-like primary particles and has a specific surface of 25 m²/g. During mould filling the particles orient in the feedstock stream which affects the debinding and sintering behaviour and is the source of defects. The influence of the plate-like shape on defect formation is demonstrated in comparison to spherical-shaped particles having the same specific surfaces.     

Optimization of power cable production lines for EPM/EPDM elastomers by genetic algorithm with different peroxides

EPM/EPDM elastomers are widely used for the insulation of high and medium voltage electric cables. Insulator mechanical properties depend on the extent of vulcanization, which is obtained by manufactures using a number of different peroxides as cross‐linking agents. Vulcanization occurs in the continuous vulcanization tube, a pressurized tube filled with nitrogen at high temperatures. Then, water and/or air are used to cool the cable at ambient temperature. Changes of process variables cause considerable changes in insulator physical properties. In the present article, a genetic algorithm with zooming and elitist strategy is used for the determination of optimal production lines parameters to use to maximize rubber output mechanical properties. Nitrogen temperature T_s and exposition time t are assumed as production parameters to optimize, whereas two different output mechanical properties (tensile strength and tear resistance) are considered as objective functions. Several optimization problems are analyzed both for medium and high voltage cables. A final multiobjective optimization is presented with the corresponding Pareto frontier, where objective functions are represented by tear resistance and tensile strength. Optimal production T_s and t are obtained for all the cases analyzed. Numerical simulations show how different peroxides and insulator thicknesses sensibly influence optimal production variables. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

Evaluation of potential applications of recycled moulding and core sands to production of ceramic building materials

This study summarises the properties of ceramic materials containing used moulding sand, from processed and recycled mould and core mixes. The sand preparation procedure involves crushing and separation of metallic parts. Thus obtained substance acts as a substitute for natural quartz sand, commonly used as a leaning agent in ceramic plastic bodies to be formed into ceramic-based construction materials. The study summarises the basic functional parameters, structure and microstructure of ceramic materials made from plastic bodies containing variable qualitative proportions of used sand. The issues addressed in the paper include the potential threats associated with manufacturing and disposal of these types of materials. Potential hazards include atmospheric emissions of hazardous gaseous substances in the form of polycyclic aromatic hydrocarbons (PAHs) as derivatives of organic binders used for manufacturing of moulding and core sand mixes. These substances are formed in the process of combustion of ceramic products or can be produced when heavy metals are released from the ceramic matrix. This process can occur throughout the entire service life of ceramic products under the specific conditions. Applicability of used sand in this disposal scheme is well proved by good parameters of thus obtained ceramic materials and positive test results evidencing the absence of atmospheric emissions of hazardous substances and low-level leaching of heavy metals.     

反应器网络多目标综合优化

通过反应系统综合优化获得经济效益好、对环境友好的反应系统是大多化工厂提高全流程整体经济和环境性能的重要手段。反应器网络综合优化方法主要包括可得区法、导数分析法、超结构优化法、目标类法、经验推断法和分布参数法等,然而却很少有文献报道对反应器网络进行多目标综合优化。由于过程中往往存在多个相互冲突的目标函数,所以仅仅依靠单目标对反应器网络进行综合优化已显得不合适。本文采用分布参数法建立多目标优化模型,目标函数为经济最大化和环境影响最小,并采用非支配排序基因算法(NSGA-Ⅱ)进行优化得到Pareto最优解集。     

Techno-economical and environmental optimization of natural gas network operation

In the present study, a multi-objective approach is proposed to find optimum operating condition of natural gas network. For this purpose, a thermodynamic modeling of natural gas through the main elements of the network i.e. pipelines and compressor stations (CSs) is performed. This study aims to find optimum values of three conflicting objective functions namely maximum gas delivery flow and line pack, and minimum operating cost (sum of fuel consumption and carbon dioxide emission costs), simultaneously. Here, fast and elitist non-dominated sorting genetic-algorithm (NSGA-II) is applied by considering fourteen decision variables: number of running turbo-compressors (TCs) and rotational speed of them in compressor stations as well as gas flow rate and pressure at injection points. The results of multi-objective optimization are obtained as a set of multiple optimum solutions, called ‘the Pareto optimal solutions’. Furthermore, a set of typical constraints, governing the pipeline operation, is subjected to obtain more practical solutions. To control the constraints satisfaction and to find better solutions in optimization process, the penalty functions are defined and applied. Sensitivity analysis of change in the objective functions, when the optimum decision variables vary, is also conducted and the degree of each parameter on conflicting objective functions is investigated.     

紫外光固化纳米SiO2／改性丙烯酸松香杂化涂料的研究

通过共混法制得了紫外光固化纳米SiO2/R性丙烯酸松香杂化涂料.采用傅立叶红外光谱对其进行表征,并对涂膜的力学性能及耐热性能做了研究.研究结果表明:纳米SiO2的加入使体系的固化速率减慢,固化时间延长,涂膜交联度下降;同一纳米SiO2含量下,随着引发剂量的增加和固化时问的延长,涂膜交联度逐步增加;另外,添加纳米SiO2粒子后,可显著提高涂膜的力学性能,当纳米SiO2加入量为10%时,涂膜硬度达到4H,附着力达到1级;纳米SiO2的加入对涂膜的外观有一定影响,随着纳米SiO2加入量的增加,涂膜由无色透明变成淡白色略透明,因此为保证外观质量及涂膜力学性能,纳米SiO2加入量以在10%以内最好;热失重分析证明纳米SiO2粒子的添加对材料的耐热性能没有明显影响.     

注塑模温度场的计算机模拟

本文运用有限元法，采用二次等参单元，对注塑模二维非稳态温度场进行了数值分析，推导了有限元数值求解方程并研制了有限元求解程序软件。实例所得温度场等温线与实验所得结果基本相符，验证了计算机求解的可靠性。通过计算机模拟分析，可了解各瞬时模具温度场的分布状态，观察模具体能否使塑件均匀冷却，如不合理，可通过改变冷却管道参数，达到温度场均匀一致，从而提高塑件质量。通过程序运转，根据塑件的热定型温度，可以预知最短冷却时间，从而缩短冷却周期，提高塑件生产率     

Efficient deterministic multiple objective optimal control of (bio)chemical processes

In practical optimal control problems multiple and conflicting objectives are often present, giving rise to a set of Pareto optimal solutions. Although combining the different objectives into a convex weighted sum and varying the weights is the most common approach to generate the Pareto front (when deterministic optimisation routines are exploited), it suffers from several intrinsic drawbacks. A uniform variation of the weights does not necessarily lead to an even spread on the Pareto front, and points in non-convex parts of the Pareto front cannot be obtained [Das, I., Dennis, J.E., 1997. A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multicriteria optimization problems. Structural Optimization 14, 63-69]. Therefore, this paper investigates alternative approaches based on novel methods as normal boundary intersection [Das, I., Dennis, J.E., 1998. Normal-boundary intersection: a new method for generating the Pareto surface in nonlinear multicriteria optimization problems. SIAM Journal on Optimization 8, 631-657] and normalised normal constraint [Messac, A., Ismail-Yahaya, A., Mattson, C.A., 2003. The normalized normal constraint method for generating the Pareto frontier. Structural and Multidisciplinary Optimization 25, 86-98] to mitigate these drawbacks. The resulting multiple objective optimal control procedures are successfully used in (i) the design of a chemical reactor with conflicting conversion and energy costs, and (ii) the control of a bioreactor with a conflict between yield and productivity.     

An Approach to Continuous Approximation of Pareto Front Using Geometric Support Vector Regression for Multi-objective Optimization of Fermentation Process

The approaches to discrete approximation of Pareto front using multi-objective evolutionary algorithms have the problems of heavy computation burden, long running time and missing Pareto optimal points...     

Optimization of membrane gas separation systems using genetic algorithm

Genetic algorithm is applied for the optimization of the membrane gas separation systems. Air separation for enriched oxygen production is the selected system for investigation. Optimizations for single and triple objective functions are studied. The optimization problem involves the selection of the optimal system configurations from three alternatives, including continuous membrane column (CMC), single stripper permeator (SSP), and two stripper in series permeator (TSSP), as well as the optimal operating conditions. Models of the three configurations and the genetic algorithm procedure are computerized. The objective functions discussed are the Rony separation index, power consumption per unit equivalent pure oxygen, and the membrane area. Both high-pressure and low-pressure (vacuum) operation modes are optimized and the effects of different oxygen product purity and feed rate are analyzed. For single objective function optimization, the solutions obtained using genetic algorithm are slightly inferior in one case but superior in other cases compared to those by pure mathematical optimization methods. For triple objective function optimization, the Pareto plots presenting multiple trade-off solutions are generated. In general, compared to high-pressure operation mode, the product recovery and power consumption for low-pressure operation mode are lower. For almost all the cases studied, CMC configuration with its high flexibility appears in the optimal solutions.