超滤对血液透析传质性能的影响

本文对空心纤维型血液透析器中的传质过程进行了研究,提出了伴有超滤的血液透析过程中血液一侧传质的数学模型,并用分离变量法获得了该模型的分析解.实验数据表明,用该模型能较好地描述具有超滤的血液透析过程的传质机理.     

纳滤膜技术在维生素B12生产中的应用

为提高维生素B12提取过程中的收率、降低水资源消耗,采用纳滤膜对维生素B12超滤滤液进行浓缩。考察了pH值、压力、浓缩倍数对膜通量的影响。     

超滤(UF)技术处理乳化油废水的研究

采用超滤工艺一间歇式错流操作模型一处理乳化油废水,选用了聚乙烯乙二醇超滤膜(PEG)和卷式膜组件,采用不同的超滤模型对超滤过程中超滤膜透水率、乳化油废水中的COD去除率的变化进行了实验研究,实验结果表明该模型对乳化油废水具有良好的处理效果。     

越橘花色苷不同提取工艺研究

对国产红豆越橘中花色苷的提取工艺进行了研究,得到了最佳提取工艺,即pH值为2的酸性水液提取,超滤法纯化。     

茶叶茶多酚、咖啡碱提取及超滤-吸附综合分离纯化过程研究

介绍了采用三级错流提取茶叶有效成分茶多酚、咖啡碱的优化提取工艺。该工艺提取率高达９０％ 以上,其提取液经醋酸纤维素复合钛微孔体超滤膜初步纯化,可得到茶多酚含量大于４０％ 的部标三级品。并建立了茶叶水提取液超滤过程修正凝胶极化模型。超滤透过液经聚酰胺树脂吸附、８５％ 乙醇洗脱,得到茶多酚含量大于９０％ ,咖啡碱含量低于４％ 的部标茶多酚一级品。该工艺具有不另外添加物质、不使用有毒溶剂、工艺简单等特点。     

超滤和反渗透联用处理玉米浸渍水

对玉米浸渍水的膜分离过程进行了研究，开发出超滤和反渗透联用的分离方法。反渗透浓缩液中蛋白质的截留率为99．77％，反渗透透过液中COD值降到1000左右，可用作工艺回用水，反渗透浓缩液中可提取乳酸等有用物质，超滤浓缩液可浓缩成玉米浆。     

碱性脂肪酶提取工艺的研究

采用０．１ｍ＾２的不锈钢板框对发醇液进行过滤，在超滤过程中料液ｐＨ值应保持在７．５～８．０之间，湿度控制在１３℃以下。超滤前滤液加入０．０５％的苯甲酸钠作防腐剂，并加一定的明矾，提高过滤速度，最佳的操作条件下，酶的提取总收率在７０％以上，脂肪酶粉活力单位在４．０×１０＾４Ｕ／ｇ。     

超滤法处理丝厂废水的研究

采用中性砜中空纤维管式超滤装置，对丝厂废水中的煮茧水在不同pH值条件下的超滤进行研究，结果表明，该超滤膜对丝厂废水超滤的最佳条件是碱性范围。浓缩60倍的浓缩兴，其蛋白质含量高达7．75％（质量分数）。     

超滤和纳滤膜分离提取纳他霉素

为提高纳他霉素(natamycin)生产提取得率,减少溶剂使用,本文采用超滤、纳滤操作对工业生产的纳他霉索发酵液进行处理。实验结果表明:操作压力、操作时间及料液流速对超滤过程有很大影响。通过超滤可将蛋白质等大分子杂质去除,然后再用纳滤膜对超滤渗透液进行浓缩纯化,对纳滤工艺的操作条件如进料压力、料液pH、浓缩倍数等进行了研究。采用超滤、纳滤技术提取纳他霉素,其收率可达62.74%。     

超滤技术在红花黄色素提取中的应用研究

常规醇沉法提取生产红花黄色素流程长,工艺复杂.本文从超滤对红花提取液中主要杂质(蛋白、鞣质、多糖)的截留作用,从红花黄色素提取率以及超滤过程的操作稳定性方面探讨了超滤技术在红花黄色素提取中应用的可行性.通过实验发现,选用截留值(1～3)×104的聚砜超滤膜对提取液中的蛋白、鞣质有较好的截留效果,对多糖的截留效果不明显,超滤纯化后的红花黄色素质量与提取率明显优于醇沉法.同时超滤时料液的浓度和温度对操作的稳定性有较大影响,但控制合适的温度和浓度可得到较长时间的稳定操作时间.     

Kinetics and thermodynamics of paclitaxel extraction from plant cell culture

We investigated the effect of temperature on the efficiency of paclitaxel extraction from biomass. In addition, kinetic and thermodynamic studies of this extraction process were performed. The concentration of extracted paclitaxel increased with increasing extraction temperature and extraction time. When the experimental data were applied to various kinetic models, the hyperbolic model (second-order model) was the most appropriate. The predictive model was developed to predict the concentration of extracted paclitaxel at different temperatures at a given time. The Gibbs free energy change was determined to be negative, while enthalpy change and entropy change were positive. These results indicate that this extraction process is spontaneous, endothermic, and irreversible.     

Supervised sparse preserving projections model based on distributed principal component analysis for chemical process monitoring

For the monitoring of large-scale chemical processes, the distributed method is often used to extract local feature information and model the extracted local feature information to obtain a process monitoring model. But the distributed process monitoring model often contains more process variables, which makes the local information of the process data flooded. To make up for the insufficient extraction of local information in traditional distributed process monitoring, supervised sparse preserving projections model based on distributed principal component analysis (DPCA-SSPP) is proposed in this paper. First, the process data are decomposed by the PCA algorithm, and the principal component space and residual space are obtained. Second, the variables of each sub-block are selected according to the maximum correlation criterion, and the SSPP process monitoring model is established for each sub-block. Finally, the monitoring results of each sub-block are combined together to form a global monitoring result through the Bayesian information fusion strategy. The proposed scheme can be proved to be effective through the simulation on a nonlinear numerical example and the Tennessee Eastman benchmark (TE) process.     

Phase behaviour modelling of Athabasca bitumen for in situ combustion applications

Phase behaviour modelling of reservoir fluid is a fundamental step for reservoir simulation. Furthermore, as the complexity of the recovery process increases, the fluid model plays a more important role in the reliability of the simulation outputs. Although the in situ combustion enhanced oil recovery method (ISC) is one of the most complex recovery techniques available in the petroleum engineering literature, for most of the simulation jobs related to this elaborate process only simple and rudimentary fluid characterization layouts are considered. In this work, the principal fluid properties of Athabasca bitumen with regard to the ISC process are recognized, extracted from the literature, validated for consistency, and used for the development of an inclusive and accurate fluid model. Then the fluid model is fully developed while considering the ISC reaction kinetics so that the model has both accuracy, indispensable for phase behaviour modelling, and consistency, essential for the reactions definitions.     

中药材挥发油提取过程的传质动力学模型

利用Fick第二扩散定律和膜模型理论,分别建立了内扩散控制和气膜扩散控制的传质速率模型,并以苍术挥发油的提取实验以及文献数据对模型进行检验。实验结果表明,苍术颗粒半径较大时,挥发油提取过程由内扩散控制,服从一级动力学方程;颗粒半径小于0.090 mm时,出油速率由气膜扩散控制,出油量和时间呈正比。利用所建立的动力学模型对其他5种中药材的数据进行拟合,得到了与文献数据较为吻合的计算结果,表明该模型是可靠的,能反映实际提取情况,具有一定适用性。     

Local Partial Least Squares Based Online Soft Sensing Method for Multi-output Processes with Adaptive Process States Division

Local learning based soft sensing methods succeed in coping with time-varying characteristics of processes as well as nonlinearities in industrial plants. In this paper, a local partial least squares based soft sensing method for multi-output processes is proposed to accomplish process states division and local model adaptation, which are two key steps in development of local learning based soft sensors. An adaptive way of partitioning process states without redundancy is proposed based on F-test, where unique local time regions are extracted. Subsequently, a novel anti-over-fitting criterion is proposed for online local model adaptation which simultaneously considers the relationship between process variables and the information in labeled and unlabeled samples. Case study is carried out on two chemical processes and simulation results illustrate the superiorities of the proposed method from several aspects.     

Extraction of a dissolved substance from a porous body into a flowing liquid

A mathematical model is proposed to describe the extraction of a dissolved substance from a semiinfinite porous space into an external liquid flow parallel to the interface. An asymptotic expression for the concentration of the extracted substance in the flow late in the process is obtained. A condition for the applicability of this expression is formulated.     

基于多元统计方法的过程单元缓变故障识别

在实际化工生产过程中存在一些缓变故障，在发生的初期过程偏离正常工况的程度较少，且受生产数据噪声的影响，不易被传统过程监测方法及时发现。本文针对缓变故障的特点，提出了一种基于偏最小二乘法-主元分析法（PLS-PCA）的过程监测方法。首先利用偏最小二乘法（PLS）回归提取出各变量之间的关系，通过获取变量实测值与回归预测值之间的误差，以放大装置运行状态与预设状态之间的偏差，在此基础上建立基于主元分析法（PCA）的过程监测模型，实现了对缓变故障的早期识别。该过程监测模型被应用在某制氢装置预转化反应器上，结果表明该方法对缓变故障具有较好的早期识别效果，能够比工程师提前13h，比基于传统PCA的过程监测模型提前8h。     

Effect of Agglomerate Pore Structure on Efficiency of Solid-Liquid Separation by an Agglomeration Technique: Use of a Model System

Abstract

Solid-liquid separation is often difficult to achieve when the solids are finely divided. When the liquid involved is a hydrocarbon, the economics of any process involving such a separation will often depend on the ease and efficiency of liquid recovery. A process is described in which an enhanced solid-liquid separation is achieved by means of a size enlargement technique requiring agitation with a second immiscible liquid, which preferentially wets the solid surface. Potential applications for such a process include removal of ash particles in coal liquifaction and separation of solids from solvent extracted oil-sands. In this work a model system has been used in an attempt to better understand the process mechanics and the factors which affect the efficiency of liquid separation.     

Ethanol extraction of oil,gossypol and aflatoxin from cottonseed

Commercial processing of cottonseed requires hexane to extract and recover edible oil. Gossypol and aflatoxin are not removed from extracted meals. A bench-top extraction process with 95% (vol/vol) aqueous ethanol (EtOH) solvent has been developed that extracts all three of the above materials with a much less volatile solvent. In this process, cottonseed is pretreated and extracted with ambient 95% EtOH to remove gossypol and then extracted with hot 95% EtOH to extract oil and aflatoxin. Membranes and adsorption columns are used to purify the various extract streams, so that they can be recycled directly. A representative extracted meal contained a total gossypol content of 0.47% (a 70% reduction) and 3 ppb aflatoxin (a 95% reduction). Residual oil content was approximately 2%. Although the process is technically feasible, it is presently not economical unless a mill has a continual, serious aflatoxin contamination problem. However, if a plant cannot meet the hexane emission standards under the Clean Air Act of 1990, this process could provide a safer solvent that may expand the use and increase the value of cottonseed meal as a feed for nonruminants. Presented in part at the AOCS annual meeting, Toronto, Canada, May 1992.     

基于主元提取的鲁棒极限学习机研究及其化工建模应用

化工生产过程日益复杂，传统极限学习机(extreme learning machine, ELM)无法有效地对化工过程数据建模。针对该问题，提出一种基于主元提取(principal components extraction, PCE)的鲁棒极限学习机(PCE-RELM)。通过对ELM隐含层进行主元分析，提取数据的主元特征，去除变量间的线性相关性，简化研究问题。可以减小隐含层节点数对模型精度的影响，实现对ELM隐含层节点数的快速随机选取，同时使ELM具有鲁棒性。为验证提出方法的有效性，将PCE-RELM模型应用于精对苯二甲酸(purified terephthalic acid,PTA)生产过程建模。仿真结果显示，相比传统的ELM，PCE-RELM模型具有设计简单、鲁棒性好、精度高等优势，可以对化工过程控制、分析起到指导作用。