点复合吸水垫芯布的试制

介绍了点复合吸水垫芯布的试制过程,分析了工艺路线、纤维原料及配比的选择,详细叙述了工艺制作过程。为了更好衡量产品的性能,在参考了GB/T 24218.6—2010的基础上自定了吸水量和芯吸高度的测试方法。测试结果表明:该吸水垫芯布吸水效果好,伸长率达到40%～70%,同时具有好的手感。     

What color do you feel? Color choices are driven by mood

Popular opinion holds that color has specific affective meaning. Brighter, more chromatic, and warm colors were conceptually linked to positive stimuli and darker, less chromatic, and cool colors to negative stimuli. Whether such systematic color associations exist with actually mood felt remains to be tested. We experimentally induced four moods—joy, relaxation, fear, and sadness—in a between‐subject design (N = 96). Subsequently, we asked participants to select a color, from an unrestricted sample, best representing their current mood. Color choices differed between moods on hue, lightness, and chroma. Yellow hues were systematically associated with joy while yellow‐green hues with relaxation. Lighter colors were matched to joy and relaxation (positive moods) than fear and sadness (negative moods). Most chromatic colors were matched to joy, then relaxation, fear, and sadness. We conclude that color choices represent felt mood to some extent, after accounting for a relatively low specificity for color‐mood associations.     

一种参数辨识与模型匹配相结合的自适应控制

讨论了对象参数辨识与模型匹配控制(MMC)相结合的自适应控制方法。该方法是基于RIV 在线参数辨识求取时变对象参数,进而利用 MMC 方法不断修正反馈与前馈增益,使对象得到与预选模型相匹配的动态响应。实验室一模拟对象与一实际工业对象的数字仿真结果说明了该方法的可行性。该算法能被改进为一种实时在线的计算机控制策略而加以实施。     

Prediction of vapor—liquid—liquid equilibria by means of a modified regula—falsi method

A simple method is proposed for predicting vapor—liquid—liquid equilibria (T—P—y—x—x′) by means of a modified regula-falsi iteration process, which was developed for solving simultaneous high-order equations using the principles of the original regula-falsi method for a single variable. The application of the proposed method to both the interpolation and extrapolation cases are presented. A procedure for changing a diverging process into a converging one is also suggested.The success of the proposed method is demonstrated by predicting the vapor—liquid—liquid equilibria for the nitrogen—methane—ethane system at eight isotherms from 94·3 to 123·4°K and the liquid—liquid equilibria for the n-octane—octene-1—nitroethane system at 273·1°K. The proposed method appears to be particularly useful for the prediction of liquid—liquid equilibria in the vicinity of the plait point.     

PAT method to gather bioprocess parameters in real-time using simple input variables and first principle relationships

The efficient quantification of bioprocess parameters is of high importance for strain characterization and process development. Here, we present a method, which allows the quantification of the specific growth rate, the specific substrate uptake rate and the growth stoichiometry, in a real-time context. The method is solely based on the combination of first principle relationships, using unstructured kinetic modeling, elemental- and mass balancing. Hence, very little prior knowledge is required. Off gas measurements of CO₂ and O₂ as well as base consumption were used as the only input variables to the method, which was executed in real-time along with the bioprocess.We demonstrate the capacity of the method by fed-batch cultivations of the methylotrophic yeast Pichia pastoris as well as by batch cultivations of P. pastoris and Saccharomyces cerevisiae on various carbon substrates. In fed-batch, with an accelerated and decelerated exponential feed profile, the method was able to efficiently quantify the maximum specific growth rate, as well as to investigate growth stoichiometry at low growth rates for maintenance effects. Furthermore, the method allows to correctly identify the timely adaptation of the specific substrate uptake rate and the specific growth rate as well as the oxidative capacity in batch cultures and to distinguish substrate specific kinetics. Further real-time outputs are concentrations of components such as biomass and substrate. The validity of the derived parameters is checked for consistency using redundancy and a statistical test.This method contributes to process understanding, because the method consistently quantifies bioprocess parameters, which can be used to analyze their correlation to critical quality attributes. Furthermore, the real-time availability of the parameters allows the development of process control strategies. This matches Quality by Design (QbD) and Process Analytical Technology (PAT) in its main objectives.     

HfCl4/NaBH4体系对亚砜的脱氧还原

对HfCl4/NaBH4体系下亚砜的脱氧还原反应进行了研究。考察了溶剂、温度、摩尔比等因素对该反应的影响。结果表明,在HfCl4/NaBH4体系下,当溶剂为四氢呋喃(THF)、n(底物):n(HfCl4):n(NaBH4)=0.8:0.34:4.0时,亚砜回流反应0.6～1.5 h,脱氧还原得收率88%～99%的硫醚产物。此外,在上述脱氧反应过程中,—NO2,—OMe,—F,—Cl,—Br等官能团具有兼容性。该法对二苯基亚砜、二苄基亚砜尤为适合,收率高达98%～99%。     

Data-Efficient Quickest Change Detection with On–Off Observation Control

Abstract

In this article we extend Shiryaev's quickest change detection formulation by also accounting for the cost of observations used before the change point. The observation cost is captured through the average number of observations used in the detection process before the change occurs. The objective is to select an on–off observation control policy that decides whether or not to take a given observation, along with the stopping time at which the change is declared, to minimize the average detection delay, subject to constraints on both the probability of false alarm and the observation cost. By considering a Lagrangian relaxation of the constraint problem and using dynamic programming arguments, we obtain an a posteriori probability-based two-threshold algorithm that is a generalized version of the classical Shiryaev algorithm. We provide an asymptotic analysis of the two-threshold algorithm and show that the algorithm is asymptotically optimal—that is, the performance of the two-threshold algorithm approaches that of the Shiryaev algorithm—for a fixed observation cost, as the probability of false alarm goes to zero. We also show, using simulations, that the two-threshold algorithm has good observation cost-delay trade-off curves and provides significant reduction in observation cost compared to the naïve approach of fractional sampling, where samples are skipped randomly. Our analysis reveals that, for practical choices of constraints, the two thresholds can be set independent of each other: one based on the constraint of false alarm and another based on the observation cost constraint alone.     

加氢裂化装置生产指导系统的研究与应用

加氢裂化工艺中,催化剂温度等过程变量对最终产品的产量质量指标有着至关重要的影响,而在现实的工业生产中,分散控制系统（DCS）测量得到的过程数据和实验室分析得到的质量指标数据由于各种原因并不能有效地整合,从而造成数据和投资的浪费。本文研究开发了一种生产指导系统,通过采集DCS和实验室分析数据,建立过程变量和最终产品质量等指标的数学关系来指导用户调整一些可调过程变量,从而提高产品质量。实践证实了该系统的有效性。     

基于CW-HCA联合指标的高含硫天然气净化过程故障监测

高含硫天然气（HSG）净化过程复杂,导致安全开发风险极高。因此保障净化系统可靠运行、实现过程安全生产具有重要意义。对于类似化工过程,在独立成分分析（ICA）方法基础上,高阶累积量分析（HCA）用样本三阶累积量代替均值方差构造统计指标大大提高了检测率。然而,HCA构造独立分量空间指标时未考虑不同独立分量间重要性差异,这可能致使监测结果经样本高阶累积后出现一定程度的偏差。同时,采用多指标监测策略可能出现指标间监测结果相互冲突问题。为此,提出一种基于贡献度加权高阶累积量分析（CW-HCA）联合指标的故障监测方法。该方法根据独立分量的贡献度对样本的三阶累积量进行加权;再将加权后的指标与残差空间指标联合获得联合指标,实现监测。TE以及HSG净化过程的实验结果表明,所提算法相比ICA算法、HCA算法具有有效性和优越性。     

Gel permeation chromatography: Automatic data acquisition and reduction in real-time with a process computer

A real-time computer system is described which minimizes the total analysis time in gel permeation chromatography by automatically acquiring the data, performing the necessary calculations and displaying the molecular weight distribution and molecular weight averages as soon as the polymer peak has eluted. The calculation method described here is valid for linear homopolymers only, and does not include corrections for instrumental peak broadening. The experimental results show good reproducibility and precision. On-line changes of the constants and other parameters may be implemented by means of an auxiliary program which runs in parallel with the data analysis program. A system such as that described here is suitable for utilization as a measurement technique in process control applications. The programs are written in CORAL 66 for a Ferranti Argus 700 E computer.     

Microwave analysis of PACVD diamond deposition reactor based on electromagnetic modelling

The production of high quality diamond films by microwave plasma assisted CVD, with rapid growth rates and good uniformity over large surfaces, requires perfectly optimized reactors from the microwave design point of view. Most MW plasma assisted CVD reactors used for diamond film deposition work on the resonant cavity principle. The design of such reactors relies on 3 choices: i) choice of a suitable resonant mode (i.e. with an electric field structure conducive to plasma ignition), ii) choice of a MW coupling system to excite the cavity, and iii) choice of a quartz window to delimit a reduced pressure zone inside the cavity, so as to obtain the plasma in front of the substrate [1].In this paper, we present an analysis method for MW plasma reactors relying on EM modelling, which allows for the identification of a resonant mode responsible for plasma ignition, applied to an existing reactor exhibiting plasma instabilities and requiring constant supervision.This analysis method, which can be generalised to any resonant cavity reactor, can describe the device behaviour (shape and location of the plasma, occurrence of instabilities) as a function of the various cavity geometrical configurations and to get a first estimate of the process performance.On the basis of such an analysis, it was possible to propose modifications to the reactor considered in order to improve process stability, and obtain higher growth rates. First growth tests done on diamond mono- and nano-crystalline films show excellent material quality and an increase in growth rate by more than an order of magnitude.     

Multi-model based process condition monitoring of offshore oil and gas production process

Offshore oil and gas production platforms are uniquely hazardous in which the operating personnel have to work in a perilous environment surrounded by extremely flammable hydrocarbons. A failure in an equipment could quickly propagate to others resulting in leaks, fires and explosions, causing loss of life, capital invested and production downtime. A method for preventing such accidents is to deploy intelligent monitoring tools which continuously supervise the process and the health of equipments to provide context-specific decision support to operators during safety-critical situations. Such an intelligent system, which is condition driven is developed and described in this paper. Since relevant process data is unavailable in the literature, a dynamic model of an offshore oil and gas production platform was developed using gPROMS and data to reflect operating conditions under normal, fault conditions and maintenance activities were simulated. The different maintenance activities and normal conditions are explicitly considered as separate states of the process. The simulated data are then used to train principal component analysis monitoring models for each of these states. Online fault detection and identification are performed by identifying the operating state in real-time and triggering the respective model. In this paper, the dynamic model and the condition monitoring system are described.     

一种基于经验增强的实时优化方法MEO

根据实时优化问题的特点,提出了一种实时优化方法——MEO(mnemonic enhancement optimization),它是一种高效的基于经验增强的实时优化方法。设计了MEO框架及其具体实现步骤,基于Aspen Plus平台开发了MEO通用代理服务器系统。结合Aspen Plus OOMF 脚本语言与AOS NLP/NLA接口混合编程实施了MEO通用代理服务器系统。并应用脱丙烷塔和脱丁烷塔的联塔系统及大规模乙烯分离系统进行测试,结果显示相比于传统方法,MEO不但具有很好的实时性和收敛性,而且具有很好的鲁棒性和开放性,为实时操作优化的进行奠定了基础。     

Extremum seeking control using a partial sum of input-output product

Recent extremum seeking control that uses a continuous perturbation and the integral feedback of perturbation- output product is based on a static nonlinear process. The method can be applied to dynamic nonlinear processes for tracking and maintaining the optimal operating points. It has several tuning parameters, such as the integral controller gain and the magnitude and frequency of the continuous perturbation signal. The frequency of the continuous perturbation signal should be low enough to ensure the time-scale separation between the real-time optimization and the process dynamics for the closed-loop stability. However, for some processes, fast perturbations are preferred because they can be attenuated easily in subsequent processes such as buffers and storages. For this, we propose an extremum seeking control method where the partial sum of perturbation-output product is used for a faster squarewave perturbation. Simulations for two processes of parallel competing reactions have been given, and a simple liquid level system to test extremum seeking control methods is suggested.     

维生素类化合物结晶提纯法研究进展

维生素类化合物是人体必需的营养元素,维生素缺乏会导致人体健康受到严重影响,提纯是制备维生素类化合物的重要过程,结晶法有很好的选择性,析出的晶体纯度高,结晶过程成本低,设备简单,因此广泛用于各种维生素的精制。本文中特别介绍了维生素结晶的降温法、蒸发法、溶析法、熔融结晶法以及结晶分离的新技术。     

On-line process fault detection and diagnosis in plants with recycle

A process fault detection and diagnosis system is performed for the complex case of plant-wide control in processes with recycle in which the control system is the inventory control. It is considered an artificial neural network based supplement of a fuzzy system in a block oriented configuration. A methodology to design the system is described. As a case study, a chemical plant with a recycle stream is considered. Faults in supply of raw materials and in controllers are simulated. Performance of the system to handle simultaneous faults is also analysed. A comparison is made against a classification method (artificial neural networks) and an inference method (knowledge — based system).     

Suspension of flexible cylinders in laminar liquid flow

A methodology for particle-resolved simulation of dense suspensions of flexible cylindrical particles in Newtonian liquid flow is described. It is based on the Lattice–Boltzmann method for solving the liquid flow and an immersed boundary method for imposing no-slip at the particle surfaces and providing the distribution of liquid–solid interaction forces over the particle surfaces. These forces—along with contact forces—translate, rotate as well as bend the cylindrical particles. Verification tests have been performed for a single cylinder settling and deforming under gravity at a low Reynolds number. The method has been applied to a clamped flexible cylinder in microchannel flow for which experimental data are available. It then is used to investigate the behavior of hundreds of flexible cylinders with length over diameter aspect ratios of 4 and 6 in a container agitated by an impeller at a Reynolds number of 87 which implies laminar flow. The overall solids volume fraction is 15%. We study the effect of the bending stiffness of the particles on the solids suspension process, on the extent of particle deformation as well as on the torque required to spin the impeller.     

Designing biomass supply chains within planetary boundaries

The design of sustainable supply chains, which recently emerged as an active area of research in process systems engineering, is vital to ensure sustainable development. Despite past and ongoing efforts, the available methods often overlook impacts beyond climate change or incorporate them via standard life cycle assessment metrics that are hard to interpret from an absolute sustainability viewpoint. We here address the design of biomass supply chains considering critical ecological limits of the Earth—planetary boundaries—which should never be surpassed by anthropogenic activities. Our method relies on a mixed-integer linear program that incorporates a planetary boundaries-based damage model to quantify absolute sustainability precisely. We apply this approach to the sugarcane-to-ethanol industry in Argentina, identifying the optimal combination of technologies and network layout that minimize the impact on these ecological boundaries. Our framework can find applications in a wide range of supply chain problems related to chemicals and fuels production, energy systems, and agriculture planning.     

Simultaneous mixed-integer dynamic scheduling of processes and their energy systems

Increasingly volatile electricity prices make simultaneous scheduling optimization desirable for production processes and their energy systems. Simultaneous scheduling needs to account for both process dynamics and binary on/off-decisions in the energy system leading to challenging mixed-integer dynamic optimization problems. We propose an efficient scheduling formulation consisting of three parts: a linear scale-bridging model for the closed-loop process output dynamics, a data-driven model for the process energy demand, and a mixed-integer linear model for the energy system. Process dynamics is discretized by collocation yielding a mixed-integer linear programming (MILP) formulation. We apply the scheduling method to three case studies: a multiproduct reactor, a single-product reactor, and a single-product distillation column, demonstrating the applicability to multiple input multiple output processes. For the first two case studies, we can compare our approach to nonlinear optimization and capture 82% and 95% of the improvement. The MILP formulation achieves optimization runtimes sufficiently fast for real-time scheduling.     

Uncertainty‐conscious methodology for process performance assessment in biopharmaceutical drug product manufacturing

This work presents an uncertainty‐conscious methodology for the assessment of process performance—for example, run time—in the manufacturing of biopharmaceutical drug products. The methodology is presented as an activity model using the type 0 integrated definition (IDEF0) functional modeling method, which systematically interconnects information, tools, and activities. In executing the methodology, a hybrid stochastic–deterministic model that can reflect operational uncertainty in the assessment result is developed using Monte Carlo simulation. This model is used in a stochastic global sensitivity analysis to identify tasks that had large impacts on process performance under the existing operational uncertainty. Other factors are considered, such as the feasibility of process modification based on Good Manufacturing Practice, and tasks to be improved is identified as the overall output. In a case study on cleaning and sterilization processes, suggestions were produced that could reduce the mean total run time of the processes by up to 40%. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1272–1284, 2018