Robust dynamic optimization for nonlinear chemical processes under measurable and unmeasurable uncertainties

We formulate an integrated framework for the robust dynamic optimization of nonlinear chemical processes under measurable and unmeasurable uncertainties. An affine decision rule is proposed to approximate the causal dependence of the wait-and-see decision variables on the gradually revealed measurable uncertainties. To overcome the computational intractability of the proposed model, a linearization technique based on the first-order Taylor expansion is introduced around the nominal values of uncertainties to derive the robust dynamic counterpart, which can be discretized to a large-scale nonlinear programming (NLP) formulation. Effects of first discretizing the dynamic models or introducing the affine decision rule are investigated. The proposed framework is also compared with the state-of-the-art re-optimization and traditional robust optimization approaches. An illustrative example and an industrial semi-batch 2-mercaptobenzothiazole production case are involved to demonstrate the advantages and applicability of the proposed framework.     

New parameter tuning method of washout filter-aided controller for dynamic behavior adjustment

Stabilizing unstable operating points is an effectiveway to enhance process benefits and safety, which motivates the development for a variety of advanced control strategies. The washout filter-aided controller (WFC), originally used for electric power system and aircraft, has been introduced to adjust the dynamic behavior of chemical process. However, the parameter tuning method faces two major limitations:the dimension of operating variables must be equal to or greater than that of state variables and only one positive real eigenvalue exists in the open loop system. To overcome the two limitations, this paper proposes a new parameter tuning method, so that theWFC is applicable in most chemical processes. By solving a constrained optimization problem, the controller parameters are determined under the constraint that the reassignment of the eigenvalues of the unstable desired operating point can satisfy the stability condition. Thus parts of the equilibrium manifold including the desired operating point are stabilized without affecting the shape of the equilibrium manifold. Finally, the effectiveness of the WFC improved by the proposed parameter tuning method is illustrated through a case study for propanediol anaerobic fermentation.     

Systematic controllability analysis for chemical processes

Modern chemical industrial processes are becoming more and more integrated and consist of multiple interconnected nonlinear process units. These strong interactions profoundly complicate a system's inherent properties and further alter the plant‐wide process dynamics. This may lead to a poor control performance and cause plant‐wide operability problems. To ensure entire processes run robustly and safely, with considerable profitability, it is crucial to recognize the inherent characteristics that can jeopardize controllability and process behavior at the early design stage. With a focus on inherently safer designs, from a plant‐wide perspective, a systematic method for chemical processes controllability analysis is addressed in this study. In the proposed framework, based on open‐loop stability/instability and minimum/nonminimum‐phase behavior, the entire operating zone of the process can be categorized into distinct subregions with different inherent properties. Variations in the inherent characteristics of a plant‐wide process with the operation and design conditions, over the feasible operation region, can be probed and analyzed. An attempt of this framework is made to illustrate how to clarify the roots of the poor controllability that arise in the design and operation of a large scale chemical process, and the results can provide guidance for both deciding the optimal operation conditions and selecting the most suitable control structure. Singularity theory is also applied in the framework to improve the computational efficiency. The framework is illustrated with two case studies. One involves a reactor‐external heat exchanger network and the other a more complex plant‐wide process, comprising a reactor, an extractor, and a distillation column. © 2012 American Institute of Chemical Engineers AIChE J, 58: 3096–3109, 2012     

我国磷化工对外贸易动态比较优势分析

根据比较优势调整磷化工产品贸易结构这一思路,首先运用散点图、核密度曲线两种统计方法分析了1997—2009年我国磷化工产品贸易结构和比较优势的变化,然后用相对变动的RSCA指数和世界磷化工产品进口需求的平均增长率的二维分析框架分析了我国磷化工出口产品比较优势与世界需求动态的整合情况。研究显示:我国磷化工产品贸易结构没有发生大的变动,比较优势没有很明显的流动性;出口专业化越来越集中在具有比较优势的磷化工产品上,出口贸易专业化程度略微增加;我国磷化工产品贸易模式的不整合率升高。相对于世界进口需求而言,我国磷化工对外贸易的调整效率是下降的。     

On identification of well‐conditioned nonlinear systems: Application to economic model predictive control of nonlinear processes

The focus of this work is on economic model predictive control (EMPC) that utilizes well‐conditioned polynomial nonlinear state‐space (PNLSS) models for processes with nonlinear dynamics. Specifically, the article initially addresses the development of a nonlinear system identification technique for a broad class of nonlinear processes which leads to the construction of PNLSS dynamic models which are well‐conditioned over a broad region of process operation in the sense that they can be correctly integrated in real‐time using explicit numerical integration methods via time steps that are significantly larger than the ones required by nonlinear state‐space models identified via existing techniques. Working within the framework of PNLSS models, additional constraints are imposed in the identification procedure to ensure well‐conditioning of the identified nonlinear dynamic models. This development is key because it enables the design of Lyapunov‐based EMPC (LEMPC) systems for nonlinear processes using the well‐conditioned nonlinear models that can be readily implemented in real‐time as the computational burden required to compute the control actions within the process sampling period is reduced. A stability analysis for this LEMPC design is provided that guarantees closed‐loop stability of a process under certain conditions when an LEMPC based on a nonlinear empirical model is used. Finally, a classical chemical reactor example demonstrates both the system identification and LEMPC design techniques, and the significant advantages in terms of computation time reduction in LEMPC calculations when using the nonlinear empirical model. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3353–3373, 2015     

Recent progress on equation-oriented optimization of complex chemical processes

Process optimization in equation-oriented (EO) modeling environments favors the gradient-based opti-mization algorithms by their abilities to provide accurate Jacobian matrices via automatic or symbolic differentiation.However,computational inefficiencies including that in initial-point-finding for Newton type methods have significantly limited its application.Recently,progress has been made in using a pseudo-transient (PT) modeling method to address these difficulties,providing a fresh way for-ward in EO-based optimization.Nevertheless,research in this area remains open,and challenges need to be addressed.Therefore,understanding the state-of-the-art research on the PT method,its principle,and the strategies in composing effective methodologies using the PT modeling method is necessary for further developing EO-based methods for process optimization.For this purpose,the basic concepts for the PT modeling and the optimization framework based on the PT model are reviewed in this paper.Several typical applications,e.g.,complex distillation processes,cryogenic processes,and optimizations under uncertainty,are presented as well.Finally,we identify several main challenges and give prospects for the development of the PT based optimization methods.     

Fault detection for chemical process based on nonlinear dynamic global-local preserving projections

The performance of the traditional nonlinear fault detection method based on kernel mapping is greatly influenced by the type of kernel function and the tuning of kernel parameters. To solve this problem, a method named nonlinear dynamic global-local preserving projections(NDGLPP) is proposed for nonlinear process fault detection. Firstly, dynamic global-local preserving projection algorithm is used to reduce the dimension of data matrix. Since the second order polynomial mapping is established for the reduced dimension matrix to extract the relevant properties of nonlinear space. Then the two steps are iterated to obtain the higher-order nonlinear mapping. Finally, the proposed method is applied to the ethylene distillation process and Tennessee Eastman (TE) process simulation to verify the effectiveness and feasibility of the detection method.     

基于非线性动态全局局部保留投影算法的化工过程故障检测

传统基于核映射的非线性故障检测方法的性能受核函数类型和核参数的调优影响较大,且实际工业环境中对过程变量的非线性阶数存在很多物理限制。针对这一问题,提出一种非线性动态全局局部保留投影(nonlinear dynamic global-local preserving projections,NDGLPP)的故障检测算法。该方法首先使用动态全局局部保留投影算法对数据矩阵进行降维;然后对降维后的矩阵建立二阶多项式映射提取非线性空间的相关特性;接着通过迭代这两个步骤以获得高阶非线性映射;最后,将所提方法应用于乙烯精馏过程和Tennessee Eastman(TE)过程仿真中,验证了检测方法的有效性和可行性。     

化工-动力多联产产品成本分摊方法研究

化工-动力多联产系统是一种高效、清洁的能源系统,建立科学合理的成本分摊方法,为制定合理的产品价格体系提供依据,有利于推动化工-动力多联产系统发展。在借鉴热电联产成本分摊方法研究的基础上,提出了化工-动力多联产的产品成本分摊方法。通过分析比较,认为考虑了调整系数的火用法能够充分调动双方的积极性,可作为化工-动力多联产产品定价的基本依据,推动化工-动力多联产的发展。     

Numerical modeling of the dynamic tensile behavior of irregular fibers

Most fibers are irregular and are often subjected to rapid straining during mechanical processing and end‐use applications. In this article, the effect of fiber dimensional irregularities on the dynamic tensile behavior of irregular fibers was examined using the finite‐element method (FEM). Fiber dimensional irregularities are simulated with sine waves of different magnitude (10, 30, and 50% level of diameter variation). The tensile behavior of irregular fibers was examined at different strain rates (333, 3333, and 30,000%/s). The breaking load and breaking extension of irregular fibers at different strain rates were then calculated from the finite‐element model. The results indicate that strain rate has a significant effect on the dynamic tensile behavior of an irregular fiber, and that the position of the thinnest segment along the fiber significantly affects the simulation results. Under dynamic conditions, an irregular fiber does not necessarily break at the thinnest segment, which is different from the quasi‐static results. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 91: 2855–2861, 2004     

化工过程大范围工况变化的工况迁移控制策略判定

化工过程出现大范围的工况变化时，复杂的迁移控制策略会带来一定的操作不确定性，因此需要对控制策略进行选择判定。考虑到直接估计工况变化过程生产指标变化量带来的判定误差，引入了中间变量，提出了基于中间变量的控制策略选择判定方法，并分析给出了构建中间变量的基本准则。进而通过对某实际乙烯精馏塔工况变化过程的仿真研究，说明了中间变量的引入能够很大程度地降低对生产指标的估计误差，验证了基于中间变量的控制策略选择判定方法的可用性。     

A model-based characterization of the long-term asymptotic behavior of nonlinear discrete-time processes using invariance functional equations

The present research work proposes a new approach to the problem of quantitatively characterizing the long-term dynamic behavior of nonlinear discrete-time processes. It is assumed that in order to analyze the process dynamic behavior and digitally simulate it for performance monitoring purposes, the discrete-time dynamic process model considered can be obtained: (i) either through the employment of efficient and accurate discretization methods for the original continuous-time process which is mathematically described by a system of nonlinear ordinary (ODEs) or partial differential equations (PDEs) or (ii) through direct identification methods. In particular, nonlinear processes are considered whose dynamics can be viewed as driven: (i) either by an external time-varying “forcing” input/disturbance term, (ii) by a set of time-varying process parameters or (iii) by the autonomous dynamics of an upstream process. The formulation of the problem of interest can be naturally realized through a system of nonlinear functional equations (NFEs), for which a rather general set of conditions for the existence and uniqueness of a solution is derived. The solution to the aforementioned system of NFEs is then proven to represent a locally analytic invariant manifold of the nonlinear discrete-time process under consideration. The local analyticity property of the invariant manifold map enables the development of a series solution method for the above system of NFEs, which can be easily implemented with the aid of a symbolic software package such as MAPLE. Under a certain set of conditions, it is shown that the invariant manifold computed attracts all system trajectories, and therefore, the asymptotic process response and long-term dynamic behavior are determined through the restriction of the discrete-time process dynamics on the invariant manifold.     

The impact of surface science on the commercialization of chemical processes

Surface science developed instruments for atomic- and molecular-scale studies of catalyst surfaces, their composition and structure, both in a vacuum and at high pressures, under reaction conditions (bridging the pressure gap). Surfaces ranging from single crystals, nanoparticles and thin films to porous high surface area catalytic materials have been studied. Classes of surface structure sensitive and insensitive reactions have been identified by surface science studies, including ammonia synthesis, hydrodesulfurization, reforming, combustion and hydrogenation. Rates of reactions often vary by orders of magnitude between using the right and the wrong surface structures. The roles of many promoters that modify the catalyst surface structures and bonding of adsorbates have been verified. Surface reaction intermediates could be identified and the mobility of adsorbates and the adsorbate induced reconstruction of the catalysts attest to the dynamic nature of the catalytic systems during the reaction turnover. The important active sites for catalysis include the low coordination surface step, kink, oxygen and chloride ion vacancies sites and sites at oxide-metal interfaces. Uncovering the molecular ingredients of heterogeneous catalysts will have a major impact on the understanding of reaction selectivity to help the evolution of green chemistry and selective reaction of many types.     

基于被控变量在线建模的化工过程实时优化方法

选择合适的被控变量可对过程进行实时优化(RTO),但现有方法在设计阶段确定被控变量后,不允许对其进行在线调整,导致了RTO效果的局限性。针对这一问题,提出了一种基于被控变量在线建模的方法,使用局部建模技术在线寻找相似样本并建立一阶最优性必要条件(NCO)的估计模型,将其作为被控变量更新控制回路,在反馈控制作用下达到更好的RTO效果。对一个蒸发过程的研究表明,此方法能够通过对NCO的在线准确建模,增加生产过程的经济效益。     

微波强化化工过程技术进展

化工过程强化是企业节能减排的主要途径,化工过程强化手段有多种,简要介绍了微波在催化、合成、萃取、降解及破乳过程的强化作用机理,并介绍了微波在这些过程中的强化效果与应用进展。     

A generalized framework for solving dynamic optimization problems using the artificial chemical process paradigm: Applications to particulate processes and discrete dynamic systems

The solution of optimal control problems (OCPs) becomes a challenging task when the analyzed system includes non-convex, non-differentiable, or equation-free models in the set of constraints. To solve OCPs under such conditions, a new procedure, LARES-PR, is proposed. The procedure is based on integrating the LARES algorithm with a generalized representation of the control function. LARES is a global stochastic optimization algorithm based on the artificial chemical process paradigm. The generalized representation of the control function consists of variable-length segments, which permits the use of a combination of different types of finite elements (linear, quadratic, etc.) and/or specialized functions. The functional form and corresponding parameters are determined element-wise by solving a combinatorial optimization problem. The element size is also determined as part of the solution of the optimization problem, using a novel two-step encoding strategy. These building blocks result in an algorithm that is flexible and robust in solving optimal control problems. Furthermore, implementation is very simple.The algorithm's performance is studied with a challenging set of benchmark problems. Then LARES-PR is utilized to solve optimal control problems of systems described by population balance equations, including crystallization, nano-particle formation by nucleation/coalescence mechanism, and competitive reactions in a disperse system modeled by the Monte Carlo method. The algorithm is also applied to solving the DICE model of global warming, a complex discrete-time model.     

Influence of cure schedule and solvent exposure on the dynamic mechanical behavior of a vinyl ester resin containing glass fibers

This study deals with the dynamic mechanical properties of a glass-reinforced vinyl ester resin. The viscoelastic parameters of the loss factor and the storage modulus as a function of the cure temperature were used as a criterion to determine the optimum cure conditions to be employed. It is shown that the cure temperature usually used to cure these resins is not enough to reach the maximum glass transition temperature, and, therefore, an additional postcure should be used. The influence of several solvents on the dynamic mechanical behavior of these resins cured following the cure pathway proposed by the supplier was also analyzed. This behavior was compared with the solvent uptake at various exposure times, and the changes observed were related to the crosslink density as well as to the chemical structure of both the resin and the solvent. Finally, the effects of varying the exposure temperature were also investigated for the resin exposed to a liquid which simulates petroleum fluid. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 70: 2595–2602, 1998     

Structure promoted electrochemical behavior and chemical stability of AgI-doped solid electrolyte in sulfide glass system

Ion-conducting chalcogenide glass is a promising solid electrolyte with excellent conductivity and energy density for all-solid-state batteries. A suitable ionic channel for carriers in the amorphous network is urgently needed. In this work, the structural evolution of co-doped metal cations (Ge and Ga) in the glass matrix and its influence on electrochemical behavior were studied using a series of Ge_xGa_16-xSb₆₄S₁₂₈-40AgI glass samples. The macroscopic properties of samples were examined by X-ray diffraction (XRD), differential scanning calorimetry (DSC), and Raman tests. The electrochemical behavior of samples was investigated by AC impendence spectroscopy and cyclic voltammetry (CV) measurement. Furthermore, a deliquescence experiment was applied for the chemical stability test of glass samples. The ionic conductivity of samples was developed by adding Ga components. Notably, the electrochemical window of electrolytes was remarkably wide at approximately 5 V. The resistance of samples to humidity was characterized by the decreased Raman peaks. Analysis results show that the Ga-related bonding structure evidently increased the chemical stability compared with the non-Ga sample. This work provides an insight into the effective and stable ions transport, especially in the Ge(Ga)SbS glass system. These results promote the further investigation of sulfide solid electrolytes and practical application of all-solid-state batteries.     

复合桩基桩土非线性相互作用的数值分析

为了对复合桩基桩土非线性相互作用的工作机理进行深入分析,利用ABAQUS对常规桩筏基础(3D桩距)和复合桩基(6D桩距)进行了三维弹塑性分析.利用无厚度接触面单元模拟筏板-桩-土的非线性接触特性,采用Mohr-Cou lomb弹塑性本构模型描述土的非线性特性,桩设为弹性,得到了沉降、桩土荷载分担比、土体绕桩流动等变化情况,并对二者进行了对比分析.分析结果基本反映了桩-土-筏的实际工作性状,并验证了复合桩基理论的正确性.