A unified lubrication approach for the design of a coat-hanger die

A simple unified lubrication approach has been proposed to design a coat-hanger die that can deliver wide and uniform liquid sheets. This approach requires that the wall stress in the manifold be constant. With this constraint, any inelastic non-Newtonian fluid model can be used to describe the liquid motion inside the die. Fluid models that can represent the pseudoplastic or viscoplastic behavior of polymeric liquids have been selected for illustration. A general equation that can be solved to determine the effect of production variations on flow uniformity inside the die has also been derived.     

A least squares approach to model reduction and the design of low-order controllers

State space process models and feedback control laws are simplified by eliminating selected state variables using a modified least squares technique. The revised technique uses random perturbations to excite the high order system and the resulting reduced-order models tend to be more robust than those derived using conventional least squares and deterministic inputs. Low-order controllers were designed for a pilot scale, double effect evaporator using the modified least squares approach. These controllers performed well in both experimental and simulated response tests.     

Simplified design of proportional-integral-derivative (PID) controller to give a time domain specification for high order processes

An efficient simplified method is proposed for the time domain design of industrial proportional-integral-derivative (PID) controllers and lead-lag compensators for high order single input single output (SISO) systems. The proposed analytical method requires no trial error steps for a lead-lag compensator design in the time domain by using the root-locus method. A practical PID controller design method was obtained based on the corresponding lead-lag compensator to give a required time-domain specification. Simulation studies were carried out to illustrate the control performance of the controllers by the proposed method. The proposed PID controller and lead-lag compensator directly satisfied time domain control specifications such as damping ratio, maximum overshoot, settling time and steady sate error without trial and error steps. The suggested algorithm can easily be integrated with a toolbox in commercial software such as Matlab.     

Analytical design of PID controller cascaded with a lead-lag filter for time-delay processes

An analytical method for the design of a proportional-integral-derivative (PID) controller cascaded with a second-order lead-lag filter is proposed for various types of time-delay process. The proposed design method is based on the IMC-PID method to obtain a desired, closed-loop response. The process dead time is approximated by using the appropriate Pade expansion to convert the ideal feedback controller to the proposed PID·filter structure with little loss of accuracy. The resulting PID·filter controller efficiently compensates for the dominant process poles and zeros and significantly improves the closed-loop performance. The simulation results demonstrate the superior performance of the proposed PID·filter controller over the conventional PID controllers. A guideline for the closed-loop time constant, λ, is also suggested for the FOPDT and SOPDT models.     

Analytical design of proportional-integral controllers for the optimal control of first-order processes with operational constraints

A novel analytical design method of industrial proportional-integral (PI) controllers was developed for the optimal control of first-order processes with operational constraints. The control objective was to minimize a weighted sum of the controlled variable error and the rate of change in the manipulated variable under the maximum allowable limits in the controlled variable, manipulated variable and the rate of change in the manipulated variable. The constrained optimal servo control problem was converted to an unconstrained optimization to obtain an analytical tuning formula. A practical shortcut procedure for obtaining optimal PI parameters was provided based on graphical analysis of global optimality. The proposed PI controller was found to guarantee global optimum and deal explicitly with the three important operational constraints.     

A computer aided methodology for the design of decentralized controllers

The use of decentralized controller is justified if tuning is simplified and the resulting control system is failure tolerant. The ability to satisfy these criteria with a given plant depends, in turn, on the choices of control structure and tuning parameters. Interaction Measures (IM's) are analysis tools which aid the designer in addressing each of these choices in a rigorous, quantitative manner. This communication presents a synopsis of existing IM's and shows how these can form the basis of a computer aided methodology for the design of decentralized controllers.     

A unified approach to the synthesis of control structures for complex chemical plants

The problem of synthesis of process control structures for a chemical plant is formulated. The multilayer decomposition approach is used to classify disturbances in order to decompose control tasks into regulatory and optimizing control. The chemical plant is decomposed along the multiechelon concept to provide subsystmes for which optimizing and regulatory control structures are developed. Feedback optimizing control structures are introduced along with their attractiveness in translation of economic objectives into process variables.

The result is an algorithm to generate alternative control structures, mainly based on simple structural models.     

Two-degree-of-freedom output feedback controllers for nonlinear processes

In this work, a nonlinear output feedback control algorithm is proposed, in the spirit of model-state feedback control. The structure provides state estimates using a process model, the measured output, and the residual between the model output and the measured output. These estimates will track the process states at a rate determined by a set of tunable parameters. An algebraic transformation of the state estimates is incorporated in the control structure to ensure that the input/output gain of the observer matches the model upon which the static state feedback control law is based. The transformed states are then used in the control law. This leads to a controller of minimal order possessing integral action. The control structure is shown to have the same properties as the standard model-state feedback structure. The resulting algorithm is a two-degree of freedom control law, in the sense that the control action is not a function of the error only, but the output and the set point are processed in different ways. Finally, a simulation example using an exothermic CSTR operating at an open-loop unstable steady state is used to demonstrate the closed-loop performance of the proposed method.     

A unified model of property integration for batch and continuous processes

This article aims to present a general model for synthesis of property‐based resource conservation networks. The proposed model is applicable to batch and continuous processes. Therein, the process systems are characterized by properties instead of composition that is found in most published works to date in the area of resource conservation. By treating continuous process as a special case of batch processes, both kinds of operations can be optimized with a unified model that is developed on the basis of a superstructure. The overall framework of property network is adopted, where material reuse/recycle, interception, and waste treatment are all taken into consideration. Apart from direct reuse/recycle, interception devices are employed to improve stream properties for further recovery, whereas effluent treatment is needed for compliance with environmental discharge limits. In addition, storage vessels are employed in batch processes to override intrinsic time constraint. Four case studies are solved to illustrate the proposed approach. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

Hybrid simulation-optimization based approach for the optimal design of single-product biotechnological processes

In this work, we present a systematic method for the optimal development of bioprocesses that relies on the combined use of simulation packages and optimization tools. One of the main advantages of our method is that it allows for the simultaneous optimization of all the individual components of a bioprocess, including the main upstream and downstream units. The design task is mathematically formulated as a mixed-integer dynamic optimization (MIDO) problem, which is solved by a decomposition method that iterates between primal and master sub-problems. The primal dynamic optimization problem optimizes the operating conditions, bioreactor kinetics and equipment sizes, whereas the master levels entails the solution of a tailored mixed-integer linear programming (MILP) model that decides on the values of the integer variables (i.e., number of equipments in parallel and topological decisions). The dynamic optimization primal sub-problems are solved via a sequential approach that integrates the process simulator SuperPro Designer^® with an external NLP solver implemented in Matlab^®. The capabilities of the proposed methodology are illustrated through its application to a typical fermentation process and to the production of the amino acid L-lysine.     

A unified approach to determine principal permeability of fibrous porous media

This paper presents a unified approach (UA) to determining permeability in liquid composite molding. The UA applies both to the channel flow and the radial flow experiment and it unifies the data processing of almost all known permeability measurement methods. It permits principal permeability to be calculated from experimental measurements which are carried out in an arbitrary co-ordinate system. This paper describes the UA and its main features. Further, the UA is applied to a number of experimental results for radial flow and channel flow measurements to demonstrate its validity. In addition, the algorithms of current permeability measurement methods are classified according to the UA, and, where necessary, differences are discussed. Some data processing algorithms were found to contain weaknesses or shortcomings.     

A multiscale systems approach to microelectronic processes

This paper describes applications of molecular simulation to microelectronics processes and the subsequent development of techniques for multiscale simulation and multiscale systems engineering. The progression of the applications of simulation in the semiconductor industry from macroscopic to molecular to multiscale is reviewed. Multiscale systems are presented as an approach that incorporates molecular and multiscale simulation to design processes that control events at the molecular scale while simultaneously optimizing all length scales from the molecular to the macroscopic. It is discussed how design and control problems in microelectronics and nanotechnology, including the targeted design of processes and products at the molecular scale, can be addressed using the multiscale systems tools. This provides a framework for addressing the “grand challenge” of nanotechnology: how to move nanoscale science and technology from art to an engineering discipline.     

Smith predictor based fractional-order PI control for time-delay processes

A new fractional-order proportional-integral controller embedded in a Smith predictor is systematically proposed based on fractional calculus and Bode’s ideal transfer function. The analytical tuning rules are first derived by using the frequency domain for a first-order-plus-dead-time process model, and then are easily applied to various dynamics, including both the integer-order and fractional-order dynamic processes. The proposed method consistently affords superior closed-loop performance for both servo and regulatory problems, since the design scheme is simple, straightforward, and can be easily implemented in the process industry. A variety of examples are employed to illustrate the simplicity, flexibility, and effectiveness of the proposed SP-FOPI controller in comparison with other reported controllers in terms of minimum the integral absolute error with a constraint on the maximum sensitivity value.     

A soft-sensor approach to flow regime detection for milling processes

Due to the many industrial applications of rotating drums, a wide range of operating conditions, including different particle flow regimes, are used. Knowledge of the flow regimes inside a drum is beneficial for process optimisation and control. This paper shows how the unique insights provided by a discrete element method (DEM) model of a rotating drum can be used to create soft-sensor models that detect flow regime. Impacts between particles and the drum wall are simulated, from which the feature variables are extracted. A soft-sensor model which links these feature variables to flow regime is constructed using the multivariate statistical technique of Fisher discriminant analysis (FDA). This model is able to successfully classify new testing data, which are not used in soft-sensor model training, as belonging to rolling, cascading and cataracting flow regimes.     

基于改进的时滞分析算法的化工过程故障定位

在现代化工过程中,故障在局部出现后往往会通过物流连接、控制系统的作用下传递到整个流程。识别故障的传播机理,诊断出故障的根本原因对于生产的经济性或安全性都具有重大的意义。时滞分析是一种基于数据的算法,具有不依赖机理模型,获得的结果易于解读等特性,被认为是一种很实用的故障识别算法。将小波降噪技术、全流程节点划分等方法与时滞分析算法相结合,可以较好地克服化工过程在线数据的强噪声特点以及模型中冗余时滞的干扰,改进的算法具有更好的鲁棒性,具有化工全流程诊断的能力。通过对TE模型的故障定位研究,结果显示该方法可对异常工况进行故障隔离,并能给出扰动传播路径,有助于故障机理的研究。     

A unified approach to the hydraulics and mass transfer in randomly packed towers

New robust correlations and mechanistic model of macroscopic fluid dynamic and gas–liquid mass transfer characteristics for randomly packed towers were developed based on first principles, neural network computing and dimensional analysis (artificial neural network and dimensional analysis, ANN–DA). These tools concerned the loading and flooding capacities, the total liquid hold-up, the irrigated pressure drop, the local volumetric liquid-side, k_La, and gas-side, k_Ga, mass transfer coefficients, the overall volumetric, K_La and K_Ga, mass transfer coefficients, and the packing fractional wetted area. Validation of these tools was performed by interrogating a broad experimental database including over 10,750 measurements published in the literature over the past seven decades. The fully-predictive mechanistic model proved powerful in forecasting the tower hydraulics below the loading point without requiring any adjustable parameter. On the other hand, the ANN–DA correlations proved highly powerful in correlating the tower fluid dynamics and gas–liquid mass transfer regardless of the operating flow regime. These approaches were also benchmarked with respect to the comprehensive Billet and Schultes (Trans. Industr. Chem. Eng. 77 (1999) 498) phenomenological approach and the classical Onda et al. (J. Chem. Eng. Japan 1 (1968) 56) mass transfer correlations.     

A unified approach to conformational statistics of classical polymer and polypeptide models

We present a unified method to generate conformational statistics, which can be applied to any of the classical discrete-chain polymer models. The proposed method employs the concepts of Fourier transform and generalized convolution for the group of rigid-body motions in order to obtain probability density functions of chain end-to-end distance. In this paper, we demonstrate the proposed method with three different cases: the freely rotating model, independent torsion-angle energy model, and interdependent pair-wise energy model (the last two are also well-known as the rotational isomeric state model). As for numerical examples, for simplicity, we assume homogeneous polymer chains. For the freely rotating model, we verify the proposed method by comparing with well-known closed-form results for mean-squared end-to-end distance. In the interdependent pair-wise energy case, we take polypeptide chains such as polyalanine and polyvaline as examples.     

A new approach to the design of stable proteins

We propose a simple algorithm to design a sequence which fitsa given protein structure with a given energy. The algorithmis a modification of the Metropolis Monte Carlo scheme in sequencespace with an evolutionary temperature which sets the energyscale. There is a one to one correspondence between this optimizationscheme and the Ising model of ferromagnetism. This analogy impliesthat the design algorithm does not encounter multiple-minimaproblems and is very fast. The algorithm is tested by ‘predicting’the primary structures of four proteins. In each case the calculatedprimary structures had statistically significant homology withthe natural structures.