Comparison of three control strategies for optimization of spray dryer operation

Spray drying is the preferred process to reduce the water content of many chemicals, pharmaceuticals, and foodstuffs. A significant amount of energy is used in spray drying to remove water and produce a free flowing powder product. In this paper, we present and compare the performance of three controllers for operation of a four-stage spray dryer. The three controllers are a proportional-integral (PI) controller that is used in industrial practice for spray dryer operation, a linear model predictive controller with real-time optimization (MPC with RTO, MPC-RTO), and an economically optimizing nonlinear model predictive controller (E-NMPC). The MPC with RTO is based on the same linear state space model in the MPC and the RTO layer. The E-NMPC consists of a single optimization layer that uses a nonlinear system of ordinary differential equations for its predictions. The PI control strategy has a fixed target that is independent of the disturbances, while the MPC-RTO and the E-NMPC adapt the operating point to the disturbances. The goal of spray dryer operation is to optimize the profit of operation in the presence of feed composition and ambient air humidity variations; i.e. to maximize the production rate, while minimizing the energy consumption, keeping the residual moisture content of the powder below a maximum limit, and avoiding that the powder sticks to the chamber walls. We use an industrially recorded disturbance scenario in order to produce realistic simulations and conclusions. The key performance indicators such as the profit of operation, the product flow rate, the specific energy consumption, the energy efficiency, and the residual moisture content of the produced powder are computed and compared for the three controllers. In this simulation study, we find that the economic performance of the MPC with RTO as well as the E-NMPC is considerably improved compared to the PI control strategy used in industrial practice. The MPC with RTO improves the profit of operation by 8.61%, and the E-NMPC improves the profit of operation by 9.66%. The energy efficiency is improved by 6.21% and 5.51%, respectively.     

Model based feedforward control of an industrial glass feeder

This article presents the automation of set point changes of an industrial glass feeder in container glass production. A model is proposed consisting of multiple first order partial differential equations (PDEs). Based on the derived model a feedforward control approach is presented. The approach allows for the calculation of control inputs out of reference trajectories of the system outputs and is used to perform automated set point changes with short transition time. Finally, the approach is implemented at an industrial glass feeder. Measurement results from the Thüringer Behälterglas GmbH (Schleusingen, Germany) are included.     

Model predictive control of a fluidized bed dryer with an inline NIR as moisture sensor

Fluid bed drying and near infrared (NIR) spectroscopy are technologies widely used to dry and measure moisture content and other pharmaceutical granular materials’ attributes, respectively. This work focused on controlling a bench top fluid bed dryer using an industrial control system, the model predictive control (MPC) strategy, and NIR measurements of the moisture content of pharmaceutical powders. The MPC was implemented to reach the desired drying end-point while simultaneously manipulating two variables: airflow and inlet air temperature. These two manipulated variables were constrained based on the physical and chemical behavior of the process. The results showed that the use of the MPC with the inline NIR produced an adequate control performance and resulted at the same time in a reduction in energy consumption of as much as 60% in one case when compared with the current industrial practices.     

颗粒物料传热传质过程的数值仿真与实验研究

转筒干燥器的主体是略带倾斜并能回转的圆筒体，是一种既受高温加热又兼输送的设备，它的应用十分广泛。该文较为系统地进行了转筒干燥器物料的传热传质过程的分析，并进行了试验研究。利用质量平衡方程、能量平衡方程、传热方程和传质方程，建立了颗粒物料在转筒干燥器干燥过程中的传热传质数学模型，该模型能够较好地预测干燥过程中物料颗粒的温度和含湿量的变化，仿真结果与实验结果吻合良好。该仿真程序对此类问题的研究具有参考价值。     

Laplace transform finite volume modeling of water hammer along fluid–structure interaction

Water hammer or propagation of pressure waves generates profound forces through pipelines of industrial high pressure processes which causes structural vibration of the pipe in both radial and axial directions. To model the sudden rupture of a pipeline system the fluid–structure interaction, FSI, is taken into account by coupling the structural vibration equations to the fluid dynamic equation. In this paper, Laplace transform finite volume, LTFV, which is a new technique along the finite element method is developed to treat fluid transient and the structural vibration equations respectively.To evaluate the numerical results, a Thermal Hydraulic Test Loop (THTL facility) which has been designed and constructed for experimental research on the physical phenomena, characteristics and performance of the safety systems involved in plants is used. To conduct tests for representing a sudden break condition in the loop, the THTL facility has been equipped by devices and sensors to record pressure and vibration signals during simulated accidents. Under steady condition, by an electrical signal an electric valve, Break valve, is opened and simultaneously pressure along pipe vibration signals close to valve is recorded. Comparing the experimental data to results from numerical modeling validated the implemented method.     

机器人喷涂过程中的喷炬建模及仿真研究

本文在研究了喷涂机器人的喷炬特性后，根据物理模型采用了一种简化的数学模型来 描述在喷炬流场中的涂料流量分布函数．并从上述函数出发，进一步得到了喷涂的涂料沉积 方程．根据仿真实验与实际喷涂的数据进行比较，证明了模型的正确性．这一喷炬模型是喷 涂机器人离线编程系统的重要组成部分．     

A structured modeling approach for dynamic hybrid fuzzy-first principles models

Hybrid fuzzy-first principles models can be attractive if a complete physical model is difficult to derive. These hybrid models consist of a framework of dynamic mass and energy balances, supplemented with fuzzy submodels describing additional equations, such as mass transformation and transfer rates. In this paper, a structured approach for designing this type of model is presented. The modeling problem is reduced to several simpler problems, which are solved independently: hybrid model structure and subprocess determination, subprocess behavior estimation, identification and integration of the submodels to form the hybrid model. The hybrid model is interpretable and transparent. The approach is illustrated using data from a (simulated) fed-batch bioreactor.     

Numerical solution of a phase field model for incompressible two-phase flows based on artificial compressibility

We present an artificial compressibility based numerical method for a phase field model for simulating two-phase incompressible viscous flows. The phase model was proposed by Liu and Shen [Physica D. 179 (2003) 211–228], in which the interface between two fluids is represented by a thin transition region of fluid mixture that stores certain amount of mixing energy. The model consists of the Navier–Stokes equations coupled with the Allen–Cahn equation (phase field equation) through an extra stress term and a transport term. The extra stress in the momentum equations represents the phase-induced capillary effect for the mixture due to the surface tension. The coupled equations are cast into a conservative form suitable for implementation with the artificial compressibility method. The resulting hyperbolic system of equations are then discretized with weighted essentially non-oscillatory (WENO) finite difference scheme. The dual-time stepping technique is applied for obtaining time accuracy at each physical time step, and the approximate factorization algorithm is used to solve the discretized equations. The effectiveness of the numerical method is demonstrated in several two-phase flow problems with topological changes. Numerical results show the present method can be used to simulate incompressible two-phase flows with small interfacial width parameters and topological changes.     

Development of a parallel implicit solver of fluid modeling equations for gas discharges

A parallel fully implicit PETSc-based fluid modeling equations solver for simulating gas discharges is developed. Fluid modeling equations include: the neutral species continuity equation, the charged species continuity equation with drift-diffusion approximation for mass fluxes, the electron energy density equation, and Poisson's equation for electrostatic potential. Except for Poisson's equation, all model equations are discretized by the fully implicit backward Euler method as a time integrator, and finite differences with the Scharfetter–Gummel scheme for mass fluxes on the spatial domain. At each time step, the resulting large sparse algebraic nonlinear system is solved by the Newton–Krylov–Schwarz algorithm. A 2D-GEC RF discharge is used as a benchmark to validate our solver by comparing the numerical results with both the published experimental data and the theoretical prediction. The parallel performance of the solver is investigated.     

丙烯聚合动态模型在牌号切换过程中的应用

分析了聚丙烯牌号切换过程中的过渡策略,并在Hypol工艺上,利用丙烯聚合动态模型和熔融指数(MFR)的软测量,结合工业实际生产数据,对聚丙烯的牌号切换过程进行了模拟,结果显示,利用丙烯聚合动态模型可以如实地反应聚丙烯的牌号切换过程,通过模拟的结果,可以找出最佳牌号切换策略,制定出最佳的生产过渡方案,取得明显的经济效益。     

Polymer grade transition control using advanced real-time optimization software

This paper describes the application of an industrial real-time optimization package (ROMeo¹) to the nonlinear model predictive control (NLMPC) of a simulated polymer grade transition. The NLMPC algorithm is formulated using orthogonal collocation to integrate the model equations, and sequential quadratic programming to solve the resulting nonlinear programming problem. A receding horizon estimation scheme and, separately, a Luenberger observer are designed to reconstruct unmeasured states. The resulting algorithm is demonstrated on two simulated polymerization case studies: (i) continuous methyl methacrylate and (ii) gas-phase polyethylene.     

Decoupled Energy Stable Schemes for a Phase Field Model of Three-Phase Incompressible Viscous Fluid Flow

We develop a numerical approximation for a hydrodynamic phase field model of three immiscible, incompressible viscous fluid phases. The model is derived from a generalized Onsager principle following an energetic variational formulation and is consisted of the momentum transport equation and coupled phase transport equations. It conserves the volume of each phase and warrants the total energy dissipation in time. Its numerical approximation is given by a set of easy-to-implement, semi-discrete, linear, decoupled elliptic equations at each time step, which can be solved efficiently using fast solvers. We prove that the scheme is energy stable. Mesh refinement tests and three numerical examples of three-phase viscous fluid flows in 3D are presented to benchmark the effectiveness of the model as well as the efficiency of the numerical scheme.     

Gluon matter plasma in the compact star core within a fluid QCD model

The structure of a compact star core filled with gluon matter plasma is investigated within the fluid-like QCD framework. The energy-momentum tensor, density and pressure relevant to gluonic plasma having the nature of a fluid bulk of gluon sea are derived within the model. It is shown that the model provides a new equation of state for the perfect fluid with only a single parameter of fluid distribution, ϕ(x). The results are applied to constructing the equation of state describing the gluonic plasma dominated compact star core. The equations of pressure and density distribution are solved analytically for a small compact star core radius. The phase transition of the plasma near the core surface is also discussed.     

Langevin Particle: A Self‐Adaptive Lagrangian Primitive for Flow Simulation Enhancement

We develop a new Lagrangian primitive, named Langevin particle, to incorporate turbulent flow details in fluid simulation. A group of the particles are distributed inside the simulation domain based on a turbulence energy model with turbulence viscosity. A particle in particular moves obeying the generalized Langevin equation, a well known stochastic differential equation that describes the particle's motion as a random Markov process. The resultant particle trajectory shows self‐adapted fluctuation in accordance to the turbulence energy, while following the global flow dynamics. We then feed back Langevin forces to the simulation based on the stochastic trajectory, which drive the flow with necessary turbulence. The new hybrid flow simulation method features nonrestricted particle evolution requiring minimal extra manipulation after initiation. The flow turbulence is easily controlled and the total computational overhead of enhancement is minimal based on typical fluid solvers.     

Direct identification of continuous time delay systems from step responses

In this paper, a simple yet robust method is proposed for identification of linear continuous time delay processes from step responses. New linear regression equations are directly derived from the process differential equation. The regression parameters are then estimated without iterations, and an explicit relationship between the regression parameters and those in the process are given. Due to use of the process output integrals in the regression equations, the resulting parameter estimation is very robust in the face of large measurement noise in the output. The proposed method is detailed for a second-order plus dead-time model with one zero, which can approximate most practical industrial processes, covering monotonic or oscillatory dynamics of minimum-phase or non-minimum-phase processes. Such a model can be obtained without any iteration. The effectiveness of the identification method has been demonstrated through simulation.     

Performance of a new partitioned procedure versus a monolithic procedure in fluid–structure interaction

Fluid–structure interaction (FSI) can be simulated in a monolithic way by solving the flow and structural equations simultaneously and in a partitioned way with separate solvers for the flow equations and the structural equations. A partitioned quasi-Newton technique which solves the coupled problem through nonlinear equations corresponding to the interface position is presented and its performance is compared with a monolithic Newton algorithm. Various structural configurations with an incompressible fluid are solved, and the ratio of the time for the partitioned simulation, when convergence is reached, to the time for the monolithic simulation is found to be between 1/2 and 4. However, in this comparison of the partitioned and monolithic simulations, the flow and structural equations have been solved with a direct sparse solver in full Newton–Raphson iterations, only relatively small problems have been solved and this ratio would likely change if large industrial problems were considered or if other solution strategies were used.     

Improved process control of an industrial sludge centrifuge-dryer installation through binary logistic regression modeling of the fouling issues

Biological wastewater treatment generates huge amounts of waste sludge which need to be dewatered and eventually dried to minimize transportation and incineration costs. A characteristic feature of sludge in this context is that it turns into a sticky substance during its drying process inducing fouling problems in the drying installation. At the wastewater treatment plant of Monsanto in Antwerp, Belgium, one enclosed centrifuge-dryer system is used to dry the sludge. In the past, this installation had to be shut down regularly due to dryer fouling problems. To avoid these operational problems, a binary logistic regression analysis is presented in this research based on a 5-year database, resulting in an empirical model for the evaluation of the dryer fouling risk as a function of the sludge feed characteristics. The model inputs are the sludge volume index (SVI) and the dosing of clay additive and tertiary (flotation) sludge, the latter containing polyaluminumchloride (PACl), to the sludge feed of this particular system.By exploiting the knowledge captured by this model, the derived control strategy is based on the value of the SVI. Whenever the SVI is high the original high clay dosing to the feed needs to be maintained. At moderate SVI values, implying an intrinsically better sludge dewaterability, the strategy dictates a reduction in the clay dosing to the sludge feed to have a reduced sludge solids dryness after dewatering, thereby avoiding that the sludge exhibits its most sticky phase when passing the most fouling sensitive part of the dryer. When the SVI is lower than 50 mL/g the control strategy states that conditioning of the sludge with PACl is required to mask the stickiness instead of postponing it, avoiding that the stickiness of the sludge already hampers the dewatering stage of the process.     

Automatic control of the simulated moving bed process for C8 aromatics separation using asymptotically exact input/output-linearization

An approach to automatic control of the simulated moving bed process (SMB) applied to the separation of C₈ aromatics is presented. The principle of asymptotically exact input/output-linearization is used. The controller is based on a nonlinear state estimator using the true moving bed model (TMB). The estimator receives measurement data from four spectroscopic measurement cells. The problem of moving measurement positions with respect to the TMB model is addressed. An exactly linearizing feedback of the estimated states is designed using the nonlinear TMB model equations. The performance of the controller is shown in simulations using a detailed SMB model as a representative of the real process.     

Physics-based flow estimation of fluids

We present a physics-based method to compute the optical flow of a fluid. In most situations, gray level changes in an image do not provide sufficient information to completely ascertain optical flow, necessitating the use of a supplementary constraint. For this, the smoothness constraint is often employed. This constraint is, however, general and does not express well a priori knowledge of a specific object. We therefore propose a method in which physical equations describing the object are used as supplementary constraints. In this way, more accurate flow estimation can be achieved. The physical model employed is a combination of the continuity equation and Navier-Stokes’ equations. After describing how we integrate these equations into fluid flow estimation, we demonstrate the effectiveness of the proposed method by presenting experimental results of its application to simulated and real Karman flows.     

The stickiness intention of group-buying websites: The integration of the commitment–trust theory and e-commerce success model

The success of consumer-to-business (C2B) group-buying websites (GBWs) relies heavily on consumers’ relationships with the GBWs, a topic not yet adequately investigated in the existing literature. In addition, there is a transition from the technical and/or transactional views in e-commerce studies to a relational view. However, such studies have focused on business-to-consumer contexts. By integrating the e-commerce success model and commitment–trust theory, we developed a model of GBW stickiness, which is examined using data collected from 280 GBW users. The results indicated that relationship commitment, trust, and satisfaction were key determinants of stickiness intention. Theoretical and practical implications are also discussed.