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Control model

Chelation Control Model- "Anti-Cram" selectivity... [Pg.92]

Batch Control Models and Terminology, ISA-dS88.01, Instmment Society of America, Research Triangle Park, N.C., 1995. [Pg.80]

More recent work has shown that the observed variation in propagation rate constants with composition is not sufficient to define the polymerization rates.5" 161,1152 There remains some dependence of the termination rate constant on the composition of the propagating chain. Thus, the chemical control (Section 7.4.1) and the various diffusion control models (Section 7.4.2) have seen new life and have been adapted by substituting the terminal model propagation rate constants (ApXv) with implicit penultimate model propagation rate constants (kpKY -Section 7.3.1.2.2). [Pg.366]

In evaluating the kinetics of copolymerization according to the chemical control model, it is assumed that the termination rate constants k,AA and A,Br are known from studies on homopolymerization. The only unknown in the above expression is the rate constant for cross termination (AtAB)- The rate constant for this reaction in relation to klAA and kmB is given by the parameter . [Pg.367]

Values of 0 required to fit the rate of copolymerization by the chemical control model were typically in the range 5-50 though values <1 are also known. In the case of S-MMA copolymerization, the model requires 0 to be in the range 5-14 depending on the monomer feed ratio. This "chemical control" model generally fell from favor wfith the recognition that chain diffusion should be the rate determining step in termination. [Pg.368]

In the classical diffusion control model it is assumed that propagation occurs according to the terminal model (Scheme 7.1). The rate of the termination step is limited only by the rates of diffusion of the polymer chains. This rate may be dependent on the overall polymer chain composition. However, it does not depend solely on the chain end.166,16... [Pg.368]

In eq. 68, is defined as in the chemical control model but this expression is cast in terms of the monomer feed composition rather than the radical chain end population. [Pg.369]

Mcllvried and Massoth [484] applied essentially the same approach as Hutchinson et al. [483] to both the contracting volume and diffusion-controlled models with normal and log—normal particle size distributions. They produced generalized plots of a against reduced time r (defined by t = kt/p) for various values of the standard deviation of the distribution, a (log—normal distribution) or the dispersion ratio, a/p (normal distribution with mean particle radius, p). [Pg.73]

An excellent way to treat such data is to use reaction probability models.(1,2) In the NMR analysis of tacticity, it is frequently possible to distinguish whether the configuration is chain-end controlled or catalytic-site controlled during polymerization. Various statistical models have been proposed. The chain-end controlled models include Bemoullian (B), and first- and second-order Markovian (Ml and M2) statistics.(1) The simplest catalytic-site controlled model is the enantiomorphic site (E) model.(3) The relationship between the chain-end and catalytic-site controlled models and possible hybrid models have been delineated in a recent article.(4)... [Pg.174]

Fl-Monltor Universal Safety Monitor and Controller-Model FM/U/B Flsons Instruments... [Pg.452]

Eurotherm 3 term controller - Model 818-S Sackville Trading Estate, Hove... [Pg.453]

One possibility for increasing the minimum porosity needed to generate disequilibria involves control of element extraction by solid-state diffusion (diffusion control models). If solid diffusion slows the rate that an incompatible element is transported to the melt-mineral interface, then the element will behave as if it has a higher partition coefficient than its equilibrium partition coefficient. This in turn would allow higher melt porosities to achieve the same amount of disequilibria as in pure equilibrium models. Iwamori (1992, 1993) presented a model of this process applicable to all elements that suggested that diffusion control would be important for all elements having diffusivities less than... [Pg.198]

BALZHISER, SAMUELS, AND Eliassen Chemical Engineering Thermodynamics BEQUETTE Process Control Modeling, Design and Simulation BEQUETTE Process Dynamics... [Pg.635]


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See also in sourсe #XX -- [ Pg.74 ]




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A Model for the Control of Metabolic Reaction Chains

A Physics-based, Control-oriented Model

Adaptive Low-Order Posi-Cast Control of a Combustor Test-Rig Model

Adaptive control model reference

Adaptive control/modelling

Adsorption diffusion-controlled kinetics model

Adsorption kinetics model mixed diffusion-kinetic-controlled

Allosteric control Monod-Wyman-Changeux model

Alternative models nucleation-controlled mechanisms

Application of neural networks to modelling, estimation and control

Barrier-controlled model

Batch process control activity model

Behavioral Model Control Theory

Cardiovascular Models and Control Fernando Casas, William D. Timmons

Case study implementation of feedback control systems based on hybrid neural models

Chelation control computational modeling

Chelation control model

Chemical Control Model

Collision- and Diffusion-Controlled Models

Computational modeling controlled radical

Computer Modeling and Control

Control model development

Control model development concentration dynamics

Control modeling and

Control models, respiratory

Control of the Kinematic model

Control probabilistic models

Control systems model parameters

Control theory models

Control theory, model-based

Control volume, environmental modeling

Control-Oriented SCR Model

Controlled Relaxation model

Controller design distributed model-based

Controller design model predictive

Copolymerization chemical control model

Copolymerization diffusion control models

Default Control Structure and Simplified Heat Transfer Models

Demand support control-model

Diffusion-control model

Diffusion-controlled model

Diffusion-controlled model computer simulation results

Diffusion-controlled model concentration profiles

Diffusion-controlled model kinetic rate

Diffusion-controlled model kinetics

Diffusion-controlled oxidation molecular models

Diffusion-controlled reactions. Black sphere model

Discrete control models

Distillation control scheme design using dynamic models

Distillation control scheme design using steady-state models

Eccentric Control Rod in Two-group Model

Enantiomorphic site control statistical model

Fault Propagation Model for Control Valve Represented as SDG

Fundamentals of Mathematical Modeling, Simulation, and Process Control

Gene control model

General model control

Generic Model Control

Hydrous oxide control model

Inter-model control

Internal Model Control (IMC)

Internal Model Control (IMC) Tuning Rules

Internal model control

Internal model control system

Intracellular control level modeling

Kinetic-controlled models

Local control theory model parameters

Mathematical Modeling and Process Control

Mathematical models of diffusion-controlled oxidation

Metabolic control models

Metabolic control models comparisons

Microprocessor-controlled model

Mobility control simulation model

Model Algorithmic Control

Model Predictive Control of Batch Processes (SHMPC)

Model Predictive Heuristic Control

Model Study via Chelation Control in the Aldol Reaction by Kalesse

Model predictive control

Model predictive control (MPC

Model predictive control advantages

Model predictive control algorithms

Model predictive control constraints

Model predictive control controller

Model predictive control description

Model predictive control disadvantages

Model predictive control dynamic programming

Model predictive control enhancements

Model predictive control history

Model predictive control integrators

Model predictive control moving horizon

Model predictive control nonlinearity

Model predictive control prediction horizon

Model predictive control standard quadratic programming

Model predictive control step-response

Model predictive control tuning parameters

Model reduction and hierarchical controller design

Model reference adaptive control (MRAC)

Model systems, kinetically controlled

Model-Based CD Control Performance

Model-Based Control and Optimization

Model-Based and ANN Control

Model-Predictive Control of Continuous Processes

Model-View-Controller

Model-based closed-loop control

Model-based control

Model-based control algorithms

Model-based control performance

Model-free control system

Modeling of Creep-Controlled Crack Growth

Modeling, linear control system

Modelling biological controls

Models Based on a Rate-Controlling Step

Models for On-Line Control

Models for diffusion-controlled, steady-state processes

Models size control

Neural Network-Based Model Reference Adaptive Control

Nonlinear Internal Model Control

Nonlinear model predictive control

Nonlinear model predictive controller

Personal control model

Polymer Actuators Modeling and Control

Post-transcriptional control model

Predictive modeling/control

Process Modeling and Control

Process Modelling and Control

Process Monitoring, Modeling and Control

Process control empirical models

Process control linear models

Process control models

Process control nonlinear models

Process control physical models

Process control/design/modelling

Propagation-Controlled Model

Quantitative models of diffusion-controlled adsorption

Radical polymerization controlled chain length models

Rate controlled process models

Rate controlled process models pore diffusion

Rate controlled process models solid film

Rate-controlled sorption model

Rate-controlled sorption transport model

Reaction diffusion control model

Remote control model

Ring of Control Rods in Two-group Model

Self-control models

State-Space Model for Control Design

Stationary self-control model

Steady-state model feedforward control

Steps in chemical process modelling control

Stochastic model predictive control

Surface models Rigidity control

TB Model Exposure Control Plan

Template-Controlled Growth of Model Catalysts

Theoretical models of diffusion-controlled adsorption kinetics

Valve, control dynamic model

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