Dynamic Chemical Processes Research Articles

The identification of nonlinear models for process control using tailored “plant-friendly” input sequences

Abstract This paper considers certain practical aspects of the identification of nonlinear empirical models for chemical process dynamics. The primary focus is the identification of second-order Volterra models using input sequences that offer the following three advantages: (1) they are “plant friendly;” (2) they simplify the required computations; (3) they can emphasize certain model parameters over others. To provide a quantitative basis for discussing the first of these advantages, this paper defines a friendliness index f that relates to the number of changes that occur in the sequence. For convenience, this paper also considers an additional nonlinear model structure: the Volterra–Laguerre model. To illustrate the practical utility of the input sequences considered here, second-order Volterra and Volterra–Laguerre models are developed that approximate the dynamics of a first-principles model of methyl methacrylate polymerization.

Constrained Optimization of Nonlinear, Dynamic Chemical Processes – A Normalized Form Approach

In chemical manufacturing processes, optimization problems with differential-algebraic constraints are frequently encountered. In general, these problems are difficult to solve and solution approaches are usually based on discretization schemes. This paper proposes an alternative method to determine optimal setpoint trajectories for a class of dynamic systems with differential-algebraic constraints. The method exploits di ff erential flatness to explicitly eliminate the differential state equations. The resulting optimization problem is an algebraic, nonlinearly constrained optimization problem, and can be solved by nonlinear programming. The proposed approach has the potential to reduce the amount of on-line computation required to solve a specific class of these problems in real-time.

Environmental high resolution electron microscopy of gas‐catalyst reactions

Environmental electron microscopy has become an important scientific method for fundamental studies of dynamic chemical reaction processes in heterogeneous catalysis and of catalytic growth of carbon nanotubes. Outstanding contributions are resulting from the ability to observe gas‐catalyst surface reactions in situ, on the atomic scale. A great deal of structural and chemical information including lattice modification of working catalysts is possible. This is key to understanding novel reaction processes, including release mechanism of structural oxygen in oxide catalysts in selective oxidation of hydrocarbons and to designing improved catalysts. This brief survey of the recent spectacular developments in environmental high resolution electron microscopy shows that new opportunities are being opened up in catalysis.

Brain imaging. Functional consequences of ethanol in the central nervous system.

In recent years, sophisticated methods have been developed to view structure and function within the living brain. Functional imaging methods are used to visualize dynamic chemical processes that are linked to brain activity. Increased neural activity, for example, leads to greater glucose and oxygen consumption and greater regional rates of blood flow to meet elevated energy demands. Mapping these changes provides quantitative visual descriptions of localized changes in brain activity that result from behavioral or pharmacological manipulations. This chapter first describes several current methods and how they are used to study the effects of alcohol on brain function. In the second part, the effects of acute intoxication are discussed with emphasis on the complex nature of alcohol's effects in the central nervous system, which depend on dose, time since administration, and environmental context. In the final part, the functional consequences of long-term exposure to alcohol as well as diseases associated with chronic alcoholism are reviewed.

Positron emission tomography of large rock samples using a multiring PET instrument

The technique of positron emission tomography (PET) is well established in the field of medical imaging. Non-medical applications have also been shown to be valuable in the measurement of dynamic chemical processes, specifically in the determination of the characteristics of small rock samples. Since rock is more dense than tissue, the problems of attenuation and scatter are accentuated. However, we are able to show that measurement of porosity in a large rock sample (21.5 cm diameter) is indeed practicable using three-dimensional (3-D) acquisition techniques. Due to multiple scattering of the photons in the rock and the cylindrical symmetry of the experiment, we measured a scatter distribution which is approximately homogeneous, allowing a correction for scattered radiation with a simple method. The problems of determining attenuation coefficients and applying a scatter correction makes absolute quantisation difficult. However, relative changers in porosity within the sample can be measured with a spatial resolution not appreciably different from that in water.

Quartz crystal impedance studies at 10 MHz of viscoelastic liquids and films

A rapid measurement of the components R and XL of AT-cut quartz crystal electroacoustic impedance at 10 MHz is reported. Parametric impedance plane plots (XLvs. R) are introduced to analyse the effect of mass/volume and viscoelastic changes in the films and liquids in contact with the quartz crystal during dynamic chemical or electrochemical processes. Experimentaldata for selected systems, viscoelastic films and liquids, self-assembledlayers and electroactive polymers, are presented. These results are discussedon the basis of the model of Granstaff and Martin to describe the real andimaginary components of the Butterworth–van Dyke (BVD) equivalen circuit impedance in terms of the density, mass and shear modulus of the viscoelastic film or liquid. The possibility of separating the inertial (rigid) mass and the viscoelastic components of quartz impedance when dynamic processes take place is analysed for the selected experimental data presented.

Detection of equipment faults in automatically controlled processes

AbstractBased on the UBET, a new strategy for identifying faulty equipment for dynamic chemical processes under automatic control is presented. The strategy is designed to distinguish between measurement biases, controller biases, and process leaks. For illustration purposes, application is given to a level control process under pseudo‐steady state. This approach was inspired by the work of Rollins and Devanathan to identify biased measurements under dynamic conditions. Advantages of this method are that it is not computationally intensive, can accurately detect and specifically identify the type of fault, and can accurately determine the time when the fault occurs.

Flexibility Analysis of Dynamic Chemical Processes

This paper considers the development of a framework for the assessment of feasibility and flexibility of dynamic chemical processes. The dynamic feasibility find dynamic flexibility analysis problems are formulated as two-stage semi-infinite dynamic optimization problems. It is shown that, when the uncertainty considered is time-invariant or its profile over time is known, both formulations reduce to dynamic optimization problems that can be solved using currently available techniques. The applicability of the approach is illustrated with an example from the area of batch reactors operation.

Dynamic Chemical Processes of Detonations: Underwater Explosion and Combustion Processes With the use of Water as an Oxidant

AbstractThe possibility of producing underwater unconfined explosions with the use of propylcarborane as a fuel and water as an oxidant was demonstrated experimentally. The specific TNT equivalent of the energy release in the explosion reaction between propylcarborane and water was found to be 1.5 times higher than conventional explosives. A possibility of organizing the combustion of initially unmixed propylcarborane and water was experimentally proven as well

Dynamics of chemical processes in polar solvents.

Understanding solution-phase chemistry requires a microscopic description of the electronic structure of the reacting molecules, and of the complex influence of the solvent medium on the reaction energetics and dynamics. Processes involving reactant charge-transfer are of particular importance in chemistry and biochemistry, and are strongly influenced by polar media. Recent advances in experimental ultrafast laser spectroscopy and in computer simulation are working together to provide insight into the underlying molecular principles governing this class of processes in solution.

Calculation of multicomponent chemical equilibria in gas-solid-liquid systems; calculation methods, thermochemical data, and applications to studies of high-temperature volcanic gases with examples from Mount St. Helens

This paper documents the numerical formulations, thermochemical data base, and possible applications of computer programs, SOLVGAS and GASWORKS, for calculating multicomponent chemical equilibria in gas-solid-liquid systems. SOLVGAS and GASWORKS compute simultaneous equilibria by solving simultaneously a set of mass balance and mass action equations written for all gas species and for all gas-solid or gas-liquid equilibria. The programs interface with a thermo-chemical data base, GASTHERM, which contains coefficients for retrieval of the equilibrium constants from 25[degrees] to 1200[degrees]C. The programs and data base model dynamic chemical processes in 30- to 40-component volcanic-gas systems. The authors can model gas evaporation from magma, mixing of magmatic and hydrothermal gases, precipitation of minerals during pressure and temperature decrease, mixing of volcanic gas with air, and reaction of gases with wall rock. Examples are given of the gas-evaporation-from-magma and precipitation-with-cooling calculations for volcanic gases collected from Mt. St. Helens in September 1981. The authors predict: (1) the amounts of trace elements volatilized from shallow magma, deep magma, and wall rock, and (2) the solids that precipitate from the gas upon cooling. The predictions are tested by comparing them with the measured trace-element concentrations in gases and the observed sublimate sequence. This leads to themore » following conclusions: (1) most of the trace elements in the Mt. St. Helens gases are volatilized from shallow magma as simple chlorides; (2) some elements (for example, Al, Ca) exist dominantly in rock aerosols, not gases, in the gas stream; (3) near-surface cooling of the gases triggers precipitation of oxides, sulfides, halides, tungstates, and native elements; and (4) equilibrium cooling of the gases to 100[degrees]C causes most trace elements, except for Hg, Sb, and Se, to precipitate from the gas. 94 refs., 30 figs., 7 tabs.« less

Dynamic process simulation using a concurrent differential and algebraic solver

Rigorous modeling of dynamic chemical processes results in systems of differential and algebraic equations (DAEs) whose solution on sequential computers can be highly time consuming. A possible alternative for the solution of very large systems of DAEs is to use concurrent computation on multiprocessor computers, or multicomputers. The waveform relaxation (WR) method, an operator-splitting approach to the solution of such DAE systems, partitions the problem into several lower order systems (subsystems). These subsystems can then be solved using standard integration codes. This method results in algorithms with a highly parallelizable concurrent fraction and low sequential overhead, which are especially suitable for coarseand medium-grain MIMD distributed-memory machines. In this paper, we describe a new simulation code, DAWRS (Differential- Algebraic Waveform Relaxation Solver) to solve DAEs on parallel machines using the WR method. Using a rigorous model for distillation columns, we illustrate how this code can be efficiently applied to the simulation of dynamic chemical processes, and what the limiting factors (in terms of efficiency) turn out to be. A process network involving several distillation columns, with various configurations and dimensions, is given as an illustration of large scale dynamic simulation.

On the nature of fault space classification structure developed by neural networks

Recent research efforts have shown that backpropogation neural networks can be successfully used for fault diagnosis in steady-state and dynamic chemical processes. This approach relies on the non-linear classification properties of neural networks. The diagnostic ability depends on the discrimination of decision regions corresponding to various fault classes, by the neural network. The delineation of decision regions for a given number of fault classes, in turn, hinges on several factors, such as the choice of training data, the number of input and hidden nodes, and the extent of training. In this study, the impact of hidden units and input units on fault space structure and fault classification performance for a given set of training data, is examined. The studies were conducted using a simulation of a chemical reactor. It was observed that the recall and single-fault generalization performances of the neural networks are very good. However, to achieve such good results one needs to have a rich training data set. The results indicate that as the number of hidden units is increased, the amount of training required for correct recall decreases considerably, showing that the delineation of the fault space into different decision regions becomes easier. Also, with a greater number of hidden units, there is a small improvement in single-fault generalization. However, significant improvements in two-fault generalization performance are possible only with the addition of extra input units that convey more information about the state of the system being diagnosed.

Qualitative Simulation for Expert Systems

Monitoring dynamic chemical processes poses a challenging diagnostic problem when the diagnosIs must be performed while the system operates, when multiple faults are common, and when observations are limited to a relatively small set of variables. The monitoring process involves collecting measurements from sensors, combining this data Into a picture of the current state of the system, and assessing any departure from expected behavior. We present a method called MIMIC for monitoring continuous-variable dynamic systems. MIMIC relies primarily on knowledge derived from a qualitative or semiquantitative model of the monitored system and exploits the system's temporal behavior for diagnosis. The goal of the diagnostic system is to mimic the condition of the physical system by identifying parameter ranges in a model of the process that are consistent with the observations.

Theoretical estimates of the dynamic, radiative and chemical effects of clouds on tropospheric trace gases

Using a subhemispheric-scale tropospheric chemistry model, we examine the influence of cloud-scale processes on regional-scale tropospheric chemistry. Reactions producing sulfuric acid and ozone (O 3) are found to be very sensitive to the dynamic, radiative, and aqueous chemical processes occurring in clouds. During a three-day spring-time period over the northeast U.S., aqueous-phase chemical reactions in clouds occupying 1–2% of the tropospheric volume are calculated to oxidize SO 2 to sulfuric acid at a rate comparable to gas-phase reactions occurring throughout the troposphere. During the passage of a midlatitude cyclonic storm system, the model calculates that over 65% of the sulfuric acid in the troposphere over the northeast U.S. is formed in cloud droplets via aqueous-phase chemical reactions. The model calculations show that the vertically integrated O 3 formation rate is enhanced by ∼50% when vertical motions in clouds are allowed to rapidly transport surface-emitted nitrogen oxides and organic compounds into the upper troposphere This results from a rapid dilution and transport of these oxidant precursors out of the planetary boundary layer into a colder and drier chemical environment where photolysis rates are significantly enhanced by cloud albedo. Below-cloud photolysis rates are calculated to be sensitive to the mean cloud-drop radius and cloud liquid-water content, implying that photochemistry during cloudy periods is sensitive to the microphysical structure of overlying clouds. Sulfuric acid and O 3 formation rates are highly correlated with tropospheric cloud amount, implying that an uncertainty in the mesoscale distribution of cloudiness leads to a similar uncertainty in the rates of these tropospheric chemical reactions. At present, it is difficult to evaluate parameterizations of these cloud-scale processes in regional or global-scale tropospheric chemical models. These model results suggest that accurate microphysical, dynamical and mesoscale characterizations of clouds are required in regional or global-scale tropospheric chemical models.

Optimization of semibatch polymerization reactions

Dynamic chemical processes often require a multiobjective formulation for complete process optimization. Specifically, semibatch copolymerization systems are analyzed using vector-objective techniques to determine the tradeoffs between the different goals: narrow the copolymer composition and polydispersity distributions, and minimize the time of reaction. Due to the complexities of the detailed kinetic models, simpler tendency models are evaluated by fitting proposed reaction networks to experimental data. Simulation studies of an acrylonitrile—styrene copolymer and a step-wise oligomer are then used to determine optimal production schemes.

Proflavin binding to poly[d(A-T)] and poly[d(A-br5U)]: triplet state and temperature-jump kinetics.

The delayed fluorescence properties of proflavin have been exploited in studies of the excited-state binding kinetics of the dye to poly[d(A-T)] and its brominated analogue poly[d(A-br5U)] at room temperature and pH 7. The two analyzed luminescence decay times of the DNA-dye complex are dependent on the total nucleic acid concentration. This dependence is shown to reflect a temporal coupling of the intrinsic delayed emission decay rates with the dynamic chemical kinetic binding processes in the excited state. Temperature-jump kinetic studies conducted on the brominated polymer and corresponding information on poly[d(A-T)] from a previous study [Ramstein, J., Ehrenberg, M., & Rigler, R. (1980) Biochemistry 19, 3938-3948] provide complementary information about the ground state. In the ground state, the poly[d(A-T)]-proflavin complex has one chemical relaxation time, which reaches a plateau at high DNA concentrations. The brominated DNA-dye complex exhibits two relaxation times: a faster relaxation mode that behaves similarly to that for the unhalogenated DNA and a slower relaxation mode that is apparent at high DNA concentrations. The ground-state kinetic data are analyzed in terms of two alternative models incorporating series and parallel reaction schemes. The former consists of two sequential binding steps--a fast bimolecular process followed by a monomolecular step--while the latter consists of two coupled bimolecular steps. A similar analysis for the excited-state data yields reasonable kinetic constants only for the series model, which, in accordance with previous proposals for acridine intercalators, consists of a fast outside binding step followed by intercalation of the dye. A comparison of the ground- and excited-state kinetic parameters reveals that the external binding process is much stronger and the intercalation is much weaker in the excited state. That the excited-state data are only consistent with the series model suggests that delayed luminescence studies may provide a general tool for distinguishing between the two kinetic mechanisms. In particular, we demonstrate the use of delayed luminescence spectroscopy as a tool for probing dynamic DNA-ligand interactions in solution.

Chemical process dynamics, Rezso Mohilla and Bela Ferencz, vol. 4 of fundamental studies in engineering, Elsevier/North Holland, 1982, 299 pages, $63.75

AIChE JournalVolume 29, Issue 1 p. 171-171 Book Chemical process dynamics, Rezso Mohilla and Bela Ferencz, vol. 4 of fundamental studies in engineering, Elsevier/North Holland, 1982, 299 pages, $63.75 G. D. Martin, G. D. Martin Setpoint, Inc., 950 Threadneedle, Suite 200, Houston, TX 77079Search for more papers by this author G. D. Martin, G. D. Martin Setpoint, Inc., 950 Threadneedle, Suite 200, Houston, TX 77079Search for more papers by this author First published: January 1983 https://doi.org/10.1002/aic.690290128AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume29, Issue1January 1983Pages 171-171 RelatedInformation

Dynamics of chemical processes at surfaces

Dynamics of chemical processes at surfaces

Computer simulation of the dynamics of chemical processes

This paper is an appraisal of classical trajectory techniques in chemical dynamics. Limitations of the method are examined, and recent efforts to overc