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Mathematical models combinations

Armstrong W, Beckett PM. 1987. Internal aeration and the development of stelar anoxia in submerged roots. A multishelled mathematical model combining axial diffusion of oxygen in the cortex with radial losses to the stele, the wall layers and the rhizosphere. New Phytologist 105 221-245. [Pg.259]

Theoretical investigations of the problem were carried out on the base of the mathematical model, combining both deterministic and stochastic approaches to turbulent combustion of organic dust-air mixtures modeling. To simulate the gas-phase flow, the k-e model is used with account of mass, momentum, and energy fluxes from the particles phase. The equations of motion for particles take into account random turbulent pulsations in the gas flow. The mean characteristics of those pulsations and the probability distribution functions are determined with the help of solutions obtained within the frame of the k-e model. [Pg.225]

The creation of the Institute of Catalysis was Boreskov s life work. He was the director of the Institute from the time of its foundation in 1958. He formulated the main research problems of the Institute the development of scientific bases for foreseeing catalytic action and scientific bases of catalyst preparation and mathematical modeling, combined with solutions of applied problems essential for modem industry. In a fairly short period of time the Institute has gained world-wide recognition. In 1980 it received an International Gold Mercury prize. [Pg.319]

There is some uncertainty connected with testing techniques, errors of characteristic measurements, and influence of fectors that carmot be taken into account for building up a model. As these factors cannot be evaluated a priori and their combination can bring unpredictable influence on the testing results it is possible to represent them as additional noise action [4], Such an approach allows to describe the material and testing as a united model — dynamic mathematical model. [Pg.188]

Distillation Columns. Distillation is by far the most common separation technique in the chemical process industries. Tray and packed columns are employed as strippers, absorbers, and their combinations in a wide range of diverse appHcations. Although the components to be separated and distillation equipment may be different, the mathematical model of the material and energy balances and of the vapor—Hquid equiUbria are similar and equally appHcable to all distillation operations. Computation of multicomponent systems are extremely complex. Computers, right from their eadiest avadabihties, have been used for making plate-to-plate calculations. [Pg.78]

The formulation step may result in algebraic equations, difference equations, differential equations, integr equations, or combinations of these. In any event these mathematical models usually arise from statements of physical laws such as the laws of mass and energy conservation in the form. [Pg.425]

The effect of the disturbance on the controlled variable These models can be based on steady-state or dynamic analysis. The performance of the feedforward controller depends on the accuracy of both models. If the models are exac t, then feedforward control offers the potential of perfect control (i.e., holding the controlled variable precisely at the set point at all times because of the abihty to predict the appropriate control ac tion). However, since most mathematical models are only approximate and since not all disturbances are measurable, it is standara prac tice to utilize feedforward control in conjunction with feedback control. Table 8-5 lists the relative advantages and disadvantages of feedforward and feedback control. By combining the two control methods, the strengths of both schemes can be utilized. [Pg.730]

A combination of dimensional similitude and the mathematical modeling technique can be useful when the reactor system and the processes make the mathematical description of the system impossible. This combined method enables some of the critical parameters for scale-up to be specified, and it may be possible to characterize the underlying rate of processes quantitatively. [Pg.1046]

Once the designer has developed confidence in the analysis techniques pertaining to the various parts of a design concept (whether derived from mathematical models or from physical models), the designer can begin the process of synthesis. Synthesis is basically the combining of the analyses (and any other pertinent information) to... [Pg.377]

The kinetic models are the same until the final stage of the solution of the reactor balance equations, so the description of the mathematics is combined until that point of departure. The models provide for the continuous or intermittent addition of monomer to the reactor as a liquid at the reactor temperature. [Pg.201]

On the continuum level of gas flow, the Navier-Stokes equation forms the basic mathematical model, in which dependent variables are macroscopic properties such as the velocity, density, pressure, and temperature in spatial and time spaces instead of nf in the multi-dimensional phase space formed by the combination of physical space and velocity space in the microscopic model. As long as there are a sufficient number of gas molecules within the smallest significant volume of a flow, the macroscopic properties are equivalent to the average values of the appropriate molecular quantities at any location in a flow, and the Navier-Stokes equation is valid. However, when gradients of the macroscopic properties become so steep that their scale length is of the same order as the mean free path of gas molecules,, the Navier-Stokes model fails because conservation equations do not form a closed set in such situations. [Pg.97]

Statistical and algebraic methods, too, can be classed as either rugged or not they are rugged when algorithms are chosen that on repetition of the experiment do not get derailed by the random analytical error inherent in every measurement,i° 433 is, when similar coefficients are found for the mathematical model, and equivalent conclusions are drawn. Obviously, the choice of the fitted model plays a pivotal role. If a model is to be fitted by means of an iterative algorithm, the initial guess for the coefficients should not be too critical. In a simple calculation a combination of numbers and truncation errors might lead to a division by zero and crash the computer. If the data evaluation scheme is such that errors of this type could occur, the validation plan must make provisions to test this aspect. [Pg.146]

What is commonly understood by a fundamental approach is applying theoretically based mathematical models of necessary equipment items. Intrinsic (not falsified by processes other than a chemical transformation) kinetics of all processes are investigated, transport phenomena are studied, flow patterns are identified, and relevant microscopic phenomena are studied. It is intended to separately study as many intrinsic stages as possible and to combine results of these investigations into a mathematical model. Such a model contains only a limited amount of theory (grey models, gross models, or tendency models). Obviously, the extrapolation power of these models strongly depends on the content of theory. The model... [Pg.226]

Based on a detailed mathematical model, one can make computer simulations of the behaviour of various reactor types. Optimization of operating conditions and design parameters can be done for each reactor type. Downstream equipment should also be taken into account since the cost of product isolation and purification can heavily influence the final choice of all equipment items. A proper combination of investment and operating costs is used as the... [Pg.381]

Finally, mention should be made of the two effects of interaction of the mathematical model whose negative coefficients show minima of flashpoints for the binary butanol/cyclohexanol and butanol/pentanol combinations. Can they be explained by the presence of azeotropes in these substances The tables examined did not list these mixtures and there was no time to do an experimental check with the students. [Pg.71]

This gives an example of fate modeling in which the risks of an insect growth inhibitor, CGA-72662, in aquatic environments were assessed using a combination of the SWRRB and EXAMS mathematical models.. Runoff of CGA-72662 from agricultural watersheds was estimated using the SWRRB model. The runoff data were then used to estimate the loading of CGA-72662 into the EXAMS model for aquatic environments. EXAMS was used to estimate the maximum concentrations of CGA-72662 that would occur in various compartments of the defined ponds and lakes. The maximum expected environmental concentrations of CGA-72662 in water were then compared with acute and chronic toxicity data for CGA-72662 in fish and aquatic invertebrates in order to establish a safety factor for CGA-72662 in aquatic environments. [Pg.249]

Figures 4.1 and 4.2 depict the superstructures on which the mathematical model is based. Figure 4.1 represents a situation where reusable water storage does not exist. In this situation, water used in each water using operation j can be supplied from the fresh water header, the recycle/reuse water header or a combination of both headers. Water from each operation j can be recycled to the same operation, reused in downstream processes and/or dispensed with as effluent. On the other... Figures 4.1 and 4.2 depict the superstructures on which the mathematical model is based. Figure 4.1 represents a situation where reusable water storage does not exist. In this situation, water used in each water using operation j can be supplied from the fresh water header, the recycle/reuse water header or a combination of both headers. Water from each operation j can be recycled to the same operation, reused in downstream processes and/or dispensed with as effluent. On the other...
Since these two types of processes have drastically different effects on the conversion levels achieved in chemical reactions, they provide the basis for the development of mathematical models that can be used to provide approximate limits within which one can expect actual isothermal reactors to perform. In the development of these models we will define a segregated system as one in which the first effect is entirely responsible for the spread in residence times. When the distribution of residence times is established by the second effect, we will refer to the system as mixed. In practice one encounters various combinations of these two limiting effects. [Pg.408]

Cold flow studies have several advantages. Operation at ambient temperature allows construction of the experimental units with transparent plastic material that provides full visibility of the unit during operation. In addition, the experimental unit is much easier to instrument because of operating conditions less severe than those of a hot model. The cold model can also be constructed at a lower cost in a shorter time and requires less manpower to operate. Larger experimental units, closer to commercial size, can thus be constructed at a reasonable cost and within an affordable time frame. If the simulation criteria are known, the results of cold flow model studies can then be combined with the kinetic models and the intrinsic rate equations generated from the bench-scale hot models to construct a realistic mathematical model for scale-up. [Pg.318]

The development of new polyanhydrides has sparked researchers to developed new device fabrication and characterization techniques, instrumentation, and experimental and mathematical models that can be extended to the study of other systems. The growing interest in developing new chemistries and drug release systems based on polyanhydrides promises a rich harvest of new applications and drug release technologies, as well as new characterization techniques that can be extended to other materials. Future endeavors will likely focus on multicomponent polyanhydride systems, combining new chemical functionalities to tailor polyanhydrides for specific applications. [Pg.214]


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