Thermophysical property estimation

Commercially available compilations of pure component characteristic physical property constants and temperature-dependent properties" for convenient use in process simulators have been developed by AlChE (DIPPR), DDBST, DECHEMA, NIST (TRC), and PPDS. They should be checked first before estimating thermophysical properties. DDBST has developed a comprehensive pure component thermophysical property estimation software (Artist), where many of the methods discussed in this chapter are implemented. 

For the description of thermophysical properties, estimation methods based on the three parameter corresponding states principle mostly employ the critical temperature (Tc), the critical pressure (Pc), and the acentric factor (co) as characteristic... 

Thermophysical Property Estimation. For pure components there is not a large difference in thermophysical properties estimated by different methods except for thermal conductivity of water. The main problem is the thermal conductivity estimation of mixtures.The method of Friend and Adler (15) is suitable due to its simplicity. However, the method of Mason and Saxena as given by Touloukiau (26) estimates higher thermal conductivities and requires larger computation time than the previous method but seems to be more accurate. 

An area that has used chemical stmctures for predictive purposes quite successfully is the estimation of thermophysical properties of compounds. There has been an extensive compilation of estimation methods (81), and prediction of physical properties has been automated using these techniques (82). More recendy, the use of group contribution techniques to design new molecules that have specified properties has been described (83). This approach to compound design is being used to develop replacement materials for chloroduorocarbons. 

Much information can be understood by a review of certain thermophysical properties of materials and mixtures. In comparing the values of heats of reaction, heats of decomposition and CART to values for known hazardous compounds, an estimation of thermal hazard potential can be made. Table A.2 outlines thermal hazard ranking values that could be used in classifying materials and processes based on heats of reaction and CART determinations (Melhem and Shanley 1997). 

The enthalpies of phase transition, such as fusion (Aa,s/f), vaporization (AvapH), sublimation (Asut,//), and solution (As n//), are usually regarded as thermophysical properties, because they referto processes where no intramolecular bonds are cleaved or formed. As such, a detailed discussion of the experimental methods (or the estimation procedures) to determine them is outside the scope of the present book. Nevertheless, some of the techniques addressed in part II can be used for that purpose. For instance, differential scanning calorimetry is often applied to measure A us// and, less frequently, AmpH and AsubH. Many of the reported Asu, // data have been determined with Calvet microcalorimeters (see chapter 9) and from vapor pressure against temperature data obtained with Knudsen cells [35-38]. Reaction-solution calorimetry is the main source of AsinH values. All these auxiliary values are very important because they are frequently required to calculate gas-phase reaction enthalpies and to derive information on the strengths of chemical bonds (see chapter 5)—one of the main goals of molecular energetics. It is thus appropriate to make a brief review of the subject in this introduction. 

The thermophysical properties necessary for the growth of tetrahedral bonded films could be estimated with a thermal statistical model. These properties include the thermodynamic sensible properties, such as chemical potential /t, Gibbs free energy G, enthalpy H, heat capacity Cp, and entropy S. Such a model could use statistical thermodynamic expressions allowing for translational, rotational, and vibrational motions of the atom. 

RBDOPT is coded in an object oriented environment using (C++) and uses distributed computing techniques to speed up the calculations. The thermophysical properties are estimated using Physical Property Data Service (PPDS). PPDS supports over 900 components and 36 physical property routes including NRTL, SRK, UNIFAC and UNIQUAC. The general structure of RBDOPT is shown in Figure 9.13. RBDOPT defines a batch distillation column as an object. Procedures... 

Quantitative estimates of errors in the determined numerical values of substance concentrations at points xeq and xext as a function of the structure and dimension of x and y are obtained with great difficulty. It is only clear that when we are interested in the detailed composition of products, it is desirable to increase this dimension with thorough choice of the set of components x, and y, based on the whole preliminary knowledge about specific features of the studied process. Such an increase will be limited by the possibility to analyze numerous results. However, despite the great sophistication of the problem of specifying a list of substances, it is solved much easier than the problem of specifying a process mechanism. Both the list of elementary reactions (that can include many hundreds and even thousands of elements) and the constants of their rates are hard by far to determine than the list and thermophysical properties of reactants of the studied system. 

This Is a liquid-phase catalytic reaction system and the reaction conditions are very close to the critical conditions of the reactants propylene and benzene. The values of the thermo-physical properties (e.g., heat of formation and heat capacity) are generally not available at the reaction conditions and are difficult to evaluate accurately. We evaluated how well the thermophysical properties were estimated by simulating a commercial cumene reactor, and comparing the adiabatic temperature rise of the simulation with that of the observed data available. 

This value is much larger than the value of about 2 to 4 observed experimentally. The large deviation between the estimated value and that observed is most likely due to the assumptions made with respect to the thermophysical properties and the Lewis number. This point is discussed in Section 6.C.2.C. Although this estimate does not appear suitable, it is necessary to emphasize that the results obtained for the burning rate and the combustion evaporation coefficient derived later give good... 

Gold PI, Ogle GJ. Estimating thermophysical properties of liquids Part 4. Boiling, freezing and triple-point temperatures. Chem Eng 1969 76. 

Before proceeding, we mention sources for a few areas not covered in this chapter. Basic chemical thermodynamics is the subject of Chapter 4. For polymers and their solutions, the Polymer Handbook [1] is an indispensable source, and more on polymer thermophysical properties may be found in two books from AIChE s DIPPR project [2, 3]. The estimation of properties of mixtures described by distillation curves (typically petroleum fractions), or of the pseudocomponents derived from such curves, is covered in the AP7 Technical Data Book [4]. Many molecular data, such as dipole moments and spectroscopic constants, are tabulated in the NIST Chemistry Webbook [5]. 

Often, engineers must estimate thermophysical properties for compounds where few, if any, measurements exist. A comprehensive source for such estimation techniques is the book The Properties of Gases and Liquids [15], which should be consulted by anybody who is serious about property estimation. We will restrict ourselves here to more general comments. 

The model based on the concept of pure limiting film resistance involves the steady-state concept of the heat transfer process and omits the essential unsteady nature of the heat transfer phenomena observed in many gas-solid suspension systems. The film model discounts the effects of thermophysical properties such as the specific heat of solids and hence would not be able to predict the particle convective component of heat transfer. For estimating the contribution of the particle convective component of heat transfer, the emulsion phase/packet model given in a subsequent section should be used to describe the temperature gradient from the heating surface to the bed. 

Compute the fluid bulk mean temperature and fluid thermophysical properties on each fluid side. Since the outlet temperatures are not known for the rating problem, they are estimated initially. Unless it is known from past experience, assume an exchanger effectiveness as 60-75 percent for most single-pass crossflow exchangers or 80-85 percent for single-pass counterflow exchangers. For the assumed effectiveness, calculate the fluid outlet temperatures. 

Analytical solutions for cases of temperature-dependent thermal conductivity are available [22, 23]. In cases where the solid s thermophysical properties vary significantly with temperature, or when phase changes (solid-liquid or solid-vapor) occur, approximate analytical, integral, or numerical solutions are oftentimes used to estimate the material thermal response. In the context of the present discussion, the most common and useful approximation is to utilize transient onedimensional semi-infinite solutions in which the beam impingement time is set equal to the dwell time of the moving solid beneath the beam. The consequences of this approximation have been addressed for the case of a top hat beam, p 1 = K = 0 material without phase change [29] and the ratios of maximum temperatures predicted by the steady-state 2D analysis. Transient ID analyses have also been determined. Specifically, at Pe > 1, the diffusion in the x direction is negligible compared to advection, and the ID analysis yields predictions of Umax to within 10 percent of those associated with the 2D analysis. 

Gold, P.I., Ogle, G.J. in Chemical Engineering Estimating Thermophysical Properties of Liquids, ... 

Queimada, A. J., Stenby, E. H., Marrucho, I. M., and Coutinho, J. A. P., A new corresponding states model for the estimation of thermophysical properties of long chain n-alkanes. Fluid Phase Equilibria, 212, 303-314 (2003). 

No theory is available for estimating the heat and mass transfer coefficients using basic thermophysical properties. The analogy of heat and mass transfer can be used to obtain mass transfer data from heat transfer data and vice versa. For this purpose, the Chilton-Colburn analogies can be used [129]... 

The running cost consists of labor and utilities costs. Data on the thermophysical properties of foods and biological materials, required for estimating utilities costs, are not always at hand and so the calculation is based only on those properties pertaining to the frozen water content of the material. 

A polymer solution at 25°C flows at 1.8m/s over a heated hollow copper sphere of diameter of 30 mm, maintained at a constant temperature of 55°C (by steam condensing inside the sphere). Estimate the rate of heat loss from the sphere. The thermophysical properties of the polymer solution may be approximated by those of water, the power-law constants in the temperature interval 25 < J < 55°C are given below n = 0.26 and m = 26 — 0.0566 T where J is in K. What wiU be the rate of heat loss from a cylinder 30 mm in diameter and 60 mm long, oriented normal to flow ... 

The conditions for this simulation are shown in Figure 4.21 and sununarized in Exercise 4.2. As mentioned before, representative values are assumed for the flow rates of the species in the gas and toluene recycle streams. Also, typical values are provided for the heat transfer coefficients in both heat exchangers, taking into consideration the phases of the streams involved in heat transfer, as discussed in Section 13.3. Subroutines and models for the heat exchangers and reactor are described in the ASPEN and HYSYS modules on Heat Exchangers and Chemical Reactors on the multimedia CD-ROM that accompanies this text. In ASPEN PLUS and HYSYS.Plant, there are no models for furnaces, and hence it is recommended that you calculate the heat required using the HEATER subroutine and the Heater model, respectively. For estimation of the thermophysical properties, it is recommended that the Soave-Redlich-Kwong equation of state be used. 

This rate expression correlates well with laboratory kinetic data for temperatures in the range of 500-900°C and pressures from 1 to 250 atm, with 6.3 X 10 exp (—52,000/RT), concentrations in kmol/m , time in s. Tin K, and R = 1.987 cal/mol-K. Use the PFR model in a process simulator to determine the length of a cylindrical plug flow reactor with a length-to-diameter ratio of six that yields a toluene conversion of 75%. Use the Peng-Robinson equation of state to estimate the thermophysical properties for this vapor-phase reaction. 

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