Modeling approaches

1) The literature was reviewed in order set up generic thermodynamic models in Aspen Plus [49]. All models were refined by carrying out molar balancing on one verification case, mostly yielding a set of approach temperatures or other correlations that reflect deviations from equilibrium. Details for model setup are presented the individual gasifier sections in Chapter 6. 

2) Standardized boundary conditions for two selected coals were introduced to all the models for comparability. Their influence was assessed in a sensitivity analysis, see Section 5.6.4. 

3) After establishment of the standardized state-of-the-art gasifier models, the proposed enhanced concepts were incorporated into the flow sheets. All models were evaluated and the results can be foimd in Chapter 6. 

4) A novel ternary diagram for each coal was developed to uniformly assess the performance and potentials of all the gasification processes and the influence of the ash content shown in Chapter 7. An exergetic analysis also revealed the impact of the gas cooling methods. These results are presented in Chapter 8. 

5) Finally, the most promising concept for an advanced gasification process was selected for further development by the application of several theoretical tools. This is discussed in Chapter 9. 

The mathematical model was constracted on the basis of a three-phase plug-flow reactor model developed by Korsten and Hoffmaim [63]. The model incorporates mass transport at the gas-liquid and liquid-solid interfaces and uses correlations to estimate mass-transfer coefficients and fluid properties at process conditions. The feedstock and products are represented by six chemical lumps (S, N, Ni, V, asphaltenes (Asph), and 538°C-r VR), defined by the overall elemental and physical analyses. Thus, the model accounts for the corresponding reactions HDS, HDN, HDM (nickel (HDNi) and vanadium (HDV) removals), HD As, and HCR of VR. The gas phase is considered to be constituted of hydrogen, hydrogen sulfide, and the cracking product (CH4). The reaction term in the mass balance equations is described by apparent kinetic expressions. The reactor model equations were built under the following assumptions  

The formulation of the model equations is based on the transport of reactants between the gas-liquid-solid phases that takes place in TBRs [51]. Hydrogen, being the main gaseous reactant, is first transferred from the gas phase to the liquid bulk. The reactants in the liquid phase (chemical lumps and dissolved H2) travel to the catalyst particle in order to react Products such as H2S and CH4 are released to the gas phase passing through the liquid phase, whereas hydrocarbon products return to the liquid. 

The change in the molar flow of gaseous compounds along the reactor is equal to the gas-liquid transport rate  

The species that travel across the liquid-solid boundary are either consumed or produced by chemical reaction  

It is necessary to include a heat balance to represent the adiabatic operation of the commercial reactor. Given the assumption that the three phases are at the same temperature, the following pseudo-homogeneous energy balance is used  

As discussed in 6.2, the migrating acid plume has a pH of about 4.5, buffered by the precipitation of amorphous Al(OH)3, and carries with it the elevated concentrations of radionuclides and hazardous constituents. When the acidic water encounters calcite in the aquifer in the downgradient area, calcite dissolution occurs, and that buffers the 

Therefore, we take two steps in modeling. First, the acidic water is neutralized by titrating of calcite. The amounts of Fe and A1 hydroxides precipitated from this titration are then used in the subsequent speciation and complexation modeling. 

In the first step, acidic water of about pH 4.5 was first neutralized to a pH of 6.6 by titrating calcite using phreeqc (see 8.3). Neutralization of the acid water caused the precipitation of gypsum, and A1 and Fe hydroxides. This kind of reaction path modeling will be discussed in Chapter 8. Here, we only present the resulting compositions of the neutralized water and precipitated solids in Table 7.8. 

In the second step of the modeling exercise, speciation and surface adsorption in the neutralized water were modeled using the geochemical code minteqa2. Analytical concentrations of Cd, Ni, Be, and U (5.5, 65,4.1, and 22 x 10-6 molL-1, respectively) were used as input concentrations. The surface properties and surface complexation constants were taken from Dzombak and Morel (1990). Due to the lack of experimental data for A1 hydroxides, we assume that all A1 hydroxides have the same sorptive properties as Fe hydroxide and that the mass of A1 hydroxide was added to the Fe hydroxide concentrations. The total sorbent concentration is 5.3 g/L as Fe(OH)3, which is calculated from the first step. minteqa2 was used to calculate the partitioning of these ions between the aqueous phase and ferric iron hydrous oxide (HFO) surfaces. 

There is no heat-transfer resistance between the three phases. 

Intraparticle diffusion is considered in the apparent rate coefficients. Catalyst deactivation by coke occurs during the first 100 h of time-onstream and then reaches equilibrium. 

Metals are deposited on the catalyst during the whole cycle. 

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The working method used by the ad hoe group is the Object Modelling Technique (OMT). a recognized object modelling approach. 

Besides these LFER-based models, approaches have been developed using whole-molecule descriptors and learning algorithms other then multiple linear regression (see Section 10.1.2). 

A. M. ter laak, N. P. E. Vermeulen, Molecular-modeling approaches to predict metabolism and toxicity, in Pharmacokinetic Optimization in Drug Research, B. Testa, H. van de Water-beemd, G. Folkers, R. Guy (Eds.), Wiley-VCH, Weinheim, 2001,... 

Computer codes are used for the calculational procedures which provide highly detailed data, eg, the Ruby code (70). Rapid, short-form methods yielding very good first approximations, such as the Kamlet equations, are also available (71—74). Both modeling approaches show good agreement with experimental data obtained ia measures of performance. A comparison of calculated and experimental explosive detonation velocities is shown ia Table 5. 

Although comparative modeling is the most accurate modeling approach, it is limited by its absolute need for a related template structure. For more than half of the proteins and two-thirds of domains, a suitable template structure cannot be detected or is not yet known [9,11]. In those cases where no useful template is available, the ab initio methods are the only alternative. These methods are currently limited to small proteins and at best result only in coarse models with an RMSD error for the atoms that is greater than 4 A. However, one of the most impressive recent improvements in the field of protein structure modeling has occurred in ab initio prediction [155-157]. 

The merits and demerits of the many computer-simulation approaches to grain growth are critically analysed in a book chapter by Humphreys and Hatherly (1995), and the reader is referred to this to gain an appreciation of how alternative modelling strategies can be compared and evaluated. A still more recent and very clear critical comparison of the various modelling approaches is by Miodownik (2001). 

Whereas the JKR model approached the topic of particle adhesion from a contact mechanics viewpoint, the DMT theory simply assumes that the adhesion-induced contact has the same shape as a Hertzian indentor. The normal pressure distribution Ph(p) for the Hertzian indentor is related to the repulsive force and the distance from the center of the contact circle to the point represented by r according to the relationship [49]... 

Thus, based on the above, it is not surprising that even under the best conditions an uncertainty factor of approximately 2 is likely in estimates of the plume rise. Despite this somewhat pessimistic introduction, estimations of plume rise are worthwhile and an integral part of the dispersion analysis. Table 2 presents some of the well-known plume rise formulas used in different model approaches. The two major controlling variables which appear in many, if not all, of the plume rise formulas surveyed are ... 

Techniques for quantifying Techniques used were basically from NUREG/CR-1278 or PRA Procedun s Guide, Chapter 4. (l)THERP (1980 version NUREG/CR-1278 with appropriate factors for a tree was used in procedure defined events. (2) A time dependent modeling approach was used to quantify operator actions during a sequence. THERPmethixlr. were ii ,cd as described in WASH- Id ... 

S. Clake, D. D. Vvedensky. Origin of reflection high-energy electron-diffraction intensity oscillations during molecular-beam epitaxy a computational modeling approach. Phys Rev Lett 55 2235, 1987. 

When performing human reliability assessment in CPQRA, a qualitative analysis to specify the various ways in which human error can occur in the situation of interest is necessary as the first stage of the procedure. A comprehensive and systematic method is essential for this. If, for example, an error with critical consequences for the system is not identified, then the analysis may produce a spurious impression that the level of risk is acceptably low. Errors with less serious consequences, but with greater likelihood of occurrence, may also not be considered if the modeling approach is inadequate. In the usual approach to human reliability assessment, there is little assistance for the analyst with regard to searching for potential errors. Often, only omissions of actions in proceduralized task steps are considered. 

It is important to apply a first principles technique since an alternative ionic modelling approach based on the fom-Gordon formalism yields errors in the cell parameters as high as... 

Hallmark, S Bachman, W. and Guensler, R. (2000). Assessing the Impacts of Improved Signal Timing as a Transportation Control Measure Using an Activity-SpeciBc Modeling Approach. Transportation Research Record. Transportation Research Board. Washington, DC National Research Council. 

Extension of the model approach to the study of coordination chemistry of vitamin Bu group compounds. A. Bigotto, G. Costa, G. Mastroni, G. Pellizer, A. Puxeddu, E. Reisenhofer, L. Stefani and G. Tauzher, Inorg. Chim. Acta, Rev., 1970,4, 41-49 (43). 

Hen egg-white lysozyme catalyzes the hydrolysis of various oligosaccharides, especially those of bacterial cell walls. The elucidation of the X-ray structure of this enzyme by David Phillips and co-workers (Ref. 1) provided the first glimpse of the structure of an enzyme-active site. The determination of the structure of this enzyme with trisaccharide competitive inhibitors and biochemical studies led to a detailed model for lysozyme and its hexa N-acetyl glucoseamine (hexa-NAG) substrate (Fig. 6.1). These studies identified the C-O bond between the D and E residues of the substrate as the bond which is being specifically cleaved by the enzyme and located the residues Glu 37 and Asp 52 as the major catalytic residues. The initial structural studies led to various proposals of how catalysis might take place. Here we consider these proposals and show how to examine their validity by computer modeling approaches. 

Quantum chemical calculations, molecular dynamics (MD) simulations, and other model approaches have been used to describe the state of water on the surface of metals. It is not within the scope of this chapter to review the existing literature only the general, qualitative conclusions will be analyzed. 

The idea is that X must govern in some way all properties of the interface, including the permittivity. The latter includes an electronic and a molecular term, which have been tentatively separated7 on the basis of model approaches. In this chapter, only the correlation of the capacitance with X is relevant. The correlation between 11C and tX has been demonstrated for eight metals in aqueous solution. It has been shown26,34 that the correlation derived from sp-metals is fit also by single-crystal faces of sd-metals. In particular, the capacitance of Ag increases in the sequence... 

The origin of CIDNP lies in the microscopic behaviour of radical pairs. Our discussion of this will follow fairly closely the model approach associated with the names of Gloss, Kaptein, OosterhofF, and Adrian, rather than the more formal kinetic treatments of Fischer (1970a) and Buchachenko et al. (1970b). 

Penner, D. E., Lehrer, R., Schauble, L. (1998). From physical models to biomechanics A design based modeling approach. The Journal of the Learning Sciences, 7, 429 149. 

This technique should give reasonable results for isothermal, first-order reactions. It and other modeling approaches are largely untested for complex and nonisothermal reactions. 

Previous chapters have discussed how isothermal or adiabatic reactors can be scaled up. Nonisothermal reactors are more difficult. They can be scaled by maintaining the same tube diameter or by the modeling approach. The challenge is to increase tube diameter upon scaleup. This is rarely possible and when it is possible, scaleup must be based on the modeling approach. If the predictions are satisfactory, and if you have confidence in the model, proceed with scaleup. 

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