Modeling simulation software

California), Sibyl (Tripos, Missouri), ChemX (Chemical Design, UK), BioGraf (Molecular Simulations, California), Charmm/Quanta (Polygen Corp., Massachusetts), PC Model (Serena Software, Indiana), ChemLab (ChemLab Inc., Illinois), and a large number of personal computer-based packages. 

The computer has become an accepted part of our daily lives. Computer applications in applied polymer science now are focussing on modelling, simulation, robotics, and expert systems rather than on the traditional subject of laboratory instrument automation and data reduction. The availability of inexpensive computing power and of package software for many applications has allowed the scientist to develop sophisticated applications in many areas without the need for extensive program development. 

Often it is possible to consider the process or plant, as a system of independent sub-sets or modules, which are then modelled individually and combined to form a description of the complete system. This technique is also used in the large scale commercial simulation software, in which various library sub-routines or modules for the differing plant elements, are combined into a composite simulation program. 

Optimisation may be used, for example, to minimise the cost of reactor operation or to maximise conversion. Having set up a mathematical model of a reactor system, it is only necessary to define a cost or profit functionOptimisation and then to minimise or maximise this by variation of the operational parameters, such as temperature, feed flow rate or coolant flow rate. The extremum can then be found either manually by trial and error or by the use of a numerical optimisation algorithms. The first method is easily applied with ISIM, or with any other simulation software, if only one operational parameter is allowed to vary at any one time. If two or more parameters are to be optimised this method however becomes extremely cumbersome. 

Unfortunately, the analysis of chemical absorption is far more complex than physical absorption. The vapor-liquid equilibrium behavior cannot be approximated by Henry s Law or any of the methods described in Chapter 4. Also, different chemical compounds in the gas mixture can become involved in competing reactions. This means that simple methods like the Kremser equation no longer apply and complex simulation software is required to model chemical absorption systems such as the absorption of H2S and C02 in monoethanolamine. This is outside the scope of this text. 

The data derived from modeling at different conversion degrees (X = 5, 40, and 80%) were also compared to the results obtained from the calculation of the classical Thiele modulus. The calculated (by the Thiele modulus) and modeled (by Presto Kinetics) effectiveness factors showed comparable values. Hence, the usage of simulation software is not required to get a first impression of the diffusion limitations in a Fischer-Tropsch catalyst pore. Nevertheless, modeling represents a valuable tool to better understand conditions within a catalyst pore. 

Two extremes are encountered in process simulator software. At one extreme the process model comprises a set of equations (and inequalities) so that the process model equations form die constraints for optimization, exactly the same as described in previous chapters in this book. This representation is known as an equation-... 

Marquez, AC, Blanchar C (2004) The procurement of strategic parts. Analysis of contracts with suppliers using a system dynamics simulation model. International Journal of Production Economics 88 (1) 29-49 Mason S (2002) Simulation software buyer s guide. HE Solutions May 45-51 McAfee R, McMillan J (1987) Auctions and Bidding. Journal of Economic Literature 25 699-738... 

Using literature data on human physiology and transit patterns, Willman et al. [54] adjusted the described model to account for human physiology. There are two commercially available in silico simulation software packages,... 

Using these methods, the elementary reaction steps that define a fuel s overall combustion can be compiled, generating an overall combustion mechanism. Combustion simulation software, like CHEMKIN, takes as input a fuel s combustion mechanism and other system parameters, along with a reactor model, and simulates a complex combustion environment (Fig. 4). For instance, one of CHEMKIN s applications can simulate the behavior of a flame in a given fuel, providing a wealth of information about flame speed, key intermediates, and dominant reactions. Computational fluid dynamics can be combined with detailed chemical kinetic models to also be able to simulate turbulent flames and macroscopic combustion environments. 

Ho vever this approach does not address inter-individual variability in CYP expression nor the apparent substrate specificity of RAFs. This may be overcome through the use of intersystem extrapolation factors (ISEFs) vhich compare the intrinsic activities of rCYP versus liver microsomes and provide CYP abundance scaling by mathematical means. This employs the RAF approach and adjusts for the actual amount of liver microsomes CYP present (measured by immunochemistry) rather than a theoretical amount (Equation 8.4). Such corrections can be made using nominal specific contents of individual CYP proteins in liver microsomes or more appropriately employ modeling and simulation software (e.g., SIMCYP www.simcyp.com) which takes into account population-based variability in CYP content. 

Each vendor of SPICE simulation software has added features such as Monte Carlo analysis, schematic entry, and post simulation waveform processing, as well as extensive model libraries. In most cases, the manufacturers have modified the algorithms for controlling convergence and have added new parameters or syntax for component models. As a result, each electronic design automaton (EDA) tool vendor has the basic Berkeley SPICE 2 features and a unique set of capabilities and performance enhancements. 

The reader will also note that in some circumstances, one or more of the simulation software results did not match the hardware results. We have attempted to explain the reasons why this might have occurred. Bear in mind that SPICE is one of those labors in life where you get out of it what you put into it. If you put very little effort into understanding what the models and circuit are doing, chances are your simulation accuracy will be poor. 

They focus on the ID simulation of an urea SCR system. The system includes a model for N02 production on a DOC, a model for urea injection, urea decomposition and hydrolysis catalyst, a model for a vanadium-type SCR catalyst and a model for NH3 decomposition on a clean-up catalyst. The catalyst models consist of a ID monolith model with global kinetic reactions on the washcoat surface, kinetic parameters have been taken from literature or adjusted to experimental data from literature. The complete model was implemented in AVL BOOST (2006). AVL BOOST is an engine cycle and gas exchange simulation software tool, which allows for the building of a model of the entire engine. 

Another engine cycle and gas exchange simulation software tool which has been extended for exhaust aftertreatment simulation is GT-POWER (2006). This software includes models for engine components as well as templates for DOC, SCR catalyst, NSRC and TWC. Reaction kinetics can be provided by the user, based on templates. Kinetic parameters adaptation is supported with a built-in optimizer tool. 

Walker, P., Greiner, R., McDonald, D. and Lyne, V. (1999) The Tourism Futures Simulator Asystems thinking approach. Environmental Modeling and Software 14, 59-67. 

Several authors have already developed methodologies for the simulation of hybrid distillation-pervaporation processes. Short-cut methods were developed by Moganti et al. [95] and Stephan et al. [96]. Due to simplifications such as the use of constant relative volatility, one-phase sidestreams, perfect mixing on feed and permeate sides of the membrane, and simple membrane transport models, the results obtained should only be considered qualitative in nature. Verhoef et al. [97] used a quantitative approach for simulation, based on simplified calculations in Aspen Plus/Excel VBA. Hommerich and Rautenbach [98] describe the design and optimization of combined pervaporation-distillation processes, incorporating a user-written routine for pervaporation into the Aspen Plus simulation software. This is an improvement over most approaches with respect to accuracy, although the membrane model itself is still quite... 

Although ASPEN-Plus is widely used to simulate petrochemical processes, its uses for modeling biomass processes are limited owing to the limited availability of physical properties that best describe biomass components such as cellulose, xylan, and lignin. For example, Lynd et al. (1) used conventional methods to calculate the economic viability of a biom-ass-to-ethanol process. However, with the development by the National Renewable Energy Laboratory (NREL) of an ASPEN-Plus physical property database for biofuels components, modified versions of ASPEN-Plus software can now be used to model biomass processes (2). Wooley et al. (3) used ASPEN-Plus simulation software to calculate equipment and energy costs for an entire biomass-to-ethanol process that made use of dilute-H2S04 acid pretreatment. 

HyperChem is the PC-based molecular modeling and simulation software package marketed by Hypercube Inc. (http //www.hyper.com). The program provides molecular mechanics (with MM +, AMBER, BIO+ (CHARMm), and OPLS force... 

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