ASPEN simulation software

Perform hand calculations and verify their results with Hysys, Provision, and Aspen simulation software. 

At the core of many of these algorithms for solvent substitution is a method for predicting the properties of proposed molecules, given only the molecular structure. Much work has been done in this area alone, and several programs have been developed to guide this process. Some of these programs are listed in table 9.1. Additionally, process simulation software such as Aspen Plus contain several different approaches for the prediction of properties from molecular structure. 

Abstract In this paper, we discuss the results of a preliminary systematic process simulation study the effect of operating parameters on the product distribution and conversion efficiency of hydrocarbon fuels in a reforming reactor. The ASPEN One HYSYS-2004 simulation software has been utilized for the simulations and calculations of the fuel-processing reactions. It is desired to produce hydrogen rich reformed gas with as low as possible carbon monoxide (CO) formation, which requires different combinations of reformer, steam to carbon and oxygen to carbon ratios. Fuel properties only slightly affect the general trends. 

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. 

The simulation of the above separation scheme is performed with Aspen Plus software [23]. The starting mixture is the acrylonitrile stream given in the last... 

Four detailed case studies of realistically complex industrial-scale processes are discussed in this book. Models of three of these have been developed by Aspen Technology and Hyprotech in their commercial simulators and are available directly from the vendors. These models may be obtained electronically from the Web sites www.aspentec.com and www.hyprotech.com. We appreciate the efforts expended by these companies in making these case studies available to students and engineers. The methods developed in this book are independent of the simulation software used to model the plant. 

C, a typical residence time is 15 seconds. For a pipe reactor operating at 600°C, a typical residence time is 60 seconds. Given a target residence time, the approximate process volume required for a SCWO reactor may be calculated if the process fluid density is known. Density of the SCWO reactor fluid may be estimated by adding the densities of the gas and liquid at reactor temperature and at their respective partial pressures. When process simulator software is used, recommended equations of state are Redlich-Kwong-Soave (RKS, generally available) and SR-POLAR (for ASPEN). ... 

Constant distribution coefficient obtained by means of parameter estimation techniques using Aspen Tech simulation software. 

The fouling factor has to be determined from actual heat exchanger performance based on online measurements taken from a process unit test run. Heat exchanger clean performance is obtained from process flowsheet simulation software (e.g., Hysys by Aspen Tech or Unisim by Honeywell), while dirty performance from exchanger rating software (e.g., HTRI by Heat Transfer Research Institute). 

Unlike conventional approaches, the proposed procedure totally resynthesizes the entire process by incorporating the operating units with enhanced performances. As such it can take into account all possible outcomes, including the inevitable restructuring of the flowsheet s network structure. Design parameters for each of the technologies have been identified by the simulation software Aspen Plus, then the cost parameters have been estimated by Aspen Process Evaluator Icarus. 

Nowadays dynamic simulation is commonly used during process design, e.g. for compressor surge analysis. Simulation software tools like UniSim (Honeywell), DynSim (SimSci), Hysys, Aspen Dynamics (both AspenTech) and GPROMS (PSE Ltd) have become very powerful and are relatively easy to use. In this way the plant controllability and operability can be tested and its robustness against process upsets verified. 

An NGL plant was selected to analyze several distillation assisted heat pump processes when compared to conventional distillation. The depropanizer column which is the third column of the NGL plant was suitable for retrofitting by heat pump systems. This conventional process, along with top vapour recompression, bottom flashing and absorption heat pumps, were simulated using the Aspen Plus software, in order to determine economically the best alternative. Distillation with both top vapor recompression and bottom flashing heat pumps allows reduction of operation (energy) costs by 83.3% and 84%, respectively. This improves the economic potential (incorporating capital costs) by 53% and 54%, respectively. 

The mass- and energy-based indicators help to identify process alternatives for which sustainability metrics, environmental impact factors, as well as inherent safety indices can be estimated. The goal here is to optimize the process so that there is improvement in all these metrics with respect to the base case design. The application of the methodology requires a combination of tools ranging from databases to process simulation software (such as Aspen , Hypro , Sim Sci , etc.), to computational routines for various types of indicators and process synthesis/design tools. 

The previous chapter discussed the methods and techniques for using Aspen Plus simulation software to develop and optimize steady-state designs for azeotropic distillation systems. Once the steady-state design is complete, the dynamic controllability of the process should be explored. Only looking at the steady state does not tell you whether the process is operable. Dynamic simulations and the development of an effective control stmcture are vital parts of process development. 

Regarding the potential commercial use of millistructured reactors, one of the main aspects to be considered is its possible integration in industrial processes. In this context, not only the design of the reactor but also the way in which it interacts with the different equipment linked to it in terms of mass and heat balances should be taken into account. For the latter purpose, process simulation software such as Aspen HYSYS, Aspen Plus, PROMAX, UNISIM, and/or... 

Hand-calculated pressure drop value is 17.59 kPa, and according to Hysys, PRO/II, and Aspen it was found to be 17 kPa, 1714 kPa, and 17.16 kPa, respectively. Simulation software results were very close to each other on the contrary, hand calculation is greater than all the other results, and this is attributed to the incompressibility assumption made during hand calculation. It is clear from the solution of this example that the density of gases is a function of both temperature and pressure. 

For any process simulation that involves only vapor-liquid phases, certain key physical and thermodynamic properties must be available for each phase. Table 1.3 lists these properties for all phases. We can typically obtain these properties for pure components (i.e. n-hexane, n-heptane, etc.) from widely available databases such as DIPPR [2]. Commercial process simulation software (including Aspen HYSYS) also provides a large set of physical and thermodynamic properties for a large number of pure components. However, using these databases requires us to identify a component by name and molecular structure first, and use experimentally measured or estimated values from the same databases. Given the complexity of crude feed, it is not possible to completely analyze the crude feed in terms of pure components. Therefore, we must be able to estimate these properties for each pseudocomponent based on certain measured descriptors. 

The last step is to place the blend into the flowsheet (Figure 2.23). We have to create a new blend each time the composition of the assays changes. For the purposes of a basic simulation, a blend of assays or a blend of back-mixed products is sufficient. However, if we want to evaluate a variety of crudes, the component list can quickly become unmanageable. Recent updates to the Aspen HYSYS introduce a unified component list across all assays. Other simulation software vendors may offer similar features. A unified component list is mostly a convenience feature for the purposes of crude distillation and is not required for most simulation-based studies. 

The rigorous steady-state and dynamic models used in this book are solved using Matlab programs or Aspen Technology simulation software (Aspen Plus and Aspen Dynamics). 

CHEMCAD from Coade Engr. Software, Houston TX DesignPFD from ChemShare, Houston TX Aspen/SP from JSD Simulation Service Co., Denver CO ELECTROSIM (processes deahng with dissociation and chemical reactions), from Real Time Simulation... 

Deriving from its historical simulation environment, Aspen presents with AspenTech an operations manager suite which builds up on software investments already present in a company [105], The difference from conventional tools is the real-time performance management, which gives the user direct real-time access to production data obtained by a local process control system. Keywords are scheduling, logistics, capacity utilization and sales. 

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