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Aspen Plus V12.1 includes new features in the following areas:
AI Training
Aspen Multi-Case
Plant Data
New Sustainability Examples
Engineering Enhancements
Physical Properties
Databanks
AI Training
You can now create AI models directly within Aspen Plus to improve the accuracy of one or more models from the model library. Exposed parameters such as distillation column efficiencies, heat and mass transfer coefficients, and drying rates can be calculated to match your data rather than having to be set to constants or regressed to simple models. Click AI Training on the Home tab of the ribbon to get started.
Improved Integration with Aspen Multi-Case
Aspen Plus V12.1 offers the following improvements to integration with Aspen Multi-Case:
You can easily create an Aspen Multi-Case scenario based on the configuration of a corresponding Aspen Plus Sensitivity Analysis. All independent and dependent variables included in the Sensitivity Analysis are imported, and the new scenario is ready to run. To export the Aspen Plus Sensitivity Analysis for use in Aspen Multi-Case, on the Sensitivity Input | Vary sheet, click Send to Aspen Multi-Case.
You can quickly import multiple variables from Aspen Plus to Aspen Multi-Case. Custom Tables in Aspen Plus now include a Send to Aspen Multi-Case button. This button allows you to create a .json file that you can use to transfer all the variables from the table to Aspen Multi-Case. In Aspen Multi-Case, you can click Import Variables from JSON within a scenario to import this .json file.
Plant Data Improvements
Aspen Plus V12.1 features the following improvements for Plant Data:
You can now filter results on the Compare Result Sets form.
When plotting results, you can now plot tag results in addition to variable results.
If the quality of the Source tag is not strictly good (for example, bad, clamped, exceeding limits, or overridden) for a Critical variable, the model will not be run; this is indicated in the Status window.
Performance has been improved in cases with a large number of tags and variables. Plant Data information involving up to 50,000 tags and variables is supported, and you can open the relevant model from within the offline model without encountering performance issues.
Plant Data now lets you edit groups of tags at once in Excel and merge the updated data using the Paste from Excel button. This button appears on the Tag Manager and Selected Variables forms.
The Excel template has additional features that make it easier to load data into the template.
Pre-Averaged Data Mode is more flexible; it can work with data that is not uniform (by turning off averaging), and you can exit pre-averaged data mode by deleting all the imported data.
New Sustainability Examples
AspenTech is focused on helping our customers improve the sustainability of the process industries. Aspen Plus V12.1 includes seven new sample files to facilitate this objective. The new samples can be found by clicking Examples on the Resources ribbon tab, or by navigating to the examples folder C:\Program Files\AspenTech\Aspen Plus V12.1\GUI\Examples. A PDF file is included with each example to document the model source, assumptions, and intent, and they are listed in the help covering all example files (search for "New in V12.1"). The examples include
Four new carbon capture examples in the Carbon Capture\Industrial Scale subfolder. Each of the new carbon capture models include the absorber and solvent regeneration columns as well as the heat recovery and trim exchangers operating in a closed loop. Rate-based distillation methods and rigorous column hydraulics are applied for accuracy. The new MEA models use the ENRTL-RK property method (electrolyte NRTL with RKS equation of state) together with equilibrium chemistry and rate-based reaction kinetics in the columns. Several key model parameters are drawn from AspenTech’s proprietary ACIDGAS unary and binary databases.
Two new biofuels examples. Focus on the circular economy continues to spur research related to biofuel and biochemical application. These new examples provide resources demonstrating modeling techniques to characterize biomass and thermal conversion of biomass to bio-oil.
A new alkaline electrolysis model for production of green hydrogen. Governments, research agencies, and major corporations are spending billions of dollars developing and scaling up new technologies to decarbonize the economy. One key technology is the production of “green hydrogen”, produced by electrolysis of water using electricity from renewable sources such as wind and solar power. This set of example files includes a rigorous custom model of an alkaline electrolysis cell and an Aspen Plus process model covering the ancillary equipment supporting the electrolysis unit.
Engineering Enhancements
New options on the Setup | Calculation Options | Check Results sheet check the solid-liquid and solid-vapor equilibrium results obtained during simulation calculations.
In RCSTR blocks, you can now specify the minimum and maximum temperatures on the Convergence | Parameters sheet. Use these to constrain the solution in problems with multiple steady-state solutions (which happens in some problems with exothermic reactions). The maximum temperature step, which used to default to 50 K, now defaults to 10% of (max-min temperature) if this is less than 50 K.
Physical Properties
The Copolymer PC-SAFT and Cubic-Plus-Association models were updated to include terms for cross-association and solvation, including self-association. This includes the new parameters PCSEIJ, PCSVIJ, and PCSAIJ for PC-SAFT and parameters CPAEIJ, CPAVIJ, and CPAAIJ for CPA. For more information, see Copolymer PC-SAFT EOS Model Parameters and Cubic-Plus-Association. These features were added in V12 but inadvertently omitted from the What's New for V12.
Databanks
The PURE39 databank is still based on the 2019 public DIPPR release. The contents from DIPPR in PURE39 are the same ones as in PURE38; only parameters from AspenTech are updated, including UNIFAC group-count information and Rackett, COSTALD, and DCPLS parameters.
The new version of NIST-TRC in the NISTV121 database is still based on the same xml files for NIST-TRC in the NISTV120 database, but is created with a new NIST data converter for parsing components and parameters more efficiently. The new converter also eliminates some duplicated components and fixes identities for some components, noticeably two spin isomers of hydrogen, parahydrogen (PARA-HYDROGEN) and orthohydrogen (ORTHO-HYDROGEN).
In V11 and earlier versions, the results for ideal gas heat capacity (CPIG) in NIST-TRC were calculated with the NIST Aly-Lee equation (CPIALEE) and the NIST ThermoML Polynomial equation (CPITMLPO). In NISTV120, NIST introduced the NIST Wilhoit equation (CPIWEOS) which was not supported in Aspen Plus. The new version of NIST-TRC in the NISTV121 database has eliminated the NIST Wilhoit equation and restored NIST Aly-Lee equation as the primary equation for the ideal gas heat capacity.
Updated NIST TDE version 10.4 and Database version 10.16 are deployed. Updates include eliminating the NIST Wilhoit equation (CPIWEOS) and restoring the NIST Aly-Lee equation (CPIALEE) for the ideal gas heat capacity.
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发表于 1970-1-1 08:00:00
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