AspenTech and NIST team up to boost modeling
Process simulation made real progress in late January with Aspen Technology, Cambridge, Mass. obtaining the use of the TRC Source database and ThermoData Engine (TDE) from the U.S. Department of Commerce's National Institute of Standards and Technology (NIST), Gaithersburg, Md. Incorporating these into AspenTechs products will make it easier and faster for users to develop models, even for processes that had been hard to deal with, and will improve the accuracy of those models, says the company.
For the first time, AspenTech process modeling customers will have access to one of the worlds most comprehensive collections of experimental property data, says Mark Fusco, the companys president and CEO. This marks a paradigm shift in the physical property capabilities of a simulator, believes Suphat Watanasiri, principal technologist, physical properties, at AspenTech. Experimental data allow better property models to be developed, he explains.
Though this pact, NIST will achieve wider distribution of its data and data-analysis technology, while getting increased input from users on their requirements, notes Willie E. May, Director of NISTs Chemical Science and Technology Laboratory.
Users will gain access to critically evaluated pure-component physical-property data for a large number of components, as well as critically evaluated built-in binary interaction parameters for a wide range of systems and conditions, says Watanasiri. In addition, they will be able to take advantage of new tools for developing and fine-tuning their property models, he notes.
TRC Source is a compilation of experimental data for thermophysical and thermochemical properties, including uncertainties, for pure components, binary and ternary mixtures, and chemical reactions. The database now contains about 2.7-million data points, with as many as 500,000 new ones added annually, says Michael Frenkel, director of NISTs Thermodynamics Research Center in Boulder, Colo. It, for instance, includes data for refrigerants and heat transfer fluids that are hard to find elsewhere, he notes.
TDE is a program for on-demand generation of thermophysical property data from user inputs as well as the Source database. The product of more than a decade of work at NIST and first launched in 2004, TDE relies on dynamic data evaluation, notes Frenkel. It enforces consistency of data, evaluates the uncertainty of data, can predict values to fill gaps, and can custom fit data. It also generates evaluated parameters and correlation coefficients.
The 2006 version of aspenONE, released earlier this year, contains pure-component physical property parameters from the Source database, which adds about 12,000 components, more than doubling the total in the library. Version 2007, slated for release in the fourth quarter, will contain the experimental data on pure components from the Source. Having such data available provides traceability for results generated, notes Watanasiri. That version also will include TDEs data evaluation and prediction capability for pure components.
Releases planned over the next few years will add data for binary and ternary systems and will probably double the number of built-in binary interaction parameters available, says Watanasiri thus enabling the users to more easily create more accurate process models, out of the box.
NIST now is working on enhancements for TDE, says Frenkel. For instance, it hopes to add prediction methods based on molecular simulation, which will be useful for generating rough estimates of data that are hard to produce experimentally. NIST also plans to devote more attention to collecting data and developing prediction methods for pharmaceuticals, specialty chemicals and biofuels, he adds.
As part of the multiyear pact, AspenTech will become a member of the TRC Consortium and will provide input on the technical direction and development of TDE. Watanasiri, notes, for instance, that the company will be able to offer comments on the usability of TDE and on additional technical capabilities that industrial users would value.