Some discussions on RGibbs model in Aspen Plus Dynamics...
1) PFR configuration for RGibbs:
PFR-RGibbs additionally calculates response-delay and equipment-volume for given geometry data. We could tell it is a minimum effort to take account the holdup contribution, but it is not done in rigorous way. Personally I don't suggest PFR configuration in RGibbs since it doesn't look theoretically sound. When a holdup is considered for RGibbs, it perhaps better to combine an Instantaneous-RGibbs and a Dynamic-Mixer (before or after the RGibbs), instead of PFR-RGibbs. Basically PFR-RGibbs is not a distributed model therefore there won't be real Plug-Flow effect at all.
2) Slow performance due to PFR configuration:
Such drawback in integration performance may be because of the complexity in delay function and volume calculation. It is not directly related to RGibbs calculation. In Aspen Plus Dynamics, RGibbs is (only one!!) the procedural model, which reuses A+ RGibbs calculation. It means its computational performance in dynamics (for RGibbs block) is identical to what A+ exhibits. Basically it carries out series of SS calculation continuously along integration time.
3) Why RGibbs?
Probably the most merit of RGibbs is that it does not require reaction stoichiometry. Without such detail reaction data, RGibbs can determine phase equilibrium by minimizing Gibbs free energy, subject to atom balance constraints at given process condition (T,P or P,H). For instance, when you model a burner, which is fundamentally a reactor but you perhaps don’t know details of what’s happening inside, RGibbs may be the one to use. There is no suggested criteria to choose RGibbs, but data-availability may be one of the major reason when choosing RGibbs.
Friday, November 13, 2009
Thursday, August 13, 2009
Simulation Gets a New Dynamic
In many ways, modeling has become an established tool for process engineers. Steady-state simulations are now routine for much process design work, while the more-challenging world of dynamic simulation has virtually spawned the rapidly growing market for operator training systems (OTS’) for everything from tightly integrated petrochemical complexes to offshore platforms. However, few would question that dynamic simulation could play a greater role in process engineering. The question is whether it is now poised for wider adoption by practicing process engineers.
The ability to mathematically model a process and its unit operations from first principles arguably dates back to the advent of the first computers powerful enough to do the number crunching — but those mainframe and VAX days are long gone. “Most of us in the past in the chemical industry had our own simulators, before they became commercially available,” recalls John Pendergast, senior technical leader with Dow’s Engineering and Process Sciences Laboratory in Midland, Mich. But the processing and modeling times involved then were hardly suited to dynamic simulations. “Realistically,” he says, “the ability to solve dynamic problems is only about three to four years old.”
(click the following link to read the complete article)
The ability to mathematically model a process and its unit operations from first principles arguably dates back to the advent of the first computers powerful enough to do the number crunching — but those mainframe and VAX days are long gone. “Most of us in the past in the chemical industry had our own simulators, before they became commercially available,” recalls John Pendergast, senior technical leader with Dow’s Engineering and Process Sciences Laboratory in Midland, Mich. But the processing and modeling times involved then were hardly suited to dynamic simulations. “Realistically,” he says, “the ability to solve dynamic problems is only about three to four years old.”
(click the following link to read the complete article)
Simulation Gets a New Dynamic
Mike Spear, ChemicalProcessing.com
Efforts aim to boost the use of dynamic models by process and control engineers.
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