Written by Chris Goodell, P.E., D. WRE | WEST Consultants
Copyright © RASModel.com. 2009. All rights reserved.
The Theta Implicit Weighting Factor is used in unsteady flow HEC-RAS as a means for providing numerical stability through the imiplicit solution of the St. Venant Equations. Without going into the details, a value of 1 for Theta provides the most stability, but sacrifices some accuracy. A value of 0.6 provides the most accuracy, but is very difficult to stabilize. So...what should we use for our unsteady flow models. There is some disagreement out there among users of HEC-RAS, but here is my take: The manual, and the class that HEC holds suggests working with a Theta value of 1.0, then when your model is stabilized, reduce it as close to 0.6 as possible. In my experience, moderate to complex models never are able to maintain stability with Theta less than around 0.8. At some point in the past, I realized that most of the time, reducing the Theta value did not produce significantly different results. However, many modelers insist that Theta should be reduced. I can't disagree with that. In principle, I believe this is correct. However, in practice, my experience shows that it makes very little difference.
I think this would make a great topic for a paper, and the research would be easy to conduct. Does anyone have any thoughts on this topic?
Copyright © RASModel.com. 2009. All rights reserved.
The Theta Implicit Weighting Factor is used in unsteady flow HEC-RAS as a means for providing numerical stability through the imiplicit solution of the St. Venant Equations. Without going into the details, a value of 1 for Theta provides the most stability, but sacrifices some accuracy. A value of 0.6 provides the most accuracy, but is very difficult to stabilize. So...what should we use for our unsteady flow models. There is some disagreement out there among users of HEC-RAS, but here is my take: The manual, and the class that HEC holds suggests working with a Theta value of 1.0, then when your model is stabilized, reduce it as close to 0.6 as possible. In my experience, moderate to complex models never are able to maintain stability with Theta less than around 0.8. At some point in the past, I realized that most of the time, reducing the Theta value did not produce significantly different results. However, many modelers insist that Theta should be reduced. I can't disagree with that. In principle, I believe this is correct. However, in practice, my experience shows that it makes very little difference.
I think this would make a great topic for a paper, and the research would be easy to conduct. Does anyone have any thoughts on this topic?