SimCenter Forum

Hi Adam,

First and foremost, I am so grateful for such a valuable and detailed response. Also, I appreciate the new version with the added EDPs.
Moreover, I apologize for replying too late. I had a hectic month and wanted to try all the mentioned points before reaching out.

I thoroughly checked all the options and input data and examined different cases for a 6-story eccentrically braced frame. To make a fair comparison between PACT and PELICUN, I tried to use the same input data as follows:
a- The components' quantities are deterministic in both software (no dispersion was considered for the components).
b- In PELICUN, the number of blocks for each component is calculated by the total quantity divided by the unit quantity of the component defined in PACT. For example, if the total quantity of “B.20.22.001" is 1500 square feet (SF), the unit of this component in PACT is "30 SF". Therefore, the number of blocks in PELICUN was calculated to be 1500/30=50.
c- Similar fragilities for collapse and excessive RID were introduced (median and dispersion).
d- "Mont-Carlo" simulation with 1000 realization was used in both software.
e- Non-directional conversion factor equal to 1.2 was assigned in PACT (the default value in PELICUN).
f- IN PACT, the demands of the prototype subjected to a set of 22 ground motions were provided, while in PELICUN the median and logarithmic standard deviation of these demands were introduced. The log-stdev of each set of demands was calculated by first getting the natural logarithm of the set of 22 EDPs and then calculating the standard deviation of this set (please confirm if it is correct).
g- In PACT, the maximum residual drifts of the building (among all the stories) subjected to the set of 22 ground motions were provided. In PELICUN the ensemble median of the peak residual story drift of each story subjected to the set of 22 ground motions was introduced (similar to the other EDPs). Therefore, there is a difference in terms of providing the input data of the residual drift between PACT and PELICUN.

I examined different cases, and here are some of the findings:

Case-1: On the first try, I tried to make a simpler model for comparison, therefore I only included 2-3 components in the CMP_marginals, and excluded excessive RID and collapse cases by assigning a large number to the median of the corresponding fragilities. If the "Economies of scale" is set to "True", "True" (similar to PACT), the analysis fails (probably because no realization leads to neither collapse nor excessive drift), but if this option is set to "True", "False", the analysis converges. As can be seen in the figure, there is a small difference between CDFs of the repair cost in terms of uncertainty.

Case-2: Similar to case-1, but the collapse, and excessive RID are included. The "Economies of scale" was set to "True", "True" (similar to PACT). As shown in the figure, there is a break in the CDF of the repair cost. This break is due to the large difference between the total repair cost of the repairable cases and the replacement cost (irreparable and collapse cases). The difference between the height of the two horizontal lines infers the probability of either collapse or irreparable damage. It can be seen that PELICUN predicts a higher probability for those scenarios (which is mainly due to excessive RID and not collapse and maybe because of the different ways of providing the residual drift in the two software as mentioned in part "g" above).

Case-3: The remaining components were added, and probabilistic quantities were used for components. Excessive RID and collapse were included in the analysis and the "Economies of scale" was set to "True", "True".


Consequently, two differences can be observed between the results:
1- the probability of irreparable damage in PACT and PELICUN seems to be different (In the first post, such a difference was not observed because the prototype was a self-centering system with almost zero residual drift).
2- The uncertainty seems to be slightly different as shown in Case-1.

Please let me know if I am missing something.

Again, I appreciate your precious work, and I will be glad if I can do any help.

Pooya,

Hello,

I just wanted to share this post to show the comparison between the damage and loss assessment results, which were performed with Pelicun and PACT software for a 6-story building.
The results seem to be close; however, the uncertainty in the results based on PACT analysis is more considerable than Pelicun.

Thank you,
Pooya

Thank you so much, Adam.

Now, I completely understand the definition of the location parameter.

However, I still have a doubt about some acceleration-sensitive components that should be assigned to the floors and not the stories.
Consider two different cases in a 4-story building where we want to put a chiller (D.30.31.023) or cooling tower (D.30.31.023) either on the roof or on the ground (as far as I know both cases are very common).

How can we define the location in these two cases? Because here we have 5 floors and we want to use the EDP of the first and the last floor which are gound and roof levels.
If the offset of 1 is defined for the cooling tower, then how to use the EDP of the ground floor?
If that offset is not defined, then how to use the EDP of the roof?

So many thanks,

Pooya

Thank you, Adam

I am asking about the following line of codes which are located in the last part of the example you provided in the Jupyyter notebook:

# get only the results that describe repairable damage
agg_DF_ = agg_DF.loc[agg_DF['repair_cost'] < 2.0e7]

print('\nProbability of experiencing repairable damage:', agg_DF_.shape[0] / agg_DF.shape[0])

 I guess :

1-The probability of "repairable damage" is defined as the number of realizations whose repair cost is less than (2.0E+7) over the total number of realizations. Is that right?

2- In the realization that the building experiences collapse or excessive drift, the repair cost is taken equal to the replacement cost which is more than 2.0E+07, therefore, they will not be considered repairable cases. Is that right?

3- How did you define 2.0E+07? Is it almost half of the replacement cost? Meaning that if the repair cost is more than 50% of the replacement cost, it is not reasonable to repair the building?

Again, I really appreciate your endless support.

Pooya,

Hi Adam,

I have another question regarding the probability of repairable damage.
I was wondering whether the collapsed cases are also considered to get this probability or only the excessive RID damage state is considered to calculate it.

Thank you so much,

Hello JiaJun,

Definitely, Adam would help you way better, but I (as a user) personally think if you watch the tutorial videos on YouTube, you will learn much more.
I recommend you to watch the tutorials of PBE first and then move to Ver3 of Pelicun.

Here are the links:

https://simcenter.designsafe-ci.org/research-tools/pbe-application/
https://www.youtube.com/watch?v=0Cak4sxyvCI

I hope this would help.

Pooya,

Hello Adam,

Thank you for the updated Version 3.b4 of Pelicun.

I have a question and I will be so grateful if you could help me.

Is it possible to get a more deterministic damage and loss assessment of a building when is subjected to a specific ground motion by setting the "log_std" of the demands equal to zero?

(I know the repair time and costs are also accompanied by uncertainty as well, so the final results will not be purely deterministic).

In the example you provided in the Jupiter notebook, I set the "log_std" of the demands equal to zero, but I observed meaningful differences in the results (compared to the non-zero "log_std" case).

I attached the summary tables of the consequences here and as you can see, the standard deviation of the consequences is even larger when the "log_std" is set to zero.

Thank you so much,

Pooya