2.3.2. Outputs¶
After the DL assessment is complete, the workflow collects the EDP.csv, DM.csv, and DV.csv files produced for each building asset and aggregates the results into single output files. When run locally, the workflow returns the output in CSV format, which is located in the results folder. When run remotely, the workflow returns the output in HDF format, which is located in the job archive. The HDF files can be converted into CSV format as a post-processing step.
2.3.2.1. EDP Output File¶
File which aggregates response simulation results from the EDP.csv files of all building assets. |
||
properties |
||
|
Name of EDP type. Typical earthquake EDPS are peak floor acceleration (PFA), peak interstory drift (PID), peak floor displacement (PFA), and peak roof displacement (PRD). If IMs are used as EDPs (with the ‘IMasEDP’ EDP application), then the IM name is returned in this field. |
|
type |
string |
|
|
Location of where EDP is recorded on the model. If UserDefinedEDP is specified as the EDP application, then the location labelling is denoted in the EDP specification file. Otherwise, the numbering starts at 0, which denotes the ground level. |
|
type |
int |
|
|
Direction of the EDP is recorded. The numbering used in the file is X=1, Y=2, Z=3. |
|
type |
int |
|
|
Describes the statistic reported for each EDP. EDPs are assumed to follow a lognormal distribution described by a median parameter and beta (lognormal standard deviation) parameter. Note: If the ‘samples’ entry of the RegionalMapping application is set to 1, then only one event is assigned to each building asset and the response is reported as the ‘median’ in the EDP Output File. |
|
type |
string |
The header schema, followed by an example output, is provided:
type |
PFA |
PFA |
PFA |
PFA |
PFD |
PFD |
PFD |
PFD |
PID |
PID |
PID |
PID |
---|---|---|---|---|---|---|---|---|---|---|---|---|
loc |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
dir |
1 |
1 |
2 |
2 |
1 |
1 |
2 |
2 |
1 |
1 |
2 |
2 |
stat |
median |
beta |
median |
beta |
median |
beta |
median |
beta |
median |
beta |
median |
beta |
1 |
130.996 |
0.478197571 |
145.494 |
0.080967514 |
264.518 |
0.152547475 |
276.529 |
0.27654027 |
0.00182557 |
0.151875634 |
0.00190603 |
0.277128181 |
2.3.2.2. DM Output File¶
File which aggregates damage state estimates from the DM.csv files of all building assets. |
||
properties |
||
|
Probability of collapse for each building asset, represented as a value between 0 and 1. |
|
type |
float |
|
|
The probability of each damage state for every building asset, provided as a value between 0 and 1. Probabilities are reported for five damage states: ‘0’ indicates no damage; ‘1_1’ indicates DS1 (aesthetic damage), ‘2_1’ indicates DS2 (mild damage), ‘3_1’ indicates DS3 (moderate damage), and ‘4_1’ indicates DS4 (severe damage). The DS likelihoods are additionally reported by component group, where the following abbreviations are used: ‘S’ = structural components, ‘NS’ = all nonstructural components, ‘NSA’ = acceleration-sensitive nonstructural components, ‘NSD’ = drift-sensitive nonstructural components. The probabilities of the five damage states for each component type (across the row) should sum to 1 (total probability for the building asset). |
|
type |
float |
The header schema, followed by an example output, is provided:
Collapse |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
DS likelihood |
|
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
comp_type |
probability |
S |
S |
S |
S |
S |
S |
NS |
NS |
NS |
NS |
NS |
NSA |
NSA |
NSA |
NSA |
NSA |
NSD |
NSD |
NSD |
NSD |
NSD |
DSG_DS |
0 |
1_1 |
2_1 |
3_1 |
4_1 |
4_2 |
0 |
1_1 |
2_1 |
3_1 |
4_1 |
0 |
1_1 |
2_1 |
3_1 |
4_1 |
0 |
1_1 |
2_1 |
3_1 |
4_1 |
|
1 |
0 |
0.8 |
0.2 |
0.2 |
0.2 |
0.6 |
0.2 |
0.2 |
0.6 |
0.8 |
0.2 |
2.3.2.3. DV Output File¶
File which aggregates decision variable estimates from the DV.csv files of all building assets. |
||
properties |
||
|
Repair cost for the entire building asset, reported with the statistics: mean, standard deviation, 10th percentile, median (50th percentile), and 90th percentile. The currency unit for the repair cost is the same as that of the the replacementCost property provided in the building input file. If replacementCost is set equal to 1, then the repair costs in the DV Output File are reported as a percentage of the replacement cost. |
|
type |
float |
|
|
Probability of repair being impractical for the building asset, provided as a value between 0 and 1. |
|
type |
float |
|
|
Mean repair cost for the building asset reported by component group (‘S’ = structural components, ‘NS’ = all nonstructural components, ‘NSA’ = acceleration-sensitive nonstructural components, ‘NSD’ = drift-sensitive nonstructural components) and damage state (‘aggregate’ = total for the component group, ‘1_1’ = DS1, ‘2_1’ = DS2, ‘3_1’ = DS3, ‘4_1’ = DS4). |
|
type |
float |
|
|
Repair time for the entire building asset, reported with the statistics: mean, standard deviation, 10th percentile, median (50th percentile), and 90th percentile. Time is reported in units of ___. |
|
type |
float |
|
|
Number of injuries projected as a result of damage to the building asset, reported with the statistics: mean, standard deviation, 10th percentile, median (50th percentile), and 90th percentile. Injuries are provided at four severity levels. |
|
type |
float |
The header schema, followed by an example output, is provided:
DV |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Impractical |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Cost |
Repair Time |
Repair Time |
Repair Time |
Repair Time |
Repair Time |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
Injuries |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
comp_type |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
probability |
S |
S |
S |
S |
S |
S |
NS |
NS |
NS |
NS |
NS |
NSA |
NSA |
NSA |
NSA |
NSA |
NSD |
NSD |
NSD |
NSD |
NSD |
sev1 |
sev1 |
sev1 |
sev1 |
sev1 |
sev2 |
sev2 |
sev2 |
sev2 |
sev2 |
sev3 |
sev3 |
sev3 |
sev3 |
sev3 |
sev4 |
sev4 |
sev4 |
sev4 |
sev4 |
|||||
DSG_DS |
aggregate |
1_1 |
2_1 |
3_1 |
4_1 |
4_2 |
aggregate |
1_1 |
2_1 |
3_1 |
4_1 |
aggregate |
1_1 |
2_1 |
3_1 |
4_1 |
aggregate |
1_1 |
2_1 |
3_1 |
4_1 |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
aggregate |
||||||
stat |
mean |
std |
10% |
median |
90% |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
mean |
std |
10% |
median |
90% |
mean |
std |
10% |
median |
90% |
mean |
std |
10% |
median |
90% |
mean |
std |
10% |
median |
90% |
mean |
std |
10% |
median |
90% |
|
1 |
0.056575 |
0.034084051 |
0.0138 |
0.08 |
0.086525 |
0 |
0.000725 |
0.003625 |
0.05585 |
0.005 |
0.027 |
0.082416667 |
0.0544 |
0.005 |
0.027 |
0.08 |
0.00145 |
0.00725 |
0.29 |
0.58 |
0 |
0 |
0.87 |
7.25E-05 |
0.000145 |
0 |
0 |
0.0002175 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |