Difference between revisions of "UCVM Vs30"

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 +
== UCVM Vs30 Method ==
 +
 +
 +
==== Vs30 at recording stations ====
 +
* For interpretation of recorded data, use in order of preference
 +
** values listed as "Vs30 (m/s) selected for analysis" in the NGA-West2 database flatfile
 +
** if stations are not included in the NGA-West2 database, we will use the values from Will et al. 2015 as retrieved from UCVM (with interpolation)
 +
* For interpretation of simulation data
 +
** We retrieved the Vs30 values using UCVM v19.4 for CVM-S4.26.M01 (cvmsi), for CVM-S4.26 (to show impact of adding .M01 GTL), for CVM-S4 (to check if Vs30 matches .M01 exactly), and from the Wills 2015 Vs30 model embedded in UCVM.
 +
* For the Vs30_query against the models uses a slowness algorithm, and a 1 meter spacing.
 +
* The Wills 2015 Vs30 values are based a processing sequence that includes converting a GIS shape file into a rasterized Vs30 grid of values produced by Kevin Milner. Kevin provided a file raster_0.00025.flt, which is rasterized with 0.00025 degree spacing (~25 meters). This file is then used to generate an etree which is used to stored the rasterized data. When query points are given between grid points, then ucvm implements interplolation of Vs30 values between associated grid points. More
 +
* More details on the Willis Map integration here: [[Wills Map]].
 +
* Descriptions of UCVM Vs30 Slowness algorithm here: [[UCVM_Vs30]].
 +
* Description of CyberShake Vs30 Slowness algorithm here: [[CyberShake_Code_Base#Stochastic%20codes]]
 +
 +
{| class="wikitable"
 +
|+UCVM Vs30 Values
 +
|-
 +
|Lon
 +
|Lat
 +
|Vs30 - Wills 2015 (UCVM v19.4)
 +
|Vs30 - Slowness Method (1m spacing) (CVM-S4.26.M01 - cvmsi)
 +
|Vs30 - Slowness Method (CVM-S4.26 - cvms5)
 +
|Vs30 - Slowness Method (CVM-S4 - cvms)
 +
|Vs30 - Slowness Method (CVM-H - cvmh)
 +
|-
 +
| -117.9568
 +
| 33.8401
 +
| 293.500
 +
| 284.461 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_0]
 +
| 838.630
 +
| 284.461
 +
|120.690
 +
|-
 +
| -117.8179
 +
| 33.8533
 +
| 351.900
 +
| 329.762 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_1]
 +
| 850.496
 +
| 329.762
 +
| 394.852
 +
|-
 +
| -117.8869
 +
| 33.8891
 +
| 312.445
 +
| 344.043 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_2]
 +
| 861.493
 +
| 344.043
 +
| 345.057
 +
|-
 +
| -117.9590
 +
| 33.8663
 +
| 228.200
 +
| 287.845 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_3]
 +
| 839.552
 +
| 287.845
 +
| 120.690
 +
|-
 +
| -117.9311
 +
| 33.9085
 +
| 386.600
 +
| 349.812 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_4]
 +
| 901.162
 +
| 349.812
 +
| 551.916
 +
|-
 +
| -117.9558
 +
| 33.9315
 +
| 386.600
 +
| 349.317 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_5]
 +
| 889.947
 +
| 349.317
 +
| 705.182
 +
|-
 +
| -117.8033
 +
| 33.9273
 +
| 385.100
 +
| 367.423 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_6]
 +
| 907.358
 +
| 367.423
 +
| 360.902
 +
|-
 +
| -117.8571
 +
| 33.8530
 +
| 228.200
 +
| 329.762 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_7]
 +
| 847.254
 +
| 329.762
 +
| 281.789
 +
|-
 +
| -118.0469
 +
| 33.8892
 +
| 228.200
 +
| 287.845 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_8]
 +
| 838.561
 +
| 287.845
 +
| 285.982
 +
|-
 +
| -118.0575
 +
| 33.9282
 +
| 386.600
 +
| 354.637 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_9]
 +
| 855.127
 +
| 354.637
 +
| 224.184
 +
|-
 +
| -117.8656
 +
| 34.0210
 +
| 419.818
 +
| 370.670 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_10]
 +
| 955.197
 +
| 370.670
 +
| 426.076
 +
|-
 +
| -117.9812
 +
| 33.8077
 +
| 228.200
 +
| 285.871 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_11]
 +
| 839.554
 +
| 285.871
 +
| 237.354
 +
|-
 +
| -117.9224
 +
| 33.8717
 +
| 293.500
 +
| 362.574 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_12]
 +
| 845.207
 +
| 362.574
 +
| 262.028
 +
|-
 +
| -117.9237
 +
| 33.9454
 +
| 385.411
 +
| 331.459 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_13]
 +
| 932.222
 +
| 331.459
 +
|726.045
 +
|-
 +
| -117.9508
 +
| 34.0095
 +
| 293.500
 +
| 309.646 [http://hypocenter.usc.edu/research/ucvmc_result/vs30_slowness/slowVS30_14]
 +
| 937.482
 +
| 309.646
 +
|1062.044
 +
|}
 +
 +
 +
We are reviewing the algorithms used to calculate Vs30 in UCVM.
 +
 +
== UCVM CS173 Model-based Vs30 ==
 +
Vs30 based on tiled models queried at 1m spacing 0-29m depth using slowness calculation
 +
[[File:vs30_cs173.png|right|350px]]
 +
 +
== UCVM Etree Vs30 Map ==
 +
Vs30 from UCVM etree map, based on Willis 2006 map and Wald Topography (outside California)
 +
[[File:Vs3 ucvm etree.png|right|350px]]
 +
 +
== Vs30 Test Points shown On Map ==
 +
Vs30 from UCVM etree map, based on Willis 2006 map and Wald Topography (outside California)
 +
[[File:Profile_test_points.png|right|350px]]
 +
 +
 +
 +
 
== Introduction ==
 
== Introduction ==
−
 
 
There may be an issue with how UCVM calculates Vs30 values. Presently UCVM uses the following formula:
 
There may be an issue with how UCVM calculates Vs30 values. Presently UCVM uses the following formula:
−
 
+
#31/ sum(Vs sampled from [0,30] at 1 meters, for 31 total values)
−
sum(Vs sampled from [0,30] at 1 meters, for 31 total values) / 31
 
  
 
Rob has suggested that the correct formula should be:
 
Rob has suggested that the correct formula should be:
 +
#30 / sum(1 / (Vs sampled from [0, 30) at 1 meters, for 30 total values))
  
−
30 / sum(1 / (Vs sampled from [0, 30) at 1 meters, for 30 total values))
+
This can have a significant impact for Vs30 calculations. For the BBP1D model, UCVM calculates the Vs30 as 932m/s, whereas Rob's formula calculates it as 862m/s.
  
−
This can have a significant impact for Vs30 calculations. For the BBP1D model, UCVM calculates the Vs30 as 932m/s, whereas Rob's formula calculates it as 862m/s.
+
Another approach was used in CyberShake Study 15.12, in conversations with Rob:
 +
#Vs30 = 30 / Sum (1/(Vs sampled from [0.5,29.5] in 1 meter increments, for 30 total values)).
  
−
Another approach was used in CyberShake Study 15.12, in conversations with Rob: Vs30 = 30 / Sum (1/(Vs sampled from [0.5,29.5] in 1 meter increments, for 30 total values)).
+
== Points for comparison ==
 +
We have selected 6 points to compare Vs30 as generated using the CyberShake approach (using half-meters) to other UCVM approaches.
  
−
== Points for comparison ==
+
*Input points for ucvm_query:
  
−
We have selected 6 points to compare Vs30 as generated using the CyberShake approach (using half-meters) to other UCVM approaches.
+
  34.1484  -118.1712
 +
  34.5570 -118.1250
 +
  34.0192 -118.2860
 +
  34.6402 -118.9192
 +
  36.1397 -120.3602   
 +
  34.2667 -119.2285   
  
 
{| border="1"
 
{| border="1"
−
! lat !! lon !! Velocity model !! CyberShake-generated Vs30
+
! lat !! lon !! Velocity model !! CyberShake-generated Vs30 !! UCVM 18.5 Gen Vs30 !! UCVM 18.5 (Wills 2015) !! UCVM Vs30 etree.map (Wills 2006) !! UCVM Vs30 etree.map (Wills 2015)
 
|-
 
|-
−
| 34.148426 || -118.17119 || CVM-S4.26.M01 || 838.8
+
| 34.148426 || -118.17119 || CVM-S4.26.M01 || 838.8 || 821.328 || 821.335 || 748.00 || 710.1 (cvmsi)
 
|-
 
|-
−
| 34.557 || -118.125 || CVM-S4.26.M01 || 2573.6
+
| 34.557 || -118.125 || CVM-S4.26.M01 || 2573.6 || 2573.634 || 324.974 || 497.68 || 402.1 (cca)
 +
|-
 +
| 34.0192 || -118.286 || CVM-S4.26.M01 || 313.1 || 310.574 || 310.574 || 280.0 || 293.5 (cvmsi)
 
|-
 
|-
−
| 34.0192 || -118.286 || CVM-S4.26.M01 || 313.1
+
| 34.64021 || -118.91919 || CCA-06 || 3393.9 || 3331.251 || 561.377 || 748.0 || 710.1 (cca)
 
|-
 
|-
−
| 34.64021 || -118.91919 || CCA-06 || 3393.9
+
| 36.13968 || -120.36015 || CCA-06 || 2277.2 || 2279.326 || 261.704 || 349.0 || 293.5 (cca)
 
|-
 
|-
−
| 36.13968 || -120.36015 || CCA-06 || 2277.2
+
| 34.26667 || -119.22848 || CCA-06 || 902.3 || 902.013 || 244.135 || 280.0 || 325.5 (cca)
−
|-
 
−
| 34.26667 || -119.22848 || CCA-06 || 902.3
 
 
|}
 
|}
  
−
== UCVMC v18.5 results ==
+
== Querying cs173 slow due to the fine resolution ==
 +
To run on max memory on hpc cluster nodes
  
 
<pre>
 
<pre>
−
-bash-4.2$ ./vs30_query -f ../conf/ucvm.conf -m cvmsi < in.txt
+
#!/bin/bash
−
-118.1712    34.1484    821.328
+
#SBATCH -p scec
−
-118.1250    34.5570  2573.634
+
#SBATCH --ntasks=1 #number of tasks with one per processor
−
-118.2860    34.0192    310.574
+
#SBATCH -N 1 # number of nodes
−
-118.9192    34.6402  3393.808
+
#SBATCH --mem 0 # Set to unlimited memory
−
-120.3602    36.1397  2436.254
+
#SBATCH --time=12:00:00
−
-119.2285    34.2667    283.145
+
#SBATCH -o ucvm2mesh_mpi_%A.out
 +
#SBATCH -e ucvm2mesh_mpi_%A.err
 +
#SBATCH --export=NONE
 +
#SBATCH --mail-user=maechlin@usc.edu
 +
#SBATCH --mail-type=END
 +
 
 +
cd /auto/scec-00/maechlin/ucvmc185/utilities
 +
srun -v --mpi=pmi2 /auto/scec-00/maechlin/ucvmc185/utilities/plot_vs30_map.py -b 30.5,-126.0 -u 42.5,-112.5 -s 0.01 -a s -c cs173 -o vs30_cs173.png
 +
-bash-4.2$
 +
 
 
</pre>
 
</pre>
  
 +
== Related Links: ==
 +
Plot command used to plot_vs30_map.
 +
./plot_vs30_map.py -b 30.5,-126.0 -u 42.5,-112.5 -s 0.05 -a s -c cs173 -o vs30_cs173.png
 +
 +
Scott posted vs30 values from CyberShake here:
 +
http://scec.usc.edu/scecpedia/CyberShake_Study_15.12#Vs_values_v2.0
 +
 +
== Notes on Software Implementation for Review ==
  
 
<pre>
 
<pre>
−
-bash-4.2$ ./vs30_query -f ../conf/ucvm.conf -m cca < in.txt
+
    UCVM/src/ucvm/ucvm_map.c
−
-118.1712   34.1484      0.000
+
    -- etree from Walls data
−
-118.1250   34.5570  2582.267
+
        is used to calculate interpolated vs30 values
−
-118.2860    34.0192     0.000
+
          4 surrounding points -- interploate_bilinear
−
-118.9192    34.6402   3331.251
+
   
−
-120.3602    36.1397   2279.326
+
    UCVM/src/vs30/vs30_query.c
−
-119.2285    34.2667    902.013
+
    -- vs30 calculated as 'slowness'
 +
        vs= 31/vs_sum  (vs_sum => sum of(1/query_data.cmb.vs)
 +
                        where z from 0 to 30)
 +
 
 +
    cvmh1511/src/vs30_gtl.c
 +
    -- vs30 derived GTL base on Ely (2010)
 +
        gtl model file is loaded into model
 +
        location is 'rounded' in retrieving
 +
        -> These gtl file are generated from Wills
 +
            cvm_vs30_wills.hdr
 +
            cvm_vs30_wills.mdl
 +
 
 +
    cvms5/src/cvms5.c, cca/src/cca.c
 +
    -- cvms5_get_vs30_based_gtl()
 +
          calls
 +
          cvms5_get_vs30_value()
 +
              -- get 4 surrounding points from etree(payload 0,1,2,3)
 +
                and bilinear interpolation?
 +
suspicous selection:
 +
   vs30_payload[0].vs30 = percent * vs30_payload[0].vs30 + (1 - percent) * vs30_payload[1].vs30;
 +
   vs30_payload[1].vs30 = percent * vs30_payload[2].vs30 + (1 - percent) * vs30_payload[3].vs30;
 +
        return vs30_payload[0].vs30;
 +
 
 +
     cvms -- no vs30
 +
    cencal -- no vs30
 +
 
 +
    cvms426/src/vs30_gtl.c
 +
    -- >>vs30_gtl.c - Vs30 derived GTL based on Ely (2010)
 +
        >>06/2013: DJG - taken from CVM-H and adapted to CVM-S4.23
 +
        >>sprintf(gtldir, "%s/cvm_vs30_wills", modelpath);
 +
        >>if (ADD_GTL) {
 +
        >>   gtl_setup(gtldir);
 +
  gcoor[0]=round((entry->coor_utm[0]-gtl.extent[0])/gtl.spacing);
 +
   gcoor[1]=round((entry->coor_utm[1]-gtl.extent[2])/gtl.spacing);
 +
    location is using rounded() to get the grid point
 +
 
 +
 
 
</pre>
 
</pre>
 +
 +
== Related Entries  ==
 +
*[[UCVM]]

Latest revision as of 15:59, 12 May 2020

UCVM Vs30 Method

Vs30 at recording stations

  • For interpretation of recorded data, use in order of preference
    • values listed as "Vs30 (m/s) selected for analysis" in the NGA-West2 database flatfile
    • if stations are not included in the NGA-West2 database, we will use the values from Will et al. 2015 as retrieved from UCVM (with interpolation)
  • For interpretation of simulation data
    • We retrieved the Vs30 values using UCVM v19.4 for CVM-S4.26.M01 (cvmsi), for CVM-S4.26 (to show impact of adding .M01 GTL), for CVM-S4 (to check if Vs30 matches .M01 exactly), and from the Wills 2015 Vs30 model embedded in UCVM.
  • For the Vs30_query against the models uses a slowness algorithm, and a 1 meter spacing.
  • The Wills 2015 Vs30 values are based a processing sequence that includes converting a GIS shape file into a rasterized Vs30 grid of values produced by Kevin Milner. Kevin provided a file raster_0.00025.flt, which is rasterized with 0.00025 degree spacing (~25 meters). This file is then used to generate an etree which is used to stored the rasterized data. When query points are given between grid points, then ucvm implements interplolation of Vs30 values between associated grid points. More
  • More details on the Willis Map integration here: Wills Map.
  • Descriptions of UCVM Vs30 Slowness algorithm here: UCVM_Vs30.
  • Description of CyberShake Vs30 Slowness algorithm here: CyberShake_Code_Base#Stochastic codes
UCVM Vs30 Values
Lon Lat Vs30 - Wills 2015 (UCVM v19.4) Vs30 - Slowness Method (1m spacing) (CVM-S4.26.M01 - cvmsi) Vs30 - Slowness Method (CVM-S4.26 - cvms5) Vs30 - Slowness Method (CVM-S4 - cvms) Vs30 - Slowness Method (CVM-H - cvmh)
-117.9568 33.8401 293.500 284.461 [1] 838.630 284.461 120.690
-117.8179 33.8533 351.900 329.762 [2] 850.496 329.762 394.852
-117.8869 33.8891 312.445 344.043 [3] 861.493 344.043 345.057
-117.9590 33.8663 228.200 287.845 [4] 839.552 287.845 120.690
-117.9311 33.9085 386.600 349.812 [5] 901.162 349.812 551.916
-117.9558 33.9315 386.600 349.317 [6] 889.947 349.317 705.182
-117.8033 33.9273 385.100 367.423 [7] 907.358 367.423 360.902
-117.8571 33.8530 228.200 329.762 [8] 847.254 329.762 281.789
-118.0469 33.8892 228.200 287.845 [9] 838.561 287.845 285.982
-118.0575 33.9282 386.600 354.637 [10] 855.127 354.637 224.184
-117.8656 34.0210 419.818 370.670 [11] 955.197 370.670 426.076
-117.9812 33.8077 228.200 285.871 [12] 839.554 285.871 237.354
-117.9224 33.8717 293.500 362.574 [13] 845.207 362.574 262.028
-117.9237 33.9454 385.411 331.459 [14] 932.222 331.459 726.045
-117.9508 34.0095 293.500 309.646 [15] 937.482 309.646 1062.044


We are reviewing the algorithms used to calculate Vs30 in UCVM.

UCVM CS173 Model-based Vs30

Vs30 based on tiled models queried at 1m spacing 0-29m depth using slowness calculation

Vs30 cs173.png

UCVM Etree Vs30 Map

Vs30 from UCVM etree map, based on Willis 2006 map and Wald Topography (outside California)

Vs3 ucvm etree.png

Vs30 Test Points shown On Map

Vs30 from UCVM etree map, based on Willis 2006 map and Wald Topography (outside California)

Profile test points.png



Introduction

There may be an issue with how UCVM calculates Vs30 values. Presently UCVM uses the following formula:

  1. 31/ sum(Vs sampled from [0,30] at 1 meters, for 31 total values)

Rob has suggested that the correct formula should be:

  1. 30 / sum(1 / (Vs sampled from [0, 30) at 1 meters, for 30 total values))

This can have a significant impact for Vs30 calculations. For the BBP1D model, UCVM calculates the Vs30 as 932m/s, whereas Rob's formula calculates it as 862m/s.

Another approach was used in CyberShake Study 15.12, in conversations with Rob:

  1. Vs30 = 30 / Sum (1/(Vs sampled from [0.5,29.5] in 1 meter increments, for 30 total values)).

Points for comparison

We have selected 6 points to compare Vs30 as generated using the CyberShake approach (using half-meters) to other UCVM approaches.

  • Input points for ucvm_query:
 34.1484  -118.1712
 34.5570 -118.1250
 34.0192 -118.2860
 34.6402 -118.9192
 36.1397 -120.3602    
 34.2667 -119.2285
lat lon Velocity model CyberShake-generated Vs30 UCVM 18.5 Gen Vs30 UCVM 18.5 (Wills 2015) UCVM Vs30 etree.map (Wills 2006) UCVM Vs30 etree.map (Wills 2015)
34.148426 -118.17119 CVM-S4.26.M01 838.8 821.328 821.335 748.00 710.1 (cvmsi)
34.557 -118.125 CVM-S4.26.M01 2573.6 2573.634 324.974 497.68 402.1 (cca)
34.0192 -118.286 CVM-S4.26.M01 313.1 310.574 310.574 280.0 293.5 (cvmsi)
34.64021 -118.91919 CCA-06 3393.9 3331.251 561.377 748.0 710.1 (cca)
36.13968 -120.36015 CCA-06 2277.2 2279.326 261.704 349.0 293.5 (cca)
34.26667 -119.22848 CCA-06 902.3 902.013 244.135 280.0 325.5 (cca)

Querying cs173 slow due to the fine resolution

To run on max memory on hpc cluster nodes 

#!/bin/bash
#SBATCH -p scec
#SBATCH --ntasks=1 #number of tasks with one per processor
#SBATCH -N 1 # number of nodes
#SBATCH --mem 0 # Set to unlimited memory
#SBATCH --time=12:00:00
#SBATCH -o ucvm2mesh_mpi_%A.out
#SBATCH -e ucvm2mesh_mpi_%A.err
#SBATCH --export=NONE
#SBATCH --mail-user=maechlin@usc.edu
#SBATCH --mail-type=END

cd /auto/scec-00/maechlin/ucvmc185/utilities
srun -v --mpi=pmi2 /auto/scec-00/maechlin/ucvmc185/utilities/plot_vs30_map.py -b 30.5,-126.0 -u 42.5,-112.5 -s 0.01 -a s -c cs173 -o vs30_cs173.png
-bash-4.2$

Related Links:

Plot command used to plot_vs30_map. ./plot_vs30_map.py -b 30.5,-126.0 -u 42.5,-112.5 -s 0.05 -a s -c cs173 -o vs30_cs173.png

Scott posted vs30 values from CyberShake here: http://scec.usc.edu/scecpedia/CyberShake_Study_15.12#Vs_values_v2.0

Notes on Software Implementation for Review

     UCVM/src/ucvm/ucvm_map.c
     -- etree from Walls data
        is used to calculate interpolated vs30 values
          4 surrounding points -- interploate_bilinear
     
     UCVM/src/vs30/vs30_query.c
     -- vs30 calculated as 'slowness'
        vs= 31/vs_sum  (vs_sum => sum of(1/query_data.cmb.vs) 
                        where z from 0 to 30) 

     cvmh1511/src/vs30_gtl.c
     -- vs30 derived GTL base on Ely (2010)
        gtl model file is loaded into model 
        location is 'rounded' in retrieving
        -> These gtl file are generated from Wills
             cvm_vs30_wills.hdr
             cvm_vs30_wills.mdl

     cvms5/src/cvms5.c, cca/src/cca.c 
     -- cvms5_get_vs30_based_gtl()
           calls
           cvms5_get_vs30_value()
              -- get 4 surrounding points from etree(payload 0,1,2,3) 
                 and bilinear interpolation?
suspicous selection:
   vs30_payload[0].vs30 = percent * vs30_payload[0].vs30 + (1 - percent) * vs30_payload[1].vs30;
   vs30_payload[1].vs30 = percent * vs30_payload[2].vs30 + (1 - percent) * vs30_payload[3].vs30;
        return vs30_payload[0].vs30;

     cvms -- no vs30
     cencal -- no vs30

     cvms426/src/vs30_gtl.c 
     -- >>vs30_gtl.c - Vs30 derived GTL based on Ely (2010)
        >>06/2013: DJG - taken from CVM-H and adapted to CVM-S4.23
        >>sprintf(gtldir, "%s/cvm_vs30_wills", modelpath);
        >>if (ADD_GTL) {
        >>   gtl_setup(gtldir);
  gcoor[0]=round((entry->coor_utm[0]-gtl.extent[0])/gtl.spacing);
  gcoor[1]=round((entry->coor_utm[1]-gtl.extent[2])/gtl.spacing);
     location is using rounded() to get the grid point

Related Entries

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