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24 changes: 24 additions & 0 deletions .github/workflows/auto_build_page.yaml
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name: Auto Build Page
run-name: Running Job ${{ github.job }}
on: [push]
jobs:
Explore-GitHub-Actions:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Delete Previous docs
run: |
rm -rf docs && mkdir docs
- name: build docs
run: |
python3 -m pip install sphinx sphinx_rtd_theme && python3 -m sphinx -b html source/ docs
- name: add .nojekyll
run: |
touch docs/.nojekyll
- name: Commit Build
run: |
git add docs/.
git config --global user.name 'Friendly Builder Bot'
git config --global user.email 'builderbot'
git commit -am "Automated Build"
git push
2 changes: 1 addition & 1 deletion docs/.buildinfo
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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 79d6335a94e577cac2362e8a02b30e10
config: 64e4293bb7889d8873522494d4958d0d
tags: 645f666f9bcd5a90fca523b33c5a78b7
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Original file line number Diff line number Diff line change
Expand Up @@ -7,32 +7,29 @@
model("basic","-ndm",3,"-ndf",6)

# the response spectrum function
timeSeries(
"Path",1,"-time",
0.0,0.06,0.1,0.12,0.18,0.24,0.3,0.36,0.4,0.42,
0.48,0.54,0.6,0.66,0.72,0.78,0.84,0.9,0.96,1.02,
1.08,1.14,1.2,1.26,1.32,1.38,1.44,1.5,1.56,1.62,
1.68,1.74,1.8,1.86,1.92,1.98,2.04,2.1,2.16,2.22,
2.28,2.34,2.4,2.46,2.52,2.58,2.64,2.7,2.76,2.82,
2.88,2.94,3.0,3.06,3.12,3.18,3.24,3.3,3.36,3.42,
3.48,3.54,3.6,3.66,3.72,3.78,3.84,3.9,3.96,4.02,
4.08,4.14,4.2,4.26,4.32,4.38,4.44,4.5,4.56,4.62,
4.68,4.74,4.8,4.86,4.92,4.98,5.04,5.1,5.16,5.22,
5.28,5.34,5.4,5.46,5.52,5.58,5.64,5.7,5.76,5.82,
5.88,5.94,6.0,
"-values",
0.2,0.38,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.4762,
0.4167,0.3704,0.3333,0.303,0.2778,0.2564,0.2381,0.2222,0.2083,0.1961,
0.1852,0.1754,0.1667,0.1587,0.1515,0.1449,0.1389,0.1333,0.1282,0.1235,
0.119,0.1149,0.1111,0.1075,0.1042,0.101,0.098,0.0952,0.0926,0.0901,
0.0877,0.0855,0.0833,0.0813,0.0794,0.0775,0.0758,0.0741,0.0725,0.0709,
0.0694,0.068,0.0667,0.0641,0.0616,0.0593,0.0572,0.0551,0.0531,0.0513,
0.0495,0.0479,0.0463,0.0448,0.0434,0.042,0.0407,0.0394,0.0383,0.0371,
0.036,0.035,0.034,0.0331,0.0322,0.0313,0.0304,0.0296,0.0289,0.0281,
0.0274,0.0267,0.026,0.0254,0.0248,0.0242,0.0236,0.0231,0.0225,0.022,
0.0215,0.021,0.0206,0.0201,0.0197,0.0193,0.0189,0.0185,0.0181,0.0177,
0.0174,0.017,0.0167,
"-factor",9.806)
Tn = [0.0, 0.06, 0.1, 0.12, 0.18, 0.24, 0.3, 0.36, 0.4, 0.42,
0.48, 0.54, 0.6, 0.66, 0.72, 0.78, 0.84, 0.9, 0.96, 1.02,
1.08, 1.14, 1.2, 1.26, 1.32, 1.38, 1.44, 1.5, 1.56, 1.62,
1.68, 1.74, 1.8, 1.86, 1.92, 1.98, 2.04, 2.1, 2.16, 2.22,
2.28, 2.34, 2.4, 2.46, 2.52, 2.58, 2.64, 2.7, 2.76, 2.82,
2.88, 2.94, 3.0, 3.06, 3.12, 3.18, 3.24, 3.3, 3.36, 3.42,
3.48, 3.54, 3.6, 3.66, 3.72, 3.78, 3.84, 3.9, 3.96, 4.02,
4.08, 4.14, 4.2, 4.26, 4.32, 4.38, 4.44, 4.5, 4.56, 4.62,
4.68, 4.74, 4.8, 4.86, 4.92, 4.98, 5.04, 5.1, 5.16, 5.22,
5.28, 5.34, 5.4, 5.46, 5.52, 5.58, 5.64, 5.7, 5.76, 5.82,
5.88, 5.94, 6.0]
Sa = [1.9612, 3.72628, 4.903, 4.903, 4.903, 4.903, 4.903, 4.903, 4.903, 4.6696172,
4.0861602, 3.6321424, 3.2683398, 2.971218, 2.7241068, 2.5142584, 2.3348086, 2.1788932, 2.0425898, 1.9229566,
1.8160712, 1.7199724, 1.6346602, 1.5562122, 1.485609, 1.4208894, 1.3620534, 1.3071398, 1.2571292, 1.211041,
1.166914, 1.1267094, 1.0894466, 1.054145, 1.0217852, 0.990406, 0.960988, 0.9335312, 0.9080356, 0.8835206,
0.8599862, 0.838413, 0.8168398, 0.7972278, 0.7785964, 0.759965, 0.7432948, 0.7266246, 0.710935, 0.6952454,
0.6805364, 0.666808, 0.6540602, 0.6285646, 0.6040496, 0.5814958, 0.5609032, 0.5403106, 0.5206986, 0.5030478,
0.485397, 0.4697074, 0.4540178, 0.4393088, 0.4255804, 0.411852, 0.3991042, 0.3863564, 0.3755698, 0.3638026,
0.353016, 0.34321, 0.333404, 0.3245786, 0.3157532, 0.3069278, 0.2981024, 0.2902576, 0.2833934, 0.2755486,
0.2686844, 0.2618202, 0.254956, 0.2490724, 0.2431888, 0.2373052, 0.2314216, 0.2265186, 0.220635, 0.215732,
0.210829, 0.205926, 0.2020036, 0.1971006, 0.1931782, 0.1892558, 0.1853334, 0.181411, 0.1774886, 0.1735662,
0.1706244, 0.166702, 0.1637602]
timeSeries("Path",1,"-time", *Tn, "-values", *Sa)

# a uniaxial material for transverse shear
uniaxialMaterial("Elastic",2,938000000.0)
Expand Down Expand Up @@ -165,12 +162,42 @@ def CQC(mu, lambdas, dmp, scalf):
u += scalf[i]*mu[i] * scalf[j]*mu[j] * rho;
return sqrt(u)

# ========================================================================
# TEST 00
# run a response spectrum analysis for each mode.
# then do modal combination in post-processing.
# Use Tn and Sa lists
# ========================================================================
responseSpectrumAnalysis(direction, '-Tn', *Tn, '-Sa', *Sa)

# read the My values [3rd column] for each step
# (1 for each mode, they are section forces associated to each modal displacement)
My = []
with open(filename, 'r') as f:
lines = f.read().split('\n')
for line in lines:
if len(line) > 0:
tokens = line.split(' ')
My.append(float(tokens[2]))

# post process the results doing the CQC modal combination for the My response (3rd column in section forces)
MyCQC = CQC(My, eigs, dmp, scalf)

print('\n\nTEST 00:\nRun a Response Spectrum Analysis for all modes.')
print('Do CQC combination in post processing.')
print('Use Tn and Sa lists.\n')
print('{0: >10}{1: >15}'.format('Mode', 'My'))
for i in range(len(eigs)):
print('{0: >10}{1: >15f}'.format(i+1, My[i]))
print('{0: >10}{1: >15f}'.format('CQC', MyCQC))

# ========================================================================
# TEST 01
# run a response spectrum analysis for each mode.
# then do modal combination in post-processing.
# Use a Path timeSeries to store the Tn-Sa pairs
# ========================================================================
responseSpectrum(tsTag, direction)
responseSpectrumAnalysis(tsTag, direction)

# read the My values [3rd column] for each step
# (1 for each mode, they are section forces associated to each modal displacement)
Expand All @@ -185,7 +212,9 @@ def CQC(mu, lambdas, dmp, scalf):
# post process the results doing the CQC modal combination for the My response (3rd column in section forces)
MyCQC = CQC(My, eigs, dmp, scalf)

print('\n\nTEST 01:\nRun a Response Spectrum Analysis for each mode.\nDo CQC combination in post processing.\n')
print('\n\nTEST 01:\nRun a Response Spectrum Analysis for all modes.')
print('Do CQC combination in post processing.')
print('Use a Path timeSeries to store Tn-Sa pairs.\n')
print('{0: >10}{1: >15}'.format('Mode', 'My'))
for i in range(len(eigs)):
print('{0: >10}{1: >15f}'.format(i+1, My[i]))
Expand All @@ -200,14 +229,15 @@ def CQC(mu, lambdas, dmp, scalf):
remove('recorder', 0)
My = []
for i in range(len(eigs)):
responseSpectrum(tsTag, direction, '-mode', i+1)
responseSpectrumAnalysis(direction, '-Tn', *Tn, '-Sa', *Sa, '-mode', i+1)
force = eleResponse(1, 'section', '1', 'force')
My.append(force[2])

# post process the results doing the CQC modal combination for the My response (3rd column in section forces)
MyCQC = CQC(My, eigs, dmp, scalf)

print('\n\nTEST 01:\nRun a Response Spectrum Analysis mode-by-mode.\nGrab results during the loop.\nDo CQC combination in post processing.\n')
print('\n\nTEST 02:\nRun a Response Spectrum Analysis mode-by-mode.')
print('Grab results during the loop and do CQC combination with them.\n')
print('{0: >10}{1: >15}'.format('Mode', 'My'))
for i in range(len(eigs)):
print('{0: >10}{1: >15f}'.format(i+1, My[i]))
Expand Down
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Original file line number Diff line number Diff line change
Expand Up @@ -4,29 +4,29 @@ wipe
model basic -ndm 3 -ndf 6

# the response spectrum function
set timeSeries_list_of_times_1 {0.0 0.06 0.1 0.12 0.18 0.24 0.3 0.36 0.4 0.42 \
0.48 0.54 0.6 0.66 0.72 0.78 0.84 0.9 0.96 1.02 \
1.08 1.14 1.2 1.26 1.32 1.38 1.44 1.5 1.56 1.62 \
1.68 1.74 1.8 1.86 1.92 1.98 2.04 2.1 2.16 2.22 \
2.28 2.34 2.4 2.46 2.52 2.58 2.64 2.7 2.76 2.82 \
2.88 2.94 3.0 3.06 3.12 3.18 3.24 3.3 3.36 3.42 \
3.48 3.54 3.6 3.66 3.72 3.78 3.84 3.9 3.96 4.02 \
4.08 4.14 4.2 4.26 4.32 4.38 4.44 4.5 4.56 4.62 \
4.68 4.74 4.8 4.86 4.92 4.98 5.04 5.1 5.16 5.22 \
5.28 5.34 5.4 5.46 5.52 5.58 5.64 5.7 5.76 5.82 \
5.88 5.94 6.0}
set timeSeries_list_of_values_1 {0.2 0.38 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.4762 \
0.4167 0.3704 0.3333 0.303 0.2778 0.2564 0.2381 0.2222 0.2083 0.1961 \
0.1852 0.1754 0.1667 0.1587 0.1515 0.1449 0.1389 0.1333 0.1282 0.1235 \
0.119 0.1149 0.1111 0.1075 0.1042 0.101 0.098 0.0952 0.0926 0.0901 \
0.0877 0.0855 0.0833 0.0813 0.0794 0.0775 0.0758 0.0741 0.0725 0.0709 \
0.0694 0.068 0.0667 0.0641 0.0616 0.0593 0.0572 0.0551 0.0531 0.0513 \
0.0495 0.0479 0.0463 0.0448 0.0434 0.042 0.0407 0.0394 0.0383 0.0371 \
0.036 0.035 0.034 0.0331 0.0322 0.0313 0.0304 0.0296 0.0289 0.0281 \
0.0274 0.0267 0.026 0.0254 0.0248 0.0242 0.0236 0.0231 0.0225 0.022 \
0.0215 0.021 0.0206 0.0201 0.0197 0.0193 0.0189 0.0185 0.0181 0.0177 \
0.0174 0.017 0.0167}
timeSeries Path 1 -time $timeSeries_list_of_times_1 -values $timeSeries_list_of_values_1 -factor 9.806
set Tn {0.0 0.06 0.1 0.12 0.18 0.24 0.3 0.36 0.4 0.42 \
0.48 0.54 0.6 0.66 0.72 0.78 0.84 0.9 0.96 1.02 \
1.08 1.14 1.2 1.26 1.32 1.38 1.44 1.5 1.56 1.62 \
1.68 1.74 1.8 1.86 1.92 1.98 2.04 2.1 2.16 2.22 \
2.28 2.34 2.4 2.46 2.52 2.58 2.64 2.7 2.76 2.82 \
2.88 2.94 3.0 3.06 3.12 3.18 3.24 3.3 3.36 3.42 \
3.48 3.54 3.6 3.66 3.72 3.78 3.84 3.9 3.96 4.02 \
4.08 4.14 4.2 4.26 4.32 4.38 4.44 4.5 4.56 4.62 \
4.68 4.74 4.8 4.86 4.92 4.98 5.04 5.1 5.16 5.22 \
5.28 5.34 5.4 5.46 5.52 5.58 5.64 5.7 5.76 5.82 \
5.88 5.94 6.0}
set Sa {1.9612 3.72628 4.903 4.903 4.903 4.903 4.903 4.903 4.903 4.6696172 \
4.0861602 3.6321424 3.2683398 2.971218 2.7241068 2.5142584 2.3348086 2.1788932 2.0425898 1.9229566 \
1.8160712 1.7199724 1.6346602 1.5562122 1.485609 1.4208894 1.3620534 1.3071398 1.2571292 1.211041 \
1.166914 1.1267094 1.0894466 1.054145 1.0217852 0.990406 0.960988 0.9335312 0.9080356 0.8835206 \
0.8599862 0.838413 0.8168398 0.7972278 0.7785964 0.759965 0.7432948 0.7266246 0.710935 0.6952454 \
0.6805364 0.666808 0.6540602 0.6285646 0.6040496 0.5814958 0.5609032 0.5403106 0.5206986 0.5030478 \
0.485397 0.4697074 0.4540178 0.4393088 0.4255804 0.411852 0.3991042 0.3863564 0.3755698 0.3638026 \
0.353016 0.34321 0.333404 0.3245786 0.3157532 0.3069278 0.2981024 0.2902576 0.2833934 0.2755486 \
0.2686844 0.2618202 0.254956 0.2490724 0.2431888 0.2373052 0.2314216 0.2265186 0.220635 0.215732 \
0.210829 0.205926 0.2020036 0.1971006 0.1931782 0.1892558 0.1853334 0.181411 0.1774886 0.1735662 \
0.1706244 0.166702 0.1637602}
timeSeries Path 1 -time $Tn -values $Sa

# a uniaxial material for transverse shear
uniaxialMaterial Elastic 2 938000000.0
Expand Down Expand Up @@ -161,12 +161,46 @@ proc CQC {mu lambdas dmp scalf} {
return [expr sqrt($u)]
}

# ========================================================================
# TEST 00
# run a response spectrum analysis for each mode.
# then do modal combination in post-processing.
# Use Tn and Sa lists
# ========================================================================
responseSpectrumAnalysis $direction -Tn $Tn -Sa $Sa

# read the My values [3rd column] for each step
# (1 for each mode, they are section forces associated to each modal displacement)
set My {}
set f [open $filename "r"]
set lines [split [read $f] "\n"]
foreach line $lines {
if {[llength $line] > 0} {
set tokens [split $line " "]
lappend My [lindex $tokens 2]
}
}
close $f

# post process the results doing the CQC modal combination for the My response (3rd column in section forces)
set MyCQC [CQC $My $eigs $dmp $scalf]

puts "\n\nTEST 00:\nRun a Response Spectrum Analysis for all modes."
puts "Do CQC combination in post processing."
puts "Use Tn and Sa lists.\n"
puts [format "%10s %15s" "Mode" "My"]
for {set i 0} {$i < [llength $eigs]} {incr i} {
puts [format "%10g %15f" [expr $i+1] [lindex $My $i]]
}
puts [format "%10s %15f" "CQC" $MyCQC]

# ========================================================================
# TEST 01
# run a response spectrum analysis for each mode.
# then do modal combination in post-processing.
# Use a Path timeSeries to store the Tn-Sa pairs
# ========================================================================
responseSpectrum $tsTag $direction
responseSpectrumAnalysis $tsTag $direction

# read the My values [3rd column] for each step
# (1 for each mode, they are section forces associated to each modal displacement)
Expand All @@ -184,7 +218,9 @@ close $f
# post process the results doing the CQC modal combination for the My response (3rd column in section forces)
set MyCQC [CQC $My $eigs $dmp $scalf]

puts "\n\nTEST 01:\nRun a Response Spectrum Analysis for each mode.\nDo CQC combination in post processing.\n"
puts "\n\nTEST 01:\nRun a Response Spectrum Analysis for all modes."
puts "Do CQC combination in post processing."
puts "Use a Path timeSeries to store Tn-Sa pairs.\n"
puts [format "%10s %15s" "Mode" "My"]
for {set i 0} {$i < [llength $eigs]} {incr i} {
puts [format "%10g %15f" [expr $i+1] [lindex $My $i]]
Expand All @@ -200,14 +236,15 @@ puts [format "%10s %15f" "CQC" $MyCQC]
remove recorder 0
set My {}
for {set i 0} {$i < [llength $eigs]} {incr i} {
responseSpectrum $tsTag $direction -mode [expr $i+1]
responseSpectrumAnalysis $direction -Tn $Tn -Sa $Sa -mode [expr $i+1]
set force [eleResponse 1 section 1 force]
lappend My [lindex $force 2]
}

# post process the results doing the CQC modal combination for the My response (3rd column in section forces)
set MyCQC [CQC $My $eigs $dmp $scalf]
puts "\n\nTEST 01:\nRun a Response Spectrum Analysis mode-by-mode.\nGrab results during the loop.\nDo CQC combination in post processing.\n"
puts "\n\nTEST 02:\nRun a Response Spectrum Analysis mode-by-mode."
puts "Grab results during the loop and do CQC combination with them.\n"
puts [format "%10s %15s" "Mode" "My"]
for {set i 0} {$i < [llength $eigs]} {incr i} {
puts [format "%10g %15f" [expr $i+1] [lindex $My $i]]
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