Direct Strength Design for Cold-Formed Steel Members with Perforations Holes Progress... ·...
Transcript of Direct Strength Design for Cold-Formed Steel Members with Perforations Holes Progress... ·...
Direct Strength Design for Cold-Formed Steel Members
with Perforations
Progress Report 4C. Moen and B.W. Schafer
AISI-COS MeetingJuly 2007
Outline• Objective• Summary of past progress• FEA of Columns with holes
– Modeling approach– Elastic buckling– Nonlinear modeling to collapse– Comparison with testing from progress report 3
• Developing DSM for columns with holes– Impact of gross vs. net area decisions on strength– Comparison of predictions for available column tests
• Conclusions• Future Work
to becovered intask groupmeeting
ObjectiveDevelopment of a general design method
for cold-formed steel members with perforations.
Direct Strength Method ExtensionsPn = f (Py, Pcre, Pcrd, Pcrl)?
How do the DSMcurves need tochange?
Gross or net, or some combination?
Explicitly model hole(s)?Accuracy? Efficiency?Identification? Just thesemodes?
Progress Report 1 & 2 HighlightElastic Buckling Modes in a Column
Pcrd=1.15Py,g
Pcrl=0.42Py,g Pcrl=0.42Py,g
Pcrd1=0.52Py,g
Pcrd2=0.54Py,g
Pcrd3=1.16Py,g
D
L L
L+DH
DH2
D+L
Distortional modes unique to a column with a hole
Unique D modes are created with the presence of a hole
Progress Report 2 HighlightInfluence of multiple holes on elastic buckling
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1
0 5 10 15 20 250
0.2
0.4
0.6
0.8
1
1.2
S/Lhole
f cr,h
oles
/f cr,n
o ho
les
hhole/h=0.66
hhole/h=0.44
hhole/h=0.19
hhole/h=0.26
2 3 4 50.75
0.8
0.85
0.9
S/Lhole
0
S Lhole hholeh
Decrease in fcr when hole spacing becomes small
S > 5Lhole or holes interact with one another
Progress Report 2 HighlightCritical buckling stress equation
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 10
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
hhole/h
plat
e bu
cklin
g co
eff.,
k
Data points from eigenbuckling analysis
Fitted curve
44462
≤+⎟⎠⎞
⎜⎝⎛−⎟
⎠⎞
⎜⎝⎛=
hh
hhk holehole
SS/2 Lhole hholeh
for S/Lhole > 5
If holes do not interact simplified elastic local buckling predictions are certainly possible.
Progress Report 3 HighlightBeams: finding Mcrl, Mcrd, Mcre for tests
Beam end restrained in 2 and 3 (v, w=0)
Beam end restrained in 2 and 3 (v, w=0)
Bottom flange restrained in 1 at support (u=0)
* **
**
**
**
Restrain node at midline of top flange in 3 (w=0) (Typ.)
Rigid body connection between top (and bottom) flange midline nodes (Typ.)
1
2
3
Care is taken to simulate tested boundary conditions in eigenbuckling analyses.
Progress Report 3 HighlightImpact of Hole on Beam Local Buckling
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 10
0.5
1
1.5
hhole/H
Mcrl ,h
ole/M
crl ,n
o ho
le
Largest decrease in critical elastic local buckling moment occurs at hhole/h= 0.25
Progress Report 3 HighlightImpact of Hole on Beam Distortional Buckling
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 10
0.5
1
1.5
hhole/H
Mcr
d,ho
le/M
crd,
no h
ole
Holes decrease critical elastic distortional buckling moment, modeling required
Progress Report 3 HighlightStrength Results from Column Tests
Holes have a small influence on compressive strength here BUT…
Ptest Mean Std. Dev.kips kips kips
362-1-24-NH 10.48362-2-24-NH 10.51362-3-24-NH 10.15362-1-24-H 10.00362-2-24-H 10.38362-3-24-H 9.94362-1-48-NH 9.09362-2-48-NH 9.49362-3-48-NH 9.48362-1-48-H 8.95362-2-48-H 9.18362-3-48-H 9.37600-1-24-NH 11.93600-2-24-NH 11.95600-3-24-NH 12.24600-1-24-H 12.14600-2-24-H 11.62600-3-24-H 11.79600-1-48-NH 11.15600-2-48-NH 11.44600-3-48-NH 11.29600-1-48-H 11.16600-2-48-H 11.70600-3-48-H 11.16
11.29
Specimen
10.38
10.11
9.35
11.34
0.20
0.24
0.23
0.21
0.17
0.27
0.15
0.31
9.17
Hole
Without Hole Short
ColumnsHole
12.04
11.85
Without Hole Long
ColumnsHole
362S162-33
600S162-33
Without Hole Long
ColumnsHole
Without Hole Short
Columns
Progress Report 3 Highlight362S162-33 Short Column
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1
0 0.05 0.1 0.15 0.2
-14
-12
-10
-8
-6
-4
-2
0
Column axial displacement (inches)
Col
umn
axia
l loa
d (k
ips)
362-2-24-NH362-2-24-H
Slotted hole influences post-peak load path and decreases column ductility.
Outline• Objective• Summary of past progress• FEA of Columns with holes
– Modeling approach– Elastic buckling– Nonlinear modeling to collapse– Comparison with testing from progress report 3
• Developing DSM for columns with holes– Impact of gross vs. net area decisions on strength– Comparison of predictions for available column tests
• Conclusions• Future Work
to becovered intask groupmeeting
FEA modeling• Objective: Develop a reliable FEA modeling
procedure/guidelines for CFS sections with holes modeled to collapse loads.
• Motivation: Available test database is limited, e.g., insufficient data on intermediate length columns with holes in local and distortional buckling, long columns with holes, holes in the flanges, etc.
• Method: Develop/improve modeling guidelines based on comparisons with testing conducted at JHU then expand to needed parametric studies
Jump to next section
FEA Modeling of Column Tests
• Begin with elastic buckling– necessary for DSM-style predictions– mode shapes are typically used as
imperfections in nonlinear models• Then move on to collapse modeling
(full nonlinear FEA models)
Elastic buckling (24 in. columns)
24” long 362 specimens
Local Buckling (L) Distortional Buckling
Hole terminates web local buckling asymmetric
distortional hole mode with local buckling at the hole
Hole shifted off centerline web
DDH+LD
Local Buckling Distortional Buckling
Holes change number of half-waves from 8 (NH) to 12 (H)
Holes cause mixed distortional – local mode
D DH+L
Elastic buckling (48 in. columns)
48” long 600 specimens
Mean STDEV Mean STDEV600s 1.01 0.03 1.19 0.18362s 1.01 0.01 1.09 0.10no holes 0.99 0.00 1.16 0.09holes 1.00 0.02 1.12 0.1948" specimens 1.01 0.02 1.03 0.0524" specimens 1.01 0.03 1.17 0.15
Distortional BucklingABAQUS/CUFSM
Local BucklingSpecimen Group
Comparison of buckling to CUFSM
Holes do not influence local.. Pcrl
(b) 600s have longer distortional buckling half-wavelength thus are more influenced by fix-fix boundary
(c) holes have only a small impact –but large variance....
(d) Shorter specimens more influenced by fix-fix boundary
FIX-FIX B.C. / PIN-PIN B.C.
b
c
d
a
b
c
d
Typical* Nonlinear FEA modeling of CFS• General:
Shell element model in ABAQUS• Solution control:
Riks (arc-length method)• Boundary Conditions:
idealized, perfect pin, perfect fixity• Material modeling:
σ-ε from flats, von Mises criteria, isotropic hardening• Geometric Imperfections:
buckling mode shapes superposed on ideal geometry, magnitude from Schafer and Peköz (1998)
• Residual Stresses: ignored
• Cold work of forming: ignored
*typical of modeling conducted in Schafer’s group
Nonlinear FEA modeling of CFS to collapse• General:
Shell element model in ABAQUS• Solution control:
Riks (arc-length method) & Stabilize (artificial damping)• Boundary Conditions:
model contact, friction, liftoff from end platens• Material modeling:
σ-ε from flats, von Mises criteria, isotropic hardening• Geometric Imperfections:
buckling mode shapes superposed on averagegeometry, magnitude from simple measurements
• Residual Stresses: in the corners, with realistic through thickness variation
• Cold work of forming: in the corners through inclusion of plastic strain, varies through the thickness, not your usual cold work...
Boundary conditions modeling
Friction-bearing end conditions are modeled in ABAQUS
1
2
3
45
6
ABAQUS Analytical Rigid Surface (Typ.)
Restrain rigid surface reference node in 2 to 6 directions
Restrain rigid surface reference node in 1 to 6 directions
Apply imposed displacement of surface in 1 direction
Assign friction contact behavior in ABAQUS between rigid surface and specimen
ABAQUS contact modeling captures lift off of lip for 600 specimen
Boundary conditions local response
specimen/model600-2-24-NH
0 0.05 0.1 0.15 0.20
2
4
6
8
10
12
14
16
18
20
axial displacement, in.
colu
mn
axia
l loa
d, k
ips
Contact SurfaceFixed-Fixed
The failure response with friction-bearing boundary conditions is similar to that with fixed-fixed boundary conditions
Boundary conditions global response
specimen/model600-2-24-NH
0 0.05 0.1 0.15 0.20
2
4
6
8
10
12
14
16
18
20
axial displacement, in.
colu
mn
axia
l loa
d, k
ips
Artificial DampingModified RiksExperiment
Artificial damping predicts stronger, more ductile response than the Riks Method
Cross section slips on platen in Riks Method here, no slip observed with artificial damping
Solution control sensitivity(and boundary conditions)
specimen/model600-2-24-NH artificial damping is more robust, but artificially high?
Eigenmodes & imperfection shapes
Hole is filled in with S9R5 elements to produce no hole local buckling shape
Imperfection shapes are developed from eigenmodes of columns without holes so that “hole” and “no hole” models can be fairly compared, but...
this means that columnswith holes have a differentimperfection shape thantheir actual first mode.. (implies potentially stifferresponse..)
First L eigenmode
Local imperfection magnitudes
web local imperfectionsmeasured as describedin progress report 3
Maximum magnitude of web displacement determinedfrom a local bucking mode in a model without holes, isset equal to the measured maximum difference from themean web location.
Imperfections modeled in this way are similar in shape and magnitude to “typical” modeling, i.e. Schafer and Peköz (1998)
Distortional imperfection magnitudes
flange anglesmeasured as describedin progress report 3
Average flange angles are used to define an initial geometry which is not at 90 degrees.
In addition, the difference between the measured flange angles along the length is used to define a distortional imperfection with a shape equal to the distortional buckling mode in a model without holes.
Imperfections modeled in this way are somewhat different in shape and magnitude to “typical” modeling, i.e. Schafer and Peköz (1998)
E
D1
B1
H
B2
D2
F1 F2
S1 S2
Current state of the art: residual stresses
• Based on a simple through thickness distribution consistent with what can be readily measured in thin cold-formed steel sheet when sliced. Distribution is not consistent with known simple mechanics...
Bending Membrane
Sheet thickness
From Weng and Pekoz
εout
decomposed
εin
membrane typically 0 or close to it.
Residual stresses and strains• Advancing collapse modeling of
CFS requires better models for residual stresses...
• This progress report provides significant new work, going back to simple basic mechanics we are developing a more realistic picture of– residual stress – residual plastic strains– cold work of forming, which
relates to residual plastic strains
On the coil (R)Residual curvature after uncoiling (Runcoil)
Flattened as sheet enters the roll-formers
Change in curvature locks in bending residual stresses in final member
DETAIL A
DETAIL A
bending the corners...
coiling, uncoiling, and flattening
bending a corner
yrx
z
ε=
1
bend radius is small, so strains are high, so high in fact that M=Mp
x
y
εout
εin
Springback and final transverse stress
the plastic momenthas a moment associated with it, when we stop bending we ‘spring back’with the same moment –but elastically!
remember, unloadingis elastic...
elastic moment ofsame magnitude asplastic moment..
resulting transverseresidual stresses fromforming a corner
Longitudinal residual stress (corner)longitudinal residual stresses from forming the corner..
)()()( yyy zreboundxelastic
bendxplastic σσνσν =+
bending a corner
yrx
z
ε=
1
bend radius is small, so strains are high, what happens to these high strains?
x
y
εout
εin
plastic strain from bending a corner
εoutεp-outεp-out
εp-in
εout
εin
von Mises yield criteria enforces that the plasticstress and strain in 3D follow 1D tensile results.So, permanent strain in the transverse direction is thesame as permanent strain in the longitudinal direction.Increase in “fy” depends on the plastic strain, whichfollows the distribution to the left. fy does not increase everywhere, fy increases most at the faces.
Longitudinal residual stresses in flats
On the coil (R)Residual curvature after uncoiling (Runcoil)
Flattened as sheet enters the roll-formers
Change in curvature locks in bending residual stresses in final member
DETAIL A
DETAIL A
( )xz ry,σ+ + =
y
z
Coiling Uncoiling Flattening
+σyield
-σyield
y
zc ),( xflatten
z ryσ z
y
),( xuncoilz ryσ
z
y
Sources of uncertainty in the flats..
Sheet has residual CONCAVE curvature coming off the coil
Sheet has residual CONVEX curvature coming off the coil
(a)
(b)
Roll-forming bed
r
1. up/down2. where in coil? r..
Residual stresses summary• New prediction model for residual stresses
and residual strains developed• Model was compared to available
experiments and shown to be a reasonable predictor
• Model intimately ties cold work of forming to residual stresses
• We are implementing this model into our nonlinear FEA, finetuning and understanding the effects.
SNEG
2
1SPOS
Element normal
εp
εpSNEG
SPOS
SNEG
SPOS
-0.50σyield
+σyield -σyield
+0.50σyield
2
SNEG
SPOS
+0.05σyield
1
-0.05σyield
-0.50σyield
+0.50σyield
Residual stresses and strains
Residual stresses and plastic strains are modeled in ABAQUS
0 0.05 0.1 0.15 0.20
2
4
6
8
10
12
14
16
18
20
axial displacement, in.
colu
mn
axia
l loa
d, k
ips
No ImpsImpsImps+Plastic StrainImps+Plastic Strain+RSExperiment
Imperfections and residual stresses
Imperfections reduce strength, residual stresses and plastic strains increase strength and change failure mode
Experiments
L+D L+4xDkips kips kips
362-1-24-NH 10.48 9.73 --- 1.08 ---362-2-24-NH 10.51 10.13 --- 1.04 ---362-3-24-NH 10.15 10.11 --- 1.00 ---362-1-24-H 10.00 10.40 --- 0.96 ---362-2-24-H 10.38 11.29 --- 0.92 ---362-3-24-H 9.94 9.96 --- 1.00 ---362-1-48-NH 9.09 11.86 10.41 0.77 0.87362-2-48-NH 9.49 11.79 10.34 0.80 0.92362-3-48-NH 9.48 11.43 8.93 0.83 1.06362-1-48-H 8.95 11.17 N/C 0.80 N/C362-2-48-H 9.18 11.13 N/C 0.82 N/C362-3-48-H 9.37 11.27 9.37 0.83 1.00600-1-24-NH 11.93 10.58 --- 1.13 ---600-2-24-NH 11.95 12.75 --- 0.94 ---600-3-24-NH 12.24 12.00 --- 1.02 ---600-1-24-H 12.14 12.57 --- 0.97 ---600-2-24-H 11.62 12.90 --- 0.90 ---600-3-24-H 11.79 12.67 --- 0.93 ---600-1-48-NH 11.15 14.09 13.87 0.79 0.80600-2-48-NH 11.44 14.13 14.06 0.81 0.81600-3-48-NH 11.29 13.22 13.13 0.85 0.86600-1-48-H 11.16 13.58 13.19 0.82 0.85600-2-48-H 11.70 13.37 10.98 0.88 1.07600-3-48-H 11.16 13.58 11.89 0.82 0.94Note: shaded values have failure mode consistent with experimentsN/C Not completed, imperfection caused excessive element distortion error in ABAQUS
Specimen Ptest
Test to PredictedPtestABAQUS models
Imperfections Imperfections
L+D L+4xD
Current model results
Results are mixed…
24 in. column strength predictions are consistent with tests
Model does not pick up global-torsional influence for 48 in. 362 columns
362-2-24-NH362-3-24-NH
362-1-24-NH362-2-24-H362-1-24-H
362-3-24-H
* *
* Failure mode observed in experiments
Predicted failure modes
24 in. 362 specimens, predicted failure modes consistent with tests for four out of six specimens
600-2-24-H600-3-24-H
600-1-24-H600-2-24-NH600-3-24-NH
600-1-24-NH
**
* Failure mode observed in experiments
Predicted failure modes
24 in. 600 specimens, predicted failure modes consistent with tests for four out six specimens
362-1-48-NH362-2-48-NH362-3-48-NH
362-1-48-NH 4xD362-2-48-NH 4xD362-3-48-NH 4xD
362-1-48-H362-2-48-H362-3-48-H
362-1-48-H 4xD362-2-48-H 4xD362-3-48-H 4xD
**
* Failure mode observed in experiments 4xType A 4 times the distortional imperfections are applied
Predicted failure modes
Local failure did not occur in experiments, predicted strength is higher than test
600-1-48-NH 4xD600-1-48-NH600-2-48-NH600-3-48-NH600-2-48-NH 4xType A600-3-48-NH 4xType A
600-1-48-H600-2-48-H600-3-48-H600-1-48-H 4xD
600-2-48-H 4xD600-3-48-H 4xD
*
* Failure mode observed in experiments 4xD 4 times the distortional imperfections are applied
Predicted failure modes
Nonlinear Modeling• Currently a work in progress, but nearing
completion.:• Mixed success, model predicts failure
modes and ultimate strength for short columns but misses long column behavior
• Validation work is underway, continuing to examine, solution method, imperfections, contact modeling, residual stresses.
• Comparison to a “typical” nonlinear CFS model will also be completed.
Outline• Objective• Summary of past progress• FEA of Columns with holes
– Modeling approach– Elastic buckling– Nonlinear modeling to collapse– Comparison with testing from progress report 3
• Developing DSM for columns with holes– Impact of gross vs. net area decisions on strength– Comparison of predictions for available column tests
• Conclusions• Future Work
to becovered intask groupmeeting
Going back to our objective...Development of a general design method
for cold-formed steel members with perforations.
Direct Strength Method ExtensionsPn = f (Py, Pcre, Pcrd, Pcrl)?
How do the DSMcurves need tochange?
Gross or net, or some combination?
Focused on two tier approach,one for general case and onefor studs with standard holesto be developed next report.
0 0.5 1 1.5 2 2.50
0.2
0.4
0.6
0.8
1
λc Pcre( )
DSM Global and Local strength
for Pcrl=0.7Py
Pnl
Pne
PnPy
λc = crey PP
0 0.5 1 1.5 2 2.50
0.2
0.4
0.6
0.8
1
λc Pcre( )
DSM Global and Local Strength
for Pcrl=0.7Py
Pnl
Pne
PnPy
for 5.1c ≤λ
for λc > 1.5
λc = crey PP
crey2c
ne P877.0P877.0P =⎟⎟⎠
⎞⎜⎜⎝
⎛
λ=
Pne = yP658.02c ⎟⎠⎞⎜
⎝⎛ λ
0 0.5 1 1.5 2 2.50
0.2
0.4
0.6
0.8
1
λc Pcre( )
DSM Global and Local Strength
for Pcrl=0.7Py
Pnl
Pne
PnPy
for 5.1c ≤λ
for λc > 1.5
λc = crey PP
crey2c
ne P877.0P877.0P =⎟⎟⎠
⎞⎜⎜⎝
⎛
λ=
for λl 776.0≤ Pnl = Pne
for λl > 0.776 Pnl = ne
4.0
ne
cr4.0
ne
cr PPP
PP
15.01 ⎟⎟⎠
⎞⎜⎜⎝
⎛
⎥⎥
⎦
⎤
⎢⎢
⎣
⎡
⎟⎟⎠
⎞⎜⎜⎝
⎛− ll
λl = lcrne PP
Pne = yP658.02c ⎟⎠⎞⎜
⎝⎛ λ
Effect of using Pynet instead of Py
0 0.5 1 1.5 2 2.50
0.2
0.4
0.6
0.8
1
λc Pcre( )
for Pcrl=0.7PyPynet=0.7Py
Pnl
Pne
Pne-net: Pne if Pynet replaces Py
Pnl-net: Pnl if Pynet replaces Pyin the global and local curves
PnPy
λc = crey PP
Pynet=0.7Py
Cap the global curve at Pynet?
0 0.5 1 1.5 2 2.50
0.2
0.4
0.6
0.8
1
λc Pcre( )
for Pcrl=0.7PyPynet=0.7Py
Pnl
Pne
Pne-cap: Pne < Pynet
Pnl-ne-cap: Pnl if Pne < Pynet used
PnPy
λc = crey PP
0 0.5 1 1.5 2 2.50
0.2
0.4
0.6
0.8
1
λc Pcre( )
Or just cap the local curve only..
for Pcrl=0.7PyPynet=0.7Py
Pnl
Pne
Pnl-capPnl<Pynet.Pn
Py
λc = crey PP
Comparison of options
0 0.5 1 1.5 2 2.50
0.2
0.4
0.6
0.8
1
λc Pcre( )
for Pcrl=0.7PyPynet=0.7Py
Pnl-ne-cap
Pnl-ne-net
Pnl-cap
Pnl
Pne
PnPy
λc = crey PP
Closer look at stub columns
0 0.5 1 1.5 2 2.50
0.2
0.4
0.6
0.8
1
λc Pcre( )
for Pcrl=0.7PyPynet=0.7Py
Pnl-ne-cap
Pnl-ne-net
Pnl-cap
Pnl
Pne
PnPy
vary
stub column..
λc = crey PP
Local buckling strength for a stub column
0 0.5 1 1.5 2 2.5 3 3.50.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1
( )
PnPne
for Pynet=0.7Py
Pnl-ne-cap
Pnl-ne-net
Pnl-cap
λl vary
Local buckling strength for a stub column
0 0.5 1 1.5 2 2.5 3 3.50.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1
( )
PnPne
λl
for Pynet=0.7Py
Pnl-ne-cap
Pnl-ne-net
Pnl-cap
initial FE simulationsshow data here soalso considering atransition line as shown.(Pnl-transition)
Intermediate length column...
0 0.5 1 1.5 2 2.50
0.2
0.4
0.6
0.8
1
λc Pcre( )
for Pcrl=0.7PyPynet=0.7Py
Pnl-ne-cap
Pnl-ne-net
Pnl-cap
Pnl
Pne
PnPy
vary
intermediate lengthcolumn...
Local buckling strength
0 0.5 1 1.5 2 2.5 30.2
0.4
0.6
0.8
1
1.2
PnPne
λl
for Pynet=0.7Py
Pnl-ne-cap
Pnl-ne-net
Pnl-cap
Outline• Objective• Summary of past progress• FEA of Columns with holes
– Modeling approach– Elastic buckling– Nonlinear modeling to collapse– Comparison with testing from progress report 3
• Developing DSM for columns with holes– Impact of gross vs. net area decisions on strength– Comparison of predictions for available column tests
• Conclusions• Future Work
to becovered intask groupmeeting
0 2 4 6 8 10 12 14 16 180
5
10
15
20
25
30
35
L/H
spec
imen
cou
nt
Tests on columns with holesReference Author Publication Date Types of Specimens Cross Section End Conditions
1 Ortiz-Colberg 1981 Stub Column Long Column Lipped Channel
Fixed-Fixed Weak Axis Pinned
2 Pekoz and Miller 1987 Stub Column Lipped Channel Fixed-Fixed 3 Sivakumaran 1994 Stub Column Lipped Channel Fixed-Fixed 4 Abdel-Rahman 1998 Stub Column Lipped Channel Fixed-Fixed 5 Pu 1999 Stub Column Lipped Channel Fixed-Fixed 6 Moen and Schafer 2007 Intermediate Len. Lipped Channel Fixed-Fixed
see progress report 1 for full details of column databasesee progress report 3 and 4 for full details of Moen and Schafer tests
Normalized lengthof tested columnswith holes.. (priorto Moen and Schafertests)
* ** *
*Normalized lengthof Moen and Schafertested columns(2 ft and 4 ft tests)
Test-to-predicted ratios for columns with holes
average STDEV average STDEV average STDEV average STDEV1 use Py everywhere 1.03 0.11 1.09 0.16 1.14 0.11 0.84 0.082 use Pynet everywhere 1.17 0.08 1.23 0.13 1.27 0.10 1.04 0.123 cap Pne and Pnd 1.15 0.07 1.30 0.04* 1.16 0.10 1.03 0.114 cap Pnl and Pnd 1.07 0.08 1.15 0.10 1.16 0.10 1.01 0.115 transition Pnl and cap Pnd 1.06 0.08 1.15 0.10 1.16 0.10 1.03 0.11
Test-to-Predicted Ratio by Failure ModeDescriptionDSM
Option Local Distortional Global Yielding
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5Option 1 - Py everywhere
λl=(Pne/Pcrl)
0.5
Pn/P
ne
DSM Local PredictionLocal Controlled TestDSM Yield ControlYield Controlled Test
Test-to-predicted ratios for columns with holes
average STDEV average STDEV average STDEV average STDEV1 use Py everywhere 1.03 0.11 1.09 0.16 1.14 0.11 0.84 0.082 use Pynet everywhere 1.17 0.08 1.23 0.13 1.27 0.10 1.04 0.123 cap Pne and Pnd 1.15 0.07 1.30 0.04* 1.16 0.10 1.03 0.114 cap Pnl and Pnd 1.07 0.08 1.15 0.10 1.16 0.10 1.01 0.115 transition Pnl and cap Pnd 1.06 0.08 1.15 0.10 1.16 0.10 1.03 0.11
Test-to-Predicted Ratio by Failure ModeDescriptionDSM
Option Local Distortional Global Yielding
DSM for Local buckling shown here
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5Option 2 - Pynet everywhere
λl=(Pne/Pcrl)
0.5
Pn/P
ne
DSM Local PredictionLocal Controlled TestDSM Yield ControlYield Controlled Test
Test-to-predicted ratios for columns with holes
average STDEV average STDEV average STDEV average STDEV1 use Py everywhere 1.03 0.11 1.09 0.16 1.14 0.11 0.84 0.082 use Pynet everywhere 1.17 0.08 1.23 0.13 1.27 0.10 1.04 0.123 cap Pne and Pnd 1.15 0.07 1.30 0.04* 1.16 0.10 1.03 0.114 cap Pnl and Pnd 1.07 0.08 1.15 0.10 1.16 0.10 1.01 0.115 transition Pnl and cap Pnd 1.06 0.08 1.15 0.10 1.16 0.10 1.03 0.11
Test-to-Predicted Ratio by Failure ModeDescriptionDSM
Option Local Distortional Global Yielding
DSM for Local buckling shown here
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5Option 3 - cap Pne, Pnd
λl=(Pne/Pcrl)
0.5
Pn/P
ne
DSM Local PredictionLocal Controlled TestDSM Yield ControlYield Controlled Test
Test-to-predicted ratios for columns with holes
average STDEV average STDEV average STDEV average STDEV1 use Py everywhere 1.03 0.11 1.09 0.16 1.14 0.11 0.84 0.082 use Pynet everywhere 1.17 0.08 1.23 0.13 1.27 0.10 1.04 0.123 cap Pne and Pnd 1.15 0.07 1.30 0.04* 1.16 0.10 1.03 0.114 cap Pnl and Pnd 1.07 0.08 1.15 0.10 1.16 0.10 1.01 0.115 transition Pnl and cap Pnd 1.06 0.08 1.15 0.10 1.16 0.10 1.03 0.11
Test-to-Predicted Ratio by Failure ModeDescriptionDSM
Option Local Distortional Global Yielding
DSM for Local buckling shown here
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5Option 4 - cap Pnl, Pnd
λl=(Pne/Pcrl)
0.5
Pn/P
ne
DSM Local PredictionLocal Controlled TestDSM Yield ControlYield Controlled Test
DSM Local PredictionLocal Controlled TestDSM Yield ControlYield Controlled Test
Test-to-predicted ratios for columns with holes
average STDEV average STDEV average STDEV average STDEV1 use Py everywhere 1.03 0.11 1.09 0.16 1.14 0.11 0.84 0.082 use Pynet everywhere 1.17 0.08 1.23 0.13 1.27 0.10 1.04 0.123 cap Pne and Pnd 1.15 0.07 1.30 0.04* 1.16 0.10 1.03 0.114 cap Pnl and Pnd 1.07 0.08 1.15 0.10 1.16 0.10 1.01 0.115 transition Pnl and cap Pnd 1.06 0.08 1.15 0.10 1.16 0.10 1.03 0.11
Test-to-Predicted Ratio by Failure ModeDescriptionDSM
Option Local Distortional Global Yielding
DSM for Local buckling shown here
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5Option 5 - transition Pnl, cap Pnd
λl=(Pne/Pcrl)
0.5
Pn/P
ne
DSM Local PredictionLocal Controlled TestDSM Yield ControlYield Controlled Test
Test-to-predicted ratios for columns with holes
average STDEV average STDEV average STDEV average STDEV1 use Py everywhere 1.03 0.11 1.09 0.16 1.14 0.11 0.84 0.082 use Pynet everywhere 1.17 0.08 1.23 0.13 1.27 0.10 1.04 0.123 cap Pne and Pnd 1.15 0.07 1.30 0.04* 1.16 0.10 1.03 0.114 cap Pnl and Pnd 1.07 0.08 1.15 0.10 1.16 0.10 1.01 0.115 transition Pnl and cap Pnd 1.06 0.08 1.15 0.10 1.16 0.10 1.03 0.11
Test-to-Predicted Ratio by Failure ModeDescriptionDSM
Option Local Distortional Global Yielding
DSM for Local buckling shown here
Outline• Objective• Summary of past progress• FEA of Columns with holes
– Modeling approach– Elastic buckling– Nonlinear modeling to collapse– Comparison with testing from progress report 3
• Developing DSM for columns with holes– Impact of gross vs. net area decisions on strength– Comparison of predictions for available column tests
• Conclusions• Future Work
to becovered intask groupmeeting
Conclusions• Past progress has established a good foundation for
completing a DSM method for members with holes– gathered test database of columns– gathered test database of beams– performed FEA eigenbuckling analysis of test data– completed new tests on columns with holes– initiated studies for simplified models of Pcr, Mcr which include the
influence of holes and will form the basis for a simplified method • Nonlinear FEA modeling
is advancing the state of the art for collapse modeling of CFS members with holes and provides a way to study details of DSM implementation
• DSM frameworkfor handling changes in elastic buckling and strength (net vs. gross) are now nearly complete – the changes are not drastic.
Future Work• Development of tiered approach for elastic
buckling (Pcrl, Pcrd, Pcre, Mcrl, Mcrd, Mcre) prediction– Simple methods for limited hole configurations– Guidance for general cases where
FEA eigenbuckling analysis must be used– Tools for automated evaluation of FEA eigenmodes
• Nonlinear FEA modeling to collapse for columns and beams with holes to augment experimental database
• Selection of final DSM expressions and reliability calculations
• Ballots and design aids
DSM and columns with holesFlexural, Torsional, or Torsional-Flexural Buckling The nominal axial strength, Pne, for flexural, … or torsional- flexural buckling is
for 5.1c ≤λ Pne = yP658.02c ⎟⎠⎞⎜
⎝⎛ λ
for λc > 1.5 crey2c
ne P877.0P877.0P =⎟⎟⎠
⎞⎜⎜⎝
⎛
λ=
where λc = crey PP
Py = AgFy Pcre= Critical elastic global column buckling load Ag = gross area of the column
Local Buckling The nominal axial strength, Pnl, for local buckling is
for λl 776.0≤ Pnl = Pne
for λl > 0.776 Pnl = ne
4.0
ne
cr4.0
ne
cr PPP
PP
15.01 ⎟⎟⎠
⎞⎜⎜⎝
⎛⎥⎥
⎦
⎤
⎢⎢
⎣
⎡⎟⎟⎠
⎞⎜⎜⎝
⎛− ll
where λl = lcrne PP Pcrl = Critical elastic local column buckling load Pne is defined above.
0. Pcr includes the hole
DSM Options...
1. Leave equations alone (except Pcr)
2. replace Py with Pyneteverywhere
3. Cap Pne to Pynet
4. Cap Pnl to Pynet
5. Cap Pnl to Pynet and add a transition portion to Pnl
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
λc=(Py/Pcre)0.5
Pn/P
y
Option 1 - Py everywhere
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
λcnet=(Pynet/Pcre)0.5
Pn/P
y
Option 2 - Pynet everywhere DSM Global Prediction
Global Controlled Test
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
λc=(Py/Pcre)0.5
Pn/P
y
Option 3 - cap Pne, Pnd
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
λc=(Py/Pcre)0.5
Pn/P
y
Option 4 - cap Pnl, Pnd
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
λc=(Py/Pcre)0.5
Pn/P
y
Option 5 - transition Pnl, cap Pnd
Global
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5Option 1 - Py everywhere
λd=(Py/Pcrd)0.5
Pn/P
y
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5Option 2 - Pynet everywhere
λdnet=(Pynet/Pcrd)0.5
Pn/P
y
DSM Dist. PredictionDist. Controlled TestDSM Yield ControlYield Controlled Test
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5Option 3 - cap Pne, Pnd
λd=(Py/Pcrd)0.5
Pn/P
y
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5Option 4 - cap Pnl
, Pnd
λd=(Py/Pcrd)0.5
Pn/P
y
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5Option 5 - transition Pnl, cap Pnd
λd=(Py/Pcrd)0.5
Pn/P
y
Distortional
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
Option 1 - Py everywhere
λd=(Py/Pcrd)0.5
Pte
st/P
n
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
Option 2 - Pynet everywhere
λdnet=(Pynet/Pcrd)0.5
Pte
st/P
n
Distortional ControlledYield Controlled
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
Option 3 - cap Pne, Pnd
λd=(Py/Pcrd)0.5
Pte
st/P
n
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
Option 4 - cap Pnl, Pnd
λd=(Py/Pcrd)0.5
Pte
st/P
n
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
Option 5 - transition Pnl, cap Pnd
λd=(Py/Pcrd)0.5
Pte
st/P
n
distortional slen. vs. test-to-pred.
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
Option 1 - Py everywhere
λl=(Pne/Pcrl
)0.5
Pte
st/P
n
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
Option 2 - Pynet everywhere
λl=(Pne/Pcrl
)0.5
Pte
st/P
n
Local ControlledYield Controlled
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
Option 3 - cap Pne, Pnd
λl=(Pne/Pcrl
)0.5
Pte
st/P
n
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
Option 4 - cap Pnl, Pnd
λl=(Pne/Pcrl
)0.5
Pte
st/P
n
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
Option 5 - transition Pnl, cap Pnd
λl=(Pne/Pcrl
)0.5
Pte
st/P
n
local slen. vs. test-to-pred.
0.5 0.6 0.7 0.8 0.9 10
0.5
1
1.5
Option 1 - Py everywhere
Anet/Ag
Pte
st/P
n
0.5 0.6 0.7 0.8 0.9 10
0.5
1
1.5
Option 2 - Pynet everywhere
Anet/Ag
Pte
st/P
n
Local ControlledYield Controlled
0.5 0.6 0.7 0.8 0.9 10
0.5
1
1.5
Option 3 - cap Pne, Pnd
Anet/Ag
Pte
st/P
n
0.5 0.6 0.7 0.8 0.9 10
0.5
1
1.5
Option 4 - cap Pnl, Pnd
Anet/Ag
Pte
st/P
n
0.5 0.6 0.7 0.8 0.9 10
0.5
1
1.5
Option 5 - transition Pnl, cap Pnd
Anet/Ag
Pte
st/P
n
Anet/Ag vs. test-to-pred.
Global strength options
0 0.5 1 1.5 2 2.50
0.2
0.4
0.6
0.8
1
λc Pcre( )
for Pcrl=0.7PyPynet=0.7Py
PnPy
λc = crey PP
1
23
4 5