Mark R. Svinkin, Member, ASCE
VibraConsult
13821 Cedar Road, #205
Cleveland, OH 441182376
PH 2163979625
FAX 2163971175
msvinkin@vulcanhammer.net
Abstract
The application of dynamic methods to driven piles has
advantages in evaluation of the hammerpilesoil system and in data
acquisition during pile driving and restrikes. Therefore during the last
twenty five years, dynamic methods have become an integral part of pile
capacity prediction and measurement for numerous projects. Dynamic
methods use good quality hardware and software, but such great tools
cannot themselves solve geotechnical problems of piling without
engineering judgment. This paper shows some engineering assessments of
determining pile capacity by dynamic formulas, wave equation analysis
and dynamic testing.
Introduction
Contemporary dynamic methods are founded on the
application of the stress wave theory to piles. There are two different
techniques of the use of wave equation analysis for determining pile
capacity: computation of pile capacity without dynamic measurements on
driven piles and a signal matching technique for computed and measured
force and velocity records at the pile head.
Dynamic methods have certain advantages and some
uncertainties in their application. The wave equation method is used for
prediction of pile capacity during both the design stage and for
construction control before restrikes. Unfortunately in most cases,
predicted pile capacity differs substantially from results of both
static and dynamic load tests. Dynamic measurements of force and
velocity at the upper end of the pile during pile driving, followed by a
signal matching procedure, is the most common method for dynamic
determination of pile capacity. This method is a convenient tool in the
pile driving industry. However, though dynamic methods have been used in
practice for years, actual accuracy of dynamic methods and understanding
the results of dynamic testing are vague.
Also, there is an attempt to breath new life into
dynamic formulas and consider a suggested formula as the better
alternative to signal matching technique. There are no theoretical and
experimental basis for such replacement.
In the medium of geotechnical engineers involved in
dynamic testing and analysis, there is a belief that hardware and
software themselves can solve geotechnical problems of piling. Indeed,
hardware and software are great tools but only tools, and these tools
cannot replace engineering judgment. It is known if we put trash in, we
will receive trash out. Computer misuse comes in many forms and among
them having computer programmers provide services they are unqualified
to perform. Formal implementation of the signal matching procedure is a
common approach in dynamic pile testing. In spite of a number of
excellent engineering assessment of results obtained from static and
dynamic tests, it is obvious that the application of dynamic methods to
piles lacks engineering judgment.
Misapplication and misuse of the specified computer
software are demonstrated. Various problems such as misleading
assessment of the accuracy of dynamic formulas, calibration of wave
equation programs, the soil consolidation effect in prediction of pile
capacity by wave equation analysis, comparison of static and dynamic
tests, prediction of pile capacity by dynamic pile testing,
overestimated capabilities of signal matching technique and others are
discussed. It is shown that dynamic methods have to be used with the
proper engineering judgment for prediction and determination of pile
capacity.
Dynamic Formulas
Determination of pile capacity by dynamic formulas is
the oldest and frequently used method. There is a great number of
dynamic formulas available with different degrees of reliability.
Dynamic formulas have been criticized in many publications.
Unsatisfactory prediction of pile capacity by dynamic formulas is well
characterized in FHWA Manual for Design and Construction of Driven Pile
Foundations, Hannigan et al.(1996): "Unfortunately, dynamic
formulas have fundamental weakness in that they do not adequately model
the dynamics of the hammerpile impact, the influence of axial pile
stiffness, or soil response. Dynamic formulas have also proven
unreliable in determining pile capacity in many circumstances. Their
continued use is not recommended on significant projects".
However, dynamic formulas are traditional dynamic
analysis techniques. For example, responses to the questionnaire
obtained from 45 state DOTs and 2 FHWA officials showed that Dynamic
Formulas usage are 45% ENR (Engineering News Records) and 16%
Gates Equation, Paikowsky and Stenersen (2000). Besides, there is an
attempt to breathe new life into dynamic formulas. Paikowsky and
Chernauskas (1992), Paikowsky et al. (1994) and Paikowsky and Stenersen
(2000) have suggested one more energy approach using dynamic
measurements for the capacity evaluation of driven piles. Liang and Zhou
(1997) have concluded regarding this method: "Although the
delivered energy is much more exactly evaluated, this method still
suffers similar drawbacks of ENR".
Authors of a new dynamic formula used the ratio, also
called index K, of the static load test capacity to the predicted
capacity to evaluate performance of the energy approach and dynamic
testing. However, such a ratio is irrelevant for verification of dynamic
formulas and dynamic testing (DT) results for two reasons: first,
dynamic testing methods yield pile capacity only for the time of testing
(Rausche et al. 1985), and second, the pile capacity from static load
test (SLT) is considered as a constant value which is a major error.
Paikowsky et al. (1994) and Paikowsky and Stenersen
(2000) use a false assumption that accuracy of Dynamic Formulas are
independent of the time between DT and SLT. However, SLT as well as DT
yields the pile capacity at the time of testing (Svinkin 1997). By way
of illustration, results of DT and SLT are shown in Figure 1 for two
identical cylindrical, 1372 mm x 127 mm, prestressed concrete
piles, TP1 and TP2 (Svinkin et al. 1994). These piles were driven at the
same site to the depth of penetration of about 24.4 m. Each of the
piles TP1 and TP2 was tested 2, 9 and 22 days after the end of initial
driving (EOID). The difference was that three restrikes were made for
TP1 and three SLTs were made for TP2. Pile capacity from three SLTs was
a function of time as well as pile capacity obtained from DT. Tested
data in Figure 1 help to explain the causes of unsatisfactory prediction
in pile capacity by dynamic formulas. Dynamic formulas using maximum
energy, pile set and maximum displacement from DT do not take into
account the time between SLT and DT. In the case of a few SLTs made on
one pile, like three SLTs performed on pile TP2, what would be the
reliability of pile capacity prediction by the energy approach methods?
Which SLT should be taken for comparison? Currently, there are no
answers to these questions. Nevertheless, Paikowsky and Stenersen (2000)
assert that the Energy Approach Formula is ideal for construction and
better than Signal Matching technique, e.g. CAPWAP program (GRL
and Associates, Inc. 1995). There are no theoretical and experimental
confirmation of such conclusions which are wrong and misleading. It is
necessary to utilize other appropriate way for comparison of results of
the Energy Approach Formula and DT which use the same dynamic
measurements. Such comparison was made in the frames of preparation of
FHWAGRL database. The results obtained were very poor and confirmed
that the Energy Approach with dynamic measurements cannot yield reliable
prediction of pile capacity. Statistical analysis itself cannot reveal
good results and replace engineering judgment if comparison of measured
pile capacities is incorrect.
Wave Equation Analysis
Limitations in Prediction of Pile Capacity
The main goal in using wave equation analysis is to provide a better prediction of the pile capacity, as a function of pile penetration resistance, than can be obtained from classical dynamic formulas. Today, the most commonly used wave equation programs are either GRLWEAP (GRL and Associates, Inc. 1997) or TNOWAVE (TNO Report 1996).
The wave equation method is used for prediction of pile
capacity prior to the beginning of pile driving and before restrikes.
However, in most cases, computed pile capacity differs substantially
from results of both static and dynamic load tests. Statistical analysis
of GRLWEAP results, Hannigan et al. (1996), computed for 99 piles driven
into various soils, has demonstrated that GRLWEAP does not have an
advantage over the Gates dynamic formula. The mean and coefficient of
variation are almost the same for both prediction methods.
Smith (1960) made his model on the basis of existing
knowledge of pile driving at the time and he supposed this model could
be improved with acquisition of new data. Results obtained by many
researchers confirmed that Smith's model is simple and sensible but with
some lack of proper presentation of soil properties.
Soil parameters considerably affect solutions of wave
equation analysis. Dynamic soil resistance parameters (damping and
quake) have to be assigned as constant values for wave equation
analysis. These parameters do not reflect the changes of soil properties
in the pilesoil interface zone after the completion of pile driving.
There have been attempts to determine values of damping
and quake from signalmatching solutions for dynamically tested driven
piles or from modified SPT. It could be beneficial for some cases, but,
in general, such approaches are not successful in finding proper values
of damping and quake. Besides complications with different models in
wave equation analysis and signalmatching technique and also with the
scale factor effect on the use of SPT results, these approaches yield
constant values of soil parameters and cannot be used in prediction of
the pile capacity as a function of time after EOID (Svinkin 1996).
Variable Soil Parameters.
Existing dynamic models of the pilesoil system mainly use a velocitydependent approach for calculation of the dynamic resistance as a damping component of the total resistance during pile driving. There are various linear and nonlinear relationships between the damping component and the velocity. A study of different soil damping models and computed pile capacities has revealed that neither the pile velocity nor the damping constant can reflect timedependent variation of the pilesoil system after EOID. The existing approach of computing the dynamic resistance does not take into account soil consolidation around the pile after EOID and therefore cannot provide determination of pile capacity as a function of time after pile installation. There is necessity to take into account soil consolidation around a pile after EOID for improvement in accuracy of wave equation analysis, Svinkin (1996).
For the idealized Smith wave equation model, it is important to find an appropriate combination of parameter values, mainly paying attention to soil variables, in order to achieve the accurate prediction of pile capacity. There is a reasonable way to enhancing prediction accuracy of the dynamic resistance with the velocity dependent approach. Variation of the pilesoil system after the completion of driving can be taken into account by a variable damping coefficient which should be considered as a function of time and other parameters characterizing soil consolidation around the pile, Svinkin (1996, 1997). It is assumed that the variable damping coefficient is independent of pile velocity. Inclusion of variable damping is thought to be the next step in the development of Smith's model with the velocity dependent approach for representation of the dynamic resistance.
The damping coefficient as a function of time can be
found on the basis of back calculations using the wave equation model of
the pilesoil system with known capacity as This procedure is in
agreement with Lambe's (1973) equation modified for a general back
analysis approach by Leroueil & Tavenas (1981). Since the variable
damping coefficient is chosen as only one soil parameter reflecting the
field soil consolidation after pile installation, this parameter can be
successfully back analyzed.
The results of back analysis has revealed that the shaft damping
coefficient in clay is much higher than in unsaturated sand, but upper
values of this coefficient in saturated sandy soil (sand with high
damping) are close to ones in clay, Svinkin and Woods (1998). Also, a
trend of the damping coefficient increase with time after EOID was found
for all soil damping models available in GRLWEAP program and this trend
is independent of the damping resistances, Svinkin (1996).
The idea of variable damping has been confirmed by results of
statistical analysis of damping coefficients from CAPWAP solutions
performed by Liang and Zhou (1997) who have found that the damping
coefficient is affected by the time. Cho et al. (2000) agree that setup
effects should be accounted for in wave equation analysis for restrikes
and suggested constant damping and quake coefficients to computing pile
capacity before restrike. This is a partial solution because these
coefficients can be used only for one restrike. The variable damping
coefficient is a solution for calculation of pile capacity before
different restrikes.
Soil
damping is the key parameter for adjustment of wave equation solutions
with timedependent soil properties in predriving analysis. The use of
the variable damping coefficient gives an opportunity to compute the
timedependent pile capacity by the wave equation method.
Software Calibration.
Existing programs for wave equation analysis are not the same. Moreover all
programs have a number of versions. Each new version gives usually
additional beneficial options to users, but it is not clear how each
program version ensures the accuracy of pile capacity calculation. There
is confusion what program yields more accurate results. The writer has
an experience of pile capacity calculation for the same hammer, pile and
soil conditions using two versions of the same program. Variation of
obtained capacities was about 20 %. This is an evidence of
contradictions available between different program versions.
Obviously,
it is necessary to calibrate each program version with some standard
data of the hammerpilesoil system in order to avoid confusion in a
choice of the program.
Dynamic
Testing
Dynamic
testing followed by a signal matching procedure has obvious advantages
in determining pile capacity at any time required after pile
installation. Since dynamic testing is often used to replace the static
loading tests, it is important to ascertain the adequacy of both SLT and
DT.
Existing
Approach for Comparison of SLT and DT.
Static analysis methods predict pile capacity as the long term
capacity after soil consolidation around the pile is complete.
Independently of the time elapsed between installation of the
test pile and the static loading test, the ratio of the predicted
ultimate load to the measured ultimate load from static loading test is
used for approximate evaluation of the reliability of design methods.
For example, Briaud and Tucker (1988) evaluated 13 methods developed to
predict the ultimate load capacity of the pile, and they used this ratio
for approximate evaluation of the reliability of design methods in
calculation of the ultimate pile load although the time elapsed between
installation of the test pile and static load test averaged 17 days.
According
to the traditional approach, the main criterion for assessment of the
pile capacity prediction based on dynamic measurements is the ratio of
capacities obtained by dynamic and static tests or vice versa (Figure
2). It is necessary to point out that a ratio of DT/SLT or vice versa,
taken for arbitrary time between compared tests, is not a verification
of dynamic testing results. It is wellknown that dynamic testing
methods yield the real static capacity of piles at the time of testing,
Rausche et al. (1985). Besides, the static capacity from SLT is
considered as a unique standard for assessment of dynamic testing
results. Unfortunately, that is a major error.
As a matter of fact, pile capacity from Static Loading Tests is a
function of time and the socalled actual static capacity from SLT is
not a constant value, Svinkin (1997; 1998).
For
the general case of assessment of reliability of the DT, the ratio of
restrikes to SLT results has been considered for various pile types,
soil conditions and times of testing lumped together as shown in Figure
2. Such mixture has no real meaning. It is not a verification of dynamic
testing at restrikes and it is not an assessment of real setup factor
because everything is lumped together without taking into account the
time between different tests. Such a comparison of the pile capacities
from SLT and DT is invalid for piles driven in soils with timedependent
properties because the soil properties at the time of DT do not
correspond to the soil properties at the time of SLT i.e. soil
consolidation is taken into account for the latter test and not
considered for the former test. As a matter of fact, such a comparison
uses pile capacity values which are incompatible from the point of DT
verification, Svinkin (1997) and Svinkin and Woods (1998).
New Criteria for Comparison of SLT and DT. Criteria should be established for correct comparison of insitu tests made at different times after EOID. It is important to find how changes of pile capacity between two compared tests may affect the accuracy of determining pile capacity by dynamic testing.
Acceptable time between tests. Pile capacity determined at EOID in various soils changes with time. After the completion of pile driving, soil consolidation, manifested by the dissipation of excess pore pressure at the soilpile interface zone, is usually accompanied by an increase in pile capacity (soil setup). In saturated sandy soils, ultimate pile capacity may decrease (soil relaxation) after initial driving due to dissipation of negative pore pressure. Changes of strength in soil after driving and the time required for return of equilibrium conditions are highly variable and depend on soil conditions, and pile type and size. The consequences of soil modification around the pile are essential with respect to changes of pile capacity. Pile capacity as a function of time is displayed, for example, in Figure 1 for piles TP1 and TP2. Comparison of values of the pile capacity obtained from two tests with arbitrary time between them show only a change of pile capacity during a considered period of the time, but it is not verification of DT.
Static
Loading Tests and Dynamic Testing present different ways of determining
pile capacity at various times after pile installation, but for valid
correlations of both tests, static and dynamic testing capacities must
be compared at the same time after pile installation in both SLT and DT
methods, Svinkin (1997; 2000) and Svinkin and Woods (1998).
The
adequacy of SLT and DT have to be confirmed by proper correlation of
time. Due to the
consolidation phenomenon in soils, comparison of SLT and DT can be made
only for tests performed immediately one after another.
In practice, it is sometimes difficult to make two immediately
successive tests, but nonetheless the time difference between both
comparable tests should not exceed 12 days during which soil setup
changes only slightly.
Rate of pile capacity change. It is important to find quantitative assessment of pile capacity change during 12 days. The rate of pile capacity change per day (setup rate), r_{R}, between two
considered tests can be calculated as
Where
R_{u1} = pile capacity from test 1; R_{u2} = pile
capacity from test 2; t_{1} and t_{2} = elapsed time in
days after EOID for test 1 and test 2, respectively.
The setup rate was calculated for different pile types tested in
various soils. Pile
capacity from dynamic testings was determined by CAPWAP analysis and the
Davisson criterion of failure load was used for static loading tests,
Davisson (1972). The obtained results are shown in Table 13. Initial
data for these tables were taken from Svinkin et al. (1994).
A description of seven prestressed concrete piles is presented in
Table 1. The depth of penetration of each pile was approximately 24.4 m.
The soil consisted of about 25.6 m of mainly gray clays followed by a
bearing layer of silty sand. Water table was at the ground surface. A
Delmag D 4613 hammer was employed for initial driving and restrikes (RSTR).
For each pile, 3 to 4 DT and/or SLT were performed after pile
installation. The elapsed time after EOID, penetration resistance and
the time dependent ultimate capacity of tested piles are shown in
Table 1 as well. It can be seen that the setup rate depends on the
elapsed time after pile installation. The setup rate was about few
hundred in 12 days after pile installation. Then the rate considerably
decreased and became 1316 %/day for four days after EOID and less than
78 %/day for 910 days after EOID, Figure 3.
Table 1. Static and Dynamic Data for Prestressed Concrete Piles in Clay over Silty Sand

Pile

Test

Time
after
EOID
(days)

Penetration
Resistance
(blows/0.3 m)

Ru
(kN)

Setup
Measd

Setup
Rate
(%/day)

No.

Description







TP1

1372 mm x 127 mm
Cylinder

EOID
RSTR1
RSTR2
RSTR3


2
9
22

38
>240
>240
>240

752
2451
2927
3545

1
3.26
3.89
4.71


113
3
2

TP2

1372 mm x 127 mm
Cylinder

EOID
SLT1
SLT2
SLT3


2
9
22

48




712
1913
2789
3189

1
2.69
3.92
4.48


84
7
1

TP3

610 mm x 610 mm
(305 mm D. void)

EOID
RSTR1
RSTR2
RSTR3
SLT


1
10
18
31

10
21
72
144


267
912
1530
1672
1841

1
3.42
5.73
6.26
6.90


242
8
1
<1

TP4

762 mm x 762 mm
(475 mm D. void)

EOID
RSTR1
RSTR2
RSTR3
RSTR4
SLT


1
4
9
18
32

14
23
60
>240
168


200
890
1299
1517
1601
2273

1
4.45
6.50
7.60
8.00
11.37


345
15
3
<1
3

TP5

762 mm x 762 mm
(475 mm D. void)

EOID
RSTR1
RSTR2
RSTR3
RSTR4
SLT


1
4
11
20
34

23
59
96
91
>240


262
952
1401
1588
1748
2473

1
3.63
5.37
6.06
6.67
9.44


263
16
2
1
3

TP6

914 mm x 127 mm
Cylinder

EOID
RSTR1
RSTR2
RSTR3
RSTR4
SLT


1
4
11
21
35

15
34
64
162
113


400
885
1241
1766
2300
2406

1
2.21
3.10
4.42
5.75
6.02


121
13
6
3
<1

TP7

914 mm x 127 mm
Cylinder (spliced)

EOID
RSTR1
RSTR2
RSTR3
RSTR4
SLT


1
4
10
20
35

32
32
102
168
186


454
876
1285
1890
2260
2406

1
1.93
2.83
4.16
4.98
5.30


93
16
8
2
<1

Table 2. Static and Dynamic Data for Piles in Unsaturated Sandy Soils

Pile

Test

Time
after
EOID
(days)

Penetration
Resistance
(blows/0.3 m)

Ru
(kN)

Setup
Measd

Setup
Rate
(%/day)

No.

Description

Embdt
(m)







1

Prestressed concrete
508 mm x 508 mm
(38 mm D. void)

38.0

EOID
RSTR1
SLT


3
12

110
1114


2487
3243
6450

1
1.30
2.59


10
11

2

Prestressed concrete
356 mm x 356 mm

27.4

EOID
RSTR1
SLT


7
16

68
78


1134
2309
3736

1
2.03
3.29


15
7

3

324 mm O.D. by 6 mm thick closed end steel pipe

25.3

EOID
RSTR1
SLT


7
14

27
48


681
1232
2224

1
1.81
3.26


12
12

Table 3. Static and Dynamic Data for Prestressed Concrete Piles in Saturated Sandy Soils

Pile

Test

Time
after
EOID
(days)

Penetration
Resistance
(blows/0.3 m)

Ru
(kN)

Setup
Measd

Setup
Rate
(%/day)

No.

Description

Embdt
(m)







CT1

457 mm x 457 mm

19.7

EOID
RSTR1
RSTR2
SLT


2
11
21

18
84
84


913
1145
1702
1666

1
1.25
1.86
1.85


13
5
<1

CT2

457 mm x 457 mm

22.9

EOID
RSTR1
RSTR2
SLT


2
11
21

42
84
60


1907
2176
2668
2540

1
1.14
1.40
1.34


7
4
<1

CT3

610 mm x 610 mm
(267 mm D. void,
solid ends)

19.5

EOID
RSTR1
RSTR2
SLT


1
10
22

34
72
108


1513

2615
2869

1

1.73
1.90



7
<1

CT4

610 mm x 610 mm
(267 mm D. void,
solid ends)

22.9

EOID
RSTR1
RSTR2
SLT


2
11
23

77
96
216


1986
2691
3617
3724

1
1.35
1.82
1.90


18
4
<1

CT5

915 mm x 915 mm
(570 mm D. void,
solid ends)

22.3

EOID
RSTR1
SLT


6
20

92
60


2949
4210
4900

1
1.43
1.66


7
1

Three piles, two prestressed concrete and one closed
ended steel pipe, are presented in Table 2. These piles were tested at
different sites but their soil conditions were very close: predominantly
unsaturated sandy soils. Soil deposits were mostly fine sands with bare
strata of silty sand at site 1 and slightly silty or clayey fine sands
at sites 2 and 3. The water table was not encountered during soil boring
on each site. For pile 1, a Kobe K45 hammer was used. Piles 2 and 3
were driven and restruck with a Vulcan 80C and 010 hammers,
respectively. For unsaturated sands, the setup rate was mostly
independent of the limited elapsed time of 1216 days after pile
installation and was found in the range of 1015 %/day.
Five prestressed concrete piles were driven on a site
with predominantly silty sands (Table 3). The water table was at a
depth of 0.6 m from ground surface. Piles CT1, CT2, CT3, and CT4 were
driven and restruck with a Kobe K25 hammer. A Delmag D 6222 hammer was
used for pile CT5. The setup rate was 718 %/day, 47 %/day, and less
than 1 %/day for 2, 1011, and 2023 days after EOID.
Thus, the rate of pile capacity change per day, r_{R},
decreases with an increase of the elapsed time after EOID and a margin
of error about 1015 %/day would be reasonable for a few days after pile
installation.
Comparison of SLT and DT. Thirty nine different piles in various soil conditions were statically and dynamically tested (Table 4). Initial data for these piles were taken from FHWAGRL database.
Explanation of abbreviations in Table 4 are as follows.
Pile number: number in parentheses is from FHWA Database; Pile
description: PSC is prestressed concrete, OEP is open ended pipe, CEP is
closed ended pipe, HP is Hpile; Soil: HWT is high water table; Time
between SLT & DT: minus and plus mean DT was made before or after
SLT, respectively; Time after EOID was shown for DT; Signal Matching:
reanalyzed results include the "automatic" or "best
match" (with asterisk), minus and plus in error mean under or
overestimated CAPWAP results.
Static load tests were carried to failure according to
the Davisson failure criterion. Dynamic records from restrike testing
were available for all piles. A signal matching technique  CAPWAP
analysis of the restrike test data was used for pile capacity
determination. The "original" CAPWAP capacities were obtained
from existing CAPWAP results. For a number of piles, additional CAPWAP
analysis was provided because of absence of the "original"
CAPWAP capacities or in order to improve signal matching results with
"automatic" or "best match" solutions.
"Automatic" is an option in the CAPWAP program with automatic
search capability which provides a solution using optimal matching of
signals with no user interaction. "Best match" is a result of
working in a manual operating mode to iteratively seek a best match.
For all considered piles, the time differences between
static and dynamic tests were 12 days, but time elapsed after EOID was
diverse. An acceptable margin of error was determined in accordance with
the setup rate in Tables 13. Compared capacities have a good agreement
within the acceptable margin of error for 28 piles (1, 3, 4, 5, 6, 8, 9,
11, 13, 15, 16, 17, 19, ,20, 21, 22, 24, 25, 26, 27, 28, 30, 31, 32, 34,
37, 38, 39). Piles with at least one CAPWAP result within the acceptable
limits were included in this group. For example, for pile 11
"original" and "automatic" CAPWAP yielded the pile
capacity with an error of 8 % and 40 %, respectively, but even
the big error is acceptable in this case because the elapsed time after
EOID was only 1 day and DT was made 2 days before SLT. Calculated
capacities for five piles (12, 14, 18, 29, 33) have errors from 20 % to
25 %. The worst results were obtained in CAPWAP analysis of six piles
(2, 7, 10, 23, 35, and 36) which were analyzed with errors between 3054
%. First three piles have underestimated results, but piles 23, 35 and
36 have overestimated pile capacity on 31 %, 54 % and 44 %,
respectively.
Table 4. Comparison of pile capacities obtained from SLT
and DT
Pile

Soil

SLT

Time
between

Dynamic Testing

Signal Matching

No.

Description

Length
(m)


(kN)

SLT & DT
(hours)

Time
a/EOID
(days)

Test

Blow
Count
(bl/0.3 m)

Original
(kN)

Error
(%)

Reanalzd
(kN)

Error
(%)

1(1)

610 mm PSC
305 mm void D.

28.42

Sand
HWT

4228

+24

13

RSTR2

360

4116

2.6

3498*

17

2(3)

610 mm PSC
305 mm void D.

20.20

Sand & Clay
HWT

3160

+24

12

RSTR2

240

2011

36

2216

30

3(5)

610 mm PSC
305 mm void D.

24.54

Sand & Clay
HWT

3560

+24

24

RSRT2

288

3573

+0.4





4(6)

610 mm PSC
305 mm void D.

37.69

Clay & Sand
HWT

3560

+24

24

RSTR2

720

3467

2.6

4041*

+14

5(7)

610 mm PSC
305 mm void D.

37.03

Sand & Clay
HWT

4361

+24

29

RSTR2

576

3386

22

4236*

3

6(46)

610 mm PSC

25.58

Sand, HWT

2216

+24

13

RSTR2

120

2114

4.6

2123

4.2

7(48)

762 mm PSC
457 mm void D.

31.10

Sand
HWT

6635

+48

31

RSTR2

432

3039

54

3836*

42

8(49)

762 mm PSC
457 mm void D.

30.80

Sand & Clay
HWT

2812

+24

10

RSTR2

144

2523

10

2376

16

9(50)

762 mm PSC
457 mm void D.

31.57

Sand & Clay
HWT

4005

+24

33

RSTR2

312





3435*

14

10(51)

762 mm PSC
457 mm void D.

30.02

Sand, HWT

6439

+24

26

RSTR2

264





3751*

42

11(56)

610 mm PSC
76 mm void D.

19.60

Sand with Silt
& Clay, HWT

3524

48

1

RSTR1

72

3253

8

2100

40

12(62)

610 mm PSC

58.52

Sand, Clay HWT

2893

+24

8

RSTR2

80

2382

17

2203

24

13(68)

610 mm PSC
102 mm void D.

27.43

Clay & Sand
HWT

4717

+48

21

RSTR1

1000

4517

4.2

4632

1.8

Table 4. continued. Comparison of pile capacities
obtained from SLT and DT
Pile

Soil

SLT

Time
between

Dynamic Testing

Signal Matching

No. 
Description

Length
(m)


(kN)

SLT & DT
(hours)

Time
a/EOID
(days)

Test

Blow
Count
(bl/0.3 m)

Original
(kN)

Error
(%)

Reanalzd
(kN)

Error
(%)

14(69)

406 mm PSC
102 mm void D.

24.38

Clay & Sand
HWT

2626

+48

15

RSTR1

180

3204

+22





15(70)

HP 346x109

27.43

Clay, HWT

2750

+48

34

RSTR1

1000

2799

+1.7





16(71)

HP 346x109 
27.43

Sand & Clay
HWT

1393

+24

10

RSRT1

96





1517*

+8.9

17(72)

610 mm x 13 mm
OEP

25.91

 
2670

+24

10

RSTR1

150





2652*

0.7

18(73)

610 mm PSC
Octagonal

25.91

Sand & Clay
HWT

4873

+24

10

RSTR1

1000

3783

22

3814

22

19(74)

305 mm PSC

27.74

Sand, Clay
& Silt, HWT

1602

+48

22

RSTR3

208





1687*

+5

20(75)

610 mm PSC 
24.84

Sand & Clay
HWT

2238

+24

3

RSTR1

24

2448

+9

2617

+17

21(76)

610 mm PSC 
20.27

Sand & Clay
HWT

4650

+24

3

RSTR1

60





5006*

+7.6

22(92)

244 mm x 14 mm
CEP

44.20

Sand & Clay 
2924

+48

52

RSTR2

602

2559

12.4

2051

43

23(102)

HP 299x79 
22.86



1664

+5

1

RSTR2

192

2185

+31





24(103)

HP 299x79 
12.19

 
2318

+5

1

RSTR1

360

2323

+0.2





25(104)

HP 299x79

24.38



1682

+5

1

RSTR1

240

1918

+14





26(121)

406 mm x 6 mm
CEP

12.10

Sand & Silt 
1161

+24

10

RSTR1

107

1077

7

1068

8

Table 4. continued. Comparison of pile capacities
obtained from SLT and DT
Pile

Soil

SLT

Time
between

Dynamic Testing

Signal Matching

No.

Description

Length
(m)


(kN)

SLT & DT
(hours)

Time
a/EOID
(days)

Test

Blow
Count
(bl/0.3 m)

Original
(kN)

Error
(%)

Reanalzd
(kN)

Error
(%)

27(122)

800 mm PSC
560 mm void D.

18.00

Clay & Sand
HWT

659

+24

10

RSTR1

46





699*

+9

28(129)

387 mm/140 mm
Timber

10.67

Clay, Loam, Till

757

+2

<1

RSTR1

60

659

13

636

16

29(130)

324 mm x 6 mm
CEP

24.99

Silt

970

+24

16

RSRT1

120

797

18

774

20

30(133)

(356 mm x 5 mm)
(318 mm x 6 mm)
(279 mm x 6 mm)
CEP

24.08

Silt & Clay

1197

+24

26

RSTR1

600

1046

13





31(154)

457 mm PSC

13.72

Sand, HWT

1041

+48

6

RSTR1

42

730

30

948

9

32(155)

457 mm PSC

10.67

Sand

757

+24

4

RSTR1

34





730*

3.5

33(165)

324 mm x 13 mm
CEP

27.43

Clay & Silt
HWT

2496

+12

17

RSTR1

96

3115

+25





34(166)

324 mm x 13 mm
CEP

27.43

Clay & Silt
HWT

2211

+24

17

RSTR1

72

2390

+8





35(169)

324 mm x 13 mm
CEP

21.00



788

24

14

RSTR1

48

1504

+54





36(170)

324 mm x 13 mm
CEP

17.00



712

24

14

RSTR1

24

1148

+44





37(183)

305 mm PSC

26.52

Sand & Silt

1691

+24

12

RSTR3

Refusal

1927

+14





38(184)

305 mm PSC

24.08

Sand & Silt

1090

+24

16

RSTR3

120

1144

+5





39(185)

244 mm x 19 mm
OEP

43.61

Clay with Silt
& Sand

1896

24

2

RSTR1

60

1900

0

1878

<1

Comments about the worst obtained results. Pile 2 was tested at the same site with piles 1, 3, 4, and 5, but only pile 2 has a big error. "Automatic" analysis decreased an error from 36 % to 30 %. Perhaps the quality of the velocity record is the reason of unsatisfactory solution. Dynamic testing records of piles 2 and 4 (for comparison) are depicted in Figure 4. For pile 7,
"automatic" analysis decreased an error in calculation of pile
capacity from 54 % to 42 %. The time between SLT and DT was 2 days,
but an elapsed time after EOID was 31 days. For such period of time the
difference between compared tests should be minimal. There is no obvious
explanation of the underestimating pile capacity for pile 7. An error in
the computed capacity of pile 10 was 42 % in spite of the
"best match" solution. Relaxation of pile capacity is possible
in saturated sand, but 42 % of decreasing pile capacity on the 26th day
after EOID and 1 day after SLT is very strange. For pile 23, the
computed pile capacity with an error of +31 % is acceptable because the
elapsed time after EOID was 1 day. Overestimating capacities for piles
35 and 36 were computed with big errors of +54 % and +44 %,
respectively. These results may be explained with implementation of DT
on one day before SLT.
It can be seen the computed capacities for 11 piles
exceeded a reasonable margin of error. The Davisson criterion determines
a conservative value of pile capacity. Maximum values of pile capacity
can be estimated with the Chin method from which results are about 20 %
to 40 % greater than from the Davisson limit, Fellenius (2001).
Therefore, computed pile capacity exceeding the Davisson limit more than
20 % should be considered as overestimating values. It is not acceptable
for pile foundation design. Underestimating pile capacities are good for
foundation safety but not acceptable from the economic standpoint.
Analysis of 39 cases revealed substantial errors in determination of the
pile capacity for 6 piles that is about 15 % of the total number of
considered piles. However, it is important to recognize such cases.
Besides formal implementation of signal matching procedure, it is
necessary to use engineering judgment in assessment of DT results. The
main objective of this study is to bring attention of geotechnical
engineers to engineering judgment of dynamic testing in order to
recognize bad situations in advance.
Effects of various factors on Results of DT. It
is important to reveal how various factors affect signal matching
results.
Time between compared tests was in the limits of 12 days. The time was 48 hours for 8 piles, 24 hours for 26 piles, 12 hours for 1 pile, 5 hours for 3 piles, and 2 hours for 1 pile. Thus, closely time correlated comparisons of SLT and DT have been made.
Time after pile installation affects the rate of pile capacity change. This rate is different for various soils, but a margin of error about 1015 %/day would be reasonable for a few days after pile installation. For short period after EOID, larger discrepancies are acceptable as was shown for pile 11 and in Figure 3.
Sequence of tests. Four piles (11, 35, 36, and 39) were dynamically tested before SLT. Piles 11 and 39 were tested on the first and the second days, respectively, after EOID when soil consolidation only started and the difference between pile capacities from DT and SLT was acceptable. Piles 35 and 36 were tested on the 14th day. DT destroyed soil consolidation around the pile and during one day soil could not reconsolidate. Perhaps this is the cause of the big discrepancy between compared pile capacities. Therefore, DT should be made after SLT to obtain better results.
Pile type. No correlations was found between pile type and pile capacities computed.
High blow count. No correlations was found between high blow count and pile capacities computed.
Signal matching technique. "Automatic" signal matching improved results computed for 8 piles (2, 6, 13, 18, 22, 26, 31, 39) and made worse calculations for 6 piles (8, 11, 12, 20, 28, 29). "Best match" changed for the worse the pile capacity of only pile 1. It is obvious that "best match" is preferred procedure in signal matching technique. Described results were obtained with CAPWAP program, but similar outputs could be expected from the use of TNODLT program, TNO Report (1996).
Dynamic records should affect computed result. One example was shown in the text. There is a trend to improve wrong records by means of signal matching technique, but it is unknown how record improvement affects computing pile capacity. It seems to be beneficial to prepare a catalog of unacceptable records.
Soil conditions. It is necessary to collect more information in order to reveal effects of soil conditions on computed results.
Prediction of Pile Capacity by DT. Obviously, at
EOID and each restrike the pilesoil system has various soil stiffness,
damping and soil mass involved in vibration. Therefore, each dynamic
testing yields pile capacity corresponding to the properties of the
pilesoil system at the time of testing. The pile capacity from a static
load test reflects a degree of soil consolidation around a pile at the
time of testing as well. Thus, static, dynamic and statnamic tests
determine pile capacity only at the time of testing.
In some publications, dynamic testing is used for a capacity prediction without prior knowledge of the static loading test, e.g. Goble (2000) and Holeyman et al. (2000). This is a misleading interpretation of DT which does not have any connection with Class A type prediction defined by Lambe (1973). No insitu pile test can predict pile capacity as a function of time after pile installation.
Overestimated software capabilities. It is
sometimes difficult to activate the pile capacity at restrike and
software users calculate the undetermined pile capacity with combined
CAPWAP analysis, Stevens (2000). The pile capacity is estimated by
compounding resistance distribution from two different DT and using the
highest values between the two for each soil element. It seems that such
a procedure overestimates capabilities of signal matching technique. It
is important to verify similar calculations with SLT or use the special
driving technique (Fellenius 1999) which means that one of the nearby
piles is driven at EOID shorter so that there is confidence that at
restrike the pile will move and its full resistance will be mobilized.
The nearby not mobilized piles can be said to have the same shaft
resistance and at least as much toe resistance.
Conclusions
The paper's objective is an attempt to emphasize the
engineering judgment and eliminate contradictions and/or
misunderstanding of determining pile capacity by dynamic methods. The
paper demonstrates misapplication and misuse of the specified computer
software. It is shown the necessity of consideration of the soil
consolidation effect in prediction of longterm pile capacity by wave
equation analysis, calibration of wave equation programs, and proper
comparison of static and dynamic tests. Also, it is underlined
impossibility to predict pile capacity by dynamic pile testing,
misleading assessment of the accuracy of dynamic formulas, and paid
attention to overestimated capabilities of signal matching technique.
Dynamic methods have to be used with the proper engineering judgment for
prediction and determination of pile capacity.
Acknowledgement
The writer is grateful to the Federal Highway
Administration (FHWA) and GRL and Associates, Inc. for assistance in the
use of FHWAGRL database. Opinions expressed in this paper are those of
the writer and not necessarily those of FHWA and GRL and Associates,
Inc. The writer wishes to thank the reviewers for their constructive
reviews of the paper.
APPENDIX I.REFERENCES
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Davisson, M.T. (1972). "High capacity piles", Proc., lecture Series, Innovations in Foundation Construction, ASCE, Illinois Section.
Fellenius, B.H. (1999). APTLY email archives.
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Svinkin, M.R., C.M. Morgano & M. Morvant (1994). "Pile capacity as a function of time in clayey and sandy soils", Proc. Fifth Inter. Conf. and Exhibition on Piling and Deep Foundations, Bruges, 1315 June, Rotterdam: Balkema, 1.11.11.11.8.
Svinkin, M.R. (1996). "Soil damping in wave equation analysis of pile capacity", In F. Townsend, M. Hussein & M. McVay (eds.), Proc. Fifth Inter. Conf. on the Application of StressWave Theory to Piles, Orlando, 1113 September, Gainesville, University of Florida, 128143,
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