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GEORISK-2004: International Workshop on Risk Assessment in Site Characterization and

Geotechnical Design, Bangalore, INDIA. November 26, 27

Examination of LRFD Recommendations for Deep Foundations Using a

Field Load Testing Program

Samuel G. Paikowsky, ScD1, and Eric Thibodeau, P.E.2 Abstract

An extensive development of resistance factors for the AASHTO specifications of Deep Foundations was undertaken under NCHRP project 24-17 and presented in NCHRP Report 507 (Paikowsky, 2004). These factors were developed based on large databases examining the deep foundations capacity prediction methods during design and construction. A pile testing program is used to evaluate the adequacy of the recommended factors for its unique, site specific conditions. An extensive load test program was conducted in 2002 by the Connecticut DOT as part of the Route I-95 New Haven Harbor Crossing Corridor Improvement Project. The testing program included the installation of 43 piles in four different sites, of which 34 were heavily instrumented and 23 were statically load tested to failure. All of the piles were driven and were dynamically monitored during driving and subsequent restrike tests. The piles of this load test program were not included as part of the database used to develop the recommendations provided in NCHRP Report 507. A thorough evaluation of the testing program is carried out via the static and dynamic pile testing results. The outcomes are compared with the findings of the aforementioned study in two ways; (a) direct comparison to the statistical values provided by the extensive databases used in the study and (b) the adequacy of the developed resistance factors to address the conditions at the

1 Professor, Geotechnical Engineering Research Laboratory. Dept. of Civil and Environmental Engineering, University of Massachusetts-Lowell, 1 University Avenue, Lowell, MA 01854, USA. Email: [email protected] 2 Geotechnical Engineer, New Hampshire DOT. Graduate student, University of Massachusetts-Lowell, 1 University Avenue, Lowell, MA 01854, USA. Email: [email protected]

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site. Investigated are the recommendations for design procedure, adequacy of subsurface conditions, number of tested piles, timing of testing and associated risk at each stage. These comparisons enable to examine the capacity evaluation methods used both in design and construction. Conclusions are derived regarding the accuracy of the predictive methods used during pile design and construction, the adequacy of the newly developed recommendations and the risk associated with their use as reflected in the specific conditions encountered at the New Haven testing site. NCHRP report 507

Overview

National Cooperative Highway Research Program (NCHRP) project 24-17 and the resulting document NCHRP Report 507 (Paikowsky, 2004) was aimed at rewriting Section 10 of the American Association of State Highway and Transportation Officials (AASHTO) Load and Resistance Factor Design (LRFD) specifications for deep foundations. The intent of LRFD based design is to separate uncertainties in loading from the uncertainties in resistance and to ensure a consistent prescribed margin of safety. While there are many existing LRFD codes (e.g., AASHTO, AUSTROADS, Ontario Bridge Code, Canadian Bridge Code, Eurocode 7), none of these codes and their associated resistance factors were consistently developed based on databases enabling the calculation of resistance factors from case histories. The current AASHTO Section 10 specification for driven piles is further complicated due to the multiplication of the resistance factor by the construction phase modifier (λv). This requires an interaction of two independent pile capacity evaluations (e.g., design phase static analyses and construction phase dynamic analyses) and results in unnecessary and confusing conservatism. In NCHRP Report 507, a reliability based calibration-utilizing databases is employed, providing a clear separation of the resistance factors on the basis of design phase and construction phase capacity predictions. Research approach

A flow chart depicting the research approach that was developed and implemented for NCHRP Report 507 is presented in Figure 1. The research approach was broken down into the following eight major phases:

1. Establish the state of practice in design and construction of deep foundations

2. Databases development

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3. Static and dynamic capacity evaluations 4. Identify controlling parameters 5. Develop statistical parameters (bias, COV) for each

analysis/prediction method 6. Research and establish recommended probability of failure

(reliability index) considering subsurface redundancy 7. Develop resistance factors for the methods based on a prescribed

target reliability and structure state 8. Evaluate the resistance factors and recommend final values

State of practice

In order to establish the current state of practice, a questionnaire was developed and circulated to all US State Highway Departments of Transportation (DOT) and Federal Highway organizations. Based on the questionnaire, about 90 percent of the respondents use Allowable Stress Design (ASD), 35 percent use AASHTO Load Factor Design (LFD), and 28 percent use AASHTO LRFD, suggesting that most State Highway Agencies use LRFD or LFD in parallel to ASD. The questionnaire was also used to select the static (design phase) and dynamic (construction phase) prediction methods for calibration. Design phase static predictions included the β-method (Bowles, 1996), Schmertmann’s method for SPT (Sharp, 1987), Meyerhof’s method (Meyerhof, 1976) as modified by Zeitlen and Paikowsky (1982), the Nordlund method (Nordlund, 1963), and Nottingham and Schmertmann’s method for CPT (Nottingham and Schmertmann, 1975) for frictional soils and α-Tomlinson (Tomlinson, 1980, 1995), α-API (Reese et al., 1998), λ-method (Vijayvergiya and Focht, 1972), and the β-method (Esrig, and Kirby, 1979) for cohesive soils. The Thurman method (cited in Hannigan et al. 1995) was selected for predicting tip resistance. Construction phase prediction methods selected for calibration included static load testing, dynamic equations, and methods that utilize dynamic measurements recorded with a Pile Driving AnalyzerTM (PDA). The dynamic equations included the Engineering News Record (ENR) (Wellington, 1892), the Gates Equation (Gates, 1957), and the Gates equation as modified by the FHWA (FHWA, 1988). Predictions utilizing the Wave Equation program GRLWEAP were also selected for calibration. Methods, which utilize dynamic measurements, included signal matching analyses using the CAse Pile Wave Analysis Program (CAPWAP), and the Energy Approach method (Paikowsky, 1982, and Paikowsky et al., 1994). The Energy Approach uses basic energy relations in conjunction with dynamic (PDA) measurements

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(Emax and Dmax) and the permanent displacement (set) of the pile (1/measured blow count) to predict pile capacity.

Database Build-Up Static – Driven Piles Dynamic – Driven Piles Static – Drilled Shafts Peripheral Databases

Questionnaire State of Practice Driven Piles and

Drilled Shafts Design and Construction

Establish Common Design Methods

and Procedures for Static Analyses

Research and establish

Recommended Pf

Evaluation of the Static Capacity of DP

and DS for all Methods/Correlation

Combinations

Evaluating Static Capacity DP

based on Dynamic Analyses

Establish Viable

Methods and Controlling

Parameters for the Dynamic

Analyses

Establish a Single Method for the Determination of Nominal Strength (capacity), it’s accuracy and LT procedure effect

Calculating the Ratio of the Nominal Strength to

Predicted Capacity

LT-Static Load Test DP-Driven Piles DS-Drilled Shafts

SGP 4/7/02

Evaluate the Nominal

Strength of all cases Develop Statistical

Parameters for the Performance of each

Analysis Method/Correlation

Combination

Calculating the Resistance Factors and Evaluating the Results

Recommended Resistance Factors

Figure 1. Framework for NCHRP 507 Research Approach (Paikowsky, 2004)

Database development

Two principal databases were compiled for LRFD calibration of driven piles, one for static analyses and one for dynamic analyses. The static analysis database for driven piles consists of 337 case histories and was developed at the University of Florida (UOF) mostly through the integration of databases gathered by the UOF, the FHWA (DiMillio, 1999), the University of Massachusetts Lowell (UML) (Paikowsky et. al., 1994), and the Louisiana Transportation Research Center. The case studies were categorized by pile type and subsurface soil types as indicated in Table 1.

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Table 1. Static Analysis Database Summary (Paikowsky, 2004)

Soil Type Number of Cases Tip Side H-Piles PPC PP

Clay 3 0 0 Sand 12 0 0

Mixed 6 15 3 Rock

Total 21 15 3 Clay 0 0 0 Sand 17 37 20

Mixed 13 50 19 Sand

Total 30 87 39 Clay 8 19 20 Sand 1 1 0

Mixed 36 34 15 Clay

Total 44 54 35 Insufficient Data 0 7 1 All Cases (337) 96 163 78

PPC- precast prestressed concrete PP - pipe piles

The dynamic analysis database (PD/LT2000) consists of a total 210 driven piles that were statically load tested to failure and dynamically monitored during driving and/or restrikes tests (403 analyzed measurements). The PD/LT2000 database is comprised of information contained in the PD/LT database (Paikowsky el al., 1994), the PD/LT2 database (Paikowsky and LaBelle, 1994), and additional pile case histories described by Paikowsky and Stenerson (2000). The piles and dynamic measurements were categorized by pile type, geographical location, soil type, soil inertia (e.g., blow count), and type of dynamic measurement (e.g., end of drive, beginning of restrike) as indicated in Table 2. In addition to the databases dealing with drilled foundations (beyond the scope of this paper) six additional peripheral databases were gathered to investigate specific issues like the influence of static load testing rate on the pile capacity, etc.

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Table 2. Dynamic Analysis Database Summary (Paikowsky, 2004)

Pile Types Geographical Location Soil Types Soil Inertia Type of

Data Pile

Type No Location No Type Side Tip Criteria No AR Time No

H-Piles 37 Northeast USA 44 92

OEP 10 Southeast USA 69

EOD &

BOR

CEP 61 North USA 24

?16 blows /10cm

272 --

Voided Conc. 35 South

USA 10

Clay/ Till 67 61

EOD &

BOR’s 30

254 9 Northwest USA 3

305 5 Southwest USA 14

< 16 blows /10cm

112 -- EOD 135

356 8 Australia 2

406 1 New

Brunswick

3

Rock 0 11

BOR 239

457 8 Holland 4

? 350 -- 134

508 8 Hong Kong 4 EOR 11

610 16 Israel 4

Squa

re C

oncr

ete

762 5 Ontario 22

Sand/ Silt 140 137 < 350 -- 255

DD 2

Oct. Conc. Sweden 1 1

3 DR

Timber 2 N/A 6

N/A 3 1 N/A 5 --

ALT 1 MT 2

Totals 210 210 210 389 389 389 OEP – Open ended pipe piles CEP – Closed ended pipe piles Northeast USA – FHWA regions 1, 2 & 3 Southeast USA – FHWA region 4 North USA – FHWA regions 5, 7 & 8 South USA – FHWA region 6 Northwest USA – FHWA region 10 Southwest USA – FHWA region 9 EOD – End of Driving BOR – Beginning of Restrike DD – During Driving DR – During Restrike ALT – Alternate measurement AR – Area Ratio N/A – Not Applicable or Unknown

Controlling parameters – Static analyses

Pile type, soil type, the determination of strength parameters and method of analysis were assumed to be the parameters controlling the calculated static capacity of a driven pile. For the possible combinations of pile type and soil types (tip and side) presented in Table 1,combination of a given soil parameter interpretation method and a method of analysis were used. This allows for clear and consistent way of capacity evaluation. Soil properties were estimated using N-values from standard penetration tests (SPT) or data obtained from cone penetration tests (CPT). Depending on the static analysis method, soil properties were estimated using both SPT and CPT correlations as presented by Kulhawy and Mayne (1990) and specified in NCHRP report 507.

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The bias (λ) is defined as the ratio of the measured nominal resistance (Rn) (as obtained from the static load test) divided by the predicted Rn and is a direct measure of the relative accuracy of the prediction where a bias greater than 1.0 signifies an underprediction and a bias of less than 1.0 signifies an overprediction. The measured nominal strength (Rn) obtained from the static load test was determined based on the Davison’s failure criterion (Davisson, 1972). This criterion was established using the following procedure: (i) assessing five different interpretation methods: Davisson’s Criterion (Davisson, 1972), Shape of Curve (similar to the procedure proposed by Butler and Hoy, 1977), Limiting Total Settlement to 25.4 mm, Limiting Total Settlement to 0.1B (Terzaghi, 1942), and the DeBeer log-log method (DeBeer, 1970), (ii) calculating a single representative nominal strength value (Rn) for each of the analyzed cases as the average of the methods considered relevant (i.e., provided a reasonable value), and (iii) this representative Rn was then directly compared with the predicted Rn for each of the methods to evaluate the bias of each of the five aforementioned methods. Of the five methods, the Davisson’s Criterion was found to perform the best overall considering its uniqueness and was therefore chosen as the single method to be used when analyzing load-displacement curves. The small bias associated with Davisson’s Criterion (mean = 1.018, stnd. Dev. = 0.101, n = 186 cases) is considered when relevant. The influence of the loading rate during the static load test was also examined and was found to be of insignificant value; hence all load test procedures were treated equally. Controlling parameters – Dynamic analyses

Statistical research performed on the piles contained in the PD/LT2000 database identified the time of testing (i.e. End of Driving vs. Beginning of Restrike) and the effects of soil inertia (due to the acceleration of the displaced soil) as controlling parameters when utilizing dynamic measurements to predict the nominal resistance (Rn) (Paikowsky et al. 1994, Paikowsky and Chernauskas, 1996). The energy loss through the work performed by the displaced soil mass at the pile tip is directly related to the acceleration of this mass. The influence of the soils acceleration may indirectly be evaluated through the driving resistance, which represents the pile’s final displacement under each hammer blow. For the case of low driving resistance (easy driving), high acceleration and velocity are developed at the pile’s tip. For high driving resistance (hard driving), there is small acceleration at the pile tip, which results in little (if any) mobilization of the soil mass beyond the radiating elastic wave. The boundary between these conditions was statistically determined and defined as 16 blows per 10 cm (4 blows per inch). The amount of the displaced soil depends on the pile type and size.

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Piles are typically classified as being small displacement or large displacement piles. As most soil displacement occurs at the pile tip, this classification can be better served by calculating the pile’s area ratio (AR), which is defined as the ratio of the pile’s embedded surface area divided by the pile tip area (Paikowsky et al., 1994). To take this effect into consideration, a quantitative boundary between “small” and “large” displacement piles of AR < 350 was proposed and, when considered in conjunction with the effects of driving resistance, was confirmed with the statistical research results obtained from the NCHRP 507 PD/LT2000 database. As a result, for dynamic predictions, NCHRP Report 507 recommended separate categories for blow count (BC) < 16 blows per 10 cm (i.e., easy driving) for the FHWA Modified Gates equation and (BC) < 16 blows per 10 cm and AR < 350 for CAPWAP analyses for the EOD condition. Resistance factor development

While the existing AASHTO LRFD resistance factors are based on first-order second-moment (FOSM), the resistance factors for NCHRP Report 507 (Paikowsky, 2004) were developed using the more invariant first-order reliability method (FORM) approach. FORM can be used to assess the reliability of a pile with respect to specified limit states and provides a means for calculating resistance factors (φ) and load factors (γ), respectively, for a given target reliability level (β). FORM requires only first and second moment information on resistances and loads (i.e., means and coefficient of variations) and an assumption of distribution shape (e.g., normal, lognormal, etc.). For NCHRP Report 507, a target reliability of 2.33 was selected for redundant structures (i.e., five or more piles per pile cap) and a target reliability of 3.00 for non-redundant structures, which translates to a probability of failure (Pf) of 1.0% and 0.1%, respectively. The resistance factors to be applied to the design phase static nominal resistance prediction are presented in Table 3 and were developed with consideration given to subsurface soil profile type (e.g., sand, clay, or mixed), pile type (e.g., PPC, PP, or H-pile), analysis method/combination, and the aforementioned redundant and non-redundant target reliability levels. The resistance factors to be applied to the construction phase dynamic nominal resistance predictions are presented in Table 4 and were developed using statistical parameters with consideration given to the time that the dynamic measurements were taken (i.e., EOD, last BOR), the effects of soil

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motion, the effects of the volume of the displaced soil, and the aforementioned redundant and non-redundant target reliability levels.

Table 3. Recommended Resistance Factors for Static Analyses (Paikowsky, 2004)

Resistance Factor (φ) Pile

Type Soil

Type Design Method/Combination Redundant Non-

Redundant Mixed SPT-97 mob 0.70 0.50

α-API Clay λ-Method β-Method Sand SPT-97 mob

FHWA CPT

0.50 0.40

β-Method/Thurman Mixed α-

Tomlinson/Nordlund/Thurman Sand Nordlund

0.40 0.30

Clay α-Tomlinson Mixed α-API/Nordlund/Thurman

0.35 0.25

Con

cret

e Pi

les (

PPC

)

Sand Meyerhof 0.20 0.15 SPT-97 mob Sand

Nordlund 0.55 0.45

SPT-97 mob 0.40 0.30 Mixed α-API/Nordlund/Thurman

Sand β-Method 0.35 0.25

Clay α-API Sand Meyerhof

0.30 0.20

α-Tomlinson/Nordlund/Thurman Mixed

β-Method/Thurman α-Tomlinson

Pipe

Pile

s (PP

)

Clay λ-Method

0.25 0.15

Mixed SPT-97 mob SPT-97 mob

0.55 0.45

Nordlund H-P

iles

Sand Meyerhof

0.45 0.35

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α-API α-Tomlinson Clay

λ-Method 0.40 0.30

α-API/Nordlund/Thurman 0.35 Mixed α-

Tomlinson/Nordlund/Thurman Sand β-Method

0.30 0.25

Mixed β-Method/Thurman 0.20 0.15 Redundant – Five or more piles under one pile cap (β = 2.33 & pf = 1.0%) Non-Redundant – Four or fewer piles under one pile cap (β = 3.0 & pf = 0.1%) Resistance factors to be applied to the interpreted failure load (nominal resistance) as determined from construction phase static load tests were developed with consideration given to the number of load tests performed at a given site, the site variability, and the variability introduced by the selected static load test failure criterion (i.e., Davisson’s Criterion). These three factors were selected since observed pile capacity differences for a certain type of static load test that is performed at the same site on the same pile type would only be reflective of spatial soil variability across the site, the inherent variabilityof the method used to evaluate the interpreted failure load, and the reduction of the uncertainty in the test results when increasing the number of tests performed. The concept of site variability relates to the variation within similar subsurface strata located at a specific site and may be assessed by determining mean (mx), standard deviation (σx), and coefficient of variation (COV) for each strata using in-situ test data such as SPT N-values, laboratory test results, or CPT data. An example of a site variability assessment using SPT N-values is presented and discussed in the following section. The recommended resistance factors for static load tests with respect to site variability (COV ranges) and the number of load tests to be performed for a given site and pile type are summarized in Table 5.

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Table 4. Recommended Resistance Factors for Dynamic Analyses (Paikowsky, 2004)

Resistance Factor (φ)

Prediction Method Case Redundant Non-

Redundant EOD 0.65 0.45

EOD(1) 0.40 0.25 Signal Matching (CAPWAP) BOR 0.65 0.50

EOD 0.55 0.40

Dynamic Measurements

Energy Approach BOR 0.40 0.30 ENR General 0.25 0.15 Gates General 0.75 0.55 Dynamic

Equations FHWA Modified General 0.40 0.25

WEAP EOD 0.40 0.25 (1) – BC < 16 BP10cm & AR < 350 Redundant – Five or more piles under one pile cap (β = 2.33 & pf = 1.0%) Non-Redundant – Four or fewer piles under one pile cap (β = 3.0 & pf = 0.1%)

Table 5. Recommended Resistance Factors for SLT (Paikowsky, 2004)

Recommended Resistance Factor (φ)

Site Variability Low Medium High

No. of Load

Tests Per Site (COV < 25%) (25% ≥ COV < 40%) (COV ≥ 40%)

1 0.80 0.70 0.55 2 0.90 0.75 0.65 3 0.90 0.85 0.75 ≥ 4 0.90 0.90 0.80

COV – Coefficient of Variation Case study – new haven pile load test program In the spring and summer of 2002, the Connecticut Department of Transportation (ConnDOT) and their Program Manager Parsons Brinckerhoff Quade & Douglas (PBQ&D) performed an extensive pile load test program as part of the Interstate I-95 New Haven Harbor Crossing Corridor Improvement Project located in the cities of New Haven, East Haven, and

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Branford Connecticut; see Figure 2. The project includes the reconstruction of approximately 11.6km of I-95, located between Exits 46 (New Haven) and 54 (Branford).

NYCT

MA

NHVT

ME

RI

Test

Note: Test Area C Not Shown In Photo

Figure 2. Locus Plan and Photograph Overview of Test Sites and Project

Location Load test program overview Four sites (designated test areas A through D) were selected for pile load testing. The program involved the installation of 43 piles (designated A-1 through A-10, B-1 through B-9, C-1 through C-12, and D-1 through D-12), of which 23 were statically load tested to failure. Most of the piles were dynamically monitored during driving and subsequent pile restrike tests. Two restrike tests were performed on each pile that was selected for static load testing. The first restrike test (BOR1) was performed between 1 and 7 days after driving and the second restrike test (BOR2) was performed between 6 and 23 days after driving. Dynamic measurements were obtained during the initial driving operation and during the first and second restrike tests. CAPWAP analyses were performed by GZA GeoEnvironmental (GZA) on one representative hammer blow from the end of initial driving and for each of the restrike tests. The static load tests (SLT) were performed after the second restrike test (BOR2), between 14 and 56 days after driving. The load tests were carried out to failure conditions using the Quick Load Test Method (ASTM D1143) (PBQ&D, 2002; GeoDesign, 2002; GZA, 2002, and H&A , 2002). 19

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Subsurface Conditions and Site Variability Assessment

A total of 22 test borings were performed within the immediate vicinity of the four load test sites. The general subsurface conditions consist of miscellaneous fill overlying organic estuarine and glacio-deltaic deposits. The organic estuarine layer was not encountered at test area D. The glacio-deltaic deposits was the principle pile bearing layer and generally consists of a red brown, medium dense to very dense, mixture of fine to medium sand and silt, with interbedded layers of silt and clay. Distinct gravel layers were also encountered within the deposit. In accordance with NCHRP Report 507 (Paikowsky, 2004), the site variability for each of the test areas was assessed using SPT N-values whereby the SPT N-values were corrected for overburden pressure, tabulated for each stratum, and the mean (mx), standard deviation (σx), and coefficient of variation (COV) calculated for each layer assuming a normal distribution. Some SPT N-values were omitted from the dataset due to the presence of strata breaks within the sample interval, the presence of obstructions (i.e., cobbles, boulders, construction debris), and sample refusals with partial sampler penetration. The variability of each stratum was then classified using the COV ranges denoted in Table 5 and is presented and summarized in Figure 3 for areas A and B and Figure 4 for areas C and D. LRFD Design phase evaluation – Static analyses The nominal resistance (Rn) for the 11 piles that were statically load tested in areas A and B was estimated using the analysis methods/combinations presented in Table 3 for the mixed soil profile. Three combinations of analyses were utilized for the pipe piles (PP) and square precast prestressed concrete piles (PPC). Since monotube piles (MT) were not included in the NCHRP 507 research, two analyses combinations were selected with a preference given to the Nordlund method (Nordlund, 1963) as it allows to consider the tapered pile sections. The soil parameter interpretations were based on average SPT N-values and the soil property correlations presented in Kulhawy and Mayne (1990). Pile types, sizes, driven lengths, calculated nominal resistance (Rn), factored resistances (Rr), the static load test interpreted failure loads (SLT), and the resulting bias (λ) associated with each prediction are summarized in Table 6. Being compatible with NCHRP Report 507; the interpreted failure loads were evaluated using Davisson’s failure criterion (Davisson, 1972).

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Area A (4 borings) Layer

No. n mx σx COV

1 12 10 8.1 81% 2 10 2 2.1 128% 3 61 18 5.0 28% 4 16 19 4.8 25%

n – Number of Values

Area B (4 borings) Layer

No. n mx σx COV

1 7 57 33.0 58% 2 22 1 1.7 121% 3 34 23 12.3 53% 4 47 22 6.6 30% 5 5 28 6.4 23%


-40

-35

-30

-25

-20

-15

-10

-5

0

5

0 10 20 30 40 50 60

SPT N'60

El.

(m)

Ground Surface

Layer No. 1: FillHigh Variability

Layer No. 2: Organic SiltHigh Variability

Layer No. 3: Glacio-Deltaic (Upper)Medium Variability

Layer No. 4: Glacio-Deltaic (Lower)Medium Variability

Mean Value Line

-55

-50

-45

-40

-35

-30

-25

-20

-15

-10

-5

0

5

0 10 20 30 40 50 60 SPT N' 60

El. (

m)

Ground Layer No. 1: Fill; High

Layer No. 2: Organic High V i bili

Layer No. 3: Glacio-Deltaic ( )High

Layer No. 4: Glacio-Deltaic Medium

Layer No. 5: Glacio-Deltaic ( )Low

(69)

(77) (86)

(99)

Mean Value

Figure 3. Site Variability Assessment for Areas A and B

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Area C (9 borings) Layer

No. n mx σx COV

1 39 28 18.9 67% 2 25 4 2.3 55% 3 9 25 12.2 48% 4 2 N/A N/A N/A 5 86 27 12.8 47%


Area D (5 borings) Layer

No. n mx σx COV

1 15 24 10.1 42% 2 59 11 4.6 42%


-35

-30

-25

-20

-15

-10

-5

0

5

10

0 10 20 30 40 50 6

SPT N'60

El.

(m)

0

Ground SurfaceLayer No. 1: FillHigh Variability (67)

Mean Value Line

Layer No. 2: Organic (Upper)

Layer No. 3: Alluvium; High Variability

Layer No. 4: Organic (Lower)

Layer No. 5: Glacio-DeltaicHigh Variability

(64)

(70)

(62)

(62)

-30

-25

-20

-15

-10

-5

0

5

10

0 10 20 30 40 50 60

SPT N'60

El.

(m)

Ground SurfaceLayer No. 1: FillHigh Variability

Layer No. 2: Glacio-DeltaicHigh Variability

Mean Value Line

Figure 4. Site Variability Assessment for Areas C and D

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Table 6. LRFD Design Phase Evaluation– Static Analyses

Pile No.

Pile Type

DL (m)

Prediction Method

Rn (kN) φ

Rr (kN)

SLT (kN) λ

β-method/Thurman 3705 1482 0.59

α-Tom/Nord/Thur 0.40

1544 A-1 PPC (356mm) 30.0

α-API/Nord/Thur 3861

0.35 1351

2180 (6/5/02)

0.56



2607 A-2 PPC (406mm) 34.9

α-API/Nord/Thur 6517 0.35 2281

2669 (6/7/02)

0.41

β-method/Thurman 5507 1377


1374 A-6 PP (457mm) 36.3


0.35 1924

3025 (6/6/02) 0.55

α-Tom/Nord/Thur 0.25 1521 A-7 MT (457mm) 28.9


0.35 2130 2771

(6/10/02) 0.46



652 A-8 PP (324mm) 36.7


0.35 912

1592 (6/10/02)

0.61



1577 B-1 PP (457mm) 43.1

α-API/Nord/Thur 6308 0.35 2208

2269 (5/23/02)

0.36



1477 B-3 PPC (406mm) 30.6


0.35 1292

2847 (6/6/02)

0.77

α-Tom/Nord/Thur 0.25 1187 B-4 MT (457mm) 27.7


0.35 1661 2002

(6/3/02) 0.42



3396 B-5 PP (610mm) 47.9


0.35 4755

3683 (6/3/02)

0.27



2094 B-6 PPC (406mm) 35.2


0.35 1832

2816 (5/30/02)

0.54



1110 B-9 PP (457mm) 37.0


0.35 1554

1957 (5/28/02) 0.44

DL – Driven Pile Length Rn – Predicted Static Nominal Resistance φ – Resistance Factor (NCHRP 507) Rr – Factored Resistance (Rn*φ) SLT – Static Load Test Nominal Resistance λ – Bias (SLT/Rn)

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The results presented in Table 6 show that the static analysis methods (all combinations) overpredicted the nominal resistance for every case. The bias associated with the methods ranged between 0.27 and 0.81 indicating overpredictions between 3.7 (Pile B-5) and 1.2 (Pile B-3) times the nominal resistance obtained from the static load tests.

LRFD Construction phase evaluation - Dynamic testing

The nominal resistance (Rn) for the 23 piles that were statically load tested in areas A through D was estimated by performing signal matching analyses (CAPWAP) using one representative hammer blow for the end of driving (EOD), BOR1 and BOR2 conditions. The top of Pile A-1 broke after the second hammer blow during the BOR2; therefore, a CAPWAP analysis was not performed. Additionally, CAPWAP data was not provided for Pile D-1 (CAPWAP EOD) and Pile D-6 (CAPWAP BOR1). As discussed previously, the boundary between soil motion effects was statistically determined and defined as 16 blows per 10 cm and the quantitative boundary between “small” and “large” displacement piles was determined to be piles with an AR < 350. This special condition applies to 13 of the 22 piles for the CAPWAP analyses that were performed for the EOD condition. The Energy Approach method (Paikowsky et al., 1994) was also used to evaluate the pile’s nominal resistance at EOD. The estimated Rn’s, factored resistances (Rr), the static load test interpreted failure loads (SLT), and the resulting bias (λ) associated with each prediction are summarized in Table 7. The interpreted failure loads were evaluated using Davisson’s failure criterion (Davisson, 1972). As shown in Table 7, the bias range, mean (mx) and standard deviations (σx) associated with the CAPWAP analyses for the EOD, BOR1, and BOR2 range between 0.81 and 1.58 (mx = 1.26, σx = 0.31), 0.66 and 1.41 (mx = 1.14, σx = 0.32), and 0.72 and 1.54 (mx = 0.94, σx = 0.23), respectively. In general, the CAPWAP predictions improved between the EOD, BOR1, and BOR2 conditions and may be attributed to pile “setup”. The bias associated with the Energy Approach method EOD predictions ranged between 0.54 and 1.58 (mx = 0.96, σx = 0.32).

Performance evaluation and risk assessment Comparison to NCHRP 507 Pile Databases The nominal resistance (Rn) predictions obtained from the static and dynamic analyses at the New Haven pile load test program were directly compared to the results obtained from the pile databases that were used to develop the LRFD recommendations presented in NCHRP Report 507 (Paikowsky, 2004). The mean bias (λ) and standard deviation (σx) were calculated for each of the predictive methods and are presented in Table 8 in comparison with values obtained from the comparable NCHRP 507 databases. Statistics for the MT piles were excluded as it pertains to two cases only.

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Table 8. Summary of Comparisons Between the Analyzed Pile Load Tests and NCHRP 507 Pile Databases

Pile Load Test Areas A and B –Static Analyses NCHRP 507 Databases Pile

Type Analysis Method pf1 pf2 n λR σx pf1 pf2 n λR σx β-method/Thurman 0.61 0.14 6% 0% 80 0.81 0.31 α-API/Nord/Thurman 5% 3% 80 0.87 0.42 PPC α-Tom/Nord/Thurman

0% 0% 4

0.57 0.15 3% 0% 33 0.96 0.47

β-method/Thurman 0% 0.41 0.09 10% 7% 29 0.54 0.26

α-API/Nord/Thurman 20% 9% 9% 32 0.80 0.36 PP α-Tom/Nord/Thurman 0%

0% 5

0.45 0.14 23%

15%

13 0.74 0.44

Pile Load Test Areas A Through D – Dynamic Analyses NCHRP 507 Databases Pile Type Analysis Method/Time pf1 pf2 n λR σx pf1 pf2 n λR σx All CAPWAP-EOD(1) 13 1.26 0.31 0% 0% 37 2.59 2.38 All CAPWAP-EOD

0% 9 1.37 0.41 1% 0% 125 1.63 0.80

All Energy Approach-EOD 5% 22 0.96 0.33 3% 0% 128 1.08 0.43

All CAPWAP-BOR1 0% 22 1.14 0.32 4% 0% 162 1.16 0.39 All CAPWAP-BOR2 9%

0%

22 0.94 0.23 4% 0% 162 1.16 0.39 pf1 – probability of failure (not considering γw) pf2 – probability of failure (considering γw) n – number of cases

λR – mean bias or bias factor σx – standard deviation (1) – BC < 16 BP10cm & AR < 350

Systematic trend of overprediction of the static methods exists in all data. The mean bias of all the static analyses combinations for areas A and B are lower than the mean bias obtained from the NCHRP Report 507 pile databases but are always within one standard deviation. These observations suggest site specific conditions for which the static analyses are systematically overpredicting the actual capacity by a higher margin than the typical site. This can be attributed to the sensitive Glacio-Delatic soils for which high resistance exists during penetration and hence in-situ testing indicates higher strength than the one actually existing in the steady state condition. The data in Table 8 indicates that the mean bias for all of the dynamic prediction methods while compared well with the mean bias obtained from the NCHRP 507 pile databases is also consistently lower. In particular the CAPWAP EOD for the thirteen piles that satisfy the blow count (BC) and area ratio (AR) special criteria. These observations can be equally explained by the Glacio-Delatic soils’ behavior. Overall, the Energy Approach method EOD and CAPWAP BOR2 yielded the most accurate nominal resistance predictions for the specific site and the original database.

Resistance Factor Evaluation – Local Calibration The static analysis methods/combinations when applied to the New Haven site, had overpredicted the nominal measured (SLT) resistance by an average

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ratio of two (3 to 3.7 for pile B-5). Attributed to the overestimation of the glacio-deltaic strength one can conclude that local calibration of LRFD parameters (i.e., resistance factors) should be considered to accommodate geographically soil specific conditions. As such, site/project specific resistance factors were developed using the FOSM for its simplicity and adequacy for local calibration as suggested in the NCHRP report 507. The FOSM equation based on Barker et al. (1991) is presented along with the relevant parameters:

})]1)(1ln[(exp{

)1()1(

222

2

22

QLQDRTQLL

DQD

R

QLQDL

L

DDR

COVCOVCOVQ

Q

COVCOVCOV

QQ

+++

+

+

++

+

=βλ

λ

γγλ

φ

(1)

Where: λR = resistance bias factor COVR = coefficient of variation of the resistance COVQD = coefficient of variation of the dead load (COVQD = 0.1) COVQL = coefficient of variation of the live load (COVQL = 0.2) βT = target reliability index (βT = 2.33 for redundant case) γD, γL = dead and live load factors (γD = 1.25, γL = 1.75) QD/QL = dead load to live load ratio (assumed 3) λQD, λQL = dead and live load bias factors (λQD = 1.05, λQL = 1.15) Site/project resistance factors were also developed for the dynamic prediction methods. The resulting site specific resistance factors are presented in Table 9 along with those recommended by NCHRP Report 507.

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Table 9. Summary of Resistance Factors

Resistance Factor Development and Comparison Local Calibration - FORM NCHRP 507

Pile

Type Analysis Method/Time λR COVR φ λR COVR φ

β-method/Thurman 0.61 0.27 0.37 0.81 0.38 0.40 α-API/Nord/Thurman 0.87 0.48 0.35 PPC α-Tom/Nord/Thurman

0.57 0.26 0.33 0.96 0.49 0.40

β-method/Thurman 0.41 0.21 0.26 0.54 0.48 0.25 α-API/Nord/Thurman 0.80 0.45 0.35

Stat

ic

PP α-Tom/Nord/Thurman

0.45 0.31 0.23 0.74 0.59 0.25

All CAPWAP-EOD(1) 1.26 0.25 0.74 2.59 0.92 0.40 All CAPWAP-EOD 1.37 0.30 0.73 1.63 0.49 0.65

All Energy Approach-EOD 0.96 0.34 0.47 1.08 0.40 0.55

All CAPWAP-BOR1 1.14 0.28 0.63 1.16 0.34 0.65 Dyn

amic

All CAPWAP-BOR2 0.94 0.25 0.56 1.16 0.34 0.65 COVR – Coefficient of variation of the

resistance (1) – BC < 16 BP10cm & AR < 350

λR – mean bias/bias factor φ - Resistance factor

The New Haven project site specific resistance factor values presented in Table 9 are overall in line with those prepared based on the national databases. For the design stage/static analyses, the NCHRP 507 resistance factors are in one case, 1.52 times those calculated for the New Haven site. When considering the fact that FORM (by which the NCHRP 507 values were calculated) provides on the average, resistance factors approximately 1.15 times those obtained via FOSM, the above ratio actually becomes only 1.32. The variation can be explained by the extreme overprediction of the pipe piles in area B, (see Table 8). For the construction phase/dynamic analyses case, the NCHRP 507 resistance factors are between 0.54 and 1.17 times (0.62 to 1.35 considering the variation between FORM and FOSM) those calculated for the New Haven site. The major difference exists in one group of predictions related to EOD cases of large soil displacements. Risk evaluation

The unique characteristics of the local Glacio-Deltaic soil deposits in the New Haven pile testing sites, resulted with significant over prediction of pile capacities even for methods that traditionally under predict pile capacity (e.g.

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CAPWAP BOR2, see Table 9). In examining the broad application of the proposed resistance factors one need therefore to address the issue of the risk associated with the use of the recommended specifications for such site. The probability of failure was evaluated directly from the case histories by applying the recommended resistance factors (NCHRP 507) to the relevant pile capacity estimation and examining if it exceeds the nominal measured resistance, hence constitutes “failure”. The total number of the “failure” cases was then divided by the total number of cases to constitute the probability of failure (Pf). The results of this procedure to the data of the New Haven site and the NCHRP 507 databases are presented in Table 8 at the columns marked by Pf1. In contrast with the WSD practice where the factored geotechnical resistance is measured against the unfactored design load, the factored resistance using LRFD is measured against a factored load. The correct evaluation of the probability of failure needs therefore to consider the nominal resistance increased by the load factors. Using the values exhibited along equation 1, this weighted load factor is 1.34. The reevaluation of the risk considering the load factors is presented in Table 8 under the columns marked by Pf2.

Using the recommended resistance factors for all the capacity evaluation methods during the design and construction stages at the New Haven site resulted with a Pf = 0% when considering the load factors. The fact that the probability of failure is not zero when not accounting for the load factors and includes “failure” of two cases out of 5 for the pipe piles static evaluation suggests that the zero probability of failure is not associated with an extra over design and the factors were prudently assigned. In the case of the original databases a probability of failure varying between 3% to 15% exists. This high actual probability of failure vs. the designated one of 1% for redundant piles (associated with a target reliability of 2.33) is a result of the use of small databases in the specific cases (e.g. 13 cases of Pipe Piles in mixed soils analyzed by the α-Tomlinson/Nordland/Thurman combination of methods) and indicate on the limitations of calibrations based on small number of case histories. For the construction stage analyses where vast databases exist, all cases resulted with a probability of failure of zero when taking into consideration the load factors. Conclusions

1. Comprehensive LRFD factors for deep foundations are proposed in NCHRP Report 507. These factors are based on the controlling parameters of the design and construction methods and databases allowing to evaluate

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the actual performance of the different capacity prediction methods; both in design and construction.

2. The NCHRP study calibrated a “complete” design methodology including

soil parameter correlations. The use of the recommended resistance factors is associated therefore with a specific design methodology for the static evaluation (design stage) and category; (e.g. time and blow count for applying dynamic analyses and site variability for static load tests) during the construction stage.

3. When developing resistance factors based on actual databases and

consistent level of reliability, one faces the difficulty of comparisons with factors in existing codes as their source is often questionable to begin with. Such evaluations are possible against case histories which were not included in the original databases.

4. The New Haven pile load testing program provides an extensive number of

case histories. The test sites contain problematic soils known to cause short term high resistance to driving which affects soil strength parameters’ interpretation and dynamic pile resistance during driving. As a result, static capacity predictions were found to be unusually higher than the actual (nominal) resistance and dynamic capacity predictions, lower than usual when compared to the capacity measured in a static load test.

5. Using the proposed resistance factors of NCHRP Report 507, resulted with

safe resistance loads for design based on static analyses. These loads were however marginal for a specific pile type (pipe piles) which suggests; a) justification for local calibration of specific soil type/pile type combinations and b) need for expansion of databases as the original databases of the problematic cases were relatively small.

6. Using the proposed resistance factors of NCHRP Report 507, resulted with

safe resistance loads based on dynamic analyses for all case histories. The predictions of the signal matching analysis (CAPWAP) at EOD though significantly under predicts the long term capacity (bias of 1.26) had shown better performance than that at the original database. The energy approach at the EOD and the signal matching at BOR2 have provided the best systematic predictions, similarly to what was obtained at the NCHRP study.

7. Local calibration using FOSM resulted with site specific resistance factors

that overall were very similar to those proposed based on the original extensive databases in spite of the special soil condition at the site. In two

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pile type/analysis type cases the resistance factors were noticeable different. For the pipe piles in static analysis, the local resistance factors provided larger safety. For CAPWAP EOD under easy driving condition, the local resistance factor would have resulted in a more prudent design.

Acknowledgements

Interest in the ConnDOT case study was stimulated by discussions and information initially provided by Mr. John Regan, P.E., geotechnical engineer with GZA of Norwood, Massachusetts. The authors also greatly appreciate the cooperation and support provided by Mr. Leo Fontaine, P.E., Principal Geotechnical Engineer with the ConnDOT, who provided most of the relevant reports and data and endured the everlasting requests for more information. The contributors to NCHRP Report 507 are also acknowledged for their work, in particular, Dr. Gregory Baecher of the University of Maryland who developed the recommendations for static load tests. The authors would also like to acknowledge the efforts of Mr. Richard Mechaber, P.G. of the New Hampshire DOT, and Ms. Mary Canniff of the University of Massachusetts Lowell for her assistance in putting this manuscript together. References

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