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Thesis Powerpoint

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Thesis Powerpoint

  1. 1. Neha Verma Graduate Student Civil Engineering Program Louisiana Tech University 1
  2. 2.  Objectives of the research  Problem definition  Scope of work  Methodology  Result Analysis  Conclusion  Recommendation 2
  3. 3.  Identify the conditions where pile setup may be incorporated in pile design.  Determine the reliability associated with pile setup prediction by LRFD implementation.  Determine resistance factors based on pile setup. 3
  4. 4.  Load and resistance factor design (LRFD) is a rational approach.  Load uncertainties, incorporated by load factors.  Resistance factors account for the uncertainties associated with material properties. 4
  5. 5.  LRFD accounts for variability in both resistance and load.  Achieves more uniform levels of safety based on strength of soil, design methods and foundation types.  Provides more consistent design and level of safety in the superstructure and substructure.  Implemented to geotechnical structures, but never to pile-setup. 5
  6. 6.  Piles driven in soft soils undergo increase in axial capacity with time known as “pile setup” or “freeze”.  Phenomenon was discovered long back in 1955 by Reese and Seed. 6
  7. 7.  During pile installation soil around pile displaced outward and exposed to large strains.  Excessive pore pressure is generated in soil, results in temporary reduction strength of soil.  Excessive pore pressure begins to dissipate and soil gains strength, hence pile capacity increases. 7 Illustration of pile setup phenomenon
  8. 8.  Numerous cases from the history and local field test data in showed pile setup.  The test data on driven piles at LA-1 relocation project indicates 30- 100 % growth in pile capacity . 8 Increase of pile capacity with time based on field data (Vesic, 1977)
  9. 9.  Expenditure on construction of pile foundation reaches millions of dollars every year (LADOTD).  The current design based on the 14 day pile resistance after the initial driving.  No incorporation of long term pile capacity increase, due to no recommendations. 9
  10. 10.  The accuracy and efficiency of different pile setup prediction methods can be determined.  The resistance factors (Ф) based on pile setup can be useful for future research and guidelines.  Incorporation of pile setup, cost effective design of pile foundation: a) Reducing length of pile. b) Varying cross-section of pile. c) Choice in using heavy or light driving equipment. 10
  11. 11.  The load data for the production pile is from phase 1-B of LA-1 relocation project in Leeville, Louisiana.  Construction of a 4-mile long high-level bridge with connecting ramps and interchanges.  The substructure of the project comprises of 16", 24", & 30" prestressed concrete (PSC) piles. 11
  12. 12. Summary of restrike records  A total of 115 restrike records on 95 piles.  63 records short term restrike less 50 hrs EOD.  21 long-term records of more than two weeks. 12
  13. 13. Load testing summary for nine test piles at LA-1 relocation project (LADOTD)  Location of test piles represent the soil  The test piles were monitored during driving by PDA (Pile Driving Analyzer)  Analyzed using CAPWAP software (Case Pile Wave Analysis Program) . 13
  14. 14. 14 Pile Pile Type Restrike Date Time (Hrs) Penetration Length (ft) Soil Type Rskin (kips) Rtip (kips) Rult (kips) NC44-07 16" SQ. PPC 10/2/2006 24 81.37 Major clay with sand 110 43 153 NC40-04 16" SQ. PPC 10/11/2006 24 81.92 Major clay with sand 208 17 225 NC36-04 16" SQ. PPC 10/21/2006 24 77.08 Major clay with sand 231 29 260 NC33-04 16" SQ. PPC 10/26/2006 24 71.44 Major clay with sand 294 17 310 NC29-02 24" SQ. PPC 1/20/2007 744 114.31 Major clay with sand 353 70 422 NC29-02 24" SQ. PPC 3/2/2007 1728 114.31 Major clay with sand 451 59 510 NC29-03 24" SQ. PPC 12/21/2006 24 114.31 Major clay with sand 213 82 294 NC29-03 24" SQ. PPC 12/27/2006 144 114.31 Major clay with sand 271 69 340 NC29-03 24" SQ. PPC 1/17/2007 672 114.31 Major clay with sand 433 72 505 NC29-03 24" SQ. PPC 3/2/2007 1728 114.31 Major clay with sand 450 70 520 : : : : : : : : : : : : : : : : : : : : : : : : : : : Information for NC site (LADOTD)
  15. 15. 0 100 200 300 400 500 600 700 0 200 400 600 800 1000 1200 1400 1600 1800 2000 Rult(kips) Time EOD (HRS) NC-Rult vs EOD Pile NC1B-03 Pile NC02-03 Pile NC06-02 Pile NC10-03 Pile NC18-03 Pile NC22-03 Pile NC24-03 Pile NC14-03 Pille NC25-02 Pile NC26-03 Pile NC28-03 Pile NC29-03 Pile NC33-04 Pile NC36-04 Pile NC40-04 Pile NC44-07 Pile NC48-05 Pile NC52-05 Pile NC56-05 Pile NC59-06 Pile NC60-05 Pile NC64-05 Pile NC66-06 Pile NC68-02 Pile NC72-05 Pile NC75-05 15 Total capacity variation with time from the restrikes at North Connector site
  16. 16. 16 0 200 400 600 800 1000 1200 0 100 200 300 400 500 600 700 Rult Time EOD (Hrs) SC-Rult vs EOD Pile SC02-02 Pile SC05-02 Pile SC10-02 Pile SC13-02 Pile SC17-03 Pile SC21-03 Pile SC25-02 Pile SC29-03 Pile SC33-03 Pile SC37-03 Pile SC41-03 Pile SC45-02 Pile SC49-02 Pile SC52-03 Pile SC54-03 Pile SC56-02 Pile SC59-03 Pile SC61-04 Total capacity variation with time from the restrikes at South Connector site
  17. 17. 17 0 200 400 600 800 1000 1200 0 1000 2000 3000 4000 5000 6000 Rult(Kips) Time EOD (Hrs) Mainline S-Rult Vs EOD Pile 20S-02 Pile 23S-02 Pile 27S-03 Pile 31S-03 Pile 34S-02 Pile 37S-03 Pile 40S-01,04 Pile 41S-03 Pile 53S-02 Pile 58S-03 Pile 61S-03 Pile 64S-01 Pile 65S-03 Pile 69S-03 Pile 73S-02 Pile 78S-03 Total capacity variation with time from the restrikes at Mainline-S site
  18. 18. 0 50 100 150 200 250 300 350 400 450 500 0 500 1000 1500 2000 Rult(Kips) Time EOD (Hrs) Ramp N1-Rult Vs EOD Pile N1- 02 Pile N1- 05 Pile N1- 09 Pile N1- 12 Pile N1- 14 Pile N1- 17 18 Total capacity variation with time from the restrikes at Ramp-N1 site
  19. 19.  The LA-1 relocation project site is dominated by clay along with silts and sand traces.  The mudline is about 1-3 feet below the water table.  The liquidity indexes 20 and 40, depth of 70 feet.  Compressive strengths from the unconsolidated undrained tests 0.1 to 0.5 tsf (tons square feet). 19
  20. 20. 20 Typical boring log data (LADOTD)
  21. 21. 21 Typical CPT log data (LADOTD)
  22. 22.  Empirical Equations. 1. Skov-Denver method. 2. Rate-based method.  Static pile capacity methods. 1. LCPC method (CPT based). 2. Schmertmann method (CPT based). 3. de-Ruiter and Beringen method (CPT based). 4. α-method (Total stress Based). 22
  23. 23.  Semi-logarithmic relation between pile capacity and time proposed by Skov and Denver (1988):  where A (0.5-0.7 LA clayey soils) is a dimensionless setup factor and based on soil type.  Q and Q0 can either be the total or the shaft pile capacity (setup) at time t and t0. Q(ult) = Q(t) (predicted skin friction) + T(t0) (measured tip resistance at the reference time) 23
  24. 24.  Developed from the combined restrike data of all the production piles of the LA-1 Relocation project;  S(t) = Skin Friction at time t;  S(t0) = Measured Skin Friction at time (t0=24 hrs);  t = time elapsed since the end of initial driving; and  t0 = Reference time i.e. 24 hrs. Q(t) = S(t) (predicted skin friction) + T(t0) (measured tip resistance at the reference time) 24
  25. 25. 25 Setup prediction for 25 hrs-7 day by Rate-based method REFERENCE PILE INFORMATION PREDICTION RATE-BASED Pile Time (Hrs) Pile Name Ref Skin Friction (S0) (Tons) Tip Resistance (tons) at (t = 24Hrs) Ref Time (t0)(Hrs) Skin Friction (Tons) Total Capacity (Tons) NC66-06 120 NC68-02 70 7.5 24 100 107 NC64-05 98 NC68-02 70 7.5 24 94 101 NC60-05 43 NC68-02 70 7.5 24 77 84 NC59-06 25 NC68-02 70 7.5 24 70 78 NC52-05 27 NC44-07 55 21.5 24 56 77 NC48-05 42 NC44-07 55 21.5 24 60 81 NC29-03 144 NC29-03 106.3 40.85 24 160 200 NC28-03 148 NC29-03 106.3 40.85 24 161 202 NC26-03 46 NC29-03 106.3 40.85 24 118 159 NC25-02 46 NC29-03 106.3 40.85 24 118 159 : : : : : : : : : : : : : : : : : : : : : : : :
  26. 26.  Proposed by Bustamante and Gianeselli (1982), based on pile type, soil type and pile cone tip elevation; or where, ks1=30-150 (pile type,soil type and installation process); kb1 = 0.15-0.60 (installation procedure and soil type); qeq = equivalent average cone friction (qc); As = pile-soil surface area; and At = pile toe area. 26
  27. 27.  Proposed by Schmertmann (1978) Shaft resistance in soil: Ultimate pile toe resistance: Ultimate pile capacity is given as: Where, K is the ratio of unit pile shaft resistance to unit cone sleeve friction and function of penetration depth; b is pile width; D is pile penetration length; qc1 is minimum of the averages of qc values from 0.7 to 4D below the pile tip; qc2 is average of minimum qc values 8D above the pile cone tip 27
  28. 28.  Proposed by de-Ruiter and Beringen (1979) Ultimate pile capacity: or where, α is 1 for normally consolidated clay, 0.5 OC; Su = qca/Nk ; qca = average qc value over a specified zone method; Nk = 15 to 20; Nc = 9; As = pile-soil surface area; and At = pile toe area. 28
  29. 29.  Also known as Tomlinson method, based on undrained soil shear strength parameters. Ultimate capacity: or where, α is the empirical adhesion factor based on the reduction of average undrained shear strength cu; Nc is a dimensionless bearing factor, the pile diameter and length of the pile, taken as 9 for deep foundation. 29
  30. 30. 1. Louisiana Pile Design and Cone penetration Test (LPD-CPT). 2. DRIVEN 1.2. 30
  31. 31.  LTRC, the load capacity/analyzing driven precast concrete piles.  Schmertmann, de-Ruiter and Beringen method and LCPC method.  Input data in order of depth, tip resistance and sleeve resistance.  Pile data information.  Output results: plots of CPT data, soil classification plot and variation of bearing capacity plot. 31
  32. 32. Plot of CPT data Plot of soil classification 32
  33. 33. 33 Variation of ultimate capacity based on three CPT methods
  34. 34. 34 Mainline-S segment based on de-Ruiter and Beringen method. Pile Name Pile Type Penetration Length (ft.) Test Data Used End Bearing Capacity (tons) Pile Shaft Capacity (tons) Ultimate Bearing Capacity (tons) 20S-02 24" SQ. PPC 81.01 CPT-366 28 104 132 23S-02 24" SQ. PPC 83.15 CPT-55 85 155 240 27S-03 24" SQ. PPC 83.15 CPT-55 85 155 240 31S-03 24" SQ. PPC 90.41 CPT 55b 95 195 290 34S-02 24" SQ. PPC 89.84 CPT 380 60 180 240 37S-03 30" SQ. PPC 144.84 CPT-57 640 420 1060 40S-02 30" SQ. PPC 72.74 CPT-387 360 140 500 41S-03 30" SQ. PPC 75.57 CPT-387 290 150 440 45S-03 30" SQ. PPC 161.58 CPT-392 260 430 690 47S-03 30" SQ. PPC 157.58 CPT-392 260 430 690 : : : : : : : : : : : : : : : : : : : : :
  35. 35.  FHWA and new version of the SPILE program.  Tomlinson (α-method), Nordlund, Thurman, Meyerhof, Cheney and Chassie.  Input parameters: unit weight, undrained shear strength, SPT N value and pile infomation.  DRIVEN 1.2 presents the output in graphical and theoretical form. 35
  36. 36. 36 Sample soil classification plot based on DRIVEN 1.2 program
  37. 37. 37 Variation of bearing capacity based on DRIVEN 1.2 program
  38. 38. 38 Mainline-S segment based on α- method α- method Prediction Pile Name Pile Size Penetration Length (ft.) Boring Log Used Rtip (tons) Rskin (tons) Rult (tons) 20S-02 24" SQ. PPC 81.01 B-54 135.54 76.71 212.25 23S-02 24" SQ. PPC 83.15 B-55B 10.8 176.33 187.13 27S-03 24" SQ. PPC 83.15 B-55B 10.8 176.33 187.13 31S-03 24" SQ. PPC 90.41 B-56 7.02 139.215 146.235 34S-02 24" SQ. PPC 89.84 B-56 7.02 136.765 143.785 37S-03 30" SQ. PPC 144.84 B-56 25.03 421.57 446.6 40S-02 30" SQ. PPC 72.74 B-58 9 161.72 170.72 41S-03 30" SQ. PPC 75.57 B-58 9 166.25 175.25 : : : : : : : : : : : : : : : : : : : : :
  39. 39.  To estimate the reliability associated with the pile setup predictions by different methods.  Calibration of LRFD has been performed. 39
  40. 40.  Calibration is the process of assigning values to resistance factors and load factors.  In the present work, LRFD components are determined based on reliability theory.  The level I probabilistic method, Mean-Value-First- Order-Second-Moment method (MVFOSM). 40
  41. 41.  Statistical parameters are determined using the measured and predicted capacity predictions, which are prerequisites for determining resistance factors. λRi is the bias factor: Rm is the measured resistance; and Rn is the predicted or nominal resistance.  Statistical uncertainties mean, standard deviation and coefficient of the variance. 41
  42. 42. λR is average resistance bias factor: σR is the resistance standard deviation: COVR is the resistance coefficient of the variance: where , N is the number of cases. 42
  43. 43. 43 Bias factor based on rate-based method for 14 days and above prediction Measured Capacity Predicted Capacity Bais Factor (λ) Pile Time (Hrs) Rskin (Tons) Rult (Tons) Rskin (Tons) Rult (Tons) Skin Friction (λ) Total Capacity (λ) NC29-02 744 176.4 211.2 271.1 279.3 0.651 0.756 NC29-02 1728 225.7 255.1 196.2 237.1 1.150 1.076 NC29-03 672 216.5 252.5 196.1 236.9 1.104 1.066 NC29-03 1728 225.1 260.1 196.2 237.1 1.147 1.097 NC28-02 218 166.7 200.0 178.0 218.8 0.936 0.914 NC14-03 644 214.5 265.0 329.2 364.7 0.652 0.727 NC10-03 285 195.5 228.0 127.5 165.0 1.533 1.382 NC10-03 323 233.0 268.0 129.6 167.1 1.798 1.604 SC54-03 648 369.4 475.0 318.1 413.1 1.161 1.150 : : : : : : : : : : : : : : : : : : : : : : : :
  44. 44.  To determine RF, latest AASHTO LRFD Specifications (Paikowsky et al. 2004) are adopted for load statics and load factor to make the pile foundation design consistent with the bridge super structure design.  In the present work, the reliability analysis is performed for a factor of safety equal to 2.5.  As per specified in the AASHTO LRFD Specifications the live load factor (γL) and dead load factor (γD) are taken as 1.75 and 1.25, respectively.  Four reliability indices are selected 2, 2.5, 3, and 2.33; which are corresponding to four different dead load to live load ratios i.e., QD/QL = 1, 2, 3 and 4. 44
  45. 45. Where, COVQD coefficients of variation for the dead load = 0.1; COVQL coefficients of variation for the live load = 0.2; λQD is the bias factor for the dead load = 1.15; λQL is the bias factor for the live load = 1.05; and COVR is the coefficients of variation of resistance (R). 45
  46. 46.  The axial design capacity of pile may be presented as:  In the future, pile foundation can be designed by using the resistance factors, ϕ, based on pile setup, and nominal resistance (Rn) of the pile. 46 𝑃𝐷𝑒𝑠𝑖𝑔𝑛 = 𝜙𝑅 𝑛
  47. 47.  The reliability analyses performed based on different elapsed times.  Skov-Denver and rate-based method, first interval: 25 hours to 7 days (1 week) after the end of driving and second interval: 7 days to 14 days (2 weeks) and more after the end of driving.  For static pile capacity methods, first interval: 48 hours after the end of driving, second interval : after 48 hours to 7days (1 week), and third interval: at 14 days (2 weeks) and more. 47
  48. 48.  Summary of statistical analysis.  Summary of resistance factors. 48
  49. 49. 49 Summary of statistical analysis for ultimate capacity
  50. 50. 50 Summary of resistance factors for skin friction
  51. 51. 51 Summary of resistance factors for ultimate capacity
  52. 52.  The values of the statistical parameters were different for different methods and different elapsed time.  Also values of the resistance factors are different for all the methods; therefore, different resistance factors must be used for different elapsed times.  No much difference was found between resistance factors of skin friction and ultimate capacity. It implies that tip resistance does not play significant role.  Resistance factors based on the static pile capacity method showed prominent variations for different time intervals. 52
  53. 53.  A Large volume of long-term restrike or long-waiting load testing data is required in order to improve the accuracy and reliability of the prediction model.  Implementation of LRFD on accurate setup predictions will generate more reliable factors. Therefore, attention must be paid to get the long-term data through dynamic monitoring and static and statnamic load testing. 53
  54. 54. 54

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