analisi e progettazione delle...

Università degli Studi Roma La SapienzaUniversità degli Studi di Napoli Federico IISeconda Università degli Studi di NapoliUniversità degli Studi di SalernoUniversità degli Studi di Napoli ParthenopeUniversità degli Studi del Sannio

Dottorato di Ricerca in Ingegneria Geotecnica

ANALISI E PROGETTAZIONE DELLE FONDAZIONIANALISI E PROGETTAZIONE DELLE FONDAZIONIStruttura del corsoStruttura del corso

10.30 – 12.00 12.30 – 13.30 15.00 – 17.30

Giovedì07.02.08

Lezione 1Criteri generali di progettazione

Lezione 2Quadro normativo di riferimento

Lezione 3Fondazioni superficiali (1)

Giovedì14.02.08

Lezione 4Fondazioni superficiali (2)

Lezione 5Pali soggetti a carico assiale

Esercitazione 1Fondazioni soggette a carichi verticali

Giovedì21.02.08

Lezione 6Sperimentazione su pali (1)

Lezione 7Sperimentazione su pali (2)

Esercitazione 2Pali soggetti a carichi trasversali

Giovedì28.02.08

Lezione 8Effetti di gruppo (Rigidezza)

Lezione 9Effetti di gruppo (Resistenza)

Esercitazione 3Gruppi di pali

Giovedì06.03.08

Lezione 10Fondazioni miste ‘platee su pali’

Lezione 11Ottimo progettuale

VERIFICA FINALE

Analisi e progettazione delle fondazioniAversa, febbraio-marzo 2008

Alessandro MandoliniSeconda Università di Napoli

Katzenbach et al., 2000:

“a new understanding of soil-structure interaction is required if the contribution of both the raft and the piles has to be taken into account for achieving an optimum design”



OPTIMUM DESIGN

Russo & Viggiani (1998), de Sanctis et al. (2002):“a design achieving maximum economy of the solution while keeping a satisfactory behaviour”

Cost

Settl

emen

t, St

ress

+

+

1

2



OPTIMUM DESIGN (curve 1 – case 1)

Cost

Settl

emen

t, St

ress

+

+

sadm

Does a solution exist in order to satisfy a given criteria ?

YES




Cost

Settl

emen

t, St

ress

+

+

sadm s∞


NO




Cost

Settl

emen

t, St

ress

+

+

s∞sadm


YES,But too costly

A change in the design may be

needed



OTHER EFFECTS OF TIME FOR PILE FOUNDATIONSCHANGE OF LOAD DISTRIBUTION AMONG PILES

Cable-stayed bridge over Garigliano River (Mandolini et al., 2005)

105 VW load cells on piles24 VW load cells at raft-soil contactOptical survey for settlement

w = 48 mmw ≈ 50 mm

αpr = 0,85

measured calculated

0,00

0,25

0,50

0,75

1,00

0 40 80 120number of piles, n

pr [-

]

Mandolini et al. (1997)

αpr ≈ 0,80

020406080

100120140

0 40 80 120

number of piles, n

wPR

[mm

]


144 piles

NAPRA (Russo, 1996)“plate on springs” approach(raft by FE, elastic raft-soil interaction,piles by NL springs)



αpr = 0,85 / 0,81

w = 48 / 56 mmw ≈ 50 mmmeasured calculated

0,00

0,25

0,50

0,75

1,00


pr [-

]


αpr ≈ 0,80

020406080

100120140

0 40 80 120

number of piles, n

wPR

[mm

]


144 piles

NAPRA (Russo, 1996)“plate on springs” approach(raft by FE, elastic raft-soil interaction,piles by NL springs)

55 piles



0,00

0,25

0,50

0,75

1,00


pr [-

]


PDR

144 piles144 piles, L = 48 m ⇒ nL ≈ 7000 m55 piles, L = 48 m ⇒ nL ≈ 2600 m

(60% SAVINGS !!!)

55 piles

0,00

0,25

0,50

0,75

1,00

0 40 80 120

number of piles, n

wPR

/ w

R [-

]


PDR






Cost

Settl

emen

t, St

ress

+

+

sadm = smin


YESWell defined




Cost

Settl

emen

t, St

ress

+

+sadm


YES(on the left)




Cost

Settl

emen

t, St

ress

+

+

sadm


NOIrrespective of

the costs

a) change of the solution

b) renouncing to satisfy criteria

smin



Differential settlementreducing piles

Optimizing criteria

0

20

40

60

80

100

0.0 0.2 0.4 0.6 0.8 1.0

w/w

r (%

)

L/B = 0.4, Krs = 0.01

0

20

40

60

80

100

0.0 0.2 0.4 0.6 0.8 1.0

n = 9

n = 25

n = 49

n = 81

n = 121

n = 169

n = 225

L/B = 0.4, Krs = 0.10

0

20

40

60

80

100

0.0 0.2 0.4 0.6 0.8 1.0

w/w

r (%

)

L/B = 0.7, Krs = 0.010

20

40

60

80

100

0.0 0.2 0.4 0.6 0.8 1.0

n = 9

n = 25

n = 49

n = 81

n = 121

n = 169

n = 225

L/B = 0.7, Krs = 0.10

0

20

40

60

80

100

0.0 0.2 0.4 0.6 0.8 1.0

w/w

r (%

)

L/B = 1.0, Krs = 0.01

Ag/A

0

20

40

60

80

100

0.0 0.2 0.4 0.6 0.8 1.0

n = 9

n = 25

n = 49

n = 81

n = 121

n = 169

n = 225

L/B = 1.0, Krs = 0.10

Ag/A

VIGGIANI, 2001




Optimizing criteria

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

1.20

0 2000 4000 6000 8000 10000

s/d = 3; L/B = 0,4s/d = 4,5; L/B = 0,4s/d = 6; L/B = 0,4s/d = 7,5; L/B = 0,4s/d = 9; L/B = 0,4s/d = 12; L/B = 0,4s/d = 15; L/B = 0,4s/d = 3; L/B = 0,7s/d = 4,5; L/B = 0,7s/d = 6,0; L/B = 0,7s/d = 7,5; L/B = 0,7s/d = 9; L/B = 0,7s/d = 12; L/B = 0,7s/d = 15; L/B = 0,7s/d = 3; L/B = 1s/d = 4,5; L/B = 1s/d = 6; L/B = 1s/d = 7,5; L/B = 1s/d = 9; L/B = 1s/d = 12; L/B = 1s/d = 15; L/B = 1

d/ d

r

Krs = 0,01

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

0 2000 4000 6000 8000 10000

s/d = 3; L/B = 0,4s/d = 4,5; L/B = 0,4s/d = 6; L/B = 0,4s/d = 7,5; L/B = 0,4s/d = 9; L/B = 0,4s/d = 12; L/B = 0,4s/d = 15; L/B = 0,4s/d = 3; L/B = 0,7s/d = 4,5; L/B = 0,7s/d = 6; L/B = 0,7s/d = 7,5; L/B = 0,7s/d = 9; L/B = 0,7s/d = 12; L/B = 0,7s/d = 15; L/B = 0,7s/d = 3; L/B = 1s/d = 4,5; L/B = 1s/d = 6; L/B = 1s/d = 7,5; L/B = 1s/d = 9; L/B = 1s/d = 12; L/B = 1s/d = 15; L/B = 1

d/ d

r

nL [m]

Krs = 0,10

rww

∆∆

rww

∆∆VIGGIANI, 2001




Optimizing criteriaVIGGIANI, 2001

- More effective for increasing L/B






- A minimum value for Ag/A exists






- A minimum value for Ag/A exists

- Beyond such minimum, the addition of piles can be detrimental





Target: ∆w/wR = 0,15

L/B = 0,4 not possible

MANDOLINI & VIGGIANI, 1997

B/L ∼ 2,5

An example of large structure

GOOSSENS & VAN IMPE, 199140 grain silos in Ghent (Belgium)

Raft: 34x84 m2; thickness 1,2 m697 driven piles: L = 13,4 m; d = 0,52 m; db = 0,80 m






Optimizing criteria

Target: ∆w/wR = 0,15

L/B = 0,4 not possible

L/B = 0,7 → 81 piles L = 31,5 mAg/A = 0,28; n•L = 2552 m

L/B = 1,0 → 30 piles L = 45 mAg/A = 0,10; n•L = 1350 m

50% SAVINGS !!!

VIGGIANI, 2001



40.00 m 47.10 m

32.7

0 m

Tower U Tower A

Y3

Y2

benchmark for optical survey

86.5

0 m

Application to full scale tall building(Mandolini & Viggiani, 1992)

Centro Direzionale di NapoliHoliday Inn + Torre Uffici

2 towers H = 86,5 m

2 independent rafts: 40mx32,7m



40.00 m 47.10 m

32.7

0 m

Tower U Tower A

Y3

Y2


86.5

0 m


q = Q/(BxL) = 0,16 MPa

qlim = 0,5 x Fγ x Nγ x γ x B ∼ 1,7 MPa

FS > 10



40.00 m 47.10 m

32.7

0 m

Tower U Tower A

Y3

Y2


86.5

0 m


637 piles CFA d = 0,6 m; L = 20 m

Qlim,S = 2,2 MNFSP = 2,5 (D.M. 11.03.1988, αPR = 1)QS = 0,9 MN



40.00 m 47.10 m

32.7

0 m

Tower U Tower A

Y3

Y2


86.5

0 m

0

10

20

30

40

50

60

0 10 20 30 40

distance across the slab [m]

settl

emen

t [m

m]

alignment Y2

alignment Y3

computed, piled raft

computed, unpiled raft


637 piles CFA d = 0,6 m; L = 20 m



40.00 m 47.10 m

32.7

0 m

Tower U Tower A

Y3

Y2


86.5

0 m

DSDB (de Sanctis et al., 2002)

318 piles CFA d = 0,6 m; L = 20 m

1.60

m

1.0 0

m

2.4 0

m

42.25 m

16.3

5 m

Ag/A = 0.30, s/d ≈ 3

distributed loadAg

concentrated loads

Using 318 piles “well located” :

w ∼ + 10%∆w ∼ - 25%



40.00 m 47.10 m

32.7

0 m

Tower U Tower A

Y3

Y2


86.5

0 m

DSDB (de Sanctis et al., 2002)

318 piles CFA d = 0,6 m; L = 20 m

1.60

m

1.0 0

m

2.4 0

m

42.25 m

16.3

5 m

Ag/A = 0.30, s/d ≈ 3

distributed loadAg

concentrated loads

nL ≅ 12700 mnL ≅ 6300 m

50% SAVINGS !!!

Raft (αpr = 0)FSR > 8

Static loadwR = 90-100 mm

Cyclic loadwR = 150-180 mm

10

Slightly silty sand

20

25 m

Made ground

5.25 m

100 20 60

N30 40 50

z [

m ]

Silty sand

SPT

30 m

0Cq [MPa]

3010 20

SPT1

SPT2

SPT3

CPT1

CPT2

B = 8,00 m

10A10

B = 6,97 m

C = 380 mcH = 10,03 m

C = 588 mcH = 11,93 m

12S1

B=12,00 m

C = 1700 mcH = 15,00 m

9

B = 6,97 m

C = 380 mcH = 10,05 m

8

B = 7,95 m

C = 495 mcH = 10,06 m

14

C = 1200 mc

B=10,00 mH = 15,00 m

B=9,90 m

C = 800 mcH = 10,25 m

10

B=9,90 m

64 8

C = 800 mcH = 10,23 m

S3

CPT1

11

S2

CPT

CPT2

C = 1320 mc

D=10,60 mH = 15,00 m

Bore holes, SPT

6 7

2

2

H = 12,08 mB = 8,01 m

C = 608 mc

54

3

B = 8,01 m

H = 12,08 mB = 8,01 m

C = 608 mc

C = 608 mcH = 12,08 m

Length (m)

H = 12,08 mB = 8,01 m

C = 608 mc

C = 1200 mcH = 15,00 mB=10,00 m

13



Steel tanks for the storage of sodium hydroxide - Napoli

D = 10-12 mH = 15 mV = 1200-1700 m3

γsodium = 15 kN/m3

P =18-25,5 MN



Steel tanks for the storage of sodium hydroxide - Napoli

10.511.1 12.5

11 13 1214

10.5

2 4 6 8 10

Lenght (m)

Lenght (m)

2 4 6 8 10

10.511.1 10.5

12141311

12.5

Conventional CB design – 128 CFA piles d = 0,6 m, L = 11,3 m

αpr = 1FSp = 2,5w = 11-13 mm

Innovative SB design – 52 CFA piles d = 0,6 m, L = 11,3 m

αpr = 0,6FSp = 1,5wmax = 35 mmDwmax = 20 mm

60% SAVINGS

Katzenbach et al., 2000: Tall buildings, Frankfurt, Germany

Piled rafts designed with the aim to:(a) Reduce settlements (avg., diff.) as well as tilting(b) Reduce stresses in the raft(c) Minimize interaction with existing buildings



Building DF [m]

Q [MN]

w [cm]

αpr [-]

Messe-Thoraus -3 400 15,0 0,80 Messeturm -14 1880 14,4 0,55 DG-Bank -12/-14 1420 11,0 0,50

Japan Centre -15,8 1050 6,0 0,40 Forum -13,5 990/920 8,0 0,35/0,40

Main Tower -21 2000 2,5 0,85 Eurotheum -13 570 3,2 0,30

1,00

1,05

1,10

1,15

1,20

1,25

0,0 0,2 0,4 0,6 0,8 1,0αpr [-]

X=K

PR/K

PG [-

]

0

5000

10000

15000

20000

25000

KPR

[MN

/m]

0,0

0,2

0,4

0,6

0,8

1,0

0 1 2 3 4 5 6R [-]

pr [-

]L

snR ⋅=

±20%

Katzenbach et al., 2000: Tall buildings, Frankfurt, Germany

Piled rafts designed with the aim to:(a) Reduce settlements (avg., diff.) as well as tilting(b) Reduce stresses in the raft(c) Minimize interaction with existing buildings





The variety of possible situationis such that any generalisation is difficult

The availability of simple and reliable methods of analysis makes possible and relatively easy

the search for an optimum solutionin each particular case

Some indications can be given

• In general, the effectiveness of a pile is reduced by the proximity to other piles in terms of both stiffness (RG < 1) and failure load



• Minimise such a negative interaction using few widely spaced piles

• A wider spacing allows the raft to transmit a larger portion of the external load directly to the soil both under working conditions and at failure



• Increasing the number of piles is generally beneficial but does not always produce an optimum solution. There is an upper limit to the useful number of piles beyond which further increase is useless or even detrimental

• To control the average settlement, an optimum performance is achieved by the use of piles with L > B spread below the whole raft area (Ag/A > 80%). This is possible for small and medium rafts, but not for large ones. In the latter case, the average settlement is but slightly reduced by the addition of piles



• To control the differential settlement ∆w, an optimum performance is achieved by suitably locating a relatively small number of piles, rather than using a larger number of piles uniformly spread or increasing the raft thickness.

• The most suited location depends on the distribution of the external loads. In the case of uniform load, the piles are best concentrated in the central zone (20% < Ag/A < 45%). Again, the longer the piles the most effective they are in reducing ∆w

• Thickness of the raft affects bending moments and ∆w, but has little effect on load sharing between raft and piles and on average settlement



• DM 14.01.08 (pubblicato su G.U. del 04.02.2008)Norme Tecniche per le Costruzioni

Resistenza di progetto, Rd ≥ Azioni (o effetto delle azioni) di progetto, Ed

Rd = Rk/γR

M1




CAP. 6 – PROGETTAZIONE GEOTECNICA§ 6.4 – Opere di fondazione§ 6.4.3 – Fondazioni su pali





6.4.3.1 - Verifiche agli stati limite ultimi

da prove di carico di progetto da formulazioni teoriche

RdγR

RdγR





‘piles as settlement reducers’(BURLAND et al., 1977)





‘piles enhancing raft’





‘piles enhancing raft’

Rd = (Rplatea,k + Rpali, k)/γR

Ghent, June 2003 - BAP IV Theme Lecture “Design of piled raft foundations: practice and developments”

CONCLUSIONS

Viggiani (2001): “It appears necessary to develop codes and regulations capable of guiding the designer in the application of innovative design criteria”Poulos (2002): “There is a need to remove perceived constraints of some old-fashioned approaches (codes)”Randolph (2003): “National design codes must adapt to permit highly loaded piles beneath (primarily) raft foundations”

Ghent, June 2003 - BAP IV Theme Lecture “Design of piled raft foundations: practice and developments”

In order to not leave these design options in a drawer, codes and

regulations should change

IT’S TIME TO CHANGE !!

Alessandro Mandolini: Bearing capacity of piled rafts

Randolph (2003): “National design codes must adapt to permit highly loaded piles beneath (primarily) raftfoundations”

“National design codes must adapt (also) to permit highly loaded raftsabove (primarily) pile foundations”




CAP. 7 – NORME PER LE OPERE INTERAGENTI CON I TERRENI E CON LE ROCCE, ….

§ 7.3 – Opere interagenti con i terreni e con le rocce§ 7.3.1 – Fondazioni delle strutture in elevato§ 7.3.1.2 – Fondazioni su pali§ 7.3.1.2.2 - Verifiche in condizioni di esercizio (SLE)

Nel progetto di una fondazione su pali è ammesso l’impiego di pali con funzione di riduzione e regolazione dei cedimenti. In questo caso, il carico limite della fondazione deve essere valutato con riferimento alla sola piastra

DFI 2006 – Risultati di una approfondita indagine

IntroduzioneIntroduzione

Aspetti Aspetti progettualiprogettuali

Condizioni di Condizioni di esercizioesercizio

Condizioni di Condizioni di rotturarottura

Contenuti Contenuti minimi di un minimi di un approccio approccio razionalerazionale

ConclusioniConclusioni

CNRIG 2006 – Alessandro Mandolini

Fondazioni su pali: dalla ricerca alle applicazioniFondazioni su pali: dalla ricerca alle applicazioni

46%

54%

0%

10%

20%

30%

40%

50%

60%

supe

rfici

ali

prof

onde

36%

10%

48%

6%

0%

10%

20%

30%

40%

50%

60%

supe

rfici

ali

supe

rfici

ali s

ute

rreni

trat

tati

su p

ali (

CB

D)

su p

ali (

SBD

)

LA SFIDA CONTINUA !

DE SANCTIS & MANDOLINI, 20060,0

0,2

0,4

0,6

0,8

1,0

0,00 0,10 0,20 0,30 0,40(Ag/A)/(s/d) [-]

αP [-]αP = 1 - 3x(Ag/A)/(s/d)

‘SHIELD’ EFFECT

QPR,lim = QG + αR • QP

αRαR



DE SANCTIS & MANDOLINI, 20060,0

0,2

0,4

0,6

0,8

1,0

0,00 0,10 0,20 0,30 0,40(Ag/A)/(s/d) [-]

αP [-]αP = 1 - 3x(Ag/A)/(s/d)

‘BRAIN’ EFFECT

QPR,lim = QG + αR • QP

αRαR





MORE BRAIN, LESS PILES

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