# Performance of Assessment

# Chapter 7

Performance of Assessment

7.1 ANALYZING OF INSTRUMENT MONITORING DATA

7.2 INTERPRETATION FROM IN-SITU TESTS

7.4 BACK ANALYSIS

7.5 FACTORS AFFECTING ASSESSMENT OF DEGREE OF CONSOLIDATION

In every soil improvement project carried out to eliminate the future settlement, certain degree of consolidation equivalent to the load of ll and future load or surcharge load is specified. Degree of consolidation usually aims is 90% related to specified load since the time required to reach 100% consolidation is much more longer than that required for 90%. Additional load equivalent to future load and to compensate short fall of load equivalent to remaining 10% of consolidation is usually put as surcharge. As such degree of consolidation is deemed necessary to assess before removal of surcharge.

Assessment of degree of consolidation can be carried out by analyzing instrument monitoring data, interpretation from in-situ tests, and analyzing of laboratory data.

## 7.1 ANALYZING OF INSTRUMENT MONITORING DATA

Of the three different methods of assessment, instrument monitoring can be carried out at regular intervals. The degree of improvement can be monitored and assessed throughout the project period. Two simple instruments that can assess the degree of consolidation are settlement plates and piezometers. The assessment of the degree of consolidation using instrument monitoring data was widely discussed by Bo et al. (1997a).

### 7.1.1 Settlement Gauges

The average degree of consolidation can be determined simply on the basis of settlement. The average degree of consolidation at a given time ‘t’ after loading is defined as the percentage of magnitude of settlement that was observed at time ‘t’ upon the estimated or calculated ultimate primary consolidation settlement.

where *S*_{t} is settlement at time t, *S*αis ultimate primary consolidation settlement and Ū(%) is the degree of consolidation. For embankments built on soft clay, the prediction of magnitude and rate of settlement are made in advance from the design parameters of pre-investigation boreholes. From measured settlement and predicted ultimate settlement, the degree of consolidation can be estimated from Eq. (7.1).

More accurate prediction of ultimate settlement from field monitoring data can be done by analyzing settlement monitoring data. Sridharan and Sreepada (1981) suggested that the hyperbolic method can be used for predicting ultimate settlement. Tan (1993) reported that the hyperbolic method is valid to predict ultimate settlement for soil improvement with vertical drains if the correct slope factor related to drain ratio and thickness is used. Asaoka (1978) proposed a settlement prediction method by using settlement monitoring data and curve fitting.

As the ultimate settlement can be well predicted after getting sufficient field settlement monitoring record, the average degree of consolidation of the compressible layer can be readily calculated from Eq. (7.1). A comparison of assessment of degree of consolidation

Table 7.1 Comparison of degree of consolidation | |||

Asaoka | Hyperbolic | Using laboratory data prediction | |

Ultimate settlement | 3.0 m | 3.005 | 3.005 |

Settlement to date | 2.404 m | 2.404 | 2.404 |

Degree of consolidation | 80.1% | 80.0% | 80% |

for one particular study area in Changi East, Singapore, by using measured and predicted ultimate settlements from different methods are shown in Table 7.1. The determination of ultimate settlements for the same study area by hyperbolic and Asaoka methods are shown in Fig. 7.1. It can be seen that the assessments of degree of consolidation are very close for the different methods used if the correct time interval is selected in the Asaoka method and sufficient duration of data available and the correct slope factor are used in the hyperbolic method. If deep multilevel settlement gauges are installed in the sublayers, the degree of consolidation of sublayers can also be estimated by applying the same methods. The degree of consolidation of sublayers assessed from deep settlement gauges are shown in Fig. 7.2.

**7.1.2** Piezometers

Piezometers are used to measure the pore pressure in the soil. If regular monitoring is carried out to measure the piezometric head together with static water level, dissipation of excess pore pressure can be detected, and thus the degree of consolidation can be assessed. Average residual excess pore pressure is defined as the ratio of excess pore pressure at time ‘t’ upon initial excess pore pressure. Therefore, the degree of consolidation can be defined as follows:

where *u*_{t} is the excess pore pressure at time t and u_{i} is the initial excess pore pressure which is equal to additional load (∆σ).

If piezometers are installed at different elevations, the average degree of consolidation for the whole compressible unit as well as the average degree of consolidation of the sublayers can be determined. The instruments monitoring data are shown in Fig. 7.3. The degree of consolidation assessed from piezometer and deep settlement gauges are compared in Fig. 7.2, and it was found that their assessed degrees of consolidation are in good agreement, although the settlement data predict a slightly higher degree of consolidation.

## 7.2 INTERPRETATION FROM IN-SITU TESTS

The degree of improvement of soil can be detected by in-situ testing. In every embankment project, the duration of preloading period is

set in advance on the basis of the predetermined time rate of consolidation of compressible layer. If prediction is accurately made, the required degree of consolidation will be met at the predetermined preloading time. Therefore at a time close to the surcharge removal, in-situ tests can be carried out to assess the degree of consolidation. Details of site investigation practice including various in-situ tests can be found in Bo and Choa (2000).

### 7.2.1 Cone Penetration Test (CPT)

Cone penetrometer test (CPT) is a very useful in-situ testing equipment in land reclamation projects. It can be used for profiling and characterizing soil. It is also a very useful tool for measuring soil improvement. Various applications of CPT in land reclamation projects were widely discussed by Bo and Choa in 2001. When CPT cone is penetrated into soft soil, excess pore pressure will be generated owing to the penetration. However, if the cone is held at the same elevation for a long time, pore pressure will dissipate until it reaches the equilibrium pore pressure. This equilibrium pore pressure will be the same as the pore pressure in the soil at the time of testing. With this measured equilibrium pore pressure from CPTU, a counter check can be done for piezometer reading, and the degree of consolidation can again be estimated by using Eq. (7.2). Fig. 7.4 shows that the pore pressure measured in the piezometers agrees quite well with that measured by long-term CPTU holding tests.

Campanella and Robertson (1988) had stated that the undrained shear strength c_{u} can be estimated from the corrected cone resistance q_{T}, total overburden pressure σ_{vo} and cone factor N_{KT}.

*N*_{KT} can be an empirical or semi-empirical cone factor and is related to plastic index. Bo et al. (1997a, 1998a and 2000a) had established the following empirical correlation for Singapore marine clays.

If a compressible layer is fully consolidated under additional surcharge load, it becomes normally consolidated with current over-burden pressure. Therefore, normalized shear strength ratio of compressible layer can be expressed as mentioned by Skempton (1954).

where is effective vertical stress. Improvement of shear strength can therefore be compared with undrained shear strength calculated from CPT and the expected improved shear strength values calculated using Eq. (7.5).

In addition, Noriaki Sugawara (1988) proposed that the overconsolidation ratio (OCR) can be computed from the corrected cone resistance and the total and effective overburden pressure as follows:

where *K* is constant and varies between 2.5 and 5.0.

Bo *et al*. (1997a and 1998a) had proposed a similar equation for estimating OCR as follows:

where an α value of 0.32 has been recommended for the Singapore marine clay.

If compressible soil is fully consolidated with the present surcharge load, the overconsolidation ratio of soil will achieve unity with the current surcharge load. Therefore, the improvement of soil can be assessed by whether it is close to the OCR of unity with current load or not.

### 7.2.2 Field Vane Shear Test (FVT)

Field vane shear test can be carried out before surcharge removal. Measured undrained eld vane shear strength can be compared with the specified undrained shear strength. Mayne and Mitchelle (1988) suggested that OCR can be estimated from undrained shear strength and plasticity index using the following relationship:

Bo *et al*. (1998a) had proposed the following equation for OCR prediction from FVT.

It can therefore be assessed whether the improved soil has attained an OCR close to unity with the existing applied load. Determining the stress history of Singapore marine clay from the field vane test was discussed by Bo et al. (2002)

### 7.2.3 Dilatometer Test (DMT)

Marchetti (1980) proposed to correlate the undrained shear strength c_{u} with the horizontal stress index *K*_{d}:

where *K*_{d} is the material index that is defined as follows:

where *P*_{0} is the A reading from dilatometer, is vertical effective stress and *u*_{0} is pre-inserting water pressure.

Bo *et al*. (1997a, 1998a, 2000a) had proposed exponential power values as 1 for upper and intermediate clays and 0.7 for lower Singapore marine clay instead of 1.25 for Eq. 7.10. Undrained shear strength calculated from dilatometer test can be compared with the expected undrained strength and the improvement can be assessed. Marchetti (1980) also proposed the following correlation for the estimation of OCR for clay from dilatometer test.

Bo *et al*. (1997a, 1998a) again had proposed power values as 1 for upper and lower Singapore marine clay and 0.8 for intermediate clay. With OCR values worked out from the dilatometer tests, one can assess the degree of improvement of compressible soil.

### 7.2.4 Self-Boring Pressuremeter Test

Windle and Worth (1977) suggested that undrained shear strength can be estimated from the limit pressure measured in the self-boring pressuremeter test.

or

where *P*_{L} is limit pressure, σ_{ho} is total horizontal stress, G is shear modulus, and *N*_{p} is the pressuremeter constant by Marsland and Randolph (1977). Range of *N*_{p} is suggested to be between 5.5 and6.8. Bo et al. (1997a, 1998a–2000a) had proposed *N*_{p} values for upper, lower and intermediate clay as 6.6, 7.2 and 6.4, respectively.

Estimation of shear modulus can be obtained from small unload– reload cycles. Undrained shear strength calculated from self-boring pressuremeter modulus can be compared with specied undrained shear strength. The improvement can then be assessed. Since the total stress can be measured from self-boring pressuremeter, the coefficient of earth pressure at rest can be calculated, and OCR can then be estimated from Eq. (7.17) based on Bo et al. (1997a, 1998a).

where is effective lateral stress and *K*_{0} is coefficient of earth pressure at rest.

where *h* is a constant between 0.32 and 0.4. It can be seen in Fig. 7.5 that the improved shear strength values calculated from various *in-situ* tests after surcharge period are quite agreeable with each other and close to the expected shear strength. Bo *et**al*. (1997a, 1998a) had proposed another way of calculating OCR from SBPT test with the following equation:

A comparison of OCR interpreted from various *in-situ* tests is shown in Fig. 7.6.

### 7.3 ANALYZING OF LABORATORY DATA

From the boreholes carried out prior to reclamation, the consolidation and shear strength of soft clay can be characterized. From the void ratio versus log effective stress curve, the expected void ratio after soil improvement can be predicted. Expected postimprovement effective stress can also be easily worked out from the following equation:

where ∆σis the additional preloading pressure after taking into account the submergence effect and settlement. U is the degree of consolidation in fraction of unity.

Undrained shear strength related to nal load can also be estimated the same way as in Eq. (7.5). Postinvestigation boreholes with continuous sampling can be carried out at a designated time close to the surcharge removal period. From the laboratory results of collected sample, improvement can be assessed. Void ratio after improvement can be compared with prior to reclamation and with expected values. The degree of consolidation can be worked out from measured void ratio and undrained strength. A conventional way to assess the degree of consolidation is to determine the preconsolidation yield stress from oedometer tests. From the preconsolidation yield stress, the degree of consolidation can be worked out by using the following equation.

where is the yield stress obtained from improved sample; is the overburden pressure before surcharging.

The comparative laboratory results from pre- and post-investigation boreholes are shown in Fig. 7.7. However, there are quite a large number of methods to determine the preconsolidation pressure from oedometer tests, such as Casagrande (1936) method, Janbu (1969) method, Butterfield (1979) method, and Sridharan et al. (1991) method. Among the methods the resulting values can differ by 10–15%.

Sridharan *et al*. (1991) stated that the method he had proposed can accurately determine the preconsolidation pressure. However, the accurate determination of preconsolidation pressure is still under question. The preconsolidation pressure can differ owing to the method of interpretation and some other complexities such as the salt content, strain rate, and temperature. The details regarding variation of preconsolidation pressure determined from various types of tests and various interpretation methods were discussed in Bo et al. (1998b). Despite this, the average degree of consolidation can still be roughly estimated. The preconsolidation pressures determined from various methods are shown in Fig. 7.8. The comparison of degree of consolidation assessed from void ratio and yield stress and undrained shear strengths is shown in Fig. 7.9.

## 7.4 BACK ANALYSIS

Predicting the magnitude and time rate of settlement plays a major role in the design of soil improvement projects with prefabricated vertical drains and surcharge. The accurate prediction of the magnitude and time rate of settlement is dependent on the selection of soil parameters and the engineer’s judgement. In most cases, the time rate of settlement is far from the predicted rate of settlement, although the soil parameters are obtained from controlled laboratory tests.

So engineers have to verify the performance of the soil by using soil instrument monitoring methods during consolidation as well as postsoil investigation boreholes in order to be able to correctly assess the degree of consolidation, make necessary adjustments, and arrive at precise judgements for future designs.

### 7.4.1 Back Analysis of Compression Parameters

Back analysis is generally carried out to verify the compression and consolidation parameters of soil. By using piezometer and settlement monitoring data, the void ratio change versus the effective stress change curve for each subsoil layer can be generated. From these actual field curves, field parameters such as compression index,

recompression index, and yield stress values can be interpreted. The void ratio versus effective stress curves for various sublayers from a particular test location are shown in Fig. 7.10. A comparison between the design parameter and the back-calculated parameters are shown in Table 7.2. It can be seen that the parameters used in the design stage are quite similar to the field parameters back analyzed from field performance. Therefore, in this case the field magnitude of settlements is very close to the predicted settlements.

Table 7.2 Comparison of design and back-analyzed parameters (after Bo et al. 1997b). | ||||||

Elevation | C_{c} | C_{r} | P_{c} | |||

(mCD) | Laboratory | Field | Laboratory | Field | Laboratory | Field |

−7.50 | 1.00 | 0.875 | 0.13 | 41.30 | <40 | |

−12.85 | 1.00 | 1.133 | 0.13 | 0.590 | 93.90 | 90.00 |

−17.40 | 0.25 | 0.343 | 0.10 | 0.030 | 272.90 | 133.70 |

−23.55 | 0.80 | 0.551 | 0.17 | 0.018 | 235.50 | 181.60 |

### 7.4.2 Back Analysis of Coefficient of Consolidation

#### 7.4.2.1 Back analysis from piezometer monitoring data

From field pore pressure or settlement monitoring data, the coefficient of consolidation due to horizontal flow can be calculated. Firstly, the degree of consolidation at any time step can be estimated using Eq. 7.2. After that the nondimensional time factor *T*_{h} can be calculated using the following equation:

where U_{h} is the degree of consolidation due to horizontal flow (in the calculation of the degree of consolidation due to vertical flow, *U*_{v} can be neglected) *T*_{h} is the nondimensional time factor of consolidation due to horizontal flow.

where n = the drain spacing ratio = (d_{e}/d_{w}); d_{e} = 1.05 × spacing for triangular pattern, 1.128 × spacing for square pattern;

*a* and *b* = width and thickness of drain.

*c*_{h} can be calculated using the total time method or the incremental time method. (Bromwell and Lambe, 1968)

Total time method

Incremental time method

#### 7.4.2.2 Back analysis from settlement monitoring data

As in pore pressure analysis, the average degree of consolidation can be simply computed from settlement monitoring data as explained in an earlier chapter. The nondimensional time factor also can be computed. *c*_{h} values can be computed by using the total time method

or the incremental time method as explained earlier. Another way of back calculating *c*_{h} values is the curve fitting method. *c*_{h} value can be found by matching with the time rate of settlement curve predicted with the help of Finite Element Method software (e.g., SAGE CRISP, 1995) for various *c*_{h} values. An example of curve matching is shown in Fig. 7.11. *c*_{h} value can also be back calculated from the settlement data by using the Asaoka (1978) method. From the slope and intercept of the best t line of Asaoka plot β_{1} value can be obtained as shown in Fig. 7.12. From these values *c*_{h} can be calculated as shown in Figure.

It should be noted that back-analyzed *c*_{h} values are usually lower than those measured from in-situ and laboratory owing to the smear effect caused by penetration. The comparison of *c*_{h} values from various measurements and back calculated from field monitoring data are shown in Fig. 7.13. It can be seen that the back analysis *c*_{h} values are found to be the lowest.

## 7.5 FACTORS AFFECTING ASSESSMENT OF DEGREE OF CONSOLIDATION

Assessing the degree of consolidation (DOC) of soil during consolidation is essential for checking the performance of vertical drains and the extent of improvement. A proper field instrumentation and monitoring scheme is normally required for assessing the degree of consolidation. The degree of consolidation can be assessed using either the settlement or the pore water pressure data. However, the result of assessment can be significantly affected by factors such as the prediction of the final settlement and the initial excess pore pressure. Factors affecting the assessment of degree of consolidation were discussed by Bo et al. (1999b).

### 7.5.1 Assessment Using Settlement Monitoring Data

DOC can be assessed using the rate of settlement which could be computed from the settlement monitoring data. To assess the DOC from settlement monitoring data, the important value to be estimated is the magnitude of ultimate settlement. Although the

ultimate settlement can be predicted using laboratory data, the predicted settlement can be far from the actual measured settlement as reported by Duncan (1993). Kobbaj *et a*l. (1998) and Abedi *et al*. (1992) are among those who have reported the underestimation of predicted final settlement using laboratory data. One reason is that the one-dimensional consolidation model is an oversimplification of the field conditions. Even though better models can be used, there may be uncertainties in soil parameter determination. In addition, the accuracy of predicted ultimate settlement is highly dependent on the accuracy of the two main parameters such as compression index (C_{c}) and the preconsolidation pressure . The preconsolidation pressure measured in the laboratory can vary with the types of test such as 24-hours loading, EOP, constant rate of loading, and constant rate of strain.

In the field, two methods are commonly used for predicting the ultimate settlement using monitoring data. One is proposed by Asaoka (1978), and the other is the hyperbolic method [Sridharan and Sreepada (1981), validated by Tan et al. (1991) and Tan (1993)]. With these methods, reliable and close prediction of ultimate settlement becomes possible although some factors affect the prediction while using these methods. A test area (Fig. 7.14) was analyzed applying both Asaoka and the hyperbolic methods in order to see the factors affecting the assessment of degree of consolidation using this method.

#### 7.5.1.1 Asaoka method

The Asaoka method is easy to use in principle; however, the predicted ultimate settlement is affected by the selected time interval. The longer the time interval, the lower the predicted ultimate settlement as shown in Table 7.3 for numbers of location at the Changi reclamation project. A similar finding was reported by Saaidin Abu Bakar in 1992. So the assessed degree of consolidation at a certain period can be varied depending on the predicted final settlement (Table 7.4 and Figs. 7.15 and 7.16).

Table 7.3 Comparison of ultimate settlements predicted using various time intervals with Asaoka method | |||

Location | 14 days(cm) | 21 days(cm) | 28 days(cm) |

A2S-071 | 192.75 | 189.2 | 188.19 |

A2S-072 | 149.36 | 145 | 142.94 |

A2S-073 | 131.33 | 135.5 | 121.83 |

DS-444 | 210.5 | 185.94 | 179.9 |

DS-457 | 123.17 | 118.44 | 116.35 |

Table 7.4 Variation of degree of consolidation at certain time due to variation of predicted ultimate settlement with Asaoka method (A2S-071) | ||||

Time interval | 1.5 yrs time | 2.0yrs time | 2.5 yrs time | 3.0yrs time |

14 days | 58.1 | 69.05 | 76.32 | 81.24 |

21 days | 59.19 | 70.34 | 77.75 | 82.77 |

28 days | 59.51 | 70.73 | 78.17 | 83.25 |

#### 7.5.1.2 Hyperbolic method

As explained by Tan et al. (1991), the ultimate settlement of homogeneous compressible layer can be predicted if the settlement has exceeded 60% of the final settlement. Tan (1993) has updated the prediction of ultimate settlement by applying the hyperbolic method for soil improvement projects that use vertical drains. In his proposal, slope factors are required to be used depending on the spacing of drain and depth of drain. However, the slope of the hyperbolic plot changes with time and thus the ultimate settlement predicted will increase with time as shown in Table 7.5, and Fig. 7.17. As such, the calculated degree of consolidation at a particular time will change with the duration of data available. The later the prediction of final settlement is carried out, the lower will be the degree of consolidation at a certain period (Table 7.6 and Fig. 7.18).

It can be seen that ultimate settlements predicted from the Asaoka method are higher than those from the hyperbolic method. It can be due to shorter selected intervals of time in the Asaoka

Table 7.5 Comparison of ultimate settlement predicted from various duration of data with hyperbolic method. | ||||

Location | 1.5 years data(cm) | 2.0years data(cm) | 2.5 years data(cm) | 3.0years data(cm) |

A2S-071 | 172.01 | 174.26 | 176.59 | 179.00 |

A2S-072 | 132.78 | 135.74 | – | – |

A2S-073 | 101.354 | 111.67 | 107.77 | 112.56 |

DS-444 | 164.46 | 166.79 | 169.20 | 169.20 |

DS-457 | 98.19 | 101.98 | 101.98 | 110.94 |

Table 7.6 Variation of degree of consolidation at certain time due to variation of predicted ultimate settlement with hyperbolic method (A2S-071) | ||||

Based on | 1.5 years time | 2.0years time | 2.5 years time | 3.0years time |

1.5 years data | 65.11 | 77.38 | 85.52 | 91.04 |

2.0years data | 64.27 | 76.38 | 84.41 | 89.86 |

2.5 years data | 63.42 | 75.37 | 83.30 | 88.68 |

3.0years data | 62.57 | 74.36 | 82.18 | 87.49 |

method. Asaoka also suggested that a longer interval would give higher accuracy and also a lower ultimate settlement. Therefore, it seems that the Asaoka method requires longer duration of monitoring to be able to select the longer time interval. The variation of settlements in three plots shown in Table 7.3 is due to slight variation of soil profile and variation of spacings. Normally, closer spacing yields higher final settlement even in the same soil condition and profile.

### 7.5.2 Assessment Using Piezometer Data

Piezometer, combined with water standpipe which measures the hydrostatic water level, provides excess pore pressure data. The degree of consolidation at a certain time can be predicted if the initial excess pore pressure is known. If piezometers are installed in the offshore condition before reclamation, initial excess pore pressure can be picked up during monitoring because the initial static pore pressure is known. Otherwise, the initial excess pore pressure is required to be calculated from the assumed bulk density of the ll material by applying the Skempton (1954) or Henkel (1960) method. It is common to assume the bulk density of 17–18 kN/m^{3} for the granular sand. In reality, the bulk density of sand can vary from 15–19 kN/m^{3} depending on the method of placement, as shown in Fig. 7.19. Therefore, the calculated excess pore pressure based on the assumed bulk density of ll material can lead to overestimation of the excess pore pressure for land ll case and underestimation for hydraulic filling. To closely measure the additional load, total earth pressure cells can be installed to monitor the initial load as well as the load changes during the consolidation period.

Another method of monitoring the applied load is by measuring bulk density, using the Gamma probe from time to time. Fig. 7.20 shows a comparison of the surcharge load calculated using the assumed bulk density and the measured from a total pressure cell. Generally, the pressure measured from the total pressure cell is higher. The increase of total pressure shown in Fig. 7.20is due to the rising of water level, which makes the soil moist. Although total pressure

increases, effective pressure will decrease owing to the submergence effect.

Although initial excess pore pressure can be estimated from applied additional load, it will again vary from in-situ measured pore pressure after loading for some cases where clay layer is underlain by hydrogeologic boundary. This phenomenon was explained in Chapter 6. In such cases, the profile of pore pressure after additional load

can be lower than that calculated, assuming that the initial pore pressure is static pressure (γ_{w}*h*). As such, overestimation of degree of consolidation will be made if the initial lower pore pressure is not taken into consideration. This sort of situation will be encountered where clay layer is underlain by water aquifer which is being extracted for water supply.

#### 7.5.2.1 Settlement of piezometer tip

Piezometers are installed at certain positions in the soil. The tip of the piezometer will settle together with the surrounding soil. On the one hand, the piezometric head will reduce with the dissipation of pore pressure; on the other hand, the piezometric head will increase due to settlement of the piezometer tip. If the settlement of piezometer tip is not corrected in calculation of excess pore pressure, the degree of consolidation will be underestimated because higher pore pressure is registering due to settled piezometer tip. This problem

was reported by Bo et al. (1998c). The comparison of corrected and uncorrected piezometric elevation is shown in Fig. 7.21.

#### 7.5.2.2 Reduction of load due to submergence and groundwater level rising

For the reclamation land, soil seldom gains the effective stress equivalent to the initial imposed load. This is due to the following factors. The first is the reduction of load due to sinking of ll below the groundwater level and another is the rise in groundwater level due to seasonal recharge. This behavior was also noticed by Mesri and Choi (1985). Therefore, the degree of consolidation based on the initial imposed load is likely to be underestimated because the available effective additional load at assessed time is much smaller than the initial load. The reduction of effective additional load due to submergence effect is shown in Fig. 7.22, and the comparison of degree of consolidations under conditions with and without considering those effects is shown in Table 7.7.

Table 7.7 Comparison of degree of consolidation with and without taking into account the reduction of additional load | |||||

Locations | 1 year | 1.5 years | 2 years | 2.5 years | 3.5 years |

A2S-071 | 60.3(71.2) | 70.3(76.8) | 72.5(79.9) | 73.2(81.5) | 80.4(84.8) |

A2S-072 | 68.8(72.5) | 71.1(74.4) | 73.0(75.3) | 82.5(82.5) | 81.2(78.9) |

A2S-073 | 54.3(62.4) | 61.3(66.4) | 61.7(66.9) | 70.3(72.2) | 75.1(73.2) |

Table 7.8 Comparison of degree of consolidation assessed from settlement and pore pressure at 2.5 years. | |||

A2S-071 | A2S-072 | A2S-073 | |

Hyperbolic | 82.18 | 86.34 | 74.42 |

Asaoka | 78.17 | 83.6 | 74.16 |

Pore pressure | 73.3 | 82.5 | 72.20 |

### 7.5.3 Discrepancy Between Degree of Consolidation Assessed from Pore Pressure and Settlement

After making necessary corrections to obtain a reliable degree of consolidation, there are still discrepancies between the values calculated from pore pressure and settlement. It is known that the degree of consolidation assessed from pore pressure is normally lower than that assessed from the settlement. Table 7.8 shows the comparison of the degree of consolidation assessed from settlement, and pore pressure for study area. Hyperbolic and Asaoka methods were used in assessing ultimate settlement, and the isochrone method was used in assessing the average degree of consolidation using pore pressure distribution.

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**Performance of Assessment**