Prediction of embankment performance using numerical analyses – Practitioner’s approach

Chan, Kim; Poon, Bosco; Perera, Darshana

doi:10.1016/j.compgeo.2017.07.012

Cited by 8 publications

(9 citation statements)

References 15 publications

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“…This supported the finding reported by Liu et al [42] that pre-overburden pressure (POP) was the most influencing random variable on the predicted settlement during the period of embankment loading. Besides, at the end of filling, the plastic deformation (shear yielding) was the dominant settlement than the consolidation settlement in which the applied load exceeded POP Chan et al [32]. However, beyond 98 days, Class A approach under-predicted the field settlement.…”

Section: Class a Predictionsmentioning

confidence: 91%

“…The work of matching techniques was reported by other authors too [7,27,28]. Kelly et al (2018) and a number of other engineers have reported on the numerical modelling development of a trial embankment built on PVD-improved estuarine soft clay of Ballina, Australia [10,[29][30][31][32][33].…”

Section: Introductionmentioning

confidence: 90%

“…The work of a number of authors on Ballina clay supports this argument. The predictions of settlements were analyzed using PLAXIS 2D by employing SSC material model and incorporating LS mesh update option by Lie et al [42], Josted et al [30], Chan et al [32] and Gong [53]. These studies showed that predicted results were found less than or equal to the field observation values.…”

Section: Probable Limits Of Predicted Settlementsmentioning

confidence: 99%

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Uncertainty Analysis in Prediction of Settlements for Spatial Prefabricated Vertical Drains Improved Soft Soil Sites

2020

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This paper presents the quantification of uncertainties in the prediction of settlements of embankments built on prefabricated vertical drains (PVDs) improved soft soil deposits based on data collected from two well-documented projects, located in Karakore, Ethiopia, and Ballina, Australia. For this purpose, settlement prediction biases and settlement distributions were statistically computed based on analyses conducted on two Class A and Class C numerical predictions made using PLAXIS 2D finite element modelling. From the results of prediction bias, Class C predictions agreed well with the field measured settlements at both sites. In Class C predictions, the computed settlements were biased to the measured values. For Class A predictions, the calculated settlement values were in the range of mean and mean minus 3SD (standard deviations) for Karakore clay, and they were within mean and mean minus 2SD limit for the Ballina soil. The contributing factors to the settlement uncertainties of the Karakore site may include variability within the soil profile of the alluvial deposit, particularly the presence of interbedded granular layer within the soft layers, and the high embankment fills, and the limited number of samples available for laboratory testing. At the Ballina test embankment site, the uncertainties may have been associated with the presence of transitional layers at the bottom of estuarine clay and sensitivity of soft soil to sample disturbances and limitations in representing all the site conditions.

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Section: Class a Predictionsmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 90%

Section: Probable Limits Of Predicted Settlementsmentioning

confidence: 99%

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Uncertainty Analysis in Prediction of Settlements for Spatial Prefabricated Vertical Drains Improved Soft Soil Sites

2020

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“…Among the successful modernizations of this method is combining the use of vertical drains or PVDs. Variation of this method has been successfully applied in many construction projects worldwide requiring ground improvements and reclamation [137]. Therefore, the theory, design, and construction methods for PVDs are significant issues in the preloading or consolidation method.…”

Section: Preloading and Prefabricated Vertical Drainsmentioning

confidence: 99%

A Review of Road Embankment Stability on Soft Ground: Problems and Future Perspective

Mamat

Kasa

Razali

2019

IIUMEJ

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This paper presents an exhaustive review of the challenges faced in the construction of road embankments on soft ground and proposes a direction for future development. Frequently used techniques for soft ground improvement are discussed. The factors that contribute to the stability of the road embankment are reviewed by approach, results of past studies, and historical cases. The findings show that settlement, slope stability, and soil bearing capacity are all challenges to constructing the road embankment. Additionally, it is found that geometric data is a key factor in embankment design. Pre-loading with prefabricated vertical drain (PVDs) methods and lightweight fill were found to be widely used techniques in soft ground improvement. The information from this study can be used to develop design guidance systems, numerical modelling, and to give an overview and knowledge to other researchers who are or will conduct research in this field. Finally, future perspectives for research are related to predictions of factors that affect the stability of road embankment with an artificial intelligence approach. ABSTRAK: Kertas ini membentangkan ulasan kajian menyeluruh mengenai cabaran yang dihadapi dalam pembinaan benteng jalanraya di atas tanah lembut dan mencadangkan ke arah pembangunan kajian masa depan. Teknik-teknik penambahbaikan tanah lembut yang sering digunakan turut dibincangkan. Faktor- faktor yang menyumbang kepada kestabilan benteng jalanraya diulas dengan pendekatan kepada kajian lepas dan sejarah kes. Hasil kajian ini didapati bahawa enapan, kestabilan cerun dan keupayaan galas tanah merupakan cabaran dalam pembinaan benteng jalanraya. Selain itu, ia didapati bahawa data geometri merupakan faktor penting kepada rekabentuk benteng. Kaedah pra pembebanan dengan prefabrikasi saliran menegak (PVDs) dan isian ringan didapati teknik yang popular digunakan dalam pembaikkan tanah lembut masa kini. Maklumat dari kajian ini boleh digunakan untuk membangunkan sistem panduan reka bentuk, pemodelan berangka serta memberi gambaran dan ilmu kepada penyelidik lain yang sedang atau akan menjalankan kajian dalam bidang ini. Akhir sekali, perspektif masa depan untuk penyelidikan berkaitan ramalan faktor-faktor yang mempengaruhi kestabilan embankment jalanraya dengan pendekatan kepintaran buatan.

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“…These measurements are used to compare predicted versus observed calculations for consolidation of the embankment and underlying strata. Field and laboratory based predictions are generally performed by using numerical methods such as onedimensional consolidation, the Terzaghi method and finite element analysis (FEA) [6,7].…”

Section: Introductionmentioning

confidence: 99%

The use of PCA and signal processing techniques for processing time-based construction settlement data of road embankments

Siddiqui

Sargent

Montague

2020

Advanced Engineering Informatics

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Instrumentation is beneficial in civil engineering for monitoring structures during their construction and operation. The data collected can be used to observe real-time response and develop data-driven models for predicting future behaviour. However, a limited number of sensors are usually used for on-site civil engineering construction due to cost restrictions and practicalities. This results in relatively small raw datasets, which often contain errors and anomalies. Interpreting and making judicious use of the available dataset for developing reliable predictive model represents a significant challenge. Therefore, it is essential to pre-process and clean the data for improving their quality. To date, little investigation has been performed in the application of such data cleaning methods to geotechnical engineering datasets collected from full-scale sites. The purpose of this study is to apply simple and effective data pre-processing techniques to site-data collected from a highway embankment constructed on a sequence of soil layers of different physical make-up and non-linear consolidation characteristics. Various cleaning methods were applied to magnetic extensometer data collected for monitoring settlement within foundation soils beneath the embankment. PCA was used to explore raw data, identify and remove outliers. Numerous filtering and smoothing methods were used to clean noise in the data and their results were further compared using RMSE and NMSE. The methods adopted for data pre-processing and cleaning proved very effective for capturing the raw settlement behaviour on site. The findings from this study would be useful to site engineers regarding complex decision-making relating to ground response due to embankment construction. This also has positive prospects for developing dynamic prediction models for embankment settlement.

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Prediction of embankment performance using numerical analyses – Practitioner’s approach

Cited by 8 publications

References 15 publications

Uncertainty Analysis in Prediction of Settlements for Spatial Prefabricated Vertical Drains Improved Soft Soil Sites

Uncertainty Analysis in Prediction of Settlements for Spatial Prefabricated Vertical Drains Improved Soft Soil Sites

A Review of Road Embankment Stability on Soft Ground: Problems and Future Perspective

The use of PCA and signal processing techniques for processing time-based construction settlement data of road embankments

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