Geotechnical Predictions Research Articles

Comparison between the measured and the numerically predicted behaviour of an instrumented piled raft

This paper presents the results of numerical predictions for an instrumented piled raft foundation of a tall building in tropical soil. The analysis was performed using 3D finite element analysis and included a comparison of foundation settlements, pile loads, skin friction mobilisation, and raft-soil contact pressure. Initially, the geotechnical model was defined based on field and laboratory test data to conduct a Class A geotechnical prediction. Subsequently, the soil parameters used in the numerical model were re-evaluated to match the measured settlements, aiming for a Class C prediction. The study discusses the main factors that affect the accuracy of the computed settlements, providing valuable insights for foundation designers. Additionally, it highlights the significance of considering the pile-soil-pile and raft-soil-pile interactions in the design of the piles beneath the raft, as these interactions impact the mobilisation of the pile skin friction at different depths.

Geotechnical Predictions in Soft Ground Using Mechanised Shield Tunnelling

Geotechnical Predictions in Soft Ground Using Mechanised Shield Tunnelling

Effect of Geological Uncertainty on the Shaft Resistance Prediction and Reliability of Piles Driven in Multi-Layered Geomaterials

This study proposes a method to quantify the effect of geological uncertainty on the predicted shaft resistance and the reliability of piles driven into multi-layered geomaterials. Several geological predicted surfaces with different levels of geological uncertainties are simulated through multiple sets of boreholes using the multinomial categorical prediction approach for the spatial Markov chain. As the number of strategically placed boreholes increases, the geological uncertainties decrease. Respective ground predicted surfaces are also simulated from these geological predicted surfaces using universal kriging and conditional simulation. The shaft resistances of the piles driven at the site are estimated for the multiple geomaterials layers using geotechnical prediction equations specified for the geomaterial type. The design reliability for the shaft resistance obtained from the various geological, ground, and geotechnical predictions is thereafter accessed through its probability of failure evaluated using the Monte Carlo simulation. This methodology is applied to the Lemhi River bridge project site in Idaho. The results illustrate the influence of geological uncertainty on the design of piles driven into multi-layered geomaterials and further help in determining an optimal site investigation plan that will improve pile design.

Probabilistic back analysis for improved reliability of geotechnical predictions considering parameters uncertainty, model bias, and observation error

The predicted performance of a geotechnical system may deviate from the in situ observation due to the uncertainties in the input geotechnical parameters, solution model, and observation error. A precise characterization of these uncertainties is a significant challenge primarily because of limited data availability. The Bayesian theory provides a means for updating these uncertainties by incorporating prior statistical information and observations. However, conventional Bayesian inference focuses on limited sources of uncertainties. This paper presents a probabilistic back analysis method for improved reliability of subsequent predictions that considers all the uncertainties. Three distinct features of this new method include: (1) multiple observations are incorporated into the Bayesian updating, (2) the statistical information of the uncertain variables is updated in a stage-by-stage manner, and (3) the posterior distributions of uncertain variables are derived with Markov Chain Monte Carlo (MCMC) simulation that is based on the Hamiltonian Monte Carlo (HMC) algorithm. Two case histories, including a braced excavation problem and a tunnel excavation problem, are analyzed to demonstrate the effectiveness of the new method. The advantages of this new back analysis method over the conventional Bayesian updating analyses are documented.

Field assessment of liquefaction prediction models based on geotechnical versus geospatial data, with lessons for each

Semi-empirical models based on in situ geotechnical tests have been the standard-of-practice for predicting soil liquefaction since 1971. More recently, prediction models based on free, readily available data were proposed. These “geospatial” models rely on satellite remote-sensing to infer subsurface traits without in situ tests. Using 15,223 liquefaction case-histories from 24 earthquakes, this study assesses the performance of 23 models based on geotechnical or geospatial data using standardized metrics. Uncertainty due to finite sampling of case-histories is accounted for and used to establish statistical significance. Geotechnical predictions are significantly more efficient on a global scale, yet successive models proposed over the last 20 years show little or no demonstrable improvement. In addition, geospatial models perform equally well for large subsets of the data—a provocative finding given the relative time- and cost-requirements underlying these predictions. Through this performance comparison, lessons for improving each class of model are elucidated in detail.

Geotechnical assessments of plain terrain fortifications in Albania

AbstractThe research includes work on historical buildings, fortifications and cult monuments. Because of its diverse architectural and historical heritages, Albania offers plenty of research opportunities particularly in the repair of the geotechnical structures. A set of geological and geotechnical conditions will be analysed in order to comprehend conditions of two case studies placed in Peqini region. These are of significant importance according to their construction and for the fact that their closed contour foundations are present from the Romans period (in the Peqini castle) and constructed with limestone material brought from an older object (in the Clock Tower). Combination of type of structure and plain terrain geological characteristics are assessed. The goal is to contribute in the geotechnical assessment and revitalization of the case studies selected as objects with value for the community and for the field of geotechnical maintenance. Ultimately, this fosters a better appreciation of the historical heritage in Albania through the understanding of their geotechnical predictions reliability.

Semmering Base Tunnel – Ground characterisation for tendering and construction

AbstractSince the start of construction on contract SBT3.1 in May 2016, all three tunnel construction contracts for the Semmering Base Tunnel are now under construction. From the geological and geotechnical point of view, this represents the transition from the geotechnical prediction for the design for tendering to the documentation in the course of construction. The paper describes the considerations about the systematics of ground characterisation and the definition of ground types in the course of producing the ground prediction for the design for tendering. It also describes the requirements for the documentation of ground conditions encountered during the advance, the updating of the prediction for the daily specification of support measures and the comparison of prediction and actual conditions for contractual purposes.

Design, prediction and monitoring of deep fill settlement

Creep settlement is an important aspect to consider where development is planned over deep compacted fill. This paper presents a case study of an earthworks design for infilling a quarry pit with sandstone and shale derived material and a comparison of predicted and monitored creep settlements. Laboratory testing was carried out during filling to assess the creep characteristics of available infilling materials. Based on the laboratory testing the influence of saturation on creep rates is discussed. Settlement monitoring points across the infilled quarry were monitored for up to 455 days. Predicted creep rates based on the results of the testing are compared with predictions based on monitoring. Monitored settlements within a few years of fill placement were variable and substantially greater than predictions based on the laboratory testing. Longer term monitoring data indicates that settlements are likely to be less than predictions based on laboratory testing. The results suggest that predictions over 30 years based on laboratory testing are conservative and lie within the normal range of accuracy of geotechnical predictions.

Stiffness at small strain: research and practice

This paper provides the background to the 50th Rankine Lecture. It considers the growth in emphasis of the prediction of ground displacements during design in the past two decades of the 20th century, as a result of the lessons learnt from field observations. The historical development of the theory of elasticity is then described, as are the constitutive frameworks within which it has been proposed that geotechnical predictions of deformation should be carried out. Factors affecting the stiffness of soils and weak rocks are reviewed, and the results of a numerical experiment, assessing the impact of a number of stiffness parameters on the displacements around a retaining structure, are described. Some field and laboratory methods of obtaining stiffness parameters are considered and critically discussed, and the paper concludes with a suggested strategy for the measurement and integration of stiffness data, and the developments necessary to improve the existing state of the art.

Bayesian Framework for Characterizing Geotechnical Model Uncertainty

As any model is only an abstraction of the real world, model uncertainty always exists. The magnitude of model uncertainty is important for geotechnical decision making. If model uncertainty is not considered, the geotechnical predictions and hence the decisions based on the geotechnical predictions might be biased. In this study, a framework for characterizing geotechnical model uncertainty using observation data is proposed. The framework is based on the concept of multivariable Bayesian updating, in which the statistics of model uncertainty are updated using observed performance data. Uncertainties in both input parameters and observed data can be considered in the proposed framework. To bypass complex computational works involved in the proposed framework, a practical approximate solution is presented. The proposed framework is illustrated by characterizing the model uncertainty of four limit equilibrium methods for slope stability analysis using quality centrifuge test data. Parametric study in the illustrative example shows that both quality and quantity of the performance data could affect the determination of the model uncertainty, and that such effects can be systematically quantified with the proposed method.

Bayesian Model Calibration Using Geotechnical Centrifuge Tests

The predicted performance using a geotechnical prediction model is expected to deviate from reality. A practical approach to assess the model error is through calibration with observed performances in physical model tests. In this paper, a Bayesian framework of model calibration using centrifuge modeling tests is proposed and the procedure of model calibration is illustrated. Two centrifuge tests conducted to investigate the performance of soil slopes under rainfall conditions are used to calibrate a coupled hydromechanical analysis model. It is found that for centrifuge tests with different levels of soil variability, the test with a smaller variability of soil properties is more efficient for model calibration. According to the concept of random field, a centrifuge model with a larger model size and accelerated to a lower acceleration is better for model calibration. When the discrepancy between the performance interpreted from the centrifuge model and the field performance is small, the improvement of the reliability estimation for a new slope is significant. However, when there is little information about the discrepancy, the reliability estimation cannot be significantly improved by the information from centrifuge modeling. The proposed procedure is shown to be able to quantify the calibration effects of centrifuge tests and may be used to achieve a more reliable calibration.

Geotechnical predictions of the excavation disturbed zone at Stripa : N. Barton, A. Makurat, K. Monsen, G. Vik & L. Tunbridge, Publikasjon - Norges Geotekniske Institutt, 194, 1994, 20 pp; reprinted from: Proc. 4th international symposium on OECD/ NEA/STRIPA Project, Stockholm, October 1992 (OECD Nuclear Energy Agency)

Geotechnical predictions of the excavation disturbed zone at Stripa : N. Barton, A. Makurat, K. Monsen, G. Vik & L. Tunbridge, Publikasjon - Norges Geotekniske Institutt, 194, 1994, 20 pp; reprinted from: Proc. 4th international symposium on OECD/ NEA/STRIPA Project, Stockholm, October 1992 (OECD Nuclear Energy Agency)

Lessons Learned from Missed Predictions

This paper focuses on the broad factors critical to the prediction process that govern the quality of predictions of the geotechnical performance of completed structures. After a discussion of these critical factors, a series of examples is described to show performance that deviated from prediction, and the probable causes of the variances are discussed. Minimal effort is made in the paper to improve the technical aspect of the predictive method. The importance of judgment (i.e. the questioning of each aspect of the prediction process) and intuition in development of geotechnical predictions is emphasized. Some kinds of predictions for which success is expected to be limited are identified. The paper concludes with a brief discussion on the development of good judgment.

Geotechnical predictions in ice affected marine environments: Clark, J I; Jordan, I J Proc International Symposium on Prediction and Performance in Geotechnical Engineering, Calgary, 17–19 June 1987P15–25. Publ Rotterdam: A A Balkema, 1987

Geotechnical predictions in ice affected marine environments: Clark, J I; Jordan, I J Proc International Symposium on Prediction and Performance in Geotechnical Engineering, Calgary, 17–19 June 1987P15–25. Publ Rotterdam: A A Balkema, 1987

Dealing with Risk and Uncertainty in Exploration: How Can We Improve?

Risk and uncertainty are inherent aspects of investing in petroleum exploration ventures. The tasks in serial exploration decision making are to be consistent in dealing with risk and uncertainty, and to perceive uncertainty realistically, reducing it where possible. Many biases exist in the mental processes by which most people make risk decisions. These biases tend to produce significant inconsistencies. Consideration of such behavioral patterns, use of quantified risk-aversion methods, and periodic review of investment decisions all help to optimize risk decision making. Judgments under uncertainty are also susceptible to biases, which commonly influence geologic estimates of (1) prospect target size, (2) discovery probability, and (3) cost of finding. Target-size estimates tend to range widely, and they seem to be accurate only within ± 1 order of magnitude of the actual size of discovered accumulations. Also, target-size forecasts tend to be significantly overoptimistic. Estimates of discovery probability also tend to be overoptimistic, because they commonly do not distinguish between noncommercial and commercial new-field wildcats. In addition, analysis of different geologic risk factors (structure, reservoir, trap, and hydrocarbon charge) may help improve perception of discovery probability, but explorationists commonly do not realize which g ologic factor actually constitutes the primary exploration hazard for a given prospect. Cost-of-finding estimates seem to show the smallest variation in predictive accuracy. Exploratory performance can be improved through constructive postmortem analysis of geotechnical predictions, review of exploration tactics versus declared strategy, and year-to-year comparison of exploration performance parameters. Performance trends can then be used to discount or enhance future prospects, modify corporate stances and procedures, and highlight functions that need improvement. Such analyses and improvements may best take the form of individual professional progress, rather than management-imposed inspection. They constitute a practical, constructive method for internal evaluation and systematic improvement of the exploration function.