C. Hsein Juang

Robust design in geotechnical engineering – an update

This paper presents an update for the robust geotechnical design (RGD) methodology, which seeks an optimal design with respect to design robustness and cost efficiency, while satisfying the safety requirements. In general, the design robustness is achieved if the system response is insensitive to the variation in the uncertain input parameters (called “noise factors”). In other words, a design is considered robust if the system response exhibits little variation, even though there is high variation in the input parameters. Robust design achieves this desirable outcome by carefully adjusting ‘design parameters’ (i.e., the parameters that can be controlled by the designer, such as the geometry and dimensions) without reducing the uncertainty in the noise factors. In this paper, the existing RGD methodology is updated with a gradient-based robustness measure and a simplified procedure for seeking the knee point. The RGD methodology and its simplified version (with new updates) are illustrated with three design examples. The results presented in this paper show that the RGD methodology and its simplified version are effective design tools that considers safety, cost and design robustness simultaneously. The advantages of the simplified RGD approach are discussed.

Efficient robust geotechnical design of drilled shafts in clay using a spreadsheet

Abstract This paper presents an efficient robust geotechnical design (RGD) approach that considers performance requirements, design robustness, and cost efficiency simultaneously. In this paper, design robustness is measured via the variation in the performance function of concern that can be evaluated using reliability analysis. Furthermore, the performance requirements of the system are also evaluated using reliability analysis. Thus, the evaluation of design robustness and the evaluation of performance requirements share common computational steps, referred to herein as computational coupling. This coupling for computational efficiency is a significant feature of the proposed RGD approach. Within the framework of the proposed RGD approach, design robustness, cost efficiency, and performance requirements can be considered simultaneously by means of multiobjective optimization. Furthermore, a practical and efficient procedure is developed for such optimization using a feature resident in a popular spread...

Robust design of rock slopes with multiple failure modes: modeling uncertainty of estimated parameter statistics with fuzzy number

The variability of shear characteristics of rock discontinuities is often difficult to ascertain. Thus, even with the reliability-based design (RBD) approach, which allows for consideration of the uncertainty of input parameters, the design of a rock slope system may be either cost-inefficient (overdesign) or unsafe (under-design), depending on whether the variation of input parameters is overestimated or underestimated. The uncertainty about the variation of input parameters is a critical issue in a RBD. This paper presents a feasible approach to addressing this problem using robust design concept. First, the uncertainty of the estimated statistics of input parameters (such as rock properties) is represented by fuzzy sets, which requires only the knowledge of lower and upper bounds of the estimated statistics. Then, the robust design concept is implemented to ensure that the final design is insensitive to, or robust against, the uncertainty of the estimated statistics of input parameters. The design methodology is demonstrated with an application to the design of a rock slope system with multiple failure modes. This design methodology, termed robust geotechnical design (RGD), aims to achieve a certain level of design robustness, in addition to meeting safety and cost requirements. In this paper, the RGD framework is realized through a multi-objective optimization, as it involves three requirements, safety, cost, and robustness. The significance of the design methodology is demonstrated with an example of rock slope design.

Optimization of site investigation program for improved statistical characterization of geotechnical property based on random field theory

AbstractThis paper presents a framework for optimization of site investigation program, within which the robustness of the site investigation program and the investigation effort are optimized. A site investigation program is judged robust if the derived statistics of the geotechnical property of interest are robust against the uncertainties caused by limited data availability and test error. In this study, a Markov chain Monte Carlo simulation-based Bayesian inference approach was used to characterize the statistics of the intended geotechnical property. The robustness of the site investigation program was formulated as a byproduct of the Bayesian inference of the geotechnical property statistics. The proposed framework for optimization of the site investigation program was implemented as a bi-objective optimization problem that considers both robustness and investigation effort. The concepts of Pareto Front and knee point were employed to aid in making an informed decision regarding selection of site investigation program. The effectiveness and significance of the proposed framework were demonstrated through a simulation study.

CONTRACTOR PREQUALIFICATION USING FUZZY SETS

Abstract Contractor prequalification involves evaluation of factors that contain a high degree of uncertainty. Current methods of contractor prequalification fail to address uncertainty in the evaluation process. The use of fuzzy sets is examined to address this shortcoming. Fuzzy sets have been employed in order to provide a more consistent, rational method of evaluating the non-random uncertainties that are present in the contractor evaluation process. The linguistic factors (such as good, fair, or poor) used in fuzzy set analysis provide a more appropriate means to model decision circumstances that occur in industry than the current crisp (usually numerical) factors. Evaluation factors from a previous study are used. Each factor was assigned a grade. Correspondingly, each grade was represented by a fuzzy set. These fuzzy sets were then weighted and combined resulting in a fuzzy set. This composite fuzzy set represents the contractors rating. When evaluating multiple contractors, each contractors comp...

Response surface-based robust geotechnical design of supported excavation – spreadsheet-based solution

ABSTRACT The robust geotechnical design (RGD) approach which involves optimization to obtain a design that is safe, cost-efficient, and robust in the face of uncertainties, can be computationally challenging for complex geotechnical structures. In this study, the RGD approach has become practical by introducing a response surface as a surrogate to finite element- or finite difference-based computer code that is used for analyzing the system, and developing a fast algorithm for the optimization process. For demonstration purposes, a real-world supported excavation project is designed using this modified RGD approach and it is compared with the one designed by a local expert.

Reliability Analysis of Soil Liquefaction Potential

The focus of this paper is on the use of first order reliability method (FORM) for reliability analysis of soil liquefaction potential. First, an empirical equation for determining liquefaction resistance, in terms of cycle resistance ratio (CRR), based on cone penetration test, is established through neural network learning of case histories. This CRR model is established based on cyclic stress ratio (CSR) model proposed by Idriss and Boulanger, and together, they form a liquefaction limit state. Within the framework of the FORM, the uncertainty of this limit state model is estimated by means of Bayesian mapping functions. Accurate reliability index and thus the probability of liquefaction can be calculated using FORM by considering both model and parameter uncertainties.

Simplified procedure for reliability-based robust geotechnical design of drilled shafts in clay using spreadsheet

ABSTRACT This paper provides a simplified procedure for reliability-based robust geotechnical design (RGD) using spreadsheet. In the RGD methodology, design robustness is achieved by adjusting “design parameters” without reducing the uncertainties in noise factors. This design approach generally involves a multi-objective optimisation, which is computationally challenging. To improve the efficiency of the RGD methodology, the design robustness is evaluated in terms of sensitivity index and the safety requirement is evaluated using mean value first order second moment (MFOSM). To ease the concern that the reliability index obtained with MFOSM may not be sufficiently accurate, a mapping function that relates MFOSM to a more accurate method such as first order reliability method is introduced. To further improve the efficiency of the proposed simplified RGD method, a new simplified procedure along with a more accurate robustness measure is developed that eliminates the need for multi-objective optimisation. With these modifications, the proposed simplified RGD method can efficiently be implemented in a single Excel spreadsheet. The proposed simplified method, which goes beyond any existing reliability-based RGD methods in terms of ease of use and computational efficiency, is illustrated in this paper with an example of robust design of drilled shaft in clay.

Reliability-Based Robust Geotechnical Design of Retaining Walls

Geotechnical design often involves high, hard-to-control parameter uncertainties, which result in high variability in the system response. The variability in system response, which is typically addressed by satisfying a minimum safety measure in the form of a factor of safety or reliability index, forces the geotechnical designer to compromise between safety and efficiency (i.e., cost). When robustness of the geotechnical design against such system response variability is not evaluated during the design process, the tradeoff between over-design for safety and under-design for cost-savings is exacerbated. This paper introduces a novel design approach, Reliability-based Robust Design Optimization that considers explicitly the reliability, robustness, and cost. This design methodology is demonstrated with the design of a cantilever retaining wall. System reliability index is used as the performance measure and the tradeoff among the computed reliability index, the variance of the reliability index (as a measure of the robustness), and the cost are investigated. The results show that for some designs (with reliability index between 3 and 3.65), no tradeoff exists between the reliability index and its variance; hence, the design with the greatest reliability index also has the highest robustness (smallest variance) for a given cost. For other designs, a tradeoff relationship exists between the reliability index and its variance for a given cost.

VERTICAL CAPACITY OF PILES USING FUZZY SETS

Abstract Because prediction of the load-carrying capacity of piles continues to challenge geo-technical engineers, new solutions are needed. The problem is aggravated by the lack of understanding of the phenomena of soil-pile interaction, and the limited quantity and inexact quality of subsurface soil information that can be provided for analysis. The use of fuzzy set theory improves the engineers ability to handle the uncertainty in the soil parameters and the prediction methods and thus improves the reliability of the pre dicted capacity. A methodology for predicting pile capacity based on fuzzy set theory is developed and implemented in a computer program. The validity of the program re sults is evaluated using a US Federal Highway Administration (FHWA) pile load test database. The comparison between predicted and measured ultimate capacities of piles in sand, clay and mixed soils shows that the predictive capability of the developed program is very good.