Shadi Najjar

Importance of Lower-Bound Capacities in the Design of Deep Foundations

There is generally a physical limit to the smallest possible capacity for a deep foundation. However, a lower bound on the capacity has rarely been accounted for in performing reliability analyses and developing reliability-based design codes. The objectives of this paper are to investigate the effect of having a lower-bound capacity on the reliability of a geotechnical engineering system and to propose a load and resistance factor design (LRFD) checking format that includes information on the lower-bound capacity in design. It is concluded that a lower-bound capacity can cause a significant increase in the calculated reliability for a geotechnical design even if it is an uncertain estimate. Two alternative LRFD formats that incorporate lower-bound capacities and that would not require substantive changes to existing codes are proposed. Real-world examples dealing with the design of onshore and offshore foundations indicate that the incorporation of a lower-bound capacity into design is expected to provide a more realistic quantification of reliability for decision-making purposes and therefore a more rational and efficient basis for design.

Shear Strength of Fiber-Reinforced Sands

Soil reinforcement using discrete randomly distributed fibers has been widely investigated over the last 30 years. Several models were suggested to estimate the improvement brought by fibers to the shear strength of soils. The objectives of this paper are to (1) supplement the data available in the literature on the behavior of fiber-reinforced sands; (2) study the effect of several parameters which are known to affect the shear strength of fiber-reinforced sands; and (3) investigate the effectiveness of current models in predicting the improvement in shear strength of fiber-reinforced sand. An extensive direct shear testing program was implemented using coarse and fine sands tested with three types of fibers. Results indicate the existence of a fiber-grain scale effect which is not catered for in current prediction models. A comparison between measured and predicted shear strengths indicates that the energy dissipation model is effective in predicting the shear strength of fiber-reinforced specimens in reference to the tests conducted in this study. On the other hand, the effectiveness of the predictions of the discrete model is affected by the parameters of the model, which may depend on the test setup and the procedure used for mixing the fibers.

A State-of-the-Art Review of Stone/Sand-Column Reinforced Clay Systems

This paper presents a state-of-the-art review of published research papers and reports that focus on the modeling, testing, and analysis of soft clays that are reinforced with sand/stone columns in relation to bearing capacity and settlement considerations. The review is presented in chronological order to shed light on the development of this field of research in the last 40+ years. The objective of the study is to assemble published results from field, laboratory, and numerical investigations of sand/stone columns in clay in one resource to provide future researchers and designers with easy access to information and data. The majority of the reviewed papers include an experimental component that is based on field or laboratory scale tests (1-g, triaxial, or centrifuge) conducted on clay specimens reinforced with partially or fully penetrating, encased or ordinary, stone or sand columns that were installed as single columns or as column groups. Some papers included numerical experiments that were based on finite element models, while others presented analytical solutions for modeling the response of the composite system. A compilation of the important findings from physical, numerical, and analytical models in addition to a summary table that facilitates access to information from various research efforts are presented in the paper.

Quantification of Model Uncertainty in Shear Strength Predictions for Fiber-Reinforced Sand

AbstractSeveral models have been suggested to estimate the improvement brought by fibers to the shear strength of fiber-reinforced sands. To date, the effectiveness and reliability of these models have not been the subject of a comprehensive evaluation. The objectives of this paper are to (1) compile the experimental data available in the literature on the behavior of fiber-reinforced sands into a comprehensive state-of-the-art database, (2) quantify the model uncertainty and bias of current strength prediction models for fiber-reinforced sands, and (3) provide insight regarding possible modifications that could be made to the formulation of available models to improve their predictive effectiveness and reduce their model uncertainty. Two models that are considered to present the best available approaches to predicting sand-fiber shear strength were evaluated, namely, the “energy-based” model and the “discrete” model. The energy-based model was found to underestimate the measured friction coefficient on a...

Importance of Proof-Load Tests in Foundation Reliability

Proof-load tests play an important role in verifying the validity of design methods and construction procedures. Recently, there has been considerable interest in maximizing the value of proof-load tests in foundation design within a reliability-based framework. The objectives of this paper are to (1) illustrate how static proof-load tests can affect the reliability and design of a tested foundation, (2) discuss the effect of uncertainty in the measured proof load on the calculated reliability, and (3) study how the results of proof-load tests conducted on a limited number of foundations using relatively small proof loads can be utilized to update the tail of the capacity distribution. Results indicate that proof loads can result in a significant increase in the reliability for a foundation, even when the proof load is significantly smaller than the predicted capacity.

Undrained shear strength characteristics of compacted clay reinforced with natural hemp fibers

Reinforcing clay with natural fibers is a common practice in various applications, such as the construction of steep slopes, repair of shallow slope failures, improving the performance of landfill covers, strengthening of roadbeds, etc. The reliance on this technique is on the rise as a result of the increasing demand for incorporating sustainable materials in construction. “Hemp” fibers are natural fibers derived from the plant Cannabis Sativa. Industrial Hemp is legally cultivated in a number of countries. Hemp is used in several industries, such as paper, textiles, clothing, biodegradable plastics, construction, body care products, food, medicine, and biofuel, in addition to applications in strengthening concrete and soils. The main objective of this paper is to investigate the potential use of natural Hemp fiber in improving the load response of compacted clays. A laboratory-testing program consisting of 18 unconsolidated undrained triaxial tests was designed for this purpose. Specimens of control clay and of clay mixed with Hemp fibers added at various fiber contents were prepared at a number of water contents and compacted using the standard proctor procedure. Specimens with diameters of 7.15 cm and heights of 14.3 cm were prepared at varying moisture contents (14%, 18%, and 20%) and mixed with fibers of 4 cm length at gravimetric contents ranging from 0.5% to 1.5%. Results show that improvements in shear strength of up to 100% could be realized for the Hemp reinforced specimens. The percent improvement increases with the fiber content up to a threshold value of 1.25% and differs depending on the magnitude of the water content used in compaction in reference to the optimum moisture content of the matrix clay.

Probabilistic Modeling of Dynamic Modulus Master Curves for Hot-Mix Asphalt Mixtures

Since the introduction of the dynamic modulus E* concept in the recent Mechanistic–Empirical Pavement Design Guide, there has been considerable interest in establishing reliable prediction models for E*. An investigation of the effectiveness of commonly used predictive models shows that E* predictions exhibit significant scatter around the measured values, with percentage of errors reaching about 6200%. A need exists for characterizing the uncertainties that are inherent in E* to serve as input to any future robust reliability analysis that aims at properly determining the probability of unsatisfactory performance of asphalt pavement systems. The primary objective of this study was to present a probabilistic model that would allow the user to determine a priori probability distribution for E* given knowledge about temperature and frequency. The seven-parameter model was based on the sigmoidal function and the shift factor that related reduced frequency to real frequency and temperature. The model was calibrated on the basis of a well-known published database that included 7,400 laboratory measurements of E* for 346 asphalt mixes. Monte Carlo simulations were used to propagate the uncertainties in the seven model parameters and determine realistic estimates of the mean, coefficient of variation, and probability distribution of E* at different frequencies and temperatures. Results showed that E* could be modeled by using a lognormal distribution with a mean that was estimated from the mean values of the parameters and a coefficient of variation that varied from a minimum of 0.55 for high values of reduced frequency to a maximum of 1.55 for lower values of reduced frequency.

Probabilistic Modeling of the Inherent Variability in the Dynamic Modulus Master Curve of Asphalt Concrete

Pavement engineers and practitioners have come to recognize the urgent need to quantify the variability in dynamic modulus, |E*|, because of its influence on the predicted performance of asphalt pavements and to adopt realistic quality assurance or quality control measures associated with pavement construction. The objective of this study was to characterize the inherent variability in |E*| across the full spectrum of the |E*| master curve (fitted with a sigmoidal function for various reduced frequencies). The study analyzed |E*| data from six mixes that included at least eight replicates within a robust probabilistic framework that allowed for a preliminary quantification of uncertainty caused by the inherent variability in |E*|. Monte Carlo simulations were used to propagate the uncertainties of the sigmoidal model coefficients to determine the mean, coefficient of variation, and probability distribution of |E*| as a function of reduced frequency. In addition, the inherent uncertainty in |E*| was propagated through forward modeling to characterize the resulting uncertainty in the predicted rut depth in the asphalt layer for a set of pavement structures. The findings show that the values of the inherent uncertainty of |E*| are relatively small for cases with reduced frequencies that are high but increase dramatically for reduced frequencies that are in the medium to low range. This uncertainty increases as the nominal maximum aggregate size (NMAS) of the mix under investigation increases. It was found that the uncertainty significantly affects the probability distribution of rut depth and implies higher variability for cases of hot weather, slow traffic, or large NMAS.

Bayesian Updating of Load Settlement Curves for Footings on Cohesionless Soil

The design of spread footings on cohesionless soils is generally governed by serviceability requirements. Recent studies have investigated the use of normalized load-settlement curves to model the behavior of footings at all levels of displacement using databases of load tests. An investigation of available databases with complete load-settlement curves indicates that more than 85% of available data corresponds to plate load tests or footings that are smaller than 1.0m in width. There is a need to confirm the applicability of these curves to footings with widths ranging from 1.0m to 10.0 m. The main objective of this paper is to update available normalized load- settlement curves using point measurements of settlement and load from full scale footings. The updating process was conducted using the first-order, second-moment Bayesian method (FSBM) which allows for determining updated load-settlement curves and quantifying the uncertainty associated with these curves to facilitate their use in practical reliability-based design of footings on cohesionless soils.

Reliability Analyses of Clay-Embedded Offshore Pipelines Under Vertical Buckling Considering Lower-Bound Pipe-Soil Capacity

This paper presents the reliability formulation and analyses for studying and quantifying probabilistically the impact of the main parameters involved in the upheaval buckling of offshore buried pipes due to high pressure high temperature conditions (HPHT) on the reliability of the pipeline. Pipelines are considered installed in a clayey trench and naturally covered. The limit state function is established in terms of the vertical pipe-soil capacity and vertical loading. A lower-bound capacity of the pipe-clayey soil system is included in the reliability analysis in order to represent more realistic conditions with regards to the uncertainty in the capacity. The lower-bound capacity is the smallest possible physical limit of the pipe-soil capacity. Reliability assessments using the main parameters that control the vertical buckling in terms of loading and capacity were performed. Consequently, the variations of the reliability index (β) with the vertical imperfection (δ) and the ratio of the cover height (depth of pipe embedment) to the pipe diameter (H/D) were quantified. The reliability index was evaluated by means of Monte Carlo simulations. The inclusion of the lower-bound capacity by means of a left-censored lognormal distribution was found to increase in some cases the values of β.Copyright