Mohamed A. Shahin

State-of-the-Art Review of Biocementation by Microbially Induced Calcite Precipitation (MICP) for Soil Stabilization

ABSTRACT Biocementation is a recently developed new branch in geotechnical engineering that deals with the application of microbiological activity to improve the engineering properties of soils. One of the most commonly adopted processes to achieve soil biocementation is through microbially induced calcite precipitation (MICP). This technique utilizes the metabolic pathways of bacteria to form calcite (CaCO3) that binds the soil particles together, leading to increased soil strength and stiffness. This paper presents a review of the use of MICP for soil improvement and discusses the treatment process including the primary components involved and major affecting factors. Envisioned applications, potential advantages and limitations of MICP for soil improvement are also presented and discussed. Finally, the primary challenges that lay ahead for the future research (i.e. treatment optimization, upscaling for in situ implementation and self-healing of biotreated soils) are briefly discussed.

Influence of Key Environmental Conditions on Microbially Induced Cementation for Soil Stabilization

AbstractMicrobially induced calcite precipitation (MICP) is a sustainable biological ground improvement technique that is capable of altering and improving soil mechanical and geotechnical engineering properties. In this paper, laboratory column studies were used to examine the effects of some key environmental parameters on ureolytic MICP mediated soils, including the impact of urease concentrations, temperature, rainwater flushing, oil contamination, and freeze–thaw cycling. The results indicate that an effective crystal precipitation pattern can be obtained at low urease activity and ambient temperature, resulting in high improvement in soil unconfined compressive strength (UCS). The microstructural images of such crystals showed agglomerated large clusters filling the gaps between the soil grains, leading to effective crystals formation. The rainwater flushing was detrimental to the biocementation process. The results also indicate that traditional MICP treatment by the two-phase injection method did ...

Probabilistic analysis of soil consolidation via prefabricated vertical drains

AbstractSoil consolidation by prefabricated vertical drains (PVDs) relies on some soil properties that are spatially variable, such as the coefficient of permeability. However, the design of soil consolidation via PVDs has been traditionally carried out deterministically and thus can be misleading because of the ignorance of the uncertainty associated with the inherent spatial variation of soil properties. In this paper, the effects of spatial variability of soil permeability on soil consolidation by PVDs are investigated stochastically, and the corresponding uncertainty associated with the degree of consolidation is statistically quantified and analyzed.

Use of evolutionary computing for modelling some complex problems in geotechnical engineering

In this paper, the feasibility of using evolutionary computing for solving some complex problems in geotechnical engineering is investigated. The paper presents a relatively new technique, i.e. evolutionary polynomial regression (EPR), for modelling three practical applications in geotechnical engineering including the settlement of shallow foundations on cohesionless soils, pullout capacity of small ground anchors and ultimate bearing capacity of pile foundations. The prediction results from the proposed EPR models are compared with those obtained from artificial neural network (ANN) models previously developed by the author, as well as some of the most commonly available methods. The results indicate that the proposed EPR models agree well with (or better than) the ANN models and significantly outperform the other existing methods. The advantage of EPR technique over ANNs is that EPR generates transparent and well-structured models in the form of simple and easy-to-use hand calculation formulae that can be readily used by practising engineers.

Artificial Intelligence in Geotechnical Engineering: Applications, Modeling Aspects, and Future Directions

Over the last decade or so, artificial intelligence (AI) has proved to provide a high level of competency in solving many geotechnical engineering problems that are beyond the computational capability of classical mathematics and traditional procedures. This chapter presents a brief overview of three selected AI techniques and their applications in geotechnical engineering, discusses some AI modeling aspects that need further attention, and provides insights into future directions and research challenges.

Utilization of Shredded Rubber Tires for Cement-Stabilized Soft Clays

Tire-soil mixtures can be used as good construction materials in many geotechnical engineering applications such as pavement foundations, lightweight fill in road embankments and lightweight backfill behind retaining walls. This paper describes research undertaken to investigate experimentally the impact of shredded rubber tires as reinforcing material on the mechanical properties of cement-stabilized soft clay, in terms of strength and stiffness. A series of laboratory experiments are carried out on cement-stabilized clay mixed with several portions of shredded rubber tires of sizes 440 μm and 4 mm. The tests conducted include compaction, unconfmed compression strength and indirect tensile strength. The results demonstrate that the use of shredded rubber tires has a potential in enhancing the ductility of cement-stabilized soft clay but decreases stiffness and ultimate resistance.

Stabilisation of ballasted rail tracks and underlying soft formation soils with geosynthetic grids and drains

Railway ballast deforms and degrades progressively under heavy cyclic loading. Ballast degradation is influenced by several factors including the amplitude and number of load cycles, gradation of aggregates, track confining pressure, angularity and fracture strength of individual grains. The degraded ballast is usually cleaned on track, otherwise, fully or partially replaced by fresh ballast, depending on the track settlement and current density. The use of composite geosynthetics at the bottom of recycled ballast layer is highly desirable to serve the functions of both drainage and separation of ballast from subballast. Construction of the rail track also requires appropriate improvement of the subgrade soils to achieve an adequately stiff surface layer prior to placing the ballast and subballast. Based on extensive research at University of Wollongong, it is found that the gradation of ballast plays a significant role in the strength, deformation, degradation, stability and drainage of rail tracks. Results from large-scale triaxial testing indicate that a small increase in confining pressure improves track stability with less ballast degradation. Bonded geogridsgeotextiles also decrease differential settlements of tracks, ballast degradation and lateral movement, and the risk of subgrade pumping. Stabilization of soft subgrade soils is also essential for improving the overall stability of track and to reduce the differential settlement during the operation of trains. This paper also highlights the

Load-settlement modelling of axially loaded drilled shafts using CPT-based recurrent neural networks

AbstractThe design of pile foundations requires good estimation of the pile load-carrying capacity and settlement. Design for bearing capacity and design for settlement have been traditionally carried out separately. However, soil resistance and settlement are influenced by each other, and the design of pile foundations should thus consider the bearing capacity and settlement inseparably. This requires the full load–settlement response of piles to be well predicted. However, it is well known that the actual load–settlement response of pile foundations can be obtained only by load tests carried out in situ, which are expensive and time-consuming. In this paper, recurrent neural networks (RNNs) were used to develop a prediction model that can resemble the full load–settlement response of drilled shafts (bored piles) subjected to axial loading. The developed RNN model was calibrated and validated using several in situ full-scale pile load tests, as well as cone penetration test (CPT) data. The results indica...

A review of artificial intelligence applications in shallow foundations

Abstract Geotechnical engineering deals with materials (e.g. soil and rock) that, by their very nature, exhibit varied and uncertain behavior because of the imprecise physical processes associated with the formation of these materials. Modeling the behavior of such materials in geotechnical engineering applications is complex and sometimes beyond the ability of most traditional forms of physically based engineering methods. Artificial intelligence (AI) is becoming more popular and particularly amenable to modeling the complex behavior of most geotechnical engineering applications, including foundations, because it has demonstrated superior predictive ability compared to traditional methods. The main aim of this paper is to review the AI applications in shallow foundations and present the salient features associated with the AI modeling development. The paper also discusses the strengths and limitations of AI techniques compared to other modeling approaches.

Numerical modeling of granular pile-anchor foundations (GPAF) in reactive soils

Abstract Laboratory and field studies have shown that granular pile-anchor foundations (GPAF) are a promising foundation system that can be used to reduce the detrimental effects of reactive soils. This paper presents results from finite element analyses undertaken on granular pile-anchor foundations in a reactive soil using PLAXIS software. The study investigated the ability of a single pile to resist forces induced by both heave and shrinkage. The results confirmed the efficiency of the granular pile-anchor foundations in resisting heave induced by moisture gain. However, in order to resist shrinkage, the GPAF system has to be reinforced with geofabric to assist resisting bulging of the granular pile into the surrounding soil. The analyses showed that success of the GPAF in heave resistance may be adversely influenced by the high stiffness of the interface, which requires only small relative movement to mobilize full resistance. The efficiency of the GPAF system increases with the ratio between the pile diameter and supported footing. Using a group of piles instead of a single pile under a footing can reduce the efficiency of the GPAF system.