Nadarajah Ravichandran

Robust Geotechnical Design of Drilled Shafts in Sand: New Design Perspective

AbstractThis paper presents a new geotechnical design concept called robust geotechnical design (RGD). This new design methodology, seeking to achieve a certain level of design robustness in addition to meeting safety and cost requirements, is complementary to traditional design methods. Here a design is considered robust if the variation in the system response is insensitive to the variation in noise factors (mainly uncertain soil parameters). To aid in selection of the best design, a Pareto front that describes a tradeoff relationship between cost and robustness at a given safety level can be established using the RGD methodology. The new design methodology is illustrated with an example of drilled-shaft design for axial compression. The significance of the RGD methodology is demonstrated.

New Soil-Water Characteristic Curve and Its Performance in the Finite-Element Simulation of Unsaturated Soils

AbstractAmong the many constitutive equations, the moisture-suction relationship, also known as the soil-water characteristic curve (SWCC), is one of the important relationships needed for modeling the dynamics of unsaturated soils using the finite-element method. In this study, a new SWCC equation is developed that uses four fitting parameters including the maximum possible suction. The new model predicts the experimental data of various soils well for a wide range of degrees of saturation (DOS), especially in high suction (above 10,000  kPa). Predicting the higher suction at low DOS is one of the deficiencies of the widely used Brooks and Corey, van Genuchten, and Fredlund and Xing models. The numerical stability and performance of the proposed, and other widely used models, are investigated by implementing these models within in a simplified finite-element program for the dynamics of unsaturated soil and simulating static and dynamic problems. For the midrange DOS, all of the aforementioned models pred...

Effect of deformation-induced suction in the behavior of unsaturated fine-grained soils using simplified finite-element model

AbstractMatric suction is one of the important variables used to characterize the deformation behavior of unsaturated soil. The stress-strain relationship and the governing differential equations are the two elements in which suction is incorporated in the development of mathematical models for the dynamics of unsaturated soils. In this paper, a simplified finite-element model was used to understand the effect of initial suction and deformation-induced suction variation in the static and dynamic behavior of silty and clayey soils. The simplified finite-element model was developed by neglecting the relative acceleration and velocity terms associated with water and air phases in the fully coupled governing differential equations. The stress-strain behavior of the solid skeleton was represented by linear elastic model, a simple model to explain the computed responses using basic theory. The suction-degree of saturation relationship was modeled by the Brooks and Corey model. Simulation results showed that the...

Seismic Site Factors and Design Response Spectra Based on Conditions in Charleston, South Carolina

Seismic site factors based on conditions typical of Charleston, South Carolina, are derived from the results of more than 13,000 one-dimensional equivalent linear and nonlinear dynamic response simulations. The site factors are plotted versus average shear wave velocity in the top 30 m (VS30) of soil and grouped by spectral acceleration and period. Median relationships for the site factors are expressed by a linear model for lower values of VS30 and a linear or exponential model for higher values. The computed factors are found to be somewhat different from the factors recommended in design codes. It is also found that amplifications greater than predicted by the common (or three-point) acceleration design response spectrum method can occur at periods greater than 1.0 s, particularly when VS30 < 200 m/s. Thus, when VS30 < 200 m/s, it is recommended that a multipoint response spectrum be constructed and compared with the three-point spectrum.

Numerical Study on the Dynamic Behavior of Retaining Walls Backfilled with Shredded Tires

Previous research has shown that shredded tires are a beneficial replacement for conventional sand backfills in retaining walls as they reduce both material costs and structural wall size requirements. To further investigate the suitability of tire shreds as a backfill material, this study evaluates the performance of retaining walls backfilled with tire shreds under dynamic loading conditions. Projected lateral earth pressures and bending moments and shear forces on the structure are evaluated for both shredded tire backfill and conventional backfill sand using a geotechnical engineering finite element software, PLAXIS. Input information for material properties of soil, sand backfill, and shredded tires is determined from laboratory testing. Through this comprehensive dynamic simulation, the safety and performance of shredded tires is confirmed for structures under earthquake loading. This demonstrates the viability of shredded tires as an economical replacement for conventional sand in the construction of retaining walls in seismic zones.

Joint Distributions of Hurricane Wind and Storm Surge for the City of Charleston in South Carolina

Major coastal cities, which have large populations and economies, are easily suffered from the losses due to hurricane wind and storm surge hazards. Although current design codes consider the joint occurrence of high wind and surge, information on site specific joint distributions of hurricane wind and storm surge along the U.S. Eastern Coast and Gulf of Mexico is still sparse and limited. In this paper, joint probability distributions of combined hurricane wind and storm surge for the City of Charleston, SC is developed. A stochastic hurricane model was used to simulate 5,000 years of synthetic hurricanes. The simulated hurricanes were inputted into the ADCIRC (Advanced Circulation) surge prediction model to compute the surge heights at selected locations. The calculated peak wind speeds and surge heights were employed to generate the joint probability distributions at each location. These joint distributions developed can be used in a multi-hazard design or risk assessment framework to consider the combined effects of hurricane wind and storm surge hazards.

Simplified Finite-Element Model for Site Response Analysis of Unsaturated Soil Profiles

AbstractA numerically stable and computationally efficient finite-element model for analyzing the dynamic response of unsaturated soil profiles in terms of total stresses is presented in this paper. The highly nonlinear, fully coupled governing differential equations are simplified by neglecting the relative accelerations and velocities of the pore fluids, and the simplified formulation is improved by incorporating an external viscous damping formulation for unsaturated soil. The surface spectral accelerations computed using the proposed model are qualitatively compared with that of DEEPSOIL and PLAXIS following a comparison of surface spectral accelerations computed using the underdamped and the damped simplified formulations. A detailed parametric study of the effect of viscous damping parameters and both elastoplastic and elastic constitutive models is also presented. A simplified soil–pile interaction study is presented to show the effect of soil–pile interaction on the computed responses. Analysis re...

Centrifuge Modeling of Unsaturated Soil-Pile System

This paper describes a geotechnical centrifuge testing procedure used for evaluating the effect of degree of saturation on the dynamic response of a pile foundation supported in Ottawa sand. Specifically, the specimen preparation, testing procedure, and sample test results are presented. A uniform degree of saturation profile with depth was developed by spraying water from the top of the model and the flow rate was controlled using servo valves. The measured data indicate that the degree of saturation of the soil affects the dynamic response of the pile foundation. In addition, the presence of the pile foundation significantly alters the computed acceleration at the surface near the pile. It is also found that the peak horizontal spectral acceleration computed at the surface near the pile increases with degree of saturation while it decreases away from the pile (free-field condition).

Performance of retaining wall backfilled with tire aggregate under static and dynamic loading conditions: conventional designs and finite element simulations

AbstractThe static and dynamic behaviours of a retaining wall backfilled with tire aggregate are investigated in this paper through conventional designs as well as coupled finite element simulation...

An agent-based framework for modeling the effectiveness of hurricane mitigation incentives

To evaluate the effectiveness of different incentives for mitigating regional hurricane hazards, an agent-based hurricane mitigation framework was developed. This framework, which consists of six essential components, is able to consider stakeholders’ points of view on the selections of hurricane retrofit measures and the dynamic evolutions of building inventories (i.e. constructions and demolitions). Based on the findings of this study, among different levels of property tax reduction, a reduction between 50% and 75% was found to be the most effective one that leads to the highest hurricane cost reduction the study region can get in a 25-year timeframe. Agent-based modeling (ABM), which has a rapid growth in the past few decades, is a relatively new computational method (Gilbert 2007). The ABM is known as a “bottom-up” model. In ABM, the behavior of a complex system is studied without having to define the global behavior of the system. Rather, the behavior of individuals or subcomponents (hereafter referred as “agents”) is defined and the interactions between the agents are modeled to unveil the global behavior (Borshchev and Filippov 2004). Agents’ behaviors are defined using certain rules. Their interactions with each other as well as the environment can affect these rules and in turn influence agents’ behaviors (Macal and North 2010). By modeling agents’ behaviors and interactions individually, the behavior of the entire system can be revealed. Nevertheless, the ABM is seldom used in hurricane related studies. Chen et al. (2006) developed an agent-based hurricane evacuation model for the Florida Keys using survey data. This model was able to estimate not only the minimum clearance time of the evacuation, but also the accommodations needed if the evacuation is interrupted by a landfall hurricane. A dynamic ABM system was developed by Dawson et al. (2011) for flood incident management. This system is able to estimate the vulnerability of individual agents in coastal communities, subject to different flood conditions, defense scenarios, warning times and evacuation strategies. The flood inundation, traffic condition, flood risk, agent’s vulnerability and agent’s behavior were modeled to evaluate the effectiveness of different FIM measures. One of the key challenges in the ABM is the modeling of individual agent (Crooks et al. 2008). Specifically, it is the modeling of agent’s demographic and psychological attributes, and their relations with agent’s behaviors. The psychological attributes usually include risk perception, subjective knowledge, hazard experience, etc. Using data from the 2003 Hurricane Loss Mitigation Baseline Survey (HLMBS) (Peacock 2003b), Peacock et al. conducted three studies in analyzing the influences of Florida residents’ demographic and psychological characteristics on (1) the status of hurricane mitigation (Peacock 2003a), (2) the hurricane risk perception (Peacock et al. 2005), and (3) the household responses to hurricane mitigation incentives (Ge et al. 2011). The influences were modeled using probabilistic models through logistic regressions. The outcomes of their studies are valuable resources for the modeling of agents’ behaviors in hurricane mitigations. In this study, an agent-based hurricane mitigation framework was developed for the purpose of evaluating the effectiveness of different incentives for 12 International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015 2 mitigating the combined effects of hurricane wind and flood hazards. A case study hurricane mitigation domain (Miami, Florida) was constructed to mimic the real configuration of the existing building stock and the attributes of residents in the study domain. The occurrence of the new building constructions, demolitions and hurricane hazards over time was modeled using historical data. Agents’ responses to hazards and incentives for retrofitting their homes, and decision-makings with regard to building retrofits were modeled using the survey data. Finally, the combined wind and flood loss estimations were performed to evaluate the cost-benefit of the hazard mitigation incentives. This paper is organized such that an overview of the agent-based hurricane mitigation framework is presented in Section 1, followed by a case study in Section 2, and preliminary findings and conclusions are given in Section 3. 1. OVERVIEW OF THE AGENT-BASED HURRICANE MITIGATION FRAMEWORK The proposed framework for agent-based regional hurricane mitigation is presented in . This framework, which is composed of six modules, accounts for agents’ responses to incentives and natural hazards in hurricane mitigations through modeling of agents’ behaviors. The six modules are Buildings, Agents, Retrofits, Hazards, Constructions & Demolitions, and Incentives (see ). The behaviors of the six modules are defined individually and the connections between them are defined using a set of rules or functional relationships. These connections are marked as arrows, which indicate directional impacts from one module to the other, in . For instance, hazards can impart damages to buildings and cause losses, and hazards are also able to influence agents’ psychological attributes or behaviors. The Retrofits module, marked as a circle, requires agents’ decision making, which is affected by both hazards and incentives. In this hurricane mitigation framework, the initial locations and characteristics of individual buildings as well as the initial locations and attributes of individual agents were first determined using historical survey data. Then, given selected incentives, simulations were performed at a fixed time interval (e.g. one month) to evaluate the performance of the entire system (i.e. all six modules and the connections). At every time step, the building characteristics and the agent attributes were updated. Agents responded to incentives and hazards, and decided if they wanted to retrofit their buildings. New constructions and demolitions occurred at every time step as well. When affected by a hurricane in a time step, the combined wind and flood losses was computed using a loss estimation framework adapted from the HAZUS-MH methodology. The updates of building characteristics, including demolitions, and agent attributes were simulated after the hurricane. The following subsections are organized to describe this process in detail. 1.1. Building locations and characteristics As mentioned above, a key feature of the agent-based modeling is to model each individual from the bottom. This requires specific modeling of each individual building that exists in the study domain. For simplicity and as an illustrative example, only residential buildings were taken into account in this study. Buildings were modeled as individual dots (dimensionless) on a map (see Figure 2) containing location and characteristic information, which are adequate for regional hurricane mitigations . Figure 2: Comparison between modeled and actual -80.358 -80.357 -80.356 -80.355 -80.354 25.616 25.617 25.618 25.619 25.62 Longitude (deg) L a t it u d e (d eg ) Figure 1: Framework for agent-based regional hurricane mitigation 12 International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015 3 locations of buildings 1.1.1. Locations of buildings The numbers of buildings in each Census block were first determined using the 2010 U.S. Census (U.S. Census Bureau 2010) and the 2011 American Community Survey (ACS) (U.S. Census Bureau 2011) data through a probabilistic method. Then, the buildings were placed along the roads but with a distance to the roads in the Census blocks. A comparison between the modeled building locations and their actual locations on a Google map is presented in Figure 2. It can be clearly seen that the modeled locations (solid circles) agree well with their actual locations. 1.1.2. Characteristics of buildings After the locations of buildings were determined, their characteristics could be assigned. The 20 building characteristics considered in this study include year structure built, household income, building square footage, number of stories, flood zone, base flood elevation, foundation type, foundation height, building replacement value, corresponding wind and flood damage functions, etc. These characteristics were selected because they are essential in hurricane loss estimation and hazard mitigation. It should be noted that these characteristics were assigned to every building using survey data. Among others, the ACS data, which is a typical source available, only provides data at Census block group (i.e. a group of Census blocks) level. Therefore, in order to assign characteristics to each individual building, we used the probability mass functions (PMFs) obtained from the survey data (e.g. ACS data) at the Census block group level. The PMF for a particular characteristic represents the discrete probability of every category in that characteristic. For instance, there are 9 categories for year structure built (2005-2010, 2000-2004, 1990-1999, ..., 1940-1949, 1910-1939). Each of them is associated with a distribution probability corresponding to a Census block group. For each building in that Census block group, the year built was randomly sampled following the PMF. In this framework, similar concept was utilized in the assignment of characteristics. The correlations between characteristics were also considered. Because the assignments heavily rely on the above-mentioned probabilistic method, statistics of the assigned characteristics were checked to ensure the accuracy in terms of capturing the trends of the PMFs used to develop the mitigation framework. PMFs were checked for the entire hurricane mitigation domain and all of them agreed well with the assigned statistics. One example is given in Figure 3. 1.2. Agent attri