Master of Science, University of Akron, 2005, Civil Engineering

When designing pavements, there are three fundamental external design parameters to evaluate (1) the characteristics of the subgrade upon which the pavement is placed, (2) the applied loads, and (3) the environment. The subgrade layer, upon which the pavement is constructed, will have a large impact on structural design. The study was based on extensive laboratory work to characterize cohesive subgrade materials. Permeability of the subgrade was obtained using a flexible wall permeameter, which simulates the actual field conditions. The factors affecting permeability were also discussed. Strength parameters were determined utilizing the static load triaxial apparatus. The Consolidated-Undrained Triaxial Compression Test and Unconfined Compression Test were performed. Resilient modulus testing was conducted using a repeated load triaxial system at different confining pressures employing AASHTO T294-92I. A new testing procedure, stage loading, was used to test the permanent deformation of subgrade materials at different stress levels and load repetitions; this technique allows researchers to explore the effect of stress history on the accumulation of plastic deformation besides saving time, effort, and test specimens. Hydraulic conductivity results showed a practically impermeable subgrade layer. From the measured data of the consolidation test, the pressure-void ratio relationship was plotted and used in determining the compression index, recompression index and maximum past pressure of the soil. In addition, the coefficients of consolidation were obtained. Mohr circles at failure and Mohr failure envelopes were drawn for the total and effective stress data obtained from the CU tests, from which shear strength parameters were determined. On the other hand, Mohr circles at failure were drawn for the unconfined compression test that indicated the cohesive subgrade soils to vary between very stiff and hard consistency. Furthermore, isotropic elasticity analysis was carr (open full item for complete abstract)

Committee: Robert Liang (Advisor) Subjects:

Doctor of Philosophy, The Ohio State University, 2015, Civil Engineering

Pavement design methodologies have over the past decades seen philosophical evolutions and eventually practical implementation of new postulates. As more contributions are made by pavement researchers to the State-of-the-Art in pavement design, there exist a chasm between pavement engineers and state-of-the-art pavement research in terms of incorporation into pavement design guidelines. In developing countries such as Guyana in South America, as well as several departments of transportation, municipalities and townships in the United States, pavement engineers still use the American Association of State Highway and Transportation Officials (AASHTO) Pavement Design Guide (1993). This empirical pavement design guide and its previous iterations were based primarily on data that was collected and processed from the then American Association of State Highway Officials (AASHO) Road Test conducted between 1958 and 1960. The limitations with continued use of this method are obvious since the data was gathered under specific environmental conditions, a specific subgrade type, and with specific materials as well as specific pavement cross-sections. The continued use of this guide does not account for advances in material technology, different types and volumes of vehicular traffic, changing climatic conditions and also can be costly in expanding road networks. To solve this dilemma pavement researchers started working toward a more mechanistic approach for design and through the work of National Cooperative Highway Research Program (NCHRP), culminated in the publishing of the Mechanistic-Empirical Pavement Design Guide (MEPDG) in 2004. The finite element model used in the MEPDG is premised upon a displacement based theory. These theories are capable of making good predictions regarding global responses such as displacements and sometimes in-plane stresses but not the transverse stress distribution. To predict transverse stress distribution, stress based theories are more su (open full item for complete abstract)

Committee: William Wolfe PhD (Advisor); Tarunjit Butalia PhD (Committee Co-Chair); Frank Croft PhD (Committee Member); Fabian Tan PhD (Committee Member) Subjects: Civil Engineering; Transportation

Master of Science in Civil Engineering, University of Toledo, 2004, Civil Engineering

Subgrade soil plays a very important role in the construction of roadways. Before the use of asphalt in the construction of roadway, roads were being constructed based on experience. The introduction of paving asphalt in road construction has led to the development of engineering procedures and designs for the methods of construction. The resilient modulus of the underlying material supporting the pavement is now considered as a key material property in the AASHTO mechanistic-empirical design procedure. Attempts have been made by researchers to predict the Subgrade resilient modulus from laboratory/field experimental methods based on the soil properties. This research seeks to develop a model for predicting the subgrade resilient modulus due to environmental conditions by considering the seasonal variation of temperature and moisture content which affects the soil. The limitation of this research model is that it cannot be used universally since environmental conditions vary from place to place, however, it can be modified to suit other local environmental conditions. The detrimental effect of low resilient modulus of subgrade soil is observed in the damaged analysis.

Committee: Andrew Heydinger (Advisor) Subjects: Engineering, Civil

Doctor of Philosophy, The Ohio State University, 2007, Civil Engineering

The resilient modulus (MR) of subgrade or unbound materials is a key parameter current and proposed methods for predicting the structural response of pavements (the 2002 Mechanistic-Empirical Pavement Design Guide, M-E PDG). Backpropagation neural network algorithms were adopted to construct artificial neural networks (ANNs) were then used to predict the resilient modulus of three Ohio cohesive soil types: A- A-6, and A-7-6. The key input parameters for ANN analysis and simulations are percent of soil particles passing through a #200 sieve, plasticity index, liquid limit, unconfined compressive strength, percent of optimum moisture content, percent moisture content, degree of saturation, confining stress, deviator stress, and MR. Once developed, the ANNs were embedded in a soil utility model. This soil utility model has several features to help users prepare the required input data for the MR prediction using the developed ANNs and analyze the outcome. These features included discrepancy estimator, an optimum moisture content estimator using a one point proctor data inquiry for similarly matched soil data sets, a basic sensitivity analysis tool, Histogram of each key required parameter, a summary report, unit conversions, the Ohio classification system, a California bearing ratio estimator, soil unconfined compressive strength (qu) estimator, and MR estimators using the developed ANNS, the algorithms defined by the M-E PDG, or the Ohio department transportation (ODOT). These ANN regression algorithms can be used as an advisory tool which predicts MR for the M-E PDG model. Some advantages of the ANN models as a regression analysis tool were that no pre-determined relationship is required. The ANN algorithms can learn from the data to handle non-linear problems. Disadvantages are that they provide no explanation on their outcomes. In addition, the results can be overfitted if ANNs are not trained properly. For future studies, statistical techniques, information theory (open full item for complete abstract)

Committee: Fabian Tan (Advisor) Subjects:

Doctor of Philosophy, The Ohio State University, 2004, Civil Engineering

The objective of this study was to evaluate existing constitutive models currently used by State Department of Transportations (DOTs) and to develop an improved model for predicting resilient modulus (Mr) of cohesive soils from simple soil properties typically measured in DOT laboratories in preference to expensive and complex Mr laboratory testing. The data set used consisted of cohesive soils typical of those used for subgrades in Ohio. Thirteen representative cohesive soils representing A-4, A-6, and A-7-6 soil types collected from road construction sites across Ohio, were tested in the laboratory to determine their basic engineering properties. Mr tests were conducted at three different moisture contents (dry of optimum moisture content, optimum moisture content, and wet of optimum moisture content). Additional tests were performed on samples compacted to optimum conditions but allowed to fully saturate. Mr predicted from six existing models studied showed wide scatter and poor correlation with the measured Mr. An improved constitutive model was developed to account for the effects on Mr of the stress state of the soil and its engineering properties obtained from simple laboratory tests. While most of the existing models investigated in this study significantly overestimated the Mr of a cohesive soil, the proposed model predictions are close to the experimental values and are in most cases a slight underestimation. This implies that Mr values predicted by the proposed model are generally slightly conservative, and can be safely used in the design of flexible pavements to be built on cohesive soils. The proposed model can be a useful and reliable tool for estimating Mr of cohesive subgrade soils using basic soil properties and the stress state of the soil.

Committee: Frank Croft (Advisor) Subjects: Engineering, Civil

Master of Science (MS), Ohio University, 1989, Civil Engineering (Engineering)

The resilient behavior is a significant parameter in the design, rehabilitation and serviceability of pavements. Resilient behavior is defined as the ratio of repeated deviator stress to that of recoverable strain. It has been found subgrade resilient modulus plays a vital role in the serviceability of flexible pavement and the object of this thesis to back calculate the subgrade resilient modulus of flexible pavements from data obtained from nondestructive testing using Dynaflect and Falling Weight Deflectometer(FWD) A research procedure to determine the value of resilient modulus from nondestructive data is formulated. To conduct experiments in the laboratory for arriving at the characteristics of resilient modulus is elaborate, cumbersome, time consuming and it requires advanced equipments to simulate the conditions the pavement is undergoing during all seasons. To overcome this, nondestructive testing of pavements is selected for obtaining the material properties for rehabilitation and reconstruction. The FWD and Dyanaflect are the nondestructive devices used in this study. The locations selected for this study are located at Auglaize, Fairfield and Vinton counties in Ohio. Nondestructive testing has been conducted on one flexible pavement at each county and the data is stored magnetic disks for analysis. Statistical analysis has been conducted for all data collected and a mean value of each sensor deflection is arrived to examine season and load variations. Using the Illipave finite element program and Illipave models the resilient modulus of subgrade material is back-calculated based on the interpretation of deflection measurements obtained from nondestructive testing. In the back-calculation- technique deflection of pavements at distinct locations along the highway measured with nondestructive testing device is used as input. Soil response parameters are assumed for finite element solution. The predicted response is then compared with measured deflections and (open full item for complete abstract)

Committee: S. Sargand (Advisor) Subjects:

Master of Science (MS), Ohio University, 1995, Civil Engineering (Engineering)

Predicting resilient modulus of highway subgrade soils in Ohio

Committee: Shad Sargand (Advisor) Subjects: Engineering, Civil

Doctor of Philosophy, University of Akron, 2007, Civil Engineering

Providing adequate drainage to a pavement system has been considered as an important design consideration to prevent premature failures due to water related problems such as pumping action, loss of support, and rutting, among others. As a result, permeable bases with drainage efficiency and structural stability characteristics have been widely used by several state DOTs in the design and construction of pavements. The Ohio Department of Transportation (ODOT) has adopted several types of materials specification for use as permeable bases: (a) unbounded base materials including: 307-IA,307-NJ, and 307-CE types, (b) stabilized base materials including: cement and asphalt treated base types. The main objective of this research is to study the performance of different permeable base materials used by the Ohio Department of Transportation (ODOT). Field monitored data combined with laboratory result data are used to determine the drainage efficiency of different permeable base materials used by ODOT. Analysis using Multi-Layer Linear Elastic Analysis (MLEA) and data obtained from field backcalculated resilient modulus are used to predict pavement service life for pavement section with different permeable base materials. To account for effect of environmental factors in pavement design, the Enhanced Integrated Climatic Model was used to predict temperature, moisture and frost depth data at the Project Site, Ohio. Comparisons were made between the predicted and measured moisture contents and temperature along the depth of pavement sections as well as frost depth at different times during the simulation period. Analysis was conducted to study the caracterization of permeable base materials in the new Mechanistic-Empirical Pavement Design Guide (MEPDG). Flexible pavement designs and performance derived from the MEPDG approach are compared for different base materials over a range of asphalt concrete layer thicknesses, base materials, subgrade and other material properties. As (open full item for complete abstract)

Committee: Robert Liang (Advisor) Subjects: Engineering, Civil