Doctor of Philosophy (PhD), Wright State University, 2006, Engineering PhD

In structural design, every component or system needs to be tested to ascertain that it satisfies the desired safety levels. Due to the uncertainties associated with the operating conditions, design parameters, and material systems, this task becomes complex and expensive. Typically these uncertainties are defined using random, interval or fuzzy variables, depending on the information available. Analyzing components or systems in the presence of these different forms of uncertainty increases the computational cost considerably due to the iterative nature of these algorithms. Therefore, one of the objectives of this research was to develop methodologies that can efficiently handle multiple forms of uncertainty. Most of the work available in the literature about uncertainty analysis deals with the estimation of the safety of a structural component based on a particular performance criterion. Often an engineering system has multiple failure criteria, all of which are to be taken into consideration for estimating its safety. These failure criteria are often correlated, because they depend on the same uncertain variables and the accuracy of the estimations highly depend on the ability to model the joint failure surface. The evaluation of the failure criteria often requires computationally expensive finite element analysis or computational fluid dynamics simulations. Therefore, this work also focuses on using high fidelity models to efficiently estimate the safety levels based on multiple failure criteria. The use of high fidelity models to represent the limit-state functions (failure criteria) and the joint failure surface facilitates reduction in the computational cost involved, without significant loss of accuracy. The methodologies developed in this work can be used to propagate various types of uncertainties through systems with multiple nonlinear failure modes and can be used to reduce prototype testing during the early design process. In this research, fast Fourier (open full item for complete abstract)

Committee: Ravi Penmetsa (Advisor) Subjects:

PhD, University of Cincinnati, 2010, Engineering and Applied Science: Civil Engineering

Proper collection and transmission of wastewater within pipe systems is of utmost importance to minimize public health problems and environmental contamination resulting from discharge of untreated sewage. However, due to reactive management strategies, overall condition status of wastewater systems has reached a sub-standard level. Moreover, budget restrictions due to competing needs are preventing sewer agencies from addressing inspection and repair/renewal of every deficient pipe. Therefore, sewer agencies are in dire need of establishing risk assessment tools in order to optimize use of limited resources by prioritizing inspection and/or renewal needs of sewer pipes. The objective of this dissertation is to develop such a risk assessment tool at an individual pipe level by combining the probability of failure values determined by statistical deterioration modeling of sewer pipes and consequences of failure values determined by examining the geographical, physical, and functional attributes of sewer pipes in the light of expert opinions that reflect the relative importance of these attributes. In order to determine probability of failure values, three statistical methods, namely ordinal regression (proportional odds model), multinomial logistic regression, and binary logistic regression, were employed in successive steps. Five ordinal regression models were generated by using logit, probit, negative log-log, complementary log-log, and cauchit link functions. Proportional odds assumption of ordinal regression was tested for each model; however, due to unsatisfactory results, ordinal regression was excluded from further analysis. Based on the percentage of correct predictions, binary logistic regression was deemed to be the most suitable method for predicting probability of failure. Consequences of failure values were determined based on a weighted scoring system. This method was selected due to uncertainties associated with direct costs of sewer failures and the (open full item for complete abstract)

Committee: Ossama Salem PhD (Committee Chair); Richard Miller PhD (Committee Member); Mark Bowers PhD (Committee Member); Ala Tabiei PhD (Committee Member) Subjects: Civil Engineering

Doctor of Philosophy, The Ohio State University, 2009, Mechanical Engineering

Bonded layered structures are widely used to meet high performance requirements that a single layer material cannot satisfy. All layered structures have a finite service life due to inevitable failures caused by chemical, thermal or mechanical loadings during operation. The inevitability of failure in a bonded layered structure demands the prediction of the service life for layered structures, and this requires understanding of the failure mechanism. The failure of bonded layered structures often initiates from a crack at surface, a crack at interface, or interfacial delamination. Failures due to surface fracture or interfacial delamination have been widely studied. However, brittle fractures originating at the interface have not been extensively investigated. In this work, the failures of bonded layered structures due to cracks/flaws initiating at the interface are investigated. A cracked bilayer domain analysis is first presented for estimation of the SIF for a 3D half-penny shaped crack originating at a bonded interface in idealized bilayer geometry subjected to remote constant tensile and proportional bending loadings. Handbook-type curve-fitted equations are obtained for the SIF as a function of modulus ratio of bonded dissimilar materials through extensive finite element parametric studies. The cracked bilayer domain analysis is then combined with macro-level stress calculations in a structure without a crack (uncracked body analysis), and a simplified method is proposed for accurate estimation of the SIF. The cracked bilayer domain analysis is extended to estimation of the SIF of a half-penny shaped crack normal to the interface in the top layer of a three-layer bonded structure. To obtain a simple estimate of the SIF, the method of reduction of an idealized cracked trilayer domain to that of a corresponding bilayer domain has been introduced based on the notion of an equivalent homogeneous material for the two bottom layers. Based on the cracked bilayer/tr (open full item for complete abstract)

Committee: Noriko Katsube PhD (Advisor); Robert Seghi DDS (Committee Member); Stanislav Rokhlin PhD (Committee Member); Mark Walter PhD (Committee Member) Subjects: Aerospace Materials; Architecture; Armed Forces; Civil Engineering; Computer Science; Design; Engineering; Industrial Engineering; Materials Science; Mechanical Engineering; Mechanics; Metallurgy; Statistics

Master of Science (MS), Ohio University, 2019, Industrial and Systems Engineering (Engineering and Technology)

This thesis develops a framework to locate critical infrastructure (CI) facilities to most fully capitalize on the supporting stations (SS) they depend on for normal operation. CI facilities include health services, transportation and electricity; agencies that impact the national economy, security and the public's health and wellbeing. SSs are facilities that provide essential services for the regular operation of a CI. For instance, the power service, communication services and water supply services are SS for the Hospital. SS are independent from the CIs that they service but have a heterogeneous probability of failure that will cripple the dependent CI. The proposed framework ranks the SS according to its cost of providing service, it incorporates the probability of failure for the SS, and determines both the optimal location of the CI and the optimal numbers of demand served. A mixed integer linear programming approach is applied to develop a Reliable Facility Location Problem considering Supporting Stations (RFLP-SS) to identify the optimal location to build a critical facility. In addition to that, The RFLP-SS determines the capacity of the optimally located facility and its allocated demands. This research highlights the importance of considering dependencies among the supporting stations that service Critical Infrastructure (CI). The thesis presents a case study in Puerto Rico to demonstrate the applicability of the proposed framework. The case study investigates the status of health services in Puerto Rico and identifies the optimal locations to establish new hospitals. The thesis recommends 11 optimal locations for new hospitals so that the people of Puerto Rico will be better served than they are currently.

Committee: Felipe Aros-Vera PhD (Committee Chair) Subjects: Operations Research

Doctor of Philosophy, University of Akron, 2017, Civil Engineering

In an effort to provide safe roadways for the traveling public, transportation agencies are challenged with combating snow and ice events throughout certain regions of the country. In order to combat these events, winter maintenance fleets are designed to mechanically and chemically remove the snow and ice from the roadways. These snow and ice removal practices require labor, equipment, and materials; therefore, snow and ice removal requires much of the transportation maintenance budget. This dissertation examines how to use winter maintenance operational data in various methods in order to improve, optimize, or justify winter maintenance operations. This dissertation will review three areas within the winter maintenance practices that may benefit from data analytics. The first analysis conducted reviewed the mechanical snow removal equipment, specifically the plow blades. These plow blades makes contact with the roadway and eventually will wear down and need to be replaced. There are several types of blades on the market which have been shown to wear at a lower rate in comparison to the current standard flame harden steel blades. Using these blade data and county data (truck number, lane-miles treated, and weather received), the probability of failure for each blade type at different quantities used per year (1 to 10 blades) for each county may be modeled. Overall these findings present that the specialty blades have a much lower probability of failure due to the low wear rate on each of them. Chemically removing snow and ice from roadways to keep the traveling public safe is highly expensive for transportation agencies. Liquid deicers have been shown to assist in chemical removal process. One common liquid deicer utilized is brine because it is made with NaCl and water in-house at a low cost. Using in-field data and lab data these chemical removal practices may be determined. These results may highly impact winter maintenance operations. The field data (open full item for complete abstract)

Committee: William Schneider PhD (Advisor); Christopher Miller PhD (Committee Member); Qindan Huang PhD (Committee Member); Stephen Duirk PhD (Committee Member); Shivakumar Sastry PhD (Committee Member) Subjects: Civil Engineering; Transportation

Master of Science in Engineering, University of Akron, 2017, Civil Engineering

In design of supported excavation, many codes and criteria can be utilized to insure the usability and stability of excavation structure. However, due to the variation and spatial variability in soil parameters, the deterministic analysis in codes may not always be safe. This paper considers the uncertainties of standard penetration blow count ((N1)60) and execute reliability analysis on the geotechnical and structural responses in supported excavation in sand, including lateral wall deflection, bending moment in wall, shear force in wall and strut force. Random field theory is adopted to generate values of (N1)60 considering effect of variation and spatial variability on sand layers. Different levels of COV and scale of fluctuation are considered to simulate various scenarios in the real field. Random finite element method and Monte-Carlo simulation are used to execute reliability analysis and the failure probabilities of multiple failure modes are estimated. An automation procedure is purposed to enhance the efficiency and accuracy in parameters input and results output. The importance and influence of spatial variability on the design of supported excavation are shown according to the analysis results.

Committee: Zhe Luo (Advisor); Junliang Tao (Committee Member); Qindan Huang (Committee Member) Subjects: Civil Engineering

Master of Science in Engineering, University of Akron, 2017, Civil Engineering

The Ohio Department of Transportation (ODOT) uses approximately 700,000 tons of salt per year to keep their roads safe of icy conditions during the winter. Recently, ODOT has been experiencing extreme salt pricing in response to their county-by-county bid process. As a result, ODOT's annual cost for snow and ice removal reached approximately $86 million from its maintenance budget. The majority of expenses are accumulated by the procurement of rock salt. In order to identify recommendations for ODOT processes, a matrix of best and current practices was developed at the national, state, and city-level pertaining to winter maintenance. A thorough evaluation of variables which affect salt pricing was conducted. The transportation of salt as well as the delivery times were analyzed. It was concluded that winter salt orders, although modeled over $6.00 less expensive than summer, run a much higher risk of being delivered late. Therefore, a ten-step storage facility evaluation process was created to determine the vulnerability of a storage facility, the estimated cost to increase the capacity, and whether the facility may act as a regional storage location. This process gives ODOT the necessary tools to evaluate their storage facilities on a case-by-case basis due to the diverse environments such as weather found throughout the state of Ohio.

Committee: William Schneider IV Ph.D., P.E. (Advisor); Teresa Cutright Ph.D. (Committee Member); Qindan Huang Ph.D. (Committee Member) Subjects: Civil Engineering

Master of Science, University of Akron, 0, Civil Engineering

The amount of alcohol-related crashes in the United States has remained consistent since 1994. There are many methods law enforcement officials have used in order to try and reduce the amount of alcohol-related crashes, as well as deter drivers from driving intoxicated; however there remains much room for improvement. One method commonly used in today's society is through the use of overtime officers patrolling for intoxicated drivers through saturation or corridor patrols. Though these methods may be seen as effective, the lack of reduction in alcohol-related crashes remains a problem. The National Highway Traffic Safety Administration utilizes Data Driven Approaches to Crime and Traffic Safety, which improves methods of enforcement through the use of hot spots created by location-based crime and crashes. The goal of this research is to reduce the amount of alcohol-related crashes by introducing a new means of patrolling through data-driven methodologies. The results of hot spot maps for a number of counties are utilized in order to move forward in the development of a new method of patrolling. The hot spot maps are broken down into local indicators of spatial association, which show statistically significant locations where intoxicated drivers are likely to be present. Route optimization models are then used to guide officers to these locations. These models are compared with traditional methods of corridor patrolling through a series of performance metrics. Failure probability models are then created to further compare the two methods of patrolling, as well as aiding captains of jurisdictions in decision-making processes. By utilizing location-based hot spots, new methodologies of patrolling may be developed in order to reduce the amount of alcohol-related crashes. This new method of patrolling will guide officers to statistically significant locations, allowing them to be more accurate while patrolling for intoxicated drivers. Additionally, this method prove (open full item for complete abstract)

Committee: William Schneider IV Dr. (Advisor); Christopher Miller Dr. (Committee Member); Stephen Duirk Dr. (Committee Member) Subjects: Civil Engineering; Transportation

Master of Science, University of Toledo, 2016, Civil Engineering

This thesis is an initial investigation into developing guidelines and criteria for reliability based inspection of overhead sign supports, bridge mounted sign supports, high light mast supports and signal supports. The desired result of reliability based inspection is to use the support condition and age to determine the inspection interval and depth of inspection to keep the all the supports in the inventory at a desired level of safety while economizing on the resources required to perform inspections. Ohio's inventory of supports is aging and it is important to safely and economically make decisions about inspection, maintenance and replacement. Currently, the Ohio Department of Transportation (ODOT) routinely performs qualitative ground based inspection of its supports. Per ODOT's inspection guidelines, overhead sign supports are inspected once every five years; bridge mounted sign supports and signal supports are inspected annually and there is no formal requirement for high light mast support structural inspections. The literature and standards on support inspection were reviewed. No previous work on reliability based inspection of supports was found. Due to the absence of reliability based inspection models for supports, the concepts of reliability based bridge inspection program were adopted to support inspection. In this study, the reliability of ODOT's ground based inspection and detailed inspection results for a sample of Ohio's supports were assessed to estimate the probability of failure of the supports and evaluate the probability of detection of the support inspection. Based on this assessment, a cost effective reliability based support inspection model was suggested and a model inspection form was provided. Reliability based inspection depends in large part on the accuracy of the inventory and depth of previous inspections. A limitation of the results of this study is that the available database does not have the temporal data necessary t (open full item for complete abstract)

Committee: Douglas Nims (Advisor); Mark Pickett (Committee Member); Liangbo Hu (Committee Member) Subjects: Civil Engineering

Doctor of Philosophy, University of Akron, 2013, Civil Engineering

With the implementation of load and resistance factor design (LRFD) by the U.S. Federal Highway Administration, the design of deep foundations is migrating from Level I (e.g., allowable stress design) codes to Level II codes (e.g., LRFD). Nevertheless, there are still unsolved issues regarding the implementation of load and resistance factor design. For example, there is no generally accepted guidance on the statistical characterization of soil properties. Moreover, the serviceability limit check in LRFD is still deterministic. No uncertainties arising in soil properties, loads and design criteria are taken into account in the implementation of LRFD. In current practice, the load factors and resistances are taken as unity, and deterministic models are applied to evaluate the displacements of geotechnical structures. In order to address the aforementioned issues of LRFD, there is a need for a computational method for conducting reliability analysis and computational tools for statistically characterizing the variability of soil properties. The objectives of this research are: 1) to develop a mathematically sound computational tool for conducting reliability analysis for deep foundations; and 2) to develop the associated computational method that can be used to determine the variability model of a soil property. To achieve consistency between the strength limit check and the serviceability limit check of the LRFD framework, performance-based design methodology is developed for deep foundation design. In the proposed methodology, the design criteria are defined in terms of the displacements of the structure that are induced by external loads. If the displacements are within the specified design criteria, the design is considered satisfactory. Otherwise, failure is said to occur. In order to calculate the probability of failure, Monte Carlo simulation is employed. In Monte Carlo simulation, the variability of the random variables that are involved in the reliability a (open full item for complete abstract)

Committee: Robert Liang Dr. (Advisor); Lan Zhang Dr. (Committee Member); Qindan Huang Dr. (Committee Member); Xiaosheng Gao Dr. (Committee Member); Chien-Chung Chan Dr. (Committee Member) Subjects: Civil Engineering; Statistics

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

Layered structures have been widely used in industrial and military applications to protect substrates from environmental effects. The same strategy has been applied to medical implants and various dental restorations such as complete and partial veneering of teeth with ceramics to protect the remaining tooth structure. We experimentally and theoretically investigate the failure mechanisms of a simple brittle layered structure subjected to a static indentation load. For this problem, cracks were observed to initiate from either the top or the bottom surface of the top layer depending on the top layer thickness, the material properties of the layers, and the indenter size. In order to model the experimentally observed variation of critical indentation load, a statistical theory with flaw distribution in brittle specimens is employed. First, we examined an existing fracture mechanics based statistical theory. We pointed out the premature use of infinitesimally small volumetric element assumption in the theoretical derivation of the failure probability prediction formula and proposed an alternative form of prediction formula. Second, using indentation tests on monolithic materials we test the hypothesis that the failure probability model developed by Fischer-Cripps and Collins (1994) can be used without introducing an empirically derived parameter and therefore can serve as a predictive tool for a cone crack imitation in a monolithic solid. Third, the above methods are modified to a layered structure, and multi-axial stress states of indentation is taken into account in the failure probability analysis. Two modes of failures, a Hertzian cone crack initiating from the contacting surface and a half-penny-shaped crack initiating from the interface, are theoretically predicted and compared with experimental data. Fourth, a finite half-penny-shaped crack perpendicular to the interfacial surface was introduced at the bottom surface of the top layer. The effect of interfacial (open full item for complete abstract)

Committee: Noriko Katsube (Advisor) Subjects: Applied Mechanics

Master of Science in Engineering, University of Akron, 2009, Mechanical Engineering

Cleavage fracture has been a very important subject for engineers for a long time because of the catastrophic result it may cause. The experimental results of cleavage fracture exhibit a large amount of scatter and show significant constraint effect, which motivated the development of statistical and micromechanics based methods in order to deal with such problem. The Weibull stress model, which is based on the weakest link statistics, uses two parameters, m and σu, to describe the inherent distribution of the micro-scale cracks once the plastic deformation has occurred and to define the relationship between the macro and micro-scale driving forces for cleavage fracture. In this paper we examine constraint effects on cleavage fracture toughness numerically using a constraint function g(M) derived from the Weibull stress model. The non-dimensional function g(M) describes the evolution of constraint loss effects on fracture toughness relative to reference plane-strain small scale yielding (SSY) condition (T-stress = 0). We performed detailed finite element analyses of single-edge notched bending specimens and compute g(M) functions for them. The g-function varies with parameters of the Weibull stress model, material flow properties and specimen geometry but not with absolute specimen size. Knowing the g-function one can construct fracture driving force curves for each absolute size of interest.

Committee: Xiaosheng Gao PhD (Advisor) Subjects: Mechanical Engineering