Compatibility of ultra high performance concrete as repair material : bond characterization with concrete under different loading scenarios

The rehabilitation of concrete structures, especially concrete bridge decks, is a major challenge for transportation agencies in the United States. Often, the most appropriate strategy to preserve or rehabilitate these structures is to provide some form of a protective coating or barrier. These surface treatments have typically been some form of polymer, asphalt, or low-permeability concrete, but the application of UHPC has shown promise for this application mainly due to its negligible permeability, but also as a result of its excellent mechanical properties, self-consolidating nature, rapid gain strength, and minimal creep and shrinkage characteristics. However, for widespread acceptance, durability and performance of the composite system must be fully understood, specifically the bond between UHPC and NSC often used in bridge decks. It is essential that the bond offers enough strength to resist the stress due to mechanical loading or thermal effects, while also maintaining an extended service-life performance. This report attempts to assess the bond strength between UHPC and NSC under different loading configurations. Different variables, such as roughness degree of the concrete substrates, age of bond, exposure to freeze-thaw cycles and wetting conditions of the concrete substrate, were included in this study. The combination of splitting tensile test with 0, 300, 600 and 900 freeze-thaw cycles was carried out to assess the bond performance under severe ambient conditions. The slant-shear test was utilized with different interface angles to provide a wide understanding of the bond performance under different combinations of compression and shear stresses. The pull-off test is the most accepted method to evaluate the bond strength in the field. This test which studies the direct tensile strength of the bond, the most severe loading condition, was used to provide data that can be correlated with the other tests that only can be used in the laboratory. The experimental program showed that the bond performance between UHPC and NSC is successful, as the strength regardless the different degree of roughness of the concrete substrate, the age of the composite specimens, the exposure to freeze-thaw cycles and the different loading configurations, is greater than that of concrete substrate and largely satisfies with ACI 546.3R-06.

Creep and shrinkage behavior of ultra high-performance concrete under compressive loading with varying curing regimes

This Ultra High Performance Concrete research involves observing early-age creep and shrinkage under a compressive load throughout multiple thermal curing regimes. The goal was to mimic the conditions that would be expected of a precast/prestressing plant in the United States, where UHPC beams would be produced quickly to maximize a manufacturing plant’s output. The practice of steam curing green concrete to accelerate compressive strengths for early release of the prestressing tendons was utilized (140°F [60°C], 95% RH, 14 hrs), in addition to the full thermal treatment (195°F [90°C], 95% RH, 48 hrs) while the specimens were under compressive loading. Past experimental studies on creep and shrinkage characteristics of UHPC have only looked at applying a creep load after the thermal treatment had been administered to the specimens, or on ambient cured specimens. However, this research looked at mimicking current U.S. precast/prestressed plant procedures, and thus characterized the creep and shrinkage characteristics of UHPC as it is thermally treated under a compressive load. Michigan Tech has three moveable creep frames to accommodate two loading criteria per frame of 0.2f’ci and 0.6f’ci. Specimens were loaded in the creep frames and moved into a custom built curing chamber at different times, mimicking a precast plant producing several beams throughout the week and applying a thermal cure to all of the beams over the weekend. This thesis presents the effects of creep strain due to the varying curing regimes. An ambient cure regime was used as a baseline for the comparison against the varying thermal curing regimes. In all cases of thermally cured specimens, the compressive creep and shrinkage strains are accelerated to a maximum strain value, and remain consistent after the administration of the thermal cure. An average creep coefficient for specimens subjected to a thermal cure was found to be 1.12 and 0.78 for the high and low load levels, respectively. Precast/pressed plants can expect that simultaneously thermally curing UHPC elements that are produced throughout the week does not impact the post-cure creep coefficient.

Detection of complex point targets with distributed assets in a MIMO radar system

The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.

Influence of traumatic impaction and pathological loading on knee menisci

Nearly half of the US population faces the risk of developing knee osteoarthritis (OA). Both in vitro and in vivo studies can aid in a better understanding of the etiology, progression, and advancement of this debilitating disorder. The knee menisci are fibrocartilagenous structures that aid in the distribution of load, attenuation of shock, alignment and lubrication of the knee. Little is known about the biochemical and morphological changes associated with knee menisci following altered loading and traumatic impaction, and investigations are needed to further elucidate how degradation of this soft tissue advances over time. The biochemical response of porcine meniscal explants was investigated following a single bout of dynamic compression with and without the treatment of the pharmaceutical drug, anakinra (IL-1RA). Dynamic loading led to a strain-dependent response in both anabolic and catabolic gene expression of meniscal explants. By inhibiting the Interleukin-1 pathway with IL-1RA, a marked decrease in several catabolic molecules was found. From these studies, future developments in OA treatments may be developed. The implementation of an in vivo animal model contributes to the understanding of how the knee joint behaves as a whole. A novel closed-joint in vivo model that induces anterior cruciate ligament (ACL) rupture has been developed to better understand how traumatic injury leads to OA. The menisci of knees from three different groups (healthy, ACL transected, and traumatically impacted) were characterized using histomorphometry. The acute and chronic changes within the knee following traumatic impaction were investigated. The works presented in this dissertation have focused on the characterization, implementation, and development of mechanically-induced changes to the knee menisci.

Modeling mechanical response of heterogeneous materials

Heterogeneous materials are ubiquitous in nature and as synthetic materials. These materials provide unique combination of desirable mechanical properties emerging from its heterogeneities at different length scales. Future structural and technological applications will require the development of advanced light weight materials with superior strength and toughness. Cost effective design of the advanced high performance synthetic materials by tailoring their microstructure is the challenge facing the materials design community. Prior knowledge of structure-property relationships for these materials is imperative for optimal design. Thus, understanding such relationships for heterogeneous materials is of primary interest. Furthermore, computational burden is becoming critical concern in several areas of heterogeneous materials design. Therefore, computationally efficient and accurate predictive tools are highly essential. In the present study, we mainly focus on mechanical behavior of soft cellular materials and tough biological material such as mussel byssus thread. Cellular materials exhibit microstructural heterogeneity by interconnected network of same material phase. However, mussel byssus thread comprises of two distinct material phases. A robust numerical framework is developed to investigate the micromechanisms behind the macroscopic response of both of these materials. Using this framework, effect of microstuctural parameters has been addressed on the stress state of cellular specimens during split Hopkinson pressure bar test. A voronoi tessellation based algorithm has been developed to simulate the cellular microstructure. Micromechanisms (microinertia, microbuckling and microbending) governing macroscopic behavior of cellular solids are investigated thoroughly with respect to various microstructural and loading parameters. To understand the origin of high toughness of mussel byssus thread, a Genetic Algorithm (GA) based optimization framework has been developed. It is found that two different material phases (collagens) of mussel byssus thread are optimally distributed along the thread. These applications demonstrate that the presence of heterogeneity in the system demands high computational resources for simulation and modeling. Thus, Higher Dimensional Model Representation (HDMR) based surrogate modeling concept has been proposed to reduce computational complexity. The applicability of such methodology has been demonstrated in failure envelope construction and in multiscale finite element techniques. It is observed that surrogate based model can capture the behavior of complex material systems with sufficient accuracy. The computational algorithms presented in this thesis will further pave the way for accurate prediction of macroscopic deformation behavior of various class of advanced materials from their measurable microstructural features at a reasonable computational cost.

Optimal game theoretic distributed control methodologies in small scale power systems

This dissertation presents the competitive control methodologies for small-scale power system (SSPS). A SSPS is a collection of sources and loads that shares a common network which can be isolated during terrestrial disturbances. Micro-grids, naval ship electric power systems (NSEPS), aircraft power systems and telecommunication system power systems are typical examples of SSPS. The analysis and development of control systems for small-scale power systems (SSPS) lacks a defined slack bus. In addition, a change of a load or source will influence the real time system parameters of the system. Therefore, the control system should provide the required flexibility, to ensure operation as a single aggregated system. In most of the cases of a SSPS the sources and loads must be equipped with power electronic interfaces which can be modeled as a dynamic controllable quantity. The mathematical formulation of the micro-grid is carried out with the help of game theory, optimal control and fundamental theory of electrical power systems. Then the micro-grid can be viewed as a dynamical multi-objective optimization problem with nonlinear objectives and variables. Basically detailed analysis was done with optimal solutions with regards to start up transient modeling, bus selection modeling and level of communication within the micro-grids. In each approach a detail mathematical model is formed to observe the system response. The differential game theoretic approach was also used for modeling and optimization of startup transients. The startup transient controller was implemented with open loop, PI and feedback control methodologies. Then the hardware implementation was carried out to validate the theoretical results. The proposed game theoretic controller shows higher performances over traditional the PI controller during startup. In addition, the optimal transient surface is necessary while implementing the feedback controller for startup transient. Further, the experimental results are in agreement with the theoretical simulation. The bus selection and team communication was modeled with discrete and continuous game theory models. Although players have multiple choices, this controller is capable of choosing the optimum bus. Next the team communication structures are able to optimize the players’ Nash equilibrium point. All mathematical models are based on the local information of the load or source. As a result, these models are the keys to developing accurate distributed controllers.

DISTRIBUTED APPROACH FOR SOLVING OPTIMAL POWER FLOW PROBLEMS IN THREE-PHASE UNBALANCED DISTRIBUTION NETWORK

The objective of this report is to study distributed (decentralized) three phase optimal power flow (OPF) problem in unbalanced power distribution networks. A full three phase representation of the distribution networks is considered to account for the highly unbalance state of the distribution networks. All distribution network’s series/shunt components, and load types/combinations had been modeled on commercial version of General Algebraic Modeling System (GAMS), the high-level modeling system for mathematical programming and optimization. The OPF problem has been successfully implemented and solved in a centralized approach and distributed approach, where the objective is to minimize the active power losses in the entire system. The study was implemented on the IEEE-37 Node Test Feeder. A detailed discussion of all problem sides and aspects starting from the basics has been provided in this study. Full simulation results have been provided at the end of the report.