Air-coupled ultrasonic tomographic imaging of concrete elements

Ultrasonic tomography is a powerful tool for identifying defects within an object or structure. This method can be applied on structures where x-ray tomography is impractical due to size, low contrast, or safety concerns. By taking many ultrasonic pulse velocity (UPV) readings through the object, an image of the internal velocity variations can be constructed. Air-coupled UPV can allow for more automated and rapid collection of data for tomography of concrete. This research aims to integrate recent developments in air-coupled ultrasonic measurements with advanced tomography technology and apply them to concrete structures. First, non-contact and semi-contact sensor systems are developed for making rapid and accurate UPV measurements through PVC and concrete test samples. A customized tomographic reconstruction program is developed to provide full control over the imaging process including full and reduced spectrum tomographs with percent error and ray density calculations. Finite element models are also used to determine optimal measurement configurations and analysis procedures for efficient data collection and processing. Non-contact UPV is then implemented to image various inclusions within 6 inch (152 mm) PVC and concrete cylinders. Although there is some difficulty in identifying high velocity inclusions, reconstruction error values were in the range of 1.1-1.7% for PVC and 3.6% for concrete. Based upon the success of those tests, further data are collected using non-contact, semi-contact, and full contact measurements to image 12 inch (305 mm) square concrete cross-sections with 1 inch (25 mm) reinforcing bars and 2 inch (51 mm) square embedded damage regions. Due to higher noise levels in collected signals, tomographs of these larger specimens show reconstruction error values in the range of 10-18%. Finally, issues related to the application of these techniques to full-scale concrete structures are discussed.

Finite difference calculations of permeability in large domains in a wide porosity range.

Determining effective hydraulic, thermal, mechanical and electrical properties of porous materials by means of classical physical experiments is often time-consuming and expensive. Thus, accurate numerical calculations of material properties are of increasing interest in geophysical, manufacturing, bio-mechanical and environmental applications, among other fields. Characteristic material properties (e.g. intrinsic permeability, thermal conductivity and elastic moduli) depend on morphological details on the porescale such as shape and size of pores and pore throats or cracks. To obtain reliable predictions of these properties it is necessary to perform numerical analyses of sufficiently large unit cells. Such representative volume elements require optimized numerical simulation techniques. Current state-of-the-art simulation tools to calculate effective permeabilities of porous materials are based on various methods, e.g. lattice Boltzmann, finite volumes or explicit jump Stokes methods. All approaches still have limitations in the maximum size of the simulation domain. In response to these deficits of the well-established methods we propose an efficient and reliable numerical method which allows to calculate intrinsic permeabilities directly from voxel-based data obtained from 3D imaging techniques like X-ray microtomography. We present a modelling framework based on a parallel finite differences solver, allowing the calculation of large domains with relative low computing requirements (i.e. desktop computers). The presented method is validated in a diverse selection of materials, obtaining accurate results for a large range of porosities, wider than the ranges previously reported. Ongoing work includes the estimation of other effective properties of porous media.

Long-term influence of chitin concentration on the resistance of cement pastes determined by atomic force microscopy

The presence of sulfates potentialize damage on cementbased materials, leading to structural failures. Therefore, structures must be designed to compensate for this effect. The mechanical properties of cement–chitin mixtures are investigated with different percentages of chitin (0.5, 1.3, and 2.1 wt.%) and aging of composite in a joint nanoscopic- and macroscopic-scale by experimental study. The objective is to increase the durability of concrete elements at coastal aquifers where concrete structures are in constant exposure to sulfate ions, chloride ions among others. Tapping mode AFM was used to characterize the surface structure and roughness of the cement pastes. To verify the chitin addition and the formation of sulfate-based aggregates Raman and IR spectra were recorded and are presented in this work. Then, force spectroscopy was used to obtain the nanomechanical properties at three different exposure times (1 day, 6 months, and 1 year) into water or a SO4 2 environment. Macroscopic parameters (e.g., compression strength of cylindrical probes) were assessed for comparison following standard guidelines. The results show a decrease of its mechanical properties as a function of the polymer concentration but more importantly, they correlate the elasticity and adhesion at the nanoscale with the behavior of the bulk material.

Development of Physics-based Models and Design Optimization of Power Electronic Conversion Systems

The main objective for physics based modeling of the power converter components is to design the whole converter with respect to physical and operational constraints. Therefore, all the elements and components of the energy conversion system are modeled numerically and combined together to achieve the whole system behavioral model. Previously proposed high frequency (HF) models of power converters are based on circuit models that are only related to the parasitic inner parameters of the power devices and the connections between the components. This dissertation aims to obtain appropriate physics-based models for power conversion systems, which not only can represent the steady state behavior of the components, but also can predict their high frequency characteristics. The developed physics-based model would represent the physical device with a high level of accuracy in predicting its operating condition. The proposed physics-based model enables us to accurately develop components such as; effective EMI filters, switching algorithms and circuit topologies [7]. One of the applications of the developed modeling technique is design of new sets of topologies for high-frequency, high efficiency converters for variable speed drives. The main advantage of the modeling method, presented in this dissertation, is the practical design of an inverter for high power applications with the ability to overcome the blocking voltage limitations of available power semiconductor devices. Another advantage is selection of the best matching topology with inherent reduction of switching losses which can be utilized to improve the overall efficiency. The physics-based modeling approach, in this dissertation, makes it possible to design any power electronic conversion system to meet electromagnetic standards and design constraints. This includes physical characteristics such as; decreasing the size and weight of the package, optimized interactions with the neighboring components and higher power density. In addition, the electromagnetic behaviors and signatures can be evaluated including the study of conducted and radiated EMI interactions in addition to the design of attenuation measures and enclosures.

The Relationship between Faculty Perceptions and Implementation of Elements of Transactional Distance Theory and Online Web-Based Course Completion Rates

The purpose of this study was to explore the relationship between faculty perceptions, selected demographics, implementation of elements of transactional distance theory and online web-based course completion rates. This theory posits that the high transactional distance of online courses makes it difficult for students to complete these courses successfully; too often this is associated with low completion rates. Faculty members play an indispensable role in course design, whether online or face-to-face. They also influence course delivery format from design through implementation and ultimately to how students will experience the course. This study used transactional distance theory as the conceptual framework to examine the relationship between teaching and learning strategies used by faculty members to help students complete online courses. Faculty members’ sex, number of years teaching online at the college, and their online course completion rates were considered. A researcher-developed survey was used to collect data from 348 faculty members who teach online at two prominent colleges in the southeastern part of United States. An exploratory factor analysis resulted in six factors related to transactional distance theory. The factors accounted for slightly over 65% of the variance of transactional distance scores as measured by the survey instrument. Results provided support for Moore’s (1993) theory of transactional distance. Female faculty members scored higher in all the factors of transactional distance theory when compared to men. Faculty number of years teaching online at the college level correlated significantly with all the elements of transactional distance theory. Regression analysis was used to determine that two of the factors, instructor interface and instructor-learner interaction, accounted for 12% of the variance in student online course completion rates. In conclusion, of the six factors found, the two with the highest percentage scores were instructor interface and instructor-learner interaction. This finding, while in alignment with the literature concerning the dialogue element of transactional distance theory, brings a special interest to the importance of instructor interface as a factor. Surprisingly, based on the reviewed literature on transactional distance theory, faculty perceptions concerning learner-learner interaction was not an important factor and there was no learner-content interaction factor.

Physics-Based Modeling of Power System Components for the Evaluation of Low-Frequency Radiated Electromagnetic Fields

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system’s EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter’s components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

Knowledge-based management systems for the police force

Knowledge-Based Management Systems enable new ways to process and analyse knowledge to gain better insights to solve a problem and aid in decision making. In the police force such systems provide a solution for enhancing operations and improving client administration in terms of knowledge management. The main objectives of every police officer is to ensure the security of life and property, promote lawfulness, and avert and distinguish wrongdoing. The administration of knowledge and information is an essential part of policing, and the police ought to be proactive in directing both explicit and implicit knowledge, whilst adding to their abilities in knowledge sharing. In this paper the potential for a knowledge based system for the Mauritius police was analysed, and recommendations were also made, based on requirements captured from interviews with several long standing officers, and surveying of previous works in the area.

A finite-strain solid–shell using local Löwdin frames and least-squares strains

A finite-strain solid–shell element is proposed. It is based on least-squares in-plane assumed strains, assumed natural transverse shear and normal strains. The singular value decomposition (SVD) is used to define local (integration-point) orthogonal frames-of-reference solely from the Jacobian matrix. The complete finite-strain formulation is derived and tested. Assumed strains obtained from least-squares fitting are an alternative to the enhanced-assumed-strain (EAS) formulations and, in contrast with these, the result is an element satisfying the Patch test. There are no additional degrees-of-freedom, as it is the case with the enhanced-assumed-strain case, even by means of static condensation. Least-squares fitting produces invariant finite strain elements which are shear-locking free and amenable to be incorporated in large-scale codes. With that goal, we use automatically generated code produced by AceGen and Mathematica. All benchmarks show excellent results, similar to the best available shell and hybrid solid elements with significantly lower computational cost.

A finite-strain solid–shell using local Löwdin frames and least-squares strains

A finite-strain solid–shell element is proposed. It is based on least-squares in-plane assumed strains, assumed natural transverse shear and normal strains. The singular value decomposition (SVD) is used to define local (integration-point) orthogonal frames-of- reference solely from the Jacobian matrix. The complete finite-strain formulation is derived and tested. Assumed strains obtained from least-squares fitting are an alternative to the enhanced-assumed-strain (EAS) formulations and, in contrast with these, the result is an element satisfying the Patch test. There are no additional degrees-of-freedom, as it is the case with the enhanced- assumed-strain case, even by means of static condensation. Least-squares fitting produces invariant finite strain elements which are shear-locking free and amenable to be incorporated in large-scale codes. With that goal, we use automatically generated code produced by AceGen and Mathematica. All benchmarks show excellent results, similar to the best available shell and hybrid solid elements with significantly lower computational cost.

Seemingly unrelated linear regression for contaminated data based on Gaussian mixtures

In this thesis, new classes of models for multivariate linear regression defined by finite mixtures of seemingly unrelated contaminated normal regression models and seemingly unrelated contaminated normal cluster-weighted models are illustrated. The main difference between such families is that the covariates are treated as fixed in the former class of models and as random in the latter. Thus, in cluster-weighted models the assignment of the data points to the unknown groups of observations depends also by the covariates. These classes provide an extension to mixture-based regression analysis for modelling multivariate and correlated responses in the presence of mild outliers that allows to specify a different vector of regressors for the prediction of each response. Expectation-conditional maximisation algorithms for the calculation of the maximum likelihood estimate of the model parameters have been derived. As the number of free parameters incresases quadratically with the number of responses and the covariates, analyses based on the proposed models can become unfeasible in practical applications. These problems have been overcome by introducing constraints on the elements of the covariance matrices according to an approach based on the eigen-decomposition of the covariance matrices. The performances of the new models have been studied by simulations and using real datasets in comparison with other models. In order to gain additional flexibility, mixtures of seemingly unrelated contaminated normal regressions models have also been specified so as to allow mixing proportions to be expressed as functions of concomitant covariates. An illustration of the new models with concomitant variables and a study on housing tension in the municipalities of the Emilia-Romagna region based on different types of multivariate linear regression models have been performed.

A Trans-dimensional inversion algorithm to model deformation sources with unconstrained shape in finite element domains

Ground deformation provides valuable insights on subsurface processes with pattens reflecting the characteristics of the source at depth. In active volcanic sites displacements can be observed in unrest phases; therefore, a correct interpretation is essential to assess the hazard potential. Inverse modeling is employed to obtain quantitative estimates of parameters describing the source. However, despite the robustness of the available approaches, a realistic imaging of these reservoirs is still challenging. While analytical models return quick but simplistic results, assuming an isotropic and elastic crust, more sophisticated numerical models, accounting for the effects of topographic loads, crust inelasticity and structural discontinuities, require much higher computational effort and information about the crust rheology may be challenging to infer. All these approaches are based on a-priori source shape constraints, influencing the solution reliability. In this thesis, we present a new approach aimed at overcoming the aforementioned limitations, modeling sources free of a-priori shape constraints with the advantages of FEM simulations, but with a cost-efficient procedure. The source is represented as an assembly of elementary units, consisting in cubic elements of a regular FE mesh loaded with a unitary stress tensors. The surface response due to each of the six stress tensor components is computed and linearly combined to obtain the total displacement field. In this way, the source can assume potentially any shape. Our tests prove the equivalence of the deformation fields due to our assembly and that of corresponding cavities with uniform boundary pressure. Our ability to simulate pressurized cavities in a continuum domain permits to pre-compute surface responses, avoiding remeshing. A Bayesian trans-dimensional inversion algorithm implementing this strategy is developed. 3D Voronoi cells are used to sample the model domain, selecting the elementary units contributing to the source solution and those remaining inactive as part of the crust.

Root cause analysis applied to a finite element model's refinement of a negative stiffness structure

Negative Stiffness Structures are mechanical systems that require a decrease in the applied force to generate an increase in displacement. They are structures that possess special characteristics such as snap-through and bi-stability. All of these features make them particularly suitable for different applications, such as shock-absorption, vibration isolation and damping. From this point of view, they have risen awareness of their characteristics and, in order to match them to the application needed, a numerical simulation is of great interest. In this regard, this thesis is a continuation of previous studies in a circular negative stiffness structure and aims at refine the numerical model by presenting a new solution. To that end, an investigation procedure is needed. Amongst all of the methods available, root cause analysis was the chosen one to perform the investigation since it provides a clear view of the problem under analysis and a categorization of all the causes behind it. As a result of the cause-effect analysis, the main causes that have influence on the numerical results were obtained. Once all of the causes were listed, solutions to them were proposed and it led to a new numerical model. The numerical model proposed was of nonlinear type of analysis with hexagonal elements and a hyperelastic material model. The results were analyzed through force-displacement curves, allowing for the visualization of the structure’s energy recovery. When compared to the results obtained from the experimental part, it is evident that the trend is similar and the negative stiffness behaviour is present.

Effect of eugenol-based endodontic sealer on the adhesion of intraradicular posts cemented after different periods

OBJECTIVE: This study evaluated in vitro the influence of an eugenol-based sealer (EndoFill) on the retention of stainless steel prefabricated posts cemented with zinc phosphate and resin-based (Panavia F) cements after different periods of root canal obturation, using the pull-out test. MATERIAL AND METHODS: Sixty upper canines were decoronated and the roots were embedded in resin blocks. The specimens were distributed into 3 groups, according to the period elapsed between canal obturation and post cementation: Group I - immediately; Group II - 72 h and Group III - 4 months. The groups were subdivided according to the type of cement used for post cementation: A - zinc phosphate and B - Panavia F. Following the experimental periods, specimens were subjected to pullout test in an Instron machine with application of tensile force at a crosshead speed of 0.5 mm/min until post dislodgement. The maximum forces required for post removal were recorded (kN) and means were subjected to statistical analysis by 2-way ANOVA and Tukey-Kramer test (α=0.001) RESULTS: There were statistically significant differences (p<0.01) between the posts cemented with zinc phosphate cement (0.2112 kN) and Panavia F (0.0501 kN). However, no statistically significant differences (p>0.05) were found between the three post cementation periods, regardless of the cement. CONCLUSIONS: It was concluded that the eugenol-based sealer influenced the tensile strength of the posts cemented with the resin cement, but had no influence on the time waited between root canal obturation and post space preparation/post cementation.

Absorption of metals and characterization of chemical elements present in three species of Gracilaria (Gracilariaceae) Greville: a genus of economical importance

Gracilaria Greville is a genus of seaweed that is economically explored by the cosmetic, pharmaceutical and food industries. One of the biggest problems associated with growing Gracilaria is the discharge of heavy metals into the marine environment. The absorption of heavy metals was investigated with the macroalga Gracilaria tenuistipitata Zhang et Xia, cultivated in a medium containing copper (Cu) and cadmium (Cd). In biological samples, EC50 concentrations of 1 ppm for cadmium and 0.95 ppm for copper were used. These concentrations were based on seaweed growth curves obtained over a period of six days in previous studies. ICP-AES was used to determine the amount of metal that seaweeds absorbed during this period. G. tenuistipitata was able to bioaccumulate both metals, about 17% of copper and 9% of cadmium. Basal natural levels of Cu were found in control seaweeds and in G. tenuistipitata exposed to Cd. In addition, the repertoire of other important chemical elements, as well as their concentrations, was determined for G. tenuistipitata and two other important seaweeds, G. birdiae Plastino & Oliveira and G. domingensis (Kützing) Sonder ex Dickie, collected in natural environments on the Brazilian shore.

Keratoconus prediction using a finite element model of the cornea with local biomechanical properties

PURPOSE: The ability to predict and understand which biomechanical properties of the cornea are responsible for the stability or progression of keratoconus may be an important clinical and surgical tool for the eye-care professional. We have developed a finite element model of the cornea, that tries to predicts keratoconus-like behavior and its evolution based on material properties of the corneal tissue. METHODS: Corneal material properties were modeled using bibliographic data and corneal topography was based on literature values from a schematic eye model. Commercial software was used to simulate mechanical and surface properties when the cornea was subject to different local parameters, such as elasticity. RESULTS: The simulation has shown that, depending on the corneal initial surface shape, changes in local material properties and also different intraocular pressures values induce a localized protuberance and increase in curvature when compared to the remaining portion of the cornea. CONCLUSIONS: This technique provides a quantitative and accurate approach to the problem of understanding the biomechanical nature of keratoconus. The implemented model has shown that changes in local material properties of the cornea and intraocular pressure are intrinsically related to keratoconus pathology and its shape/curvature.