Although it is not difficult to observe the healing of induced wounds in animal embryos, mapping the forces that drive lesion closure has proved challenging. Laser microsurgery, Atomic Force Microscopy (AFM) and other techniques can provide local information at fixed times, but all are invasive and some disrupt further development. Video Force Microscopy (VFM) has been able to map driving forces during ventral furrow formation in Drosophila (fruit fly), but challenges arose when it was applied under the assumption that the only driving forces are intracellular pressures and forces (including purse string action) along cell edges. Other possible forces of relevance include far-field stresses and in-plane cellular contractions. Mapping the forces that drive wound closure is an important problem, and so far it has remained unsolved. To investigate the process of dorsal closure, this study used a cell-based finite element (FE) model to identify the mechanical signatures of a wide variety of possible driving forces. Geometric parameters were developed to characterize the associated cell shapes and tissue motions and to quantitatively compare FE simulations with each other and with experimental data. It was discovered that edge tensions and pressures were not sufficient to drive wound healing. Wound healing can only be achieved when far-field boundary motions, edge tensions and apical area tensions act together. This thesis shows that a suitable FE model can provide information about the forces that drive wound healing, and its simulations take us one step closer to understanding the mechanics of wound healing. It also contributes to our general understanding of the forces that drive morphogenetic movements and ultimately helps us to better understand cell-based processes important for human quality of life.

Three tiers of bench-scale experiments were conducted to evaluate the use of laboratory column investigations for studying the transport and removal of pathogenic microorganisms (i.e. disease causing viruses, bacteria and protozoa) and pathogen-surrogates (i.e. (bio)colloids) in saturated porous media (filtration). These experiments were used to explore the effects of individual and concurrent factors on the transport and removal of a suite of (bio)colloids at a range of environmentally relevant conditions typical of natural riverbank filtration and engineered drinking water filters. Several bench-scale column designs were investigated to elucidate laboratory-scale column size factors that may affect reproducibility of (bio)colloid passage through granular media filtration. The physical and chemical factors investigated for their individual and concurrent effects on the transport of a suite of (bio)colloids included: media grain size, media uniformity coefficient, ionic strength, and the presence of natural organic matter. The suite of pathogens and (bio)colloids utilized in this study included PR772 bacteriophage, Escherichia coli RS2g bacteria, Salmonella typhimurium bacterial pathogen, and two sizes of fluorescent polycarbonate microspheres (1.1 μm and 4.5 μm). In addition to S. typhimurium, pathogenic bacterial strains of E. coli and Pseudomonas aeruginosa were isolated and used in an experiment to investigate the effects of bacterial exposure to different environmental water matrices (impacted by various land-uses) on the transport of pathogenic bacteria. Additionally, the effects of bacterial exposure to the different water matrices on cell size and surface EPS composition of the suite of bacterial pathogens were investigated. Pathogen and (bio)colloid removal was assessed for the three experiments by plotting breakthrough curves and/or removal value from each trial, followed by ANOVA to determine the statistical significance of the effect of each parameter studied on (bio)colloid removal. The outcomes of this work have several implications for the use of bench-scale column studies in (bio)colloid transport investigations to improve the understanding of natural and engineered filter performance. Laboratory bench-scale experiments using replicate glass columns proved to be a useful tool in investigating factors that affect (bio)colloid transport in saturated porous media. In contrasts to common recommendations for experimental design (e.g., column diameter (D) to collector diameter (d) ratio > 50), column and collector media designs with D/d between 15 and 116 did not have a significant effect on the reproducibility and removal of a suite of (bio)colloids in transport investigations using varying ionic strengths and flow velocities representative of natural subsurface environments. Accordingly, small scale column studies of (bio)colloid removal by filtration that are conducted at D/d < 50 should not be universally disregarded because of wall effects concerns. iv Observations of (bio)colloid removal by granular media filtration were generally consistent with colloid filtration theory. Grain size, ionic strength and the presence of natural organic matter significantly affected the removal of a suite of (bio)colloids at values representative of natural field conditions. Interaction effects were also identified between the chemical factors of ionic strength and natural organic matter, as well as between physical media characteristics of grain size and uniformity coefficient. These results suggest that synergistic effects within physical and chemical factors known to effect pathogen transport in saturated porous media should be considered when assessing pilot- and full-scale filter performance demonstrations. Differences in removal between the suite of bacterial pathogens investigated at conditions representative of subsurface filtration were small (<0.5 log), suggesting that nuances between the removal of various strains of bacteria that are present at the micro-scale may not be substantial at the macro- or field-scale. The effects of bacterial EPS on (bio)colloid transport may be more important in environments with profuse biofilm formation (unlike the “clean-bed” environments used in this study). Established and standardised methods for EPS extraction and characterization for a range of applications are necessary to improve our understanding of bacterial EPS production, and the effects of these compounds in a range of saturated porous media environments. A conceptual model was developed to encompass the current state of knowledge on bacterial EPS effects on bacterial removal and the results presented herein.

This dissertation develops a methodology that provides information to make optimal decisions with respect to the mission and maintenance of a system. A great amount of information is needed about a system to make such decisions, including its current condition and predictions of its future state. The problem is broken into four subproblems. In the first, a dynamic Bayesian network based system modeling approach is developed for use when the available information is heterogeneous, i.e. available in various formats from various sources (e.g., laboratory data, operational data, expert opinion, mathematical models, and reliability data). The resulting system model accounts for uncertainty and is amenable to the system health management tasks of diagnosis, prognosis, and decision-making. In the second subproblem, a diagnosis approach for systems is developed for systems in the presence of heterogeneous information. The approach accounts for and quantifies uncertainty in the probability of damage, isolation, and quantification. Next, a prognosis is considered when the available information is heterogeneous. The prognosis methodology accounts for uncertainty in diagnosis and is subjected to validation. Finally, a methodology for decision-making problem is developed for problems where the available information is heterogeneous and when assigning multiple systems to multiple missions. The methodology accounts for uncertainty in diagnosis and prognosis. The system modeling, diagnosis, prognosis, and decision-making problems are illustrated using a hydraulic actuator with multiple possible faults, while the diagnosis problem is demonstrated using a cantilever beam with possible damage at the support or a mid-span crack. The proposed methodology is general and can be applied to many different systems.

Road traffic noise is becoming a major public concern. Many transportation agencies are looking for practical and economical means to reduce traffic noise generation and propagation. In 2003, the University of Waterloo’s Centre for Pavement and Transportation Technologies (CPATT) and the Regional Municipality of Waterloo embarked on a partnership to design quiet pavement test sections and to conduct controlled sound level measurement on four different types of asphalt surface courses. Four different surface courses, two Rubberized Open Graded Friction Course Asphalt Pavements (rOFC and rOGC), Stone Mastic Asphalt Pavement (SMA), and a control mix Hot-Laid 3 (HL-3), were placed in lengths of 600 m. The overall 2.4 km test area was closed to traffic and test vehicles were driven through the test area at the prescribed control speeds with sound level meters recording sound levels both at the tire/pavement interface as well as at the monitoring stations off the roadway. Impedance Tube Method and Reverberation Time Method were performed to determine the sound absorption coefficients of the pavement mixes. In order to evaluate the sound attenuation ability of the mixes, the results from rOFC, rOGC, and SMA were used to compare with the result from the control mix HL-3. Statistical analysis of measurement results was performed to see whether the differences between mixes are significant at a 95% confidence interval. Life cycle cost analysis was also performed in order to determine the cost effectiveness of each asphalt mix. Results indicate that traffic sound level increases as vehicle speed and size increase regardless of asphalt types. rOFC and rOGC perform significantly better than HL-3, but the performance slightly deteriorate after one year because of the clogging problem. SMA does not attenuate sound as effectively when compare to HL-3 at the early age. However, sound attenuation ability improves after one year of service. Overall result indicates that rOGC performs the best among all mixes in terms of the sound attenuation ability. Life cycle cost analysis shows that HL-3 is the most economical mix but it is the worst mix in terms of sound attenuation ability. It is recommended to conduct additional sound level and skid resistance measurements in the future to monitor the long-term pavement performance. Also investigation of the relationship between the sound level and sound absorption coefficient measurements is beneficial for the future acoustical evaluation for the asphalt mix.

Peak base displacement is one of the most important quantities in the design of base-isolated buildings. During the preliminary stages of design, a nonlinear time-history analysis is often not possible or too expensive, and hence reliable measures for predicting peak base displacement must be obtained through other means. In this study, regression models are developed in order to predict the peak displacement using a series of intensity measures (IMs) as model inputs. This thesis utilizes two methods for this purpose, Principal Component Regression (PCR) and a newly proposed method known as Sorted-Input Independent Component Regression (SI-ICR). In the framework of PCR and SI-ICR, the problem that exists due to correlation of IMs is addressed, which allows the transformation of correlated components into uncorrelated ones. This step is followed by dimensionality reduction of the components that do not contribute significantly to the explained variance of the original data set. A regression model using only one IM, peak ground velocity (PGV), is also developed to compare the advantages of using multiple IMs as opposed to one. Prediction results are presented and compared to simulation results for building models with increasing degree of complexity, starting with a two degree of freedom uniaxial case to a twelve degree of freedom biaxial model. It is concluded that PCR and SI-ICR significantly outperform the PGV model with PCR slightly outperforming SI-ICR. PCR is regarded as a more suitable and practical regression method for predicting the responses of nonlinear base isolated structures.

Improving the energy efficiency of the existing building stock is beneficial in terms of reducing both operational cost and environmental impact. Solid, load bearing masonry buildings comprise an appreciable part of the existing building stock, are valued for their durability and are often of historical significance, however their thermal performance is often poor. Thermal upgrades with interior insulation are usually considered risky as this lowers the drying potential of the wall enclosure which increases the moisture content of the masonry, possibly to damaging levels during freeze-thaw cycles. The current approach to assessing the suitability of brick for exterior use is based on acceptance criteria or a severe freeze-thaw test as prescribed by ASTM and CSA. The first method is based on an incomplete understanding of freeze-thaw physics. The second method subjects the bricks to a set of conditions that cannot encompass the highly variable range of in-service exposures. Past research indicates that rigid porous materials, such as brick and concrete, experience frost damage only if saturated beyond a fixed, critical degree of saturation. A more useful approach to assessing the risk of damage due to freeze-thaw would be to determine the critical degree of saturation of a material and then compare that to anticipated moisture loads under service conditions using computer modelling software such as WUFI. A test method was developed to determine the critical degree of saturation of a material requiring less than two weeks of testing by means of frost dilatometry. Representative brick were first sliced into 10 mm thick specimens. Material properties of the brick specimens were determined, including dry weight, dry density, porosity (determined by either boiling or vacuum saturation), water uptake coefficient (A-value), and initial length, to allow for computer modeling and analysis of results. The specimens were wetted to various degrees of saturation (based on either boil or vacuum saturation), sealed in a manner to ensure minimal moisture loss, and then subjected to at least six freeze-thaw cycles. The change in length of the specimens following freeze thaw testing was measured and the expansion, which in this study was expressed in terms of microstrain, plotted against degree of saturation. Any specimen that experienced expansion greater than that attributable to instrument error was considered damaged by frost. Determining the total open porosity of a material, necessary for measuring degree of saturation, is difficult due to close voids and trapped air in dead end pores. Boiling saturation and vacuum saturation are two methods commonly used to determine open porosity. For the size of specimens used in the test, almost all water absorption when using the boil method occurred during the first hour of boiling and first hour of soaking. The repeatability of boiling to determine total open porosity is low, with approximately 10% variability experienced over three rounds of boiling. Specimens absorbed a greater or equal amount of moisture using the vacuum saturation method than the boiling saturation method, indicating that vacuum saturation is more effective at determining total open porosity. The repeatability of vacuum saturation is good with very little variability observed over 3 rounds. The benefit of boiling saturation is that its equipment requirements and procedure are simpler than that of vacuum saturation. Freeze-thaw cycling was carried out by immersing the sealed specimens in a liquid bath. The change in length was determined by measuring pins attached to the specimens with an outside digital micrometer with a ratchet stop. A combination of experimentation and computer modeling showed that the samples could be wetted to target moisture contents with excellent accuracy and that moisture redistributed evenly in less than 24 hours for most samples. The minimum required temperature of the freeze cycle was chosen to be less than -12°C, in order to freeze all water contained in pores with a radius of 10nm and greater. It was determined, for the small specimen sizes used, that the cooling and warming phases should be at least one hour in duration to ensure that the specimens entirely freeze and thaw. Three sets of brick were subjected to the test to determine their critical degree of saturation: modern extruded brick, pressed brick from the 1950s, and historic brick dating to the 1870s. The older bricks experienced frost dilatation above 0.25 and 0.30 vacuum saturation respectively, with no damage evident below these thresholds. The modern extruded brick only experienced damage at 0.87 of vacuum saturation and greater. Knowledge of the critical degree of saturation of a brick allows architects and engineers to pursue retrofit strategies that increase thermal performance without jeopardizing the durability of the material by creating the conditions that allow the moisture content to increase to dangerous levels.

Fiber-reinforced self-consolidating concrete is a relatively new material in civil engineering applications. The purpose of this study is to examine the effects of discrete Pitch-based carbon fibers on the fresh properties of self-consolidating concrete (SCC). Ten different carbon fiber-reinforced self-consolidating concrete (CFRSCC) mixtures were produced with two water/binder (W/B) ratios of 0.35 and 0.4, and 0%, 0.25%, 0.5%, 0.75%, 1% carbon fibers by concrete volume. Silica fume was used in all concrete mixtures to improve the dispersion of carbon fibers and the cohesiveness of the SCC. In addition, a high-range water reducer (HRWR) was used to enhance the workability of the concrete. The flow characteristics of the concrete mixtures were determined with respect to slump flow, J-ring slump, and T50 slump flow time. The segregation resistance of the concrete mixtures was evaluated by using the sieve stability test. Visual stability index (VSI) was also used to assess the segregation resistance of concrete. Hardened properties such as compressive strength, splitting tensile strength, and fracture energy were evaluated. Test results revealed that the increased amount of carbon fibers decreased the flowing ability (filling ability and passing ability). Therefore, a greater HRWR dosage was required to achieve the targeted flow properties. The hardened test results showed that increasing the carbon fiber content decreased the compressive strength of the SCC, while the splitting tensile strength of the SCC was increased. Based on the fresh and hardened properties, two different mixes were chosen as optimum mixes in respect to the fresh and hardened properties as well as the cost of producing CFRSCC mixtures. These two mixes were mix M1 (SCC, 0% fibers) and mix M3 (CFRSCC, 0.50% fibers). Eleven RC beams were tested to investigate three different repair configurations: flexural-top patch, flexural bottom patch and shear span patch. Three different repair patch materials were used (Sikacrete-08 SCC, M1 SCC, and M3 CFRSCC). The structural load results showed that the patch repair was most effective (increasing ultimate load and ductility) as a flexural-top patch and shear-span patch. Using a CFRSCC patch changed the mode of failure from shear to flexural failure in the shear-span patched beams.

One of the defense related research programs of recent interest is focused on developing ultra-high strength concrete (UHSC) mixtures and lightweight, rapidly deployable protective structures. A goal of these research programs is to develop protective options that depend more on system ductility or enhanced material properties to provide protection from bomb blast, shock and high-velocity projectile impact. One effort related to this involved developing a lightweight supporting structural system that could be rapidly constructed and positioned without heavy equipment or significant manpower while providing the required level of protection from specific threats by cladding it with multiple layers of thin UHSC panels. This research is concerned with modeling and simulation of such cementitious armor panels based on an accurate definition of its material characteristics through an appropriate material model reflecting the observed three-dimensional multi-scale behavior through actual tests on the material. The nature of high-velocity impact is a problem of high complexity requiring the proper definition of material model reflecting the equations of state, hydrostatic behavior, progressive damage, and strain-rate effects. In this research effort the focus has been on accurate prediction of the behavior of the cementitious armor panels by discrete numerical methods like finite element method (FEM) and smoothed particle hydrodynamics (SPH), devising appropriate material models and accurately characterizing the associated material parameters based on the tests undertaken for the purpose by a co-researcher at Armys Engineering Research and Development Center. The primary purpose of this research is to simulate high-rate ballistic impact events of small, deformable projectiles on thin, UHSC armor panels as well as uniform blast loads on similar panel structures reinforced with randomly distributed and oriented reinforcing short fibers. This needed to be accomplished with a high degree of accuracy when compared to ballistic experiments. In this dissertation, the physics of these scenarios are described in detail, a literature survey of the most prominent material models used to simulate concrete under high-rate loading is described, a superior model for the applications in this research is described along with implementation details, parametric identification of the material model for two UHSCs is presented, strategies for both FEM and SPH methodologies are given along with strengths and weaknesses of both, numerical simulations of actual ballistic impact tests are presented to validate simulation results, and a multi-scale approach for homogenizing the properties of randomly distributed short-fiber reinforcement of UHSC is proposed and validated.

The prediction of failure probability for engineering components/devices under service conditions often involves the use of predictive models and measurement data. The fact that no model is absolutely correct indicates the existence of "model uncertainty", while the available of a limited amount of data or imprecise measurements introduces an additional source of uncertainty called "data uncertainty". These two sources of uncertainty can be classified as epistemic uncertainty (uncertainty due to lack of knowledge/information). Another important source of uncertainty comes from natural variability of physical quantities. In time-dependent problems, uncertainty due to all these sources can accumulate with time, and thus can significantly affect the reliability prediction. Hence, rigorous quantification of model uncertainty, data uncertainty, and natural variability needs to be included in the reliability analysis. This research focuses on two activities to address model uncertainty: (1) model calibration, and (2) model validation. Model calibration aims to quantify the uncertainty in the estimation of model parameters based on the available information on model input and output variables. Bayesian calibration under the well known Kennedy and O'Hagan (KOH) framework is investigated and extended for multi-physics systems with various possible types of available information. Model validation is the procedure of assessing the predictability of models in the domain of intended use. Probabilistic model validation methods are developed in order to quantify the confidence in model prediction, with the capability to include fully, partially, and un-characterized validation data. A Bayesian network-based probabilistic uncertainty quantification (UQ) framework is then developed to include the results of model calibration and validation in time-dependent reliability analysis of engineering systems, including: (1) time-dependent reliability prediction for a multi-physics MEMS device, and (2) prognosis of mechanical components in service with the inclusion of monitoring data (loading history and system health).

In a traffic network users can be classified into various classes based on behavioral rules and the type of information accessible to them. However many existing models assume that the users who belong to these classes are pre-specified, which may not be sufficiently realistic, especially in the context of Advanced Traveler Information Systems (ATIS). To relax this assumption, in this thesis, a framework is proposed to model dynamic user classes, where a user may change their behavioral rules dynamically in response to information and experience. A Dynamic User Class (DUC) model has been formulated and the properties relating to equilibrium like existence and uniqueness have been discussed. An algorithm has been proposed to solve this DUC equilibrium model. The DUC model has been used to develop a Predicted, Consistent and Coordinated information strategy for Dynamic Message Signs (PCDMS). The performance of the PCDMS strategy was compared with the performance of the prevailing and User Equilibrium information strategies under different incident scenarios, and is found to yield significant travel time benefits over the other strategies in many cases. The results have important implications for Network Design and DMS location problems.