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This work aims to expand the applicability of the recently devised physics-based Calibration Integral Equation Method (CIEM) at the University of Tennessee Knoxville, for solving the Inverse Heat Conduction Problem (IHCP) as applied to a one-dimensional domain. Contrary to conventional schemes of solving the IHCP, the CIEM does not require the knowledge of the thermo-physical properties of the domain, sensor characterization and sensor probe locations. The pertinent information is implicitly accounted for via an experimental run. The experimental run ‘calibrates’ the physics of the domain and is called the ‘calibration run’. The net surface heat flux during a real ‘unknown’ run can then be reconstructed using measured in-depth real run temperature histories in conjunction with the calibration run data. The calibration integral equation(s) is identified as a Volterra integral equation of the first kind, which is well known to be ill-posed. Hence, some form of regularization is required to facilitate a stable resolution. This thesis will explore the operation of the CIEM in two parts, both using experimentally gathered data. The first part will revisit the one-probe CIEM in the light of suggesting an alternate scheme for the selection of the optimum regularization parameter and also extend its applicability to two-layer domains. The proposed scheme requires solely the calibration run temperature history for establishing an optimal band for the selection of the regularization parameter. The one-probe CIEM demands identical back boundary conditions during the calibration and ‘real’ run stages. This restriction is lifted by means of the two-probe CIEM, which will constitute the second part of this thesis. The two-probe CIEM implicitly registers the effect of the back-boundary condition via a second temperature measurement at a different probe location. This enables the reconstruction of the net surface heat flux during the ‘real’ run, independent of the ‘real’ run back-boundary condition. The considerable difficulty of simulating in the laboratory, the actual boundary conditions prevalent in a space vehicle is thus avoided. The two-probe CIEM is also applicable to multi-layer domains. Highly favorable results are presented for both one and two-probe CIEMs applied to single and two-layer domains.

Abstract: This work involves the design, microfabrication, calibration, and testing of a new silicon-based piezoresistive rosette capable of extracting the three-dimensional (3D) stresses in the silicon upon deformation. A new 10-element piezoresistive rosette was devised to extract all stress components with temperature compensation compared to the 8-element rosette developed by previous researchers, which delivers partially temperature-compensated stress output. The proposed rosette is made up of either dual- or single-polarity sensing elements through utilizing the unique behavior of the shear piezoresistive coefficient (pi44) in n-Si with impurity concentration. An analytical study was conducted to investigate the feasibility of the new approach. The analysis is based on solving the determinants of the coefficients of the matrices describing the resistance change versus stress and temperature for the sensing elements. The calculated determinants over a range of impurity concentrations showed non-zero regions, thus indicating the feasibility of the approach. A full experimental study including the microfabrication, calibration and testing of the 10-element single-polarity rosette was conducted to demonstrate the actual behavior of the rosette in extraction of the 3D stresses. An early prototype, named POC chip, using diffusion doping was used to calibrate the piezoresistive coefficients and temperature coefficient of resistance and calculate the determinants to support the analytical study. The calibration process involved applying uni-axial and thermal loads on the sensing elements. The resulting determinants from the calibration process indicated non-zero values, thus verified the experimental feasibility of the approach. On the other hand, the second prototype, named test chip, using ion implantation doping was used for testing of the rosette after conducting a full calibration process involving uni-axial, thermal, and hydrostatic loads. The testing of the test chip was conducted by applying a four-point bending of a chip-on-beam specimen at room temperature. Three chip orientations and three rosette-sites were used to induce five stress components in a controlled manner, while the out-of-plane normal stress was not tested independently due to its low sensitivity in the current microfabrication run. A finite element model (FEM) of the chip-on-beam loading was developed to compare to the stress output from the experimental testing. The five stress components were extracted from the three rosette-sites and showed good correlation with the FEM.

Both safety and the capacity of the roadway system are highly dependent on the car-following characteristics of drivers. Car-following theory describes the driver behavior of vehicles following other vehicles in a traffic stream. In the last few decades, many car-following models have been developed; however, studies are still needed to improve their accuracy and reliability. Car-following models are a vital component of traffic simulation tools that attempt to mimic driver behavior in the real world. Microscopic traffic simulators, particularly car-following models, have been extensively used in current traffic engineering studies and safety research. These models are a vital component of traffic simulation tools that attempt to mimic real-world driver behaviors. The accuracy and reliability of microscopic traffic simulation models are greatly dependent on the calibration of car-following models, which requires a large amount of real world vehicle trajectory data. In this study, the author developed a process to apply a stochastic calibration method with appropriate regularization to estimate the distribution of parameters for car-following models. The calibration method is based on the Markov Chain Monte Carlo (MCMC) simulation using the Bayesian estimation theory that has been recently investigated for use in inverse problems. This dissertation research includes a case study, which is based on the Linear (Helly) model with a different number of vehicle trajectories in a highway network. The stochastic approach facilitated the calibration of car-following models more realistically than the deterministic method, as the deterministic algorithm can easily get stuck at a local minimum. This study also demonstrates that the calibrated model yields smaller errors with large sample sizes. Furthermore, the results from the Linear model validation effort suggest that the performance of the calibration method is dependent upon size of the vehicle trajectory.

When a person estimates their global (overall) performance on a test they just completed, low performers often overestimate their performance whereas high performers estimate more accurately or slightly underestimate. Thus, low performers have been described as "unskilled and unaware" (Kruger & Dunning, 1999). However, recent evidence (Hartwig & Dunlosky, in press) demonstrates that low performers sometimes estimate accurately. What determines whether a participant estimates accurately vs. inaccurately remains unclear. Thus, the present research asks: What might participants use as the basis for their global estimates, and can it explain the accuracy of those estimates? One intuitive possibility is that participants use their response confidence in test items as the basis of their global estimates. A simple instantiation of this idea is described by the item-frequency hypothesis, which posits that participants compute the frequency of their high-confidence responses, and this frequency serves as an estimate of their global performance. A corollary of this hypothesis is that items that produce high confidence in wrong answers (i.e., false alarms, or FAs) will contribute to global overestimates, whereas items that produce low confidence in correct answers (i.e., misses) will contribute to global underestimates. Study 1 found preliminary support for the hypothesis, because the frequency of high-confidence responses on a typical trivia test was correlated with participants' global estimates, and the imbalance of FAs vs. misses predicted the accuracy of those estimates. To evaluate the hypothesis experimentally, Studies 2 and 3 manipulated the frequencies of FAs and misses that a trivia test was expected to yield, and participants were randomly assigned to receive one of the tests. Tests designed to yield many FAs (relative to misses) produced global overestimation, tests designed to yield more misses (relative to FAs) produced underestimation, and tests designed to yield a balance of FAs and misses produced accurate estimation. Thus, the selection of test items affects global estimates and their accuracy. The imbalance of FAs and misses could not explain all individual differences in estimation accuracy, but it nonetheless was a moderate predictor of global estimation accuracy.

Blood glucose monitoring is a primary tool for the care of diabetic patients. At present there is no non-invasive monitoring technique of blood glucose concentration that is widely accepted in the medical industry. Some promising success has been shown by the RIT ETA Lab research group that an antenna's resonant frequency can track, in real time, changes in glucose concentration. However, these changes in antenna response would be unique to an individual depending on various parameters such as the person's metabolism, body mass index, chemical profile etc. Therefore, amongst the several issues that still need to be addressed in the development of a noninvasive methodology; an important one is the calibration unique to each individual patient. The objective of the present work is to establish a calibration by developing an equivalent circuit model to represent the antenna input impedance with changing glucose levels. Using the calibration, the glucose level is estimated from the measurement of antenna impedance and resonant frequency at a later date. Measurements were made on a diabetic and non-diabetic subject with a blood glucose meter and with a planar dipole antenna connected to a network analyzer. The network analyzer was automated to make input impedance measurements in real-time using Labview in 15 second intervals and calculates the resonant frequency of the antenna. The resonant frequency of the antenna and the reference glucose values using a blood glucose meter were measured. The resonant frequency of the antenna is plotted in real-time for instant analysis and trends. A linear estimation for the glucose based on the resonant frequency of the antenna was compared to reference measurements taken by a blood glucose meter. 59% estimates were with 20% of the reference measurements for the diabetic patient. An equivalent circuit model, developed to estimate glucose concentration, was found to have a shunt resistance, series capacitance, and shunt inductance. The component values for this circuit are generated from the experimental results of the diabetic patient, unique to the subject. The component values are iteratively varied until they reflect the impedance of the input impedance. Because the input impedance is changing over time, the component values change over time. The calibration model uses fitted equations to the component values from the experimental result that relates the component values to a glucose concentration. This unique equation for the diabetic patient can be used to estimate the glucose level when measuring the input impedance of the antenna at a later date. The experiment was repeated on the diabetic subject and the unique calibration procedure was used to estimate the blood glucose concentration. The estimates represented by the Clarke's Error Grid compared favorably to the measurements made by the blood glucose meter.

The problem of wheel performance on deformable soil has been studied for many years, but prior to the rise of computational mechanics, such investigations have been limited to development of analytical and empirical models, as well as experimental research. Such models have merit but are necessarily highly idealized and are limited in their applications. Today, many computational models have been implemented for a wide variety of wheel/soil applications. For the specific case of sandy (i.e. non-cohesive) soils, in terms of the soil's physics the Discrete Element Method (DEM) provides arguably the most realistic model. In DEM, each element represents a single grain of soil (ideally), or may represent a group of soil particles moving together if necessary. A survey of the literature quickly reveals that DEM is computationally intensive and that a great deal of computational effort is normally spent calibrating the DEM model parameters to the desired characteristics of the soil of interest. The goal of this research was to develop and validate an approach to calibration that would require fewer resources, leaving more resources available for solving the problems of interest. This goal was realized through the collection of data over a range of values for each of five simulation parameters using two-dimensional simulations of the Direct Shear Test. By statistical processes the data was used to develop a set of equations that estimate the properties of interest for the simulated soil (small- and large-strain friction angles), based on the simulation parameters. The equations were used to calibrate a two-dimensional rigid wheel/soil simulation of the Wheel Endurance and Sand Traction Merry-Go-Round System (WEST-MGRS). The calibrated model was found to accurately predict the relative performance between a variety of configurations of grousers on actual wheels operating in sand using WEST-MGRS. Therefore, this research shows that the model can be used as a tool to compare the tractive performance of potential designs. A question that must be answered regarding experiments and simulations of the wheel/soil problem is the question of soil dimensions. Whether simulated or experimental, the system must use a soil container large enough to approximate a semi-infinite soil domain. This research expanded on previous work that had proposed a method for sizing soil dimensions in a dynamic 3-D finite element model. With minor modifications, the method was found to be effective for a wide range of wheel loads and geometries, as well as soil types.

Analog-to-digital converters (ADCs) are driven by rapid development of mobile communication systems to have higher speed, higher resolution and lower power consumption. Among multiple ADC architectures, successive approximation (SAR) ADCs attract great attention in mixed-signal design community recently. It is due to the fact that they do not contain amplification components and the digital logics are scaling friendly. Therefore, it is easier to design a SAR ADC with smaller component size in advanced technology than other ADC architectures, which decreases the power consumption and increases the speed of the circuit. However, capacitor mismatch limits the minimum size of unit capacitors which could be used for a SAR ADC with more than 10 bit resolution. Large capacitor both limits conversion speed and increases switching power. In this design project, a novel switching scheme and a novel calibration method are adopted to overcome the capacitor mismatch constraint. The switching scheme uses monotonic switching in a SAR ADC to gain one extra bit, and switches a dummy capacitor between the common mode voltage level (Vcm) and the ground (gnd) to obtain another extra bit. To keep the resolution constant, the capacitor number is reduced by two. The calibration method extracts missing code width to estimate the actual value of capacitors. The missing code extraction is accomplished by detecting metastable state of a comparator, forcing the current bit value and using less significant bits to measure the actual capacitor value. Dither method is adopted to improve calibration accuracy. Behavior model simulation is provided to verify the effectiveness of the calibration method. A circuit design of a 12 bit ADC and the simulation for schematic design is presented in this report.

In the United States, natural gas turbine generators account for approximately 7% of the total primary energy consumed. A one percent increase in gas turbine efficiency could result in savings of approximately 30 million dollars for operators and, subsequently, electricity end-users. The efficiency of a gas turbine engine is tied directly to the temperature at which the products of combustion enter the first stage, high-pressure turbine. The maximum operating temperature of the turbine components’ materials is the major limiting factor in increasing the turbine inlet temperature. In fact, current turbine inlet temperatures regularly exceed the melting temperature of the turbine vanes through advanced vane cooling techniques. These cooling techniques include vane surface film cooling, internal vane cooling, and the addition of a thermal barrier coating (TBC) to the exterior of the turbine vane. Typically, the performance of vane cooling techniques is evaluated using the adiabatic film effectiveness. However, the adiabatic film effectiveness, by definition, does not consider conjugate heat transfer effects. In order to evaluate the performance of internal vane cooling and a TBC it is necessary to consider conjugate heat transfer effects. The goal of this study was to provide insight into the conjugate heat transfer behavior of actual turbine vanes and various vane cooling techniques through experimental and analytical modeling in the pursuit of higher turbine inlet temperatures resulting in higher overall turbine efficiencies. The primary focus of this study was to experimentally characterize the combined effects of a TBC and film cooling. Vane model experiments were performed using a 10x scaled first stage inlet guide vane model that was designed using the Matched Biot Method to properly scale both the geometrical and thermal properties of an actual turbine vane. Two different TBC thicknesses were evaluated in this study. Along with the TBCs, six different film cooling configurations were evaluated which included pressure side round holes with a showerhead, round holes only, craters, a novel trench design called the modified trench, an ideal trench, and a realistic trench that takes manufacturing abilities into account. These film cooling geometries were created within the TBC layer. Each of the vane configurations was evaluated by monitoring a variety of temperatures, including the temperature of the exterior vane wall and the exterior surface of the TBC. This study found that the presence of a TBC decreased the sensitivity of the thermal barrier coating and vane wall interface temperature to changes in film coolant flow rates and changes in film cooling geometry. Therefore, research into improved film cooling geometries may not be valuable when a TBC is incorporated. This study also developed an analytical model which was used to predict the performance of the TBCs as a design tool. The analytical prediction model provided reasonable agreement with experimental data when using baseline data from an experiment with another TBC. However, the analytical prediction model performed poorly when predicting a TBC’s performance using baseline data collected from an experiment without a TBC.

Quality is difficult to measure and compare among medical providers. First, an appropriate metric must be chosen among many potential process-based and patient outcome measures. Further, when comparing providers, one must take into account the fact that patients are not homogeneous across providers. Accounting for the latter with clinical risk adjustment models is a complicated and controversial topic, as providers are increasingly paid based on their performance with respect to risk-adjusted quality measures. A modern approach to hospital quality improvement is developed by expanding on D.R. Cox's 1958 methodology for calibrating binary outcomes; using this calibration methodology and recent efficient generalized linear modeling algorithms to develop a risk-adjustment model for in-hospital morality with data on 20 million inpatient discharges from the State of California between 2004 and 2008; applying this model to obtain 2009 observed-to-expected mortality ratios for the hospitals across California; and evaluating whether or not performance-dependent relationships between hospital process changes and observed-to-expected mortality ratios exist, based on a novel sparse multiquantile regression technique that incorporates a fused-lasso-type penalty.

Risk prediction models are important tools intended to help clinicians make optimal treatment decisions. They are often developed on large reference samples for applications in different local cohorts. For example, consider transporting the US Framingham risk prediction function for coronary heart disease (CHD) to populations in Europe or Asia. In this process it is necessary to correctly re-calibrate the existing function for future applications. In this thesis we propose a new re-calibration method which could be used when transporting the risk function from a reference to the local cohort. This new method is compared with the existing re-calibration methods through numerical simulations under various assumptions and on real-life population data. In a majority of settings it outperforms the existing methods. We also explore the strengths and limitations of each re-calibration method and provide guidance for practical use of these methods. The re-calibration methods described can be used for any risk prediction models based on Cox proportional hazard regression. To facilitate convenient application we present an easy to use SAS macro. Another essential feature of a successful risk prediction model is characterized by its discrimination or its ability to separate those with events from those without events. One of the most popular measures of discrimination is the area under the Receiver Operating Characteristic (ROC) curve, often called the c statistic or just area under the curve (AUC). Various authors have extended the AUC from binary outcome applications to survival data. However, these extensions are not unique. In this thesis we compare four of these extensions using simulations and practical applications to the Framingham risk functions as well as a breast cancer risk model. We conclude that the extension proposed by Harrell and described in detail by Pencina & D'Agostino is a metric that is most consistent with the most appropriate definition of discrimination in survival. We construct a SAS code for its consistent estimator based on the work of Uno et al. We also notice large differences in magnitude between various C indices calculated on the same data and caution against comparisons across different C indices.

Dual frame surveys are becoming more common in survey practice due to rapid changes in the cost of survey data collection, as well as changes in population coverage patterns and sample unit accessibility. Many dual frame estimators have been proposed in the literature. Some of these estimators are theoretically optimal but hard to be applied in practice, whereas the rest are applicable but not as optimal as the first group. All the standard dual frame estimators require accurate information about the design domain membership. In this dissertation, a set of desirable properties for the dual frame estimators is specified. These properties are used as criteria to evaluate the standard dual frame estimators. At the same time, the Joint Calibration Estimator (JCE) is proposed as a new dual frame estimator that is simple to apply and meets most of the desirable properties for dual frame estimators. In Chapter 2, the JCE is introduced as an approximately unbiased dual frame estimator, with a degree of unbiasedness depending on the relationship between study variables and auxiliary variables. The JCE achieves better performance when the auxiliary variables can fully explain the variability in the study variables of interest or at least when the auxiliary variables are strong correlates of the study variables. The JCE for point estimates can be applied by standard survey software and can easily be extended to multiple frame survey estimation. In Chapter 3, the JCE properties are explored in the presence of the nonresponse error. Theoretically and empirically, the JCE proves to be robust to nonresponse error as long as a strong set of auxiliary variables is used. This strong set should predict both the response mechanism and the main study variables. Finally, the effect of domain misclassification on the dual frame estimators is discussed in Chapter 4. Since the JCE does not require domain membership information, it tends to be robust against domain misclassification even if domain totals are included in the calibration auxiliary variables.

The most commonly used method of determining calibration of logistic models is through the use of the Hosmer-Lemeshow goodness-of fit test (H-L test). However, a new method of calibration has been presented, known as the GiViTI Calibration Belt (GCB). Through the use of artificial and observational datasets from the GiViTI ICU study and from the Ohio State University Medical Center (OSUMC) patient readmission study, we present a comparison of the two methods of determining calibration. We have found that the GCB is most useful for identifying specific regions of miscalibration rather than an overall test of calibration. It is of particular importance in models where miscalibration is to be expected as it can identify regions of poor calibration due to insufficient numbers of observations. In models that are properly calibrated, the GCB matches the H-L test in concluding that there are no major regions of miscalibration regardless of the number of observations the model is based upon. The GCB shows promise as a tool for recalibrating models to adjust for changes in hospital practices that may have occurred after the model’s development.

Distances are regularly underestimated in immersive virtual environments (IVEs) (Witmer & Kline, 1998; Loomis & Knapp, 2003). Few experiments, however, have examined the ability of calibration to overcome distortions of depth perception in IVEs. This experiment is designed to examine the effect of calibration via haptic and visual feedback on distance estimates in an IVE. Participants provided verbal and reaching distance estimates during three sessions; a baseline measure without feedback, a calibration session with visual and haptic feedback, and finally a post-calibration session without feedback. Feedback was shown to calibrate distance estimates within an IVE. Discussion focused on the possibility that costly solutions and research endeavors seeking to remedy the compression of distances may become less necessary if users are simply given the opportunity to use manual activity to calibrate to the IVE.

Section to section alignment is a preliminary step to the creation of three dimensional reconstructions from serial section electron micrographs. Typically, the micrograph of one section is aligned to its neighbors by analyzing a set of fiducial points to calculate an appropriate polynomial transform. This transform is then used to map all of the pixels of the micrograph into alignment. Such transforms are usually linear or piecewise linear in order to limit the accumulation of small errors, which may occur with the use of higher–order approximations. Linear alignment is unable to correct common higher order geometric distortions, such as lens distortion in the case of TEM, and scan distortion in the case of transmission-mode SEM. Here, we attempt to show that standard calibration replicas may be used to calculate a high order distortion model despite the irregularities that are often present in them. We show that SEM scan distortion has much less of an effect than TEM lens distortion; however, the effect of TEM distortion on prior geometric measurements made over three-dimensional reconstructions of dendrites, axons, and synapses and their subcellular compartments is negligible.

Roadway pavement distress evaluations are vital to understanding the mechanics of pavement stability, determining the distribution of rehabilitation costs, and knowing the appropriate rehabilitation strategies. Advancements in technology over the past two decades have changed the way these surveys have been performed by means of automated data collection and interpretation. More and more state agencies have invested in automated road analyzing vehicles that are able to collect high resolution images of the pavement. Fewer have adopted automated data processing software with the ability to interpret road distresses due to the common discrepancies in distress classification algorithms. In addition to automated data acquisition and interpretation, efforts to implementing automated pavement design software have also progressed in recent years. The Mechanistic-Empirical Pavement Design Guide (MEPDG) is a recent pavement design tool that is in the process of replacing the 1993 American Association of State Highway Transportation Officials Guide as the primary design agent. MEPDG incorporates numerous pavement design traits and conditional factors to predict pavement structural performance. This document investigates the methods behind the calibration for automated pavement distress evaluation and design technologies in order to facilitate the transition into the technology-based MEPDG for the state of Arkansas. This research describes the implementation of a post-processing tool that refines the Automated Distress Analyzer (ADA) software cracking results in order to better replicate a desired outcome. The tool was first developed to help ADA match pavement cracking distress tabulations derived by human interpreters, which was considered to be the ground truth. The purpose of this research was to determine whether MEPDG distress predictions better match the tool-equipped automated tabulations as opposed to the ADA software on its own and the distress results provided by human surveyors. An ideal match between MEPDG and the ADA software results, depending on their relation to human interpretations, may lead to quicker and less error-prone methods in pavement evaluation and calibration in order to help Arkansas keep up with the MEPDG system. The results showed that MEPDG predictions match automated interpretations after the implementation of the post-processing tool better than human interpretations.

As personalized biologically-assisted models of the spine have evolved, the calibration of raw electromyographic (EMG) signals has become extremely important. The traditional method of normalizing myoelectric signals relative to subjective maximum voluntary contractions (MVCs) is believed to introduce error since true MVCs are commonly underrepresented. Additionally, this method is useless for assessing the biomechanics of symptomatic low back pain (LBP) patients since they are generally unable or unwilling to provide MVCs. Therefore, the objective of this study was to develop and validate a biologically-assisted model calibration technique that does not require MVCs for EMG normalization. The newly developed technique eliminates the need to collect MVCs by combining gain (maximal strength per unit area) and MVC into a single muscle property (gain ratio) that can be calculated during model calibration. An experiment was conducted with ten subjects (5 male, 5 female) to compare the performance and muscle property predictions from this new calibration technique to the traditional MVC-based technique. Models calibrated by each technique were then used to evaluate independent test sets of multi-planar torso exertions and asymmetrical lifts, and resultant validity measures and spinal loads were compared. No statistically significant differences in spinal loads were found between calibration techniques, though differences were observed in muscle properties for the right latissimus dorsi. Model validity measures indicated that the new calibration technique performed at least as well as MVC-based calibrations. This new calibration technique will facilitate personalized muscle property and spinal load predictions for individuals who are not willing or are not able to provide reliable MVCs. In particular, this technique may permit future efforts to evaluate symptomatic low back pain (LBP) patients, which could provide significant insight into the underlying nature of the LBP disorder.

Standard leaks are used throughout industry for various applications, such as gas transfer, calibration of mass spectrometers, and calibration of leak detectors. The ability to provide a controlled delivery of gases at relatively low flow rates makes standard leaks a popular choice for calibration standards. This ability also allows for precise quantities of gas to accumulate over time. The accumulation of gas from standard leaks is used as a “transfer standard” for making in-process adjustments to measurement instrumentation. With the advent of tighter quality control constraints, the quantification and control of leak rates is becoming an increasingly important matter, placing increased demands on the understanding of leak behavior and on the accurate measurement of leakage rates. Because of stringent quality constraints imposed by industry and technological advancements, it is essential to develop a reliable and accurate method of calibrating standard leaks. The purpose of this research was to design, implement, and validate a leak calibration stand prototype that can detect and reduce systematic errors that lead to high calibration uncertainties of standard leaks. The main contributors to high calibration uncertainty were caused by internal leaks and the outgassing from the internal surfaces, fittings, and valves within the vacuum chamber. In order to quantify the rate at which the internal surfaces of the vacuum chamber outgassed, a custom vacuum chamber was constructed inside an oven to test the effects of outgassing at various pumpdown intervals and baking temperatures. Statistical methods were used to obtain a better insight on the selection of materials, pumpdown intervals, and baking temperatures needed to achieve low and repeatable outgassing rates. This research concluded that the quantification of leakage and outgassing will completely eliminate the once unknown uncertainty component of pressure measurements in vacuum. This discovery led to the realization that an additional isolated volume can be used to “capture” the accumulation of leakage and outgassing and to correct for pressure measurements during standard leak calibrations.

Successive approximation (SAR) type Analog to Digital Conveter (ADC) is a Nyquist Rate ADC which has acquired tremendous pupularity recently due to its digital nature , minimal complexity and tiny foot print .These merits make them the most energy ecient topology for analog to digital conversion available today well suited for battery powered applications like touch screen controllers , wireless communication systems , Motion detectors etc. Enhancements in these domains is greatly linked to breakthroughs improving speed as well as performance of SAR type ADCs . In this Work we tried to understand SAR topology in depth therby opening up a new 'time' dimesion to harness more information during the SAR conversion process. A new architecture is proposed in which this auxilliary dimension is employed to signicantly improve eciency and throughput over existing SAR ADC implementations .

The Aquarius/SAC-D joint international science mission, between the National Aeronautics and Space Administration (NASA) of United States and the Argentine Space Agency (Comision Nacional de Actividades Espaciales, CONAE), was launched on a polarorbiting satellite on June 10, 2011. This mission of discovery will provide measurements of the global sea surface salinity, which contributes to understanding climatic changes in the global water cycle and how these variations influence the general ocean circulation. The Microwave Radiometer (MWR), a three channel Dicke radiometer operating at 23.8 GHz H-Pol and 36.5 GHz V-& H-Pol provided by CONAE, will complement Aquarius (NASA’s L-band radiometer/scatterometer) by providing simultaneous spatially collocated environmental measurements such as water vapor, cloud liquid water, surface wind speed, rain rate and sea ice concentration. This dissertation focuses on the overall radiometric calibration of MWR instrument. Which means establishing a transfer function that relates the instrument output to the antenna brightness temperature (Tb). To achieve this goal, the dissertation describes a microwave radiative transfer model of the instrument and validates it using the laboratory and thermal-vacuum test data. This involves estimation of the losses and physical temperature profile in the path from the receiver to each antenna feed-horn for all the receivers. As the pre-launch laboratory tests can only provide a simulated environment which is very different from the operational environment in space, an on-orbit calibration of the instrument is very important. Inter-satellite radiometric cross-calibration of MWR using the Naval Research iii Laboratory’s multi-frequency polarimetric microwave radiometer, WindSat, on board the Coriolis satellite is also an important part of this dissertation. Cross-calibration between two different satellite instruments require normalization of Tb’s to account for the frequency and incidence angle difference between the instruments. Also inter-satellite calibration helps to determine accurate antenna pattern correction coefficients and other small instrument biases.

A prototype of the Muon Telescope Detector (MTD) was installed at STAR (Solenoidal Tracker at RHIC) during run year 2007. While the cosmic and beam tests showed a ~ 60 - 70 ps timing resolution for MTD, the actual performance in Au + Au collisions at STAR was found ~300 ps. In run year 10 STAR implemented a new electronics system for MTD and a cosmic ray trigger to study the performance of its several subsystems. With the cosmic ray data, this study shows that the timing resolution of MTD can reach 99 ps after a full calibration.

ISO standard 4037 specifies that for calibrating protection level dosimeters, scattered radiation should contribute less than 5 percent of the exposure. In previous work, we reported the results of an MCNP analysis of the shadow shield technique that was performed for a calibration range with a Cs-137 irradiator. This thesis examines the energy distribution of the photons contributing to the exposure percent scatter (S%) and the detailed origin of the scatter that originates in the irradiator. In summary, it reports that: 1) the majority of S% is due to photons with energies that are significantly below the source energy, 2) a significant percentage of S% is due to photons that scatter within the source and source capsule walls, and 3) S% due to scatter within the irradiator is even more significant than we previously reported.

This thesis concerns the development and implementation of efficient optimization algorithms for simulation based functions (real world problems) that are computationally expensive to evaluate. The first contribution is a new parallel algorithm, RODDS for global optimization. RODDS algorithm is a stochastic heuristic global search algorithm, which effectively uses multi-core computers to reduce the computational expense of an optimization problem. The RODDS algorithm introduces the use of hyperspheres in candidate point generation. The optimization search is based on the concept of dynamically changing the dimensions perturbed to direct the search from a global to a local focus. Hyperspheres are used to prevent clustering of candidate points in optimization process to efficiently search the domain. We present numerical results on test problems as well as real world application problems from environmental engineering (groundwater management and watershed calibration) to document RODDS effectiveness when the computational budget is limited. RODDS algorithm achieves efficiencies greater than 1 for most applications which is very significant since implementation of parallel processing usually results in efficiency well below 1. We also present numerical results to show the efficiency of the use of hyperspheres in candidate point generation in RODDS by comparing with a parallel implementation without the hyperspheres. The next contribution is application of Radial basis function (RBF) based methods on computationally expensive optimization problems. We compare the performance of RBF methods with several popular global optimization algorithms (derivative based and heuristic) on two Groundwater superfund remediation sites (Pump and Treat system). These are two field sites Umatilla Chemical Depot (19,728 acres) and Blaine Ammunition Depot (48,800 acres). We present numerical results to indicate that RBF based methods are much more effective algorithms for computationally expensive groundwater problems, followed by a heuristic algorithm DDS. Under limited budget RBF based methods on average outperform traditional methods by an order of 100. The third contribution is a new methodology of integrating a new integer value optimizer (Search over Integers with Tabu (SIT)) with continuous value optimizer (RBF based method) to solve fixed cost problems (which are Mixed Integer value problems, MIVP). Mixed integer value problems (MIVP) in general have large search domain thus the optimization process is computationally very expensive. This approach tries to take advantage of the fact that SIT is effective for optimizing discrete variables, while response surface method is much more efficient for optimizing continuous value variables. This study tries to limit the computational expense of such kind of problems by implementing a Sequential Response Surface method in conjunction with SIT. We present numerical results to show the effectiveness of integration methodology in comparison to Genetic Algorithm based NSGA-II (Deb et. al., 2003) and the MIVP optimizer, NOMAD (Abramson et. al. 2008). The SIT-RBF methodology is shown to be distinctly better than GA (SIT-RBF resulting in 150 times better solution than GA) under limited computational budget.

This effort is focused on the design, calibration, and implementation of a high temperature heat flux sensor for thermal systems research and testing. The High Temperature Heat Flux Sensor (HTHFS) was designed to survive in the harsh thermal environments typically encountered in hypersonic flight, combustion and propulsion research, and large-scale fire testing. The sensor is capable of continuous use at temperatures up to 1000 â ¦C. Two methods for steady-state calibration of the HTHFS at elevated temperatures have been developed as a result of this research. The first method employs a water-cooled heat flux sensor as a reference standard for the calibration. The second method utilizes a blackbody radiant source and a NIST calibrated optical pyrometer as the calibration standard. The HTHFS calibration results obtained from both methods compare favorably with the theoretical sensitivity versus temperature model. Implementation of the HTHFS in several types of transient thermal testing scenarios is also demonstrated herein. A new data processing technique is used to interpret the measurements made by the HTHFS. The Hybrid Heat Flux (HHF) method accounts for the heat flow through the sensor and the heat storage in the sensor, and thus renders the HTHFS virtually insensitive to the material on which it is mounted. The calibrated output of the HTHFS versus temperature ensures accuracy in the measurements made by the sensor at high operating temperatures.

Background: Dental articulation is a method of approximating the patient's mandibular motion in order to allow for analysis of dental relations and fabrication of appliances. The most prevalent method used in teaching institutions is the semi-adjustable articulator. Several of these instruments claim interchangeability without loss of clinical accuracy and studies have supported this claim. No studies to date have assessed the interchangeability of the articulators in any relation other than hinge axis closure. Assessment of the accuracy of interchangeability of calibrated articulators will inform the profession of this parameter of articulation and allow for informed decisions on whether or not to rely on interchangeability in analysis and fabrication. Objectives: To examine the ability of an operator to set condylar inclination repeatedly on a semi-adjustable articulator. To assess the utility of a new measurement jig to assess the calibration status of articulators and to measure sample of instruments repeatability in hinge axis closure and then in measured lateral excursion to assess eccentric interchangeability. Method: 78 Unused Whip Mix 2240 and 71, 1 year-old Whip Mix 2240 semi-adjustable articulators were placed in a custom made measurement jig following calibration. Condylar inclination was evaluated with a digital angle meter and gauge blocks were utilized as reference points to measure the position (X and Y axes) of the test gauge and a height meter was used to measure the vertical (Z axis) in hinge axis closure position and in a measured lateral excursion. Results: The data suggests that: (1) A single operator was able to program the horizontal condylar inclination of the Whip Mix 2240 with 95% confidence within one degree of his target value. (2) A prescribed lateral movement on a series of new articulators was able to position a specific measurement point (maxillary first bicuspid facial cusp tip) in the same spatial location within tolerance reported for hinge axis closure of calibrated instruments. (3) A prescribed lateral movement on a series of used articulators positions a specific measurement point (maxillary first bicuspid facial cusp tip) in the same spatial location within tolerance reported for hinge axis closure of calibrated instruments (4) 88.5% of 1 year‑old instruments verified as interchangeable with the 2245 check gauge. (5) A calibrated Whip Mix 2240 can be eccentrically positioned with 95% confidence within +/‑ 0.2mm vertically and +/‑ 0.1mm horizontally.

A distributed approach can improve functionality of H/WQ (Hydrology and Water Quality) modeling by facilitating a way to explicitly incorporate spatial characteristics of a watershed into the model. The time-area approach, with its intuitive and inherently distributed concept, provides a simple method to simulate runoff mechanisms. This study developed a distributed model based on the time-area approach with the goal of improved utility and efficiency in H/WQ modeling. Uncertainty is always introduced into watershed modeling because of imperfect knowledge and scale dependant spatial heterogeneity and temporal variability. Uncertainty analysis can provide a modeler, policy maker, and stakeholder with reliability information, better understanding, and better communication about the modeling results. This study quantified uncertainty of the model parameter and output through uncertainty analysis in order to assess risk in watershed management. The main goal of this study was to develop a hydrology and sediment transport model capable of routing overland flow using a time-area concept and providing reliability of the modeling results in a probabilistic manner through uncertainty analysis. The HYSTAR (HYdrology and Sediment transport simulation using Time-ARea method) model incorporates a modified Curve Number (CN) method and the newly devised time-area routing method to estimate runoff. HYSTAR is capable of simulating direct runoff, base flow, soil moisture, and sediment load in a distributed manner and in an hourly time step. In the model, the modified CN and a continuity equation are used to calculate infiltration of the routed runoff as well as rainfall on every overland cell. The effective direct runoff volume is distributed over downstream areas using the newly developed routing method. A direct runoff hydrograph is constructed directly through the discrete convolution of the time-area histogram and the effective direct runoff volume map without employing a unit hydrograph. In addition, sediment transport is simulated using the routing method and the sediment transport capacity approach without using a delivery ratio. The sensitivity analysis found that the CN and root zone depth were the most critical parameters for runoff simulation with HYSTAR. The model provided acceptable performance in predicting runoff and sediment load of a subwatershed of the Owl Run Watershed (ORD) with the Nash-Sutcliffe efficiency coefficient and coefficient of determination greater than 0.5. However, it failed to reproduce runoff for a subwatershed of Polecat Creek Watershed (PCA), where data show that runoff is not immediately responsive to rainfall. Uncertainty analysis revealed that the confidence intervals of the simulated monthly runoff and sediment load corresponded to 9.7 % and 10.2 % of their averages, respectively, at a significance level of 0.05. In addition, the average ranges of variation created by the Digital Elevation Model (DEM) and National Land Cover Data (NLCD) errors in the simulated monthly runoff and sediment load were equivalent to 7.5 % and 15.9 % of the average of their calibrated values, respectively. Based on the uncertainty analysis results, the Margin of Safety (MOS) of Total Maximum Daily Load (TMDL) were explicitly quantified as corresponding to 7.0 % and 21.3 % of the average of the simulated runoff and sediment load for ORD at significance level of 0.05. In conclusion, the HYSTAR model provided a new way to explicitly simulate runoff and sediment load of a watershed in a distributed manner. The approach developed here retains the simplicity of a unit hydrograph approach without employing numerical methods. Uncertainty analysis found that parameter uncertainty had greater impact on the model output than did expected Geographic Information System (GIS) data errors. In addition, the impact of the topographic data error on the model output was greater than was that of the land cover data error. Finally, this study provided a proof that a 5 to 10 % MOS that many TMDL studies consider underestimates modeling uncertainty.

The strong market demand for mobile applications such as iPhone makes value on the form factor of the mobile devices. The form factor means how much we can integrate many functions in a given size of the mobile devices. The external component size is almost comparable to a chip size so that elimination of external component is crucial to the success of mobile devices in addition to the cost issues of the external components. External reference resistors are often used as the standard for calibrating voltage sources, current sources, and other component values within a circuit. Often these calibrations occur at a factory, but may also occur on an electronic device as it is used. However, external reference resistors consume area and cost and it is desirable to eliminate them. This work introduces a new way to calibrate on-chip resistance and capacitance without the external reference resistors. An integrated circuit includes a benchmarking circuitry and a tunable circuitry. The benchmarking circuit includes a target component and an internal reference component. The internal reference component exhibits a lower sensitivity to the changes in test conditions than the target component. Benchmarking Metric Measurement Module (BMMM) measures benchmarking metrics for the internal reference component and the target component. A benchmark value is calculated based on the benchmarking metrics. The novelty of this work is the powerful way to cancel the parasitic and systemic errors caused by operational amplifiers in RC tuner circuitry. This technique is broadly applicable to any RF and analog circuits that need the calibration of tunable circuit elements without external references.

The purpose of this research is to experimentally generate increasingly adverse pressure gradient flow data for comparison with published data, to find similarities allowing categorization leading to improved flow prediction.

SAR backscatter data contain both geometric and radiometric distortions due to underlying topography and the radar viewing geometry. Thus, applications using SAR backscatter data for deriving various scientific products (e.g. above ground biomass) require accurate absolute radiometric calibration. The calibration process involves estimation of the local radar scattering area through knowledge of the imaged terrain, which is often obtained through DEMs. High resolution UAVSAR data over a New Hampshire boreal forest test site was radiometrically calibrated using a low resolution SRTM DEM, and different calibration methods were tested and compared. Heteromorphic methods utilizing DEM integration are able to model scattering area better than homomorphic methods based on the local incidence or projection angle with a resultant backscatter calibration difference of less than 0.5 dB. Additionally, the impact of low DEM resolution on the calibration was investigated through a Fourier analysis of different topographic classes. Power spectra of high-resolution airborne lidar DEMs were used to characterize the topography of steep, moderate, and flat terrain. Thus, errors for a given low resolution DEM associated with a particular topographic class could be quantified through a comparison of its power spectrum with that from the lidar. These errors were validated by comparing DEM slope derived from SRTM and lidar DEMs. The impact of radiometric calibration on the biomass retrieval capabilities of UAVSAR data was investigated by fitting second-order polynomials to backscatter vs. biomass plots for the HH, HV, and VV polarizations. LVIS RH50 values were used to calculate biomass, and the process was repeated for both uncalibrated and area calibrated UAVSAR images. The calibration improved the $R^2$ values for the polynomial fits by 0.7-0.8 for all three polarizations but had little effect on the polynomial coefficients. The Fourier method for predicting DEM errors was used to predict biomass errors due to the calibration. It was revealed that the greatest errors occurred in the near range of the SAR image and on slopes facing towards the radar.

Identifying critical source areas of sediment and phosphorus nonpoint pollutant loads under alternative land use scenarios is aided by the use of hydrologic models. We applied the Soil and Water Assessment Tool (SWAT) to the Willow River watershed in St. Croix County, Wisconsin, to examine the effects of possible future scenarios and best management practices. The model was calibrated and validated to water year (WY) 1999 and WY2006 datasets, respectively, with land use configured for each year. The model performed well in calibration, but could not simulate conditions outside of the calibration conditions in the validation dataset. Sediment and phosphorus trapping was influenced by trapping between the landscape source and the watershed outlet in closed-drainage lakes, flow-through wetlands, and on-stream reservoirs. The relative contributions of pollutants were related to the landscape position of the source area and the number and trapping efficiency of the intermediate traps in the flow path. We simulated best management practices including lowered soil-test phosphorus, increased conservation tillage, lowered cattle dietary phosphorus, and changed agricultural crop rotations. Simulations demonstrated that conversion to mulch tillage and no-till from conventional tillage could reduce sediment yield on the converted lands by 3% to 27% and phosphorus yield by 5% to 21%. For the current mix of agricultural land management in the Willow Watershed, converting all cropland to mulch tillage would reduce watershed export of phosphorus by 1% and sediment export by 1%. Converting all of the agricultural land to no-till produced a modeled decrease in watershed export of sediment of 2% and a decrease in phosphorus of 7%. Simulations also demonstrated a 22% reduction watershed phosphorus export by reducing average agricultural soil-test phosphorus to 20 ppm. Converting all farm land from a mixture of cash grain rotations to a dairy rotation that included two years of corn and three years of alfalfa caused a modeled reduction in watershed phosphorus export of 15% and a modeled reduction in sediment export of iii 5%. Continued conversion of agricultural land to rural residential land uses produced lower modeled loads of watershed sediment export up to 13% and phosphorus export up to 27% depending on the area developed and the average lot size. Changes in point source phosphorus because of better wastewater treatment caused a decrease in modeled phosphorus delivery of 13% between the calibration and validation time periods. Alternative climate scenarios were also simulated, showing that evapotranspiration was the driver of the altered hydrologic cycle, and thus the driver of reduced sediment and phosphorus export.

Abdominal Aortic Aneurysms (AAAs) are localized bulges in the lower aortic artery tissue. AAAs are prone to rupture, an extremely dangerous event, in which the aorta rips open and blood is allowed to flow freely into the body’s internal cavity. The fatality rate for ruptured AAAs is over 50% so preventative surgery is the preferred method of treatment. However many AAAs never rupture and the risks involved with preventative surgery are not negligible. Clinicians therefore must decide when the risks of AAA rupture outweigh those of preventative surgery.The current clinical metric for determining the risk of AAA rupture is the transverse diameter. A 5.5 cm diameter is the suggested max allowable size. As many as 20-30% of AAAs below this threshold rupture and in practice, the operating surgeon must account for other risk factors too such as blood pressure and aneurysm shape. As a result, the decision is no more than an educated guess based on a series of known risk factors. There is a clinical desire for a more reliable and comprehensive AAA rupture risk metric.Studies have shown that maximum arterial wall Von-Mises stress, calculated using patient-specific finite element (FE) models outperforms diameter with regards to predicting AAA rupture. Modern AAA FE models employ fully coupled dynamic fluid-structure interaction (FSI) techniques in an effort to accurately measure max wall stress in-vivo and non-invasively.Published boundary conditions (BCs) for dynamic AAA model fluid domains typically involve standard flow rate and pressure conditions being applied at the inlet and outlet of the model respectively. Our lab proposes using in-vivo blood velocity measurements from phase-encoded velocimetry MRI scans to generate patient-specific fluid BCs. A patient-specific flow rate condition is applied at the inlet matching the velocimetry data read in at the inlet. A patient-specific downstream pressure is applied at the outlet. This pressure BC is derived from an optimization routine which seeks to match the modeled and measured outlet flow rates by altering the impedance at the outlet.To date, only one model has been run to convergence, due to a computation run time of over 1 month. While changes were made to the pressure condition at the outlet (a 14% increase in dynamic range) during optimization, these changes had almost no effect of the max arterial wall stress.

Recent interest in new materials, including metamaterials and magneto-dielectrics, for RF applications provided strong impetus for measurement techniques to characterize associated permittivity, permeability, and loss factors. Traditional measurement techniques are not readily available to characterize these engineered composites. For example, conventional resonant cavity methods are known to be narrowband and require careful sample preparation. For metamaterials and magneto-dielectrics, broadband characterization is particularly necessary to observe their dispersive properties. Also, a challenge with new materials, such as layered composites, is the restriction in measurable shape, size and thickness. Often, small and irregularly shaped samples are available, making their characterization challenging. With these issues in mind, this dissertation is aimed at developing new characterization techniques for novel engineered composites. Specifically, four techniques are presented to characterize textured metamaterial volumetric structures, magneto-dielectric mixtures and films, and highly conductive metallo-dielectric films. One of the presented techniques is based on a Gaussian beam illumination. In this method, the Gaussian beam is used to illuminate the center of layered material samples to avoid diffraction from sample edges. In contrast to generating the Gaussian beam using bandwidth-limited lenses, the beam was reconstructed by scanning a probe over a virtual aperture much like the synthetic aperture radar process. This approach was successfully employed at X-band (8 to 12 GHz) for the characterization of slow-wave propagation in a layered metamaterial slab. However, the Gaussian beam method is not feasible at low frequencies as it requires a large sample aperture (> 1-wavelength in size). The second characterization method was, therefore, developed to measure smaller samples (< 0.25-wavelength) in lower frequencies (100 MHz to 4.8 GHz). More specifically, a stripline fixture, supporting transverse electromagnetic wave propagation, was designed to characterize permittivity and permeability of ferrite mixtures. This approach is suitable for reasonably thick samples but not accurate for extremely thin samples (thickness < 1 mm). For thin material composites, we employed a planar microstrip line based structure for accurate measurements. Furthermore, a new de-embedding process based on full-wave simulations was developed to avoid uncertainties in conventional quasi-static de-embedding process. The last and 4th presented method was developed for material samples with high conductivity. As compared to the low-conductive materials presented already, of interest with these materials is the characterization of conductivity and resistivity. Using a 1-port reflection coefficient measurement set-up, these quantities were extracted for multilayer metallo-dielectric films over broadbandwidth (100 MHz to 15 GHz).

For decades, the pavement engineering community has continued to drive improvements in accuracy and repeatability of terrain measurement systems. Traditional terrain measurement systems are tailored for a measuring a specific scale and resolution and hence application scope. These systems tend to focus on surface roughness alone and reject either fine macrotexture or large-scale global features. This work proposes a novel improvement to the terrain measurement system, by increasing the capability to measure the terrain surface at a variety of scales. By increasing the scales of measurement, desired aspects of the terrain profile can be accurately obtained for a wide variety of applications without having to omit large-scale features or macrotexture. In addition to increasing the capabilities of the traditional terrain measurement system, methods for addressing and minimizing sources of error within the system are developed. Major sources of error in terrain measurement systems, which compromise the accuracy and repeatability of the resulting measured terrain, include scanning laser uncertainty, inertial navigation system (INS) uncertainty and drift, triggering and time synchronization, system misalignment, and post-processing errors. These errors are addressed, and an improved Vehicle Terrain Measurement System (VTMS) is proposed. A triggering and time synchronization system is developed and insight into the development of this system for a terrain measurement system is gained. All three scanning lasers are individually assessed for linearity, with sample profiles analyzed for agreement. The improved VTMS represents a significant development in terrain measurement systems.

The long term calibration history of the Landsat 5 TM instrument has recently been defined using a time series of desert sites in Northern Africa. This correction is based on the assumption that the atmosphere is invariant and the reflectance of each site is approximately constant and Lambertian over time. As a result, the top of the atmosphere reflection is assumed constant when corrected for variations in the solar elevation angle and earth-sun distance. While this is true to first order and is the basis for all current temporal calibration, there are multiple known sources of residual error in the data. A methodology is presented for reducing the variation in pseudo-invariant site trending data based on correction for the BRDF. This work establishes a means to use DIRSIG to model the L5 calibration site. It combines a digital elevation map and desert atmosphere with a surface BRDF to reduce the residual errors in the calibration data. A set of Landsat 7 ETM+ calibration days is utilized to optimize the surface reflectance properties used in DIRSIG. These optimized parameters are then used to model the L5 TM calibration days. The results of the DIRSIG modeling are compared to the solar elevation angle and time of year trends of the original data and analyzed for their effectiveness at describing and reducing the residual errors. A major goal of this effort is to understand the contribution that BRDFs make to the current calibration errors and to develop methods that are robust enough to be applicable to a wider range of sites to enable extension of the methodology to earlier data sets (e.g. Landsat MSS). Additionally, while Landsat has a 30 m reflective resolution, the pseudo-invariant site calibration approach is valid for all spatial resolutions. Depending on another instrument's field of view, the BRDF error reduction technique used by L5 TM could either be used on the same desert calibration site or on a subsection of the area.

Abstract: An attempt was made to calibrate a steady state activated sludge model (ASM2d) for the biological nutrient removal process at the Gold bar wastewater treatment plant. This calibrated model could be used on a regular basis to test various operational strategies and predict effluent quality under different scenario. To achieve this historic data from the plant database was collected based on 24 composite samples. A trial and error method of wastewater characterization of the primary effluent was attempted using the influent advisor module of the GPS-[X] software. Sensitivity analysis of kinetic parameters was carried out and the most important ones identified were calibrated (default values were modified) based on literature. After calibration it was observed that the model was overestimating the concentrations of carbonaceous biological oxygen demand, total suspended solids and orthophosphate in the effluent, compared to the actual value measured at the plant. Similarly the effluent ammonia concentration was underestimated for most days along with the nitrate and nitrite concentration. This clearly indicated the need for a more accurate calibration based on experimental data to improve prediction capabilities and the reliability of the model.

A real time low energy spectral measurement of the neutrinos coming from the Sun will give us a greater understanding of energy production in the Sun, and the mechanisms of neutrino mixing. We will, for the first time, measure the solar neutrino spectrum for all solar neutrinos

The Borexino solar neutrino detector is a real-time liquid scintillator detector designed to measure sub-MeV neutrinos. With its unprecedented level of radio-purity, Borexino is poised to provide the most precise measurements to-date of solar neutrino and geo-antineutrino fluxes. However, in order to reduce the systematic errors to sub-5% levels, the detector must be care- fully calibrated to understand, among other things, the position and energy reconstructions. To that end, the Virginia Tech component of the Borexino collaboration has constructed a system for deploying and locating calibration sources within the detector. The system was used in four separate calibration campaigns and deployed numerous sources in almost 300 locations throughout the detector. The data from the calibrations have already resulted in the reduction of several sources of systematic error by a factor of two or more. With the results from the calibration, the Borexino detector has entered a new era of low- energy, high-precision, neutrino detection. This work was supported by NSF Grant 0802114

Incorporating relevant numerical information into decision-making is a fundamental and important aspect of numeracy. However, the process through which weight is assigned to particular numerical values is not well understood. The central theory proposed in this dissertation is that the weight assigned to numerical information may be conceptualized as a function of a set of discrete and largely independent cognitive and representational cues, each of which makes a relatively unique contribution to the information weighting process. This study focuses on five cues that may frequently be important for assigning weight to numerical information (though this list is not meant to be exhaustive): a) the ease with which information can be processed, b) the extent to which information deviates from expectations, c) the manner in which information is acquired, d) the precision of numerical representations, and e) the perceived uncertainty associated with a piece of information. For ease of processing, existing research was reviewed and implications for the practice of presenting numbers were considered. Experiments were conducted to investigate the roles of the remaining cues in the information weighting process.The first experiment's results indicated that when confidence in expectations was high, information received more weight when expectations were incorrect. However, contrary to predictions, information received more weight to the extent that it conformed to expectations when confidence was low. The second experiment's results showed that the weight assigned to numerical information was greater when it had been actively searched for before its value was learned (as opposed to being passively received). In the third experiment, the precision of numerical representations (as measured by the number of significant figures) was observed to be proportional to the weight assigned to information, while differences in precision across two numbers in a comparison made that comparison less influential. Finally, in the fourth experiment, the weight assigned to the probability level (as opposed to the interval width) was greater for confidence intervals with lower probabilities and narrower ranges, and also for intervals based on subjective judgments rather than empirical data. Implications were discussed for fields including education, journalism, and risk communication, among others.

During the past decade, numerous research has been carried out in in-vehicle navigation and positioning. All the approaches are trying to solve two problems: "where am I?", and "where are they?", i.e., the automatic vehicle positioning, and the surrounding vehicle detection and tracking. Among a variety of sensor based systems, computer vision-based approaches have been one of the most popular and promising techniques, however it suffers from intensity variations, narrow fields of view, and low-accuracy depth information. Laser Ranging Sensor (LIDAR) is another attractive technology due to its high accuracy in ranging, its wide-area view, and low data-processing requirements. However, a major challenge for LIDAR-based systems is that their reliability depends on the distance and reflectivity of different objects. Moreover, LIDAR often suffers from noise issues, making it difficult to distinguish between different kinds of objects. In this dissertation, we address several fundamental problems in integrating LIDAR and camera systems for better navigation and positioning solutions. As part of the research, we present a sensor fusion system to solve the "where are they" problem. The calibration of the sensor fusion system as well as the vehicle detection and tracking algorithms are proposed to determine the states of surrounding vehicles. The "where am I" solution focuses on the integration of LIDAR and inertial sensors for advanced vehicle positioning. Moreover, a vehicle tracking approach is presented for freeway traffic surveillance system. Sensor fusion techniques have been used for years to combine sensory data from disparate sources. In this dissertation, a tightly coupled LIDAR/CV integrated system is introduced. LIDAR and camera calibration is the key component of sensor fusion system. A unique multi-planar LIDAR and computer vision calibration algorithm has been developed, which requires that the camera and LIDAR observe a planar pattern at different positions and orientations. Geometric constraints of the different 'views' of the LIDAR and camera images are resolved as the coordinate transformation and rotation coefficients. The proposed sensor fusion system is utilized for mobile platform based vehicle detection and tracking. The LIDAR sensor estimates possible vehicle positions. Different Regions of Interest (ROIs) in the imagery are defined based on the LIDAR object hypotheses. An Adaboost object classifier is then utilized to detect the vehicle in ROIs. Finally, the vehicle's position and dimensions are derived from both the LIDAR and image data. Experimental results are presented to illustrate that this LIDAR/CV system is reliable. In addition, an autonomous positioning solution for urban environment is provided in this dissertation. The positioning solution is derived by combining measurements from both LIDAR and inertial sensors, i.e., LIDAR, gyros and accelerometers. The inertial sensors provide the angular velocities as well as the accelerations of the vehicle, while LIDAR detects the landmark structures (posts and surfaces). In our implementation the positioning is performed in known environment, i.e., the map information is assumed to be a priori information. Extended Kalman Filter (EKF) is implemented in the positioning estimation. This dissertation also presents a vehicle tracking approach used in a traffic surveillance system. One of the key challenges with freeway vehicle tracking is dealing with high density traffic, where occlusion often leads to foreground splitting and merging errors. We propose a real-time multi-vehicle tracking approach, which combines both local feature tracking and a global color probability model. In our approach, the corner features are tracked to provide position estimates of moving objects. Then a color probability is calculated in the occluded area to determine which object each pixel belongs to. This approach has been proved to be scalable to both stationary surveillance video and moving camera video.

The question of how exactly the universe began is the motivation for this work. Based on the discoveries of the cosmic expansion and of the cosmic microwave background (CMB) radiation, humans have learned of the Big Bang origin of the universe. However, what exactly happened in the first moments of the Big Bang? A scenario of initial exponential expansion called "inflation" was proposed in the 1980s, explaining several important mysteries about the universe. Inflation would have generated gravitational waves that would have left a unique imprint in the polarization of the CMB. To search for this evidence for inflation, a team gathered in 2002 to design a telescope experiment called BICEP. Sited at the South Pole, BICEP was a novel 25-cm aperture refractor with 49 pairs of polarization-sensitive bolometers. We completed 3 years of successful observations from February 2006 to December 2008. To constrain the amplitude of polarization resulting from inflation, expected to be at least 7 orders of magnitude fainter than the 3 K CMB intensity, precise control of systematic effects is essential. A crucial challenge is preventing systematic errors from introducing false polarization anisotropy signal at the level corresponding to ~0.1 μK in amplitude. One main focus of this thesis is the characterization of systematic effects for BICEP. We developed a simulation framework for propagating instrumental systematic effects to the final polarization results. Based on these simulations, we established benchmarks for the characterization of critical instrumental properties including bolometer relative gains, beam mismatch, polarization orientation, telescope pointing, sidelobes, thermal stability, and timestream noise model. Guided by these benchmarks, we carefully measured these properties and have shown that we have characterized the instrument adequately to ensure that systematic errors do not limit BICEP's current cosmology results. We have analyzed the first 2 years of data, lowering the upper limits on the gravitational-wave induced polarization by an order of magnitude over all previous experiments. The systematic error analysis has identified what future refinements are likely necessary to probe CMB polarization down to levels corresponding to inflationary energy scales below 2 × 1016 GeV.

Closed-loop control of combustion is of great importance for conventional diesel engines in order to reduce the deterioration in engine performance and emissions caused by different sources of variability. Diesel engine emissions and performance are affected by variability in the combustion root-cause variables like air mass, residual mass, injection parameters etc. If combustion can be referenced based on the root-cause combustion variables, the engine performance and emissions can be improved. Such a referencing, however, leads to increased calibration effort for the combustion controller due to increase in the number of scheduling variables for generating such references as well as due to the increase in the number of references. Conventional methods for generating the set-points for the closed-loop combustion controller are not suitable as they become impractical as the number of scheduling variables increases. In this work, inverse-distance based interpolation methods have been developed to generate the set-points for the closed-loop combustion controller. The inverse-distance interpolation method provides the advantage of reduced calibration effort and can be extended to multiple-dimensional interpolation without significant increase in computational effort. In this work, a closed-loop combustion control architecture has been developed for a heavy-duty diesel engine. The inverse-distance based calibration method has been demonstrated for a simplified version of the closed-loop combustion control architecture. The method involves an optimization approach that generates a scattered set of engine operating points where the engine should be calibrated. The inverse-distance interpolation method can interpolate with the scattered calibration data set to generate the set-points for the closed-loop combustion controller. The proposed method showed a great potential to improve the calibration effort when compared to conventional calibration methods that can be applied to the set-point generation problem. The inverse-distance based calibration approach resulted in a calibration effort that is 5 to 25 times less than that of a conventional method and resulted in engine performance and emissions that are comparable to those of the conventional method.

Abstract: An experimental investigation of the mean scalar concentration field of jets into a uniform counterflow stream using planar laser induced fluorescence is presented. The centerline decay and radial spreading of the mean concentration field of the jet were investigated. Jet to counterflow velocity ratios ranging between 4 to 19 were used for two different jet diameters. Universal forms for the centerline concentration decay, and radial concentration profiles of the jet are presented. Scaling factors of the centerline concentration decay are introduced. The jet growth rate was found to be divided into two regions: the linear growth region and the power law growth region. The effects of inlet yaw angles on the penetration length, axial concentration decay and similarity region of the counterflowing jet are presented. A minimal effect of the tested inlet yaw angles on the concentration field was observed. Empirical expressions to predict the centerline concentration decay are given.

Abstract: Intuition has fallen from grace. Its authority to act as a source of evidence in philosophical discourse has recently been called into question by philosophers and cognitive psychologists alike, who claim that because of the many difficulties that plague intuition, it should not hold the evidential role it does presently. This is exceedingly troubling, since appeals to intuition are pervasive throughout, and infiltrate every level of, philosophical discourse. This paper explores the extent of intuition’s infiltration in philosophy and whether intuition is warranted in those positions. I argue that by focusing on virtues exhibited by philosophical methodology, many of the arguments made against them are defused. In spite of this, we can largely carry on utilizing the methodology which houses intuitions – Standard Philosophical Analysis – while continually attempting to revise and refine that methodology.

The objective of this thesis is to demonstrate the layered sensing concept using Master-Slave cameras. The process of 2D camera calibration and several key factors that can present error during such calibration are described. The analysis and results are based on calibration of a pinhole model camera system. The calibration is accomplished using OpenCV software and the results are analyzed using MATLAB software. These results are divided into intrinsic and extrinsic camera parameters. These parameters are then used to determine the position and orientation of the object in the camera coordinate system. This thesis also explores the use of two cameras as a Master-Slave system to demonstrate the layered sensing concept. The Master camera’s orientation, zoom, and distance from the Slave camera is fixed. Using the position and orientation of the object in the Master camera coordinate system, the position of the object in the Slave coordinate system is found using transformation matrices. This information is then used to determine the pan/tilt angles of the Slave camera. The Slave camera is then directed to focus on the object using servo control.

This thesis examines the amount of detail in 3D scene reconstruction that can be extracted using structured-light camera and projector based systems. Structured light systems are similar to multi-camera stereoscopic systems, except that a projector is use in place of at least one camera. This aids 3D scene reconstruction by greatly simplifying the correspondence problem, i.e., identifying the same world point in multiple images. The motivation for this work comes from problems involved with the helical tomotherapy device in use at the University of Minnesota. This device performs conformal radiation therapy, delivering high radiation dosage to certain patient body areas, but lower dosage elsewhere. The device currently has no feedback as to the patient's body positioning, and vision-based methods are promising. The tolerances for such tracking are very tight, requiring methods that maximize the quality of reconstruction through good element placement and calibration. Optimal placement of cameras and projectors for specific detection tasks is examined, and a mathematical basis for judging the quality of camera and projector placement is derived. Two competing interests are taken into account for these quality measures: the overall visibility for the volume of interest, i.e., how much of a target object is visible; and the scale of visibility for the volume of interest, i.e., how precisely points can be detected. Optimal calibration of camera and projector systems is examined as well. Calibration is important as poor calibration will ultimately lead to a poor quality reconstruction. This is a difficult problem because projected patterns do not conform to any set geometric constraints when projected onto general scenes. Such constraints are often necessary for calibration. However, it can be shown that an optimal image-based calibration can be found for camera and projector systems if there are at least two cameras whose views overlap that of the projector. The overall quality of scene reconstruction from structured light systems is a complex problem. The work in this thesis analyzes this problem from multiple directions and provides methods and solutions that can be applied to real-world systems.

We discuss pre-flight calibration of the E and B EXperiment (EBEX), a balloon-borne telescope designed to measure the B-mode polarization anisotropy of the cosmic microwave background (CMB). EBEX will observe the sky with 8' resolution in each of three bands centered on 150, 250 and 410 GHz. Employing over 1,400 detectors and performing polarimetry through a continuously rotating half-wave plate with fixed wire-grid polarizer, we expect to detect the B-mode signal or set a new upper limit one order of magnitude below the current value. In this thesis we describe a set of ground-based experiments devised for calibrating instrumental response to incident millimeter-wave flux with varying spectral and polarization properties. We chronicle the design, construction and execution of these experiments, along with preliminary results from tests executed prior to our North American (NA) test flight which originated at the Columbia Scientific Ballooning Facility, Ft Sumner, NM in June 2009. A brief review of this inaugural flight is provided, as is a synopsis of our current plan for a comprehensive calibration strategy to be implemented in conjunction with a future long duration balloon (LDB) flight over Antarctica.

A water quality modeling study was conducted to determine and compare nitrogen loss from agricultural systems growing switchgrass and cotton in the southeastern USA. The water quality impacts were modeled at the plot scale and at the watershed scale. The Soil and Water Assessment Tool (SWAT) was used to replicate field conditions observed at switchgrass research plots at Pee Dee Research and Educational Center at Florence, South Carolina. The plot scale modeling suggested that in the early years of growth there is significant nitrogen loss from switchgrass to streamflow and groundwater but they are significantly less as the switchgrass matures. The long-term nitrogen loss over the lifetime of switchgrass was approximately 10% that from cotton. . The watershed-scale modeling was carried out for the Black Creek watershed located in the Pee Dee River basin in South Carolina. The results were even more encouraging than those for the plot-scale modeling. The long-term loss of nitrogen was approximately 1% that from cotton when switchgrass was grown on all cotton farms in the watershed, according to the simulations. The results also indicate use of computational models to quantify nitrogen fluxes in Life Cycle Assessment (LCA) of agricultural systems growing switchgrass gives a more accurate representation of the system than using constant emission factors.

The emergence of high-fidelity vehicle and tire models has raised the requirements for terrain measurement capabilities. Inaccuracies that were once tolerable for measurement of general terrain roughness are no longer acceptable for these new applications. The techniques in this work seek to improve the quality of terrain measurement in addition to providing an objective way to describe the accuracy of these measurements. The first portion of this work develops an accuracy verification procedure for terrain measurement systems. This procedure involves a static test to assess the limitations of the profiler's laser height sensor, and a corresponding dynamic test to evaluate the limitations of the positioning sensors. Even with a well calibrated system, inertial errors will accumulate. The second portion of this work develops techniques to address these inertial errors in the data post-processing phase. A general correction technique is developed for any terrain type and a more computationally efficient technique is developed for smooth surfaces. For basic ride and handling simulations, 3D terrain surfaces are computationally impractical, as the models used for these simulations only require point excitation. Current road profilers acquiring these 2D data use single-point lasers that capture localized disturbances that would be mechanically filtered by the tire and suspension in the physical vehicle system. The final chapter in this work develops a method to extract a 2D terrain profile from a 3D terrain surface. By considering all of the information in the tire contact patch, the filtering properties of the tire are approximately emulated.

Penetration of high velocity is of concern for both civilian and military research for decades, and computerized simulation is the scholar's focus in recent years. This study presents a study on the Discrete Element Method (DEM) simulation of plain concrete target's behavior under high-velocity penetration of rigid projectile. In this thesis, different types of research works including empirical, analytical and numerical methods in penetration by the previous scholars were carefully reviewed. A DEM-based concrete model was established by using software PFC3D. The major micro-variables of the simulation program were calibrated according to the required macro-mechanical parameters. Meanwhile, their correlations within the concrete range were studied, with the sensitivity analysis and the corresponding regression equations. With the established digital concrete model, penetration simulation tests were carried out. The results of penetration depth versus impact velocity were compared with the experimental and empirical calculated results from Forrestal's work in 1994. A good agreement was obtained. Some other simulation studies, like projectile mass, geometry, penetrating acceleration, concrete response stress, strain, and strain-rate were also conducted to study the constitutive properties in this thesis.

In the modern day, recognition and tracking of face or the iris is potentially one of the most powerful ways of differentiating between an authentic person and an imposter. Our method uses stereo vision to track the 3-Dimensional coordinates of a target equivalent to a person’s eyes and using a pan-tilt unit we target these areas for additional processing such as iris or facial imaging. One of the most important parts involved in tracking is the way the pan-tilt unit is calibrated. There have been techniques in the past where PTZ (Pan-tilt-zoom) digital camera has been used and calibrated using self calibration techniques involving a checker board calibration grid but the tracking error was found to be large in these techniques. We introduce a more accurate form of calibration of the pantilt unit using photogrammetric calibration technique and view the pan-tilt unit as an emulation of a Pinhole Lens Model to detect and track the target. The system is demonstrated on ideal targets.

The microscopic traffic simulation program VISSIM is a powerful tool that has been used by transportation engineers and urban planners around the world. A VISSIM simulation is meant to depict the performance of the physical road network through the use of modeling tools and behavioral parameters. The process which gets the model to the point of matching real world conditions is called calibration and requires a means of relating the real world to the simulated world. The topic of this thesis discusses a new means of calibration using the two-fluid model. The two-fluid model is a macroscopic modeling technique which provides quantitative characteristics of the performance of traffic flow on an urban road network. The model does this by generating a relationship between the travel time, stopped time, and running time per mile. The two-fluid model has been used to evaluate the performance of road networks for decades but now it is possible to use it to calibrate a VISSIM model. For this thesis, the two-fluid model to be used for calibration was generated from data collected on the Orlando, Florida, downtown network in February, 2008, during three traffic peaks for three typical weekdays. The network was then modeled in VISSIM which required a large amount of data regarding network geometry, signal timings, signal coordination schemes, and turning movement volumes. A similar data collection exercise was conducted during November, 2008, to capture the effects of changes that took place in the network during the ten month period. Another VISSIM network was also made to match the conditions of the November network. The February field data was used to successfully calibrate the VISSIM model and the November data was used to validate the calibrated network. The validation proved that the two-fluid models from the November field data and VISSIM data are statistically similar. With the network calibrated and validated, it could be used to perform scenario tests to see how the network performance would be affected by changes to the network. The two-fluid model has often been used to compare two different physical networks or explore how the performance of a single physical network has changed over time. A similar comparison can be done with the two-fluid models from a calibrated, simulated network. By using the original calibrated models as base cases, scenarios ranging from lane closures due to traffic incidents to the addition of a whole new signalized corridor on the network can be modeled in VISSIM and compared with the corresponding base case. This would allow a governing agency to preview the effects of proposed changes.