This thesis is on fatigue crack growth assessments of a thermomechanical loaded Marine Boiler- Sunrod CPDB12. The installation position of the marine boiler in the ship in relation to its fatigue life under mode 1 loading is investigated. Thermomechanical loading embodies pressures, temperatures, RAO, subjected to the rigid body dynamic of ship in the marine environment.   Linear elastic fracture mechanics (LEFM) method was used is predicting the growth rates of the welding flaws at the joint based on stress range of the Paris law relationship. FEA Numerical simulation delivered better crack growth rate assessments and life predictions of the smallest detectable flaws in the boiler.   The identified smallest detestable flaws at the welding joint diminishing the designed safe life of the boiler significantly.  Also, installation position within the ship do affect the fatigue life of the boiler.

Operationally, marine components and structures such as boiler in a Ship, are exposed to varying mechanically and thermally induced forces. High-frequency mechanical loading arises from the cyclic pressure, temperature transients, and six directional Rapid Amplitude Operator (RAOs). These types of loadings are mainly in the elastic region usually denoted as high cycle fatigue (HCF), most pronounced during the start-up, and the shut-down sequence of operation, which are responsible for an astronomically  reduction in Marine Boiler’s lifetime as compared to land boiler with same designed operating condition. Therefore, there is a need to determine the limitations of the engineering variables of the boiler with respect to Pressure, temperature, RAOs, and best locational point for the optimization of its designed lifetime during Operation. Detailed knowledge of this interaction between varying temperatures, RAOs and load cases is of considerable importance for precise lifetime calculations.  In order to understand and analyze the material behavior under contentious stress exposure, a general-purpose linear Finite Element (FE) code, LS-DYNA software is used as a pre-processor and solver during the simulation and data are post-processed using stress-based analysis method.

RSS-based localization is a promising solution for estimating the position of a non-collaborative emitter using a network of collaborative sensors. This paper examines RSS-based localization and differential RSS (DRSS) localization in the presence of correlated shadowing with no knowledge of the emitter's reference power.  A new non-linear least squares (NLS) DRSS location estimator that uses correlated shadowing information to improve performance is introduced. The existing maximum likelihood (ML) estimator and Cram\' er Rao lower bound (CRLB) for RSS-based localization given do not account for correlated shadowing. This paper presents a new ML estimator and CRLB for RSS-based localization that account for spatially correlated shadowing and imperfect knowledge of the emitter's reference power. The performance of the ML estimator is compared to the CRLB under different simulation conditions. The ML estimator is shown to be biased when the number of sensors is small or the shadowing variance is large. The effects of correlated shadowing on an RSS-based location estimator are thoroughly examined. It is proven that an increase in correlated shadowing will improve the accuracy of an RSS-based location estimator. It is also demonstrated that the ideal sensor geometry which minimizes the average error becomes more compact as correlation is increased. A geometric dilution of precision (GDOP) formulation is derived that provides a metric for the effect of the position of the sensors and emitter on the location estimator performance. A measurement campaign is conducted that characterizes the path loss at 3.4 GHz. The measurements are compared to the log-distance model. The errors between the model and the measurements, which should theoretically be Gaussian, have a Kurtosis value of 1.31. The errors were determined to be spatially correlated with an average correlation coefficient of 0.5 at a distance of 160 meters. The performance of the location estimators in simulation is compared to the performance using measurements from the measurement campaign. The performance is very similar, with the largest difference between the simulated and actual results in the ML estimator. In both cases, the new NLS DRSS estimator outperformed the other estimators and achieved the CRLB. / Master of Science

No description available.

Muskarin-cholinerge und adrenerge Rezeptoren des autonomen Nervensystems im Respirationstrakt spielen sowohl bei der physiologischen Regulation der Atemwegsfunktion als auch bei der Entstehung und Behandlung wiederkehrender obstruktiver Atemwegserkrankungen (RAO) des Pferdes eine wichtige Rolle. Im Wesentlichen sorgen diese Rezeptorsysteme für eine Relaxation und bzw. oder Kontraktion der glatten Atemwegsmuskulatur. Bei einer Erkrankung der Atemwege wird eine Störung der Balance beider Rezeptorsysteme vermutet. Neuere Forschungsergebnisse belegen, dass zum einen der β–adrenerge Rezeptor-Gs-Protein-Adenylatzyklase-Signalweg im Respirationstrakt RAO-erkrankter Pferde beeinträchtigt ist. Gleichzeitig war die Verteilung und Dichte der muskarin-cholinergen Rezeptoren unverändert. Die Signaltransduktionswege, insbesondere die des muskarin-cholinergen Rezeptorsystems, wurden jedoch bisher noch nicht ausreichend untersucht. Membranen des Lungenparenchyms sowie des Tracheal- und Bronchialepithels mit der darunter liegenden glatten Muskulatur gesunder und RAO-erkrankter Pferde wurden hinsichtlich der Funktionalität der M2- Rezeptor-Gi-Protein-AC-Kopplungsmechanismen mittels 35S-GTPγS-Bindungsstudien untersucht. Mit verschiedenen muskarin-cholinergen Agonisten und den Substanzen N-Ethylmaleimid (NEM) und Pertussistoxin (PTX) wurde die M2-Rezeptor-Gi-Protein-Kopplung überprüft. Vorher war die Ermittlung der Konzentrationen von Na+ (200 mmol/l), Mg2+ (10 mmol/l) und GDP (10 μmol/l) zur Etablierung einer optimierten 35S-GTPγS-Bindung notwendig. Es konnte gezeigt werden, dass die Basalbindung und die Agonisten-stimulierte 35S-GTPγS-Bindung zeitabhängig ist und eine Inkubationszeit festgelegt werden musste, bei der eine hohe relative Stimulation gemessen werden konnte. Diese Inkubationszeit lag bei 120 min bei einer Temperatur von 30°C. Bis zu diesem Zeitpunkt stieg die relative Stimulation der 35S-GTPγS-Bindung. Die muskarin-cholinergen Agonisten Oxotremorin M, Carbachol und Acetylcholin waren in der Lage die 35S-GTPγS-Bindung in allen untersuchten Segmenten bei gesunden und bei an RAO-erkrankten Pferden zu stimulieren, wobei Oxotremorin M die 35S-GTPγS-Bindung stärker als Carbachol und Acetylcholin stimulierte. Die maximale relative Stimulation lag in den Bronchien bei 126 %, in der Trachea bei 104 % und in der Lunge bei 41 %. Diese segmentabhängige Stimulierbarkeit der 35S-GTPγS-Bindung entspricht der Dichte der M2-muskarin-cholinergen Rezeptoren, die an Gi-Proteine gekoppelt sind. Bei an RAO-erkrankten Pferden konnte eine tendenziell stärkere Agonisten-stimulierte Interaktion zwischen den M2-muskarincholinergen Rezeptoren und Gi-Proteinen gemessen werden (Bronchien 141 % und Lunge 78 %) als bei gesunden Pferden. Dies könnte mit einer erhöhten Anzahl an Bindungsstellen für 35S-GTPγS begründet sein, was eine erhöhte Menge an Gi-Proteinen im erkrankten Gewebe bedeuten würde. Hierfür spricht die Hemmung der 35S-GTPγS-Bindung mit NEM und PTX, die die Agonisten-vermittelte 35S-GTPγS-Bindung im Gewebe von an RAO-erkrankten Pferden schwächer hemmte als im Gewebe von gesunden Pferden. Die indirekte Messung der AC-Aktivität zeigte eine segmentabhängige Reduzierung der cAMP-Produktion von Trachea über Bronchien bis hin zur Lunge. Oxotremorin M hemmte die Forskolin-vermittelte cAMPProduktion, und PTX war in der Lage diese durch Entkopplung der Gi-Proteine vom M2-Rezeptor zu hemmen. Ein weiterer Hinweis auf die erhöhte Menge von Gi-Proteinen im Gewebe RAO-erkrankter Pferde war die gemessene Reduzierung der Forskolin-induzierten cAMP-Produktion. In der vorliegenden Arbeit wurde erstmalig die Methode zur Messung der Rezeptorinteraktion mit korrespondierenden G-Proteinen - die 35S-GTPγS-Bindung - in Geweben des Respirationstrakts von Pferden etabliert. Die Stimulation mit muskarin-cholinergen Agonisten führte zu einer erhöhten 35S-GTPγS-Bindung bei an RAO-erkrankten Pferden. Außerdem konnte bei RAO eine Reduzierung der Forskolin-induzierten cAMP-Produktion beobachtet werden. Diese Ergebnisse deuten auf eine erhöhte Gi-Proteinmenge hin. Somit verschiebt sich bei RAO das Gi/Gs-Gleichgewicht auf Seite des Gi-Protein-vermittelten Signalwegs. Diese Veränderung des M2-Rezeptor-Gi-Protein-Signalwegs trägt, wie auch die Verschiebung des muskarincholinergen/ adrenergen Gleichgewichts durch β-Adrenozeptor-Downregulation, letztendlich zur bronchokonstriktorischen Aktivität bei RAO bei. Die Ergebnisse dieser Arbeit liefern somit die Grundlage für ein Evidenz-basiertes Konzept der Pharmakotherapie der RAO des Pferdes mit Muskarin-M2-selektiven Antagonisten zusätzlich zur etablierten Basistherapie mit β2-Sympathomimetika, insbesondere wenn gegenüber diesen bereits eine Toleranz besteht.

Summer pasture-associated recurrent airway obstruction (SPARAO) is characterized by reversible airway obstruction resulting from airway hyper-reactivity to aeroallergens, mucus accumulation, and airway inflammation. These are key clinical features that are shared with human asthma, suggesting SPARAO’s utility as an animal asthma model. SPARAO affects horses maintained on pasture in conditions of high heat and humidity. Common in the southeastern United States, the cause of SPARAO is unknown, but is presumed to reflect reactivity to seasonally inhaled pasture-associated aeroallergens. This investigation sought to identify well-characterized histopathological lesions of human asthma, collectively termed ‘asthmatic remodeling’, in lung tissue from horses with SPARAO. Two histological staining techniques were used: H&E and Movat’s Pentachrome. Similar to chronic asthma, lung tissue from horses with SPARAO demonstrates statistically significant increases in airway smooth muscle, fibrosis, airway occlusion and inflammation, goblet cell hyperplasia, and remodeling of terminal bronchioles and elastin fibers.

No description available.

Field-wise wind estimation (also known as model-based wind estimation) is a sophisticated technique to derive wind estimates from radar backscatter measurements. In contrast to the more traditional method known as point-wise wind retrieval, field-wise techniques estimate wind field model parameters. In this way, neighboring wind vectors are jointly estimated, ensuring consistency. This work presents and implementation for field-wise wind retrieval for the SeaWinds scatterometer on the QuikSCAT satellite. Due to its sophistication, field-wise wind retrieval adds computational complexity and intensity. The tradeoffs necessary for practical implementations are examined and quantified. The Levenberg-Marquardt algorithm for minimizing the field-wise objective function is presented. As the objective function has several near-global local minima, several wind fields represent ambiguous wind field estimates. A deterministic method is proposed to ensure sufficient ambiguities are obtained. An improved method for selecting between ambiguous wind field estimates is also proposed. With a large set of Sea-Winds measurements and estimates available, the σ° measurement statistics are examined. The traditional noise model is evaluated for accuracy. A data-driven parameterization is proposed and shown to effectively estimate measurement bias and variance. The parameterized measurement model is used to generate Cramer-Rao bounds on estimator performance. Using the Cramer-Rao bound, field-wise and point-wise performances are compared.

Maximum likelihood symbol timing estimation for communication over a frequency non-selective MIMO fading channel is developed. The cases of known data (data-aided estimation) and unknown data (non-data-aided estimation) together with known channel and unknown channel are considered. The analysis shows that the log-likelihood functions and their approximations can be interpreted as SISO log-likelihood functions operating on each of the receive antennas. Previously published symbol timing estimators are shown to be special cases of the more general framework presented. Architectures based on both block processing and sequential processing using a discrete-time phase-locked loop are summarized. Performance examples over a MIMO channel based on measured data and on a simple stochastic MIMO channel model are given. These examples show that the mean-squared error performance of these techniques is not strongly dependent on the MIMO channel and is able to reach the Cramer Rao bound when sufficient complexity is applied.

This work addresses two primary topics related to vibrations in structures. The first topic is the use of a spatially distributed sensor network for localization of vibration events. I use a received signal strength (RSS) framework that presumes exponential energy decay with distance to the source. I derive the Cramér-Rao bound (CRB) for this parameter estimation problem, with the unknown parameters being source location, source intensity, and the energy dissipation rate. In this framework, I show that the CRB matches the variance of maximum likelihood estimators (MLEs) in more computationally expensive Monte Carlo trials. I also compare the CRB to the results of physical experiments to test the power of the CRB to predict spatial areas where MLEs show practical evidence of being ill-conditioned. Supported by this evidence, I recommend the CRB as a simple measure of localization accuracy, which may be used to optimize sensor layouts before installation. I demonstrate how this numerical optimization may be performed for some regions of interest with simple geometries. The second topic investigates modal vibrations of multi-body structures built from simple one-dimensional elements, with networks of elastic strings as the primary example. I introduce a method of using a nonlinear eigenvalue problem (NLEVP) to express boundary conditions of the vibrating elements so that the (infinitely many) eigenvalues of the full structure are the eigenvalues of the finite-dimensional NLEVP. The mode shapes of the structure can then be recovered in analytic form (not as a discretization) from the corresponding eigenvectors of the NLEVP. I show some advantages of this method over dynamic stiffness matrices, which is another NLEVP framework for modal analysis. In numerical experiments, I test several contour integration solvers for NLEVPs on sample problems generated from string networks. / Doctor of Philosophy / This work deals with two primary topics related to vibrations in structures. The first topic is the use of vibration sensors to detect movement or impact and to estimate the location of the detected event. Sensors that are close to the event will record a larger amount of energy than the sensors that are farther away, so comparing the signals of several sensors can approximately establish the event location. In this way, vibration sensors might be used to monitor activity in a building without the use of intrusive cameras. The accuracy of location estimates can be greatly affected by the relative positions of the sensors and the event. Generally, location estimates tend to be most accurate if the sensors closely surround the event, and less accurate if the event is outside of the sensor zone. These principles are useful, but not precise. Given a framework for how event energy and noise are picked up by the sensors, the Cramér-Rao bound (CRB) is a formula for the achievable accuracy of location estimates. I demonstrate that the CRB is usefully similar to the location estimate accuracy from experimental data collected from a volunteer walking through a sensor-rigged hallway. I then show how CRB computations may be used to find an optimal arrangement of sensors. The match between the CRB and the accuracy of the experiments suggests that the sensor layout that optimizes the CRB will also provide accurate location estimates in a real building. The other main topic is how the vibrations of a structure can be understood through the structure's natural vibration frequencies and corresponding vibration shapes, called the "modes" of the structure. I connect vibration modes to the abstract framework of "nonlinear eigenvalue problems" (NLEVPs). An NLEVP is a square matrix-valued function for which one wants to find the inputs that make the matrix singular. But these singular matrices are usually isolated---% distributed among the infinitely many matrices of the NLEVP in places that are difficult to predict. After discussing NLEVPs in general and some methods for solving them, I show how the vibration modes of certain structures can be represented by the solutions of NLEVPs. The structures I analyze are multi-body structures that are made of simple interconnected pieces, such as elastic strings strung together into a spider web. Once a multi-body structure has been cast into the NLEVP form, an NLEVP solver can be used to find the vibration modes. Finally, I demonstrate that this method can be computationally faster than many traditional modal analysis techniques.