Evaluation of material crack using acoustic emission technique

Cracks in civil structures can result in premature failure due to material degradation and can result in both financial loss and environmental consequences. This thesis reports an effective technique using Acoustic Emission (AE) technique to assess the severity of the crack propagation in steel structures. The outcome of this work confirms that combination of AE parametric analysis and signal processing techniques can be used to evaluate crack propagation under different loading configurations. The technique has potential application to assess and monitor the condition of civil structures.

Influence of spatial variability of permeability property on steady state seepage flow and slope stability analysis

In recent years, spatial variability modeling of soil parameters using random field theory has gained distinct importance in geotechnical analysis. In the present Study, commercially available finite difference numerical code FLAC 5.0 is used for modeling the permeability parameter as spatially correlated log-normally distributed random variable and its influence on the steady state seepage flow and on the slope stability analysis are studied. Considering the case of a 5.0 m high cohesive-frictional soil slope of 30 degrees, a range of coefficients of variation (CoV%) from 60 to 90% in the permeability Values, and taking different values of correlation distance in the range of 0.5-15 m, parametric studies, using Monte Carlo simulations, are performed to study the following three aspects, i.e., (i) effect ostochastic soil permeability on the statistics of seepage flow in comparison to the analytic (Dupuit's) solution available for the uniformly constant permeability property; (ii) strain and deformation pattern, and (iii) stability of the given slope assessed in terms of factor of safety (FS). The results obtained in this study are useful to understand the role of permeability variations in slope stability analysis under different slope conditions and material properties. (C) 2009 Elsevier B.V. All rights reserved.

Boundary-layer effects on internal flow choking in dual-thrust solid rocket motors

Theoretical studies have been carried out to examine internal flow choking in the inert simulators of a dual-thrust motor. Using a two-dimensional k-omega turbulence model, detailed parametric studies have been carried out to examine aerodynamic choking and the existence of a fluid throat at the transition region during the startup transient of dual-thrust motors. This code solves standard k-omega turbulence equations with shear flow corrections using a coupled second-order-implicit unsteady formulation. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-averaged, Navier-Stokes equations is employed. It was observed that, at the subsonic inflow conditions, there is a possibility of the occurrence of internal flow choking in dual-thrust motors due to the formation of a fluid throat at the beginning of the transition region induced by area blockage caused by boundary-layer-displacement thickness. It has been observed that a 55% increase in the upstream port area of the dual-thrust motor contributes to a 25% reduction in blockage factor at the transition region, which could negate the internal How choking and supplement with an early choking of the dual-thrust motor nozzle. If the height of the upstream port relative to the motor length is too small, the developing boundary layers from either side of the port can interact, leading to a choked,flow. On the other hand, if the developing boundary layers are far enough apart, then choking does not occur. The blockage factor is greater in magnitude for the choked case than for the unchoked case. More tangible explanations are presented in this paper for the boundary-layer blockage and the internal flow choking in dual-thrust motors, which hitherto has been unexplored.

Clinical application of biomarkers in prostate cancer in men with metabolic syndrome project: Prostate Specific Membrane Antigen (PSMA) Positron Emission Tomography (PET) in diagnosing localised prostate cancer

Localised prostate cancer is a heterogenous disease and a multi-modal approach is required to accurately diagnose and stage the disease. Whilst the use of magnetic resonance imaging (MRI) has become more common, small volume and multi-focal disease are oft en diffi cult to characterise. Prostate specifi c membrane antigen is a cell surface protein, which is expressed in nearly all prostate cancer cells. Its expression is signifi cantly higher in high grade prostate cancer cells. In this study, we compare multi-parametric magnetic resonance imaging and 68-Gallinium-PSMA PET with whole-mount pathology of the prostate to evaluate the applicability of multiparameteric (MP) MRI and 68Ga-PSMA PET in detecting and locating tumour foci in patients with localised prostate cancer.

Characterization of Failure Modes in CFRP Composites - An ANN Approach

Carbon fiber reinforced polymer (CFRP) composite specimens with different thickness, geometry, and stacking sequences were subjected to fatigue spectrum loading in stages. Another set of specimens was subjected to static compression load. On-line acoustic Emission (AE) monitoring was carried out during these tests. Two artificial neural networks, Kohonen-self organizing feature map (KSOM), and multi-layer perceptron (MLP) have been developed for AE signal analysis. AE signals from specimens were clustered using the unsupervised learning KSOM. These clusters were correlated to the failure modes using available a priori information such as AE signal amplitude distributions, time of occurrence of signals, ultrasonic imaging, design of the laminates (stacking sequences, orientation of fibers), and AE parametric plots. Thereafter, AE signals generated from the rest of the specimens were classified by supervised learning MLP. The network developed is made suitable for on-line monitoring of AE signals in the presence of noise, which can be used for detection and identification of failure modes and their growth. The results indicate that the characteristics of AE signals from different failure modes in CFRP remain largely unaffected by the type of load, fiber orientation, and stacking sequences, they being representatives of the type of failure phenomena. The type of loading can have effect only on the extent of damage allowed before the specimens fail and hence on the number of AE signals during the test. The artificial neural networks (ANN) developed and the methods and procedures adopted show significant success in AE signal characterization under noisy environment (detection and identification of failure modes and their growth).

Migraine Comorbidities : A Clinical and Molecular Genetic Study

Migraine is a highly prevalent disease, and despite several important breakthroughs there are still a many questions unanswered in the clinical, genetic and pathophysiological aspects of migraine research. Migraine has been linked to several other diseases such as epilepsy and stroke, but there are still unsolved issues concerning the true nature of these associations. Three genes predisposing to hemiplegic migraine and several loci associated to migraine have been identified, but so far no genes responsible for common forms of migraine have been recognized. Triptans have provided an important step in migraine treatment, but their usefulness in rare forms of migraine have been controversial. The Finnish Migraine Gene Project (FMGP) includes more than 1600 families and 7500 individuals. We evaluated comorbidity from 1000 consecutive subjects in the FMGP. To search for novel loci, we performed a genome-wide linkage scan in 36 families with high prevalences of migraine with visual aura. We collected 76 subjects from the FMGP who suffer from hemiplegic migraine and have used triptans. Finally, to study possible links between stroke and migraine we evaluated the prevalence of migraine in subjects with cervical artery dissection (CAD) and healthy controls. Migraine was associated with increased prevalence of allergy, hypotension and psychiatric diseases. Additionally, men suffering from migraine with aura had increased prevalence of epilepsy and stroke. Further evidence of association between migraine and epilepsy was found in our linkage study. The parametric two-point linkage analysis showed significant evidence of linkage between migraine aura and a locus on 9q21-q22. Interestingly, the same locus has been associated with occipitotemporal epilepsy. CAD seems to be a migraine risk factor, and therefore a link between stroke and migraine. Notably, CAD seems to alleviate migraine activity further indicating the association between these two conditions. Despite the contraindications of triptans, it seems that they are safe and effective in the abortive treatment of hemiplegic migraine.

Energy efficient change detection over a MAC using physical layer fusion

We propose a simple and energy efficient distributed change detection scheme for sensor networks based on Page's parametric CUSUM algorithm. The sensor observations are IID over time and across the sensors conditioned on the change variable. Each sensor runs CUSUM and transmits only when the CUSUM is above some threshold. The transmissions from the sensors are fused at the physical layer. The channel is modeled as a multiple access channel (MAC) corrupted with IID noise. The fusion center which is the global decision maker, performs another CUSUM to detect the change. We provide the analysis and simulation results for our scheme and compare the performance with an existing scheme which ensures energy efficiency via optimal power selection.

Gaussian mixture model based switched split vector quantization of LSF parameters

We address the issue of rate-distortion (R/D) performance optimality of the recently proposed switched split vector quantization (SSVQ) method. The distribution of the source is modeled using Gaussian mixture density and thus, the non-parametric SSVQ is analyzed in a parametric model based framework for achieving optimum R/D performance. Using high rate quantization theory, we derive the optimum bit allocation formulae for the intra-cluster split vector quantizer (SVQ) and the inter-cluster switching. For the wide-band speech line spectrum frequency (LSF) parameter quantization, it is shown that the Gaussian mixture model (GMM) based parametric SSVQ method provides 1 bit/vector advantage over the non-parametric SSVQ method.

Concrete-filled double skin tube columns subjected to lateral impact loading: Experimental and numerical study

This research treats the lateral impact behaviour of composite columns, which find increasing use as bridge piers and building columns. It offers (1) innovative experimental methods for testing structural columns, (2) dynamic computer simulation techniques as a viable tool in analysis and design of such columns and (3) significant new information on their performance which can be used in design. The research outcomes will enable to protect lives and properties against the risk of vehicular impacts caused either accidentally or intentionally.

Multi-Tone Testing of Linear and Nonlinear Analog Circuits using Polynomial Coefficients

A method of testing for parametric faults of analog circuits based on a polynomial representation of fault-free function of the circuit is presented. The response of the circuit under test (CUT) is estimated as a polynomial in the applied input voltage at relevant frequencies in addition to DC. Classification or Cur is based on a comparison of the estimated polynomial coefficients with those of the fault free circuit. This testing method requires no design for test hardware as might be added to the circuit fly some other methods. The proposed method is illustrated for a benchmark elliptic filter. It is shown to uncover several parametric faults causing deviations as small as 5% from the nominal values.

Macroseismology as a Component of Seismicity Assessments in an Intraplate Region: Studies of Northern Europe with Emphasis on Finland

This work focuses on the role of macroseismology in the assessment of seismicity and probabilistic seismic hazard in Northern Europe. The main type of data under consideration is a set of macroseismic observations available for a given earthquake. The macroseismic questionnaires used to collect earthquake observations from local residents since the late 1800s constitute a special part of the seismological heritage in the region. Information of the earthquakes felt on the coasts of the Gulf of Bothnia between 31 March and 2 April 1883 and on 28 July 1888 was retrieved from the contemporary Finnish and Swedish newspapers, while the earthquake of 4 November 1898 GMT is an example of an early systematic macroseismic survey in the region. A data set of more than 1200 macroseismic questionnaires is available for the earthquake in Central Finland on 16 November 1931. Basic macroseismic investigations including preparation of new intensity data point (IDP) maps were conducted for these earthquakes. Previously disregarded usable observations were found in the press. The improved collection of IDPs of the 1888 earthquake shows that this event was a rare occurrence in the area. In contrast to earlier notions it was felt on both sides of the Gulf of Bothnia. The data on the earthquake of 4 November 1898 GMT were augmented with historical background information discovered in various archives and libraries. This earthquake was of some concern to the authorities, because extra fire inspections were conducted in three towns at least, i.e. Tornio, Haparanda and Piteå, located in the centre of the area of perceptibility. This event posed the indirect hazard of fire, although its magnitude around 4.6 was minor on the global scale. The distribution of slightly damaging intensities was larger than previously outlined. This may have resulted from the amplification of the ground shaking in the soft soil of the coast and river valleys where most of the population was found. The large data set of the 1931 earthquake provided an opportunity to apply statistical methods and assess methodologies that can be used when dealing with macroseismic intensity. It was evaluated using correspondence analysis. Different approaches such as gridding were tested to estimate the macroseismic field from the intensity values distributed irregularly in space. In general, the characteristics of intensity warrant careful consideration. A more pervasive perception of intensity as an ordinal quantity affected by uncertainties is advocated. A parametric earthquake catalogue comprising entries from both the macroseismic and instrumental era was used for probabilistic seismic hazard assessment. The parametric-historic methodology was applied to estimate seismic hazard at a given site in Finland and to prepare a seismic hazard map for Northern Europe. The interpretation of these results is an important issue, because the recurrence times of damaging earthquakes may well exceed thousands of years in an intraplate setting such as Northern Europe. This application may therefore be seen as an example of short-term hazard assessment.

Non-Gaussian Cosmological Perturbations from Hybrid Inflation and Preheating

This thesis consists of four research papers and an introduction providing some background. The structure in the universe is generally considered to originate from quantum fluctuations in the very early universe. The standard lore of cosmology states that the primordial perturbations are almost scale-invariant, adiabatic, and Gaussian. A snapshot of the structure from the time when the universe became transparent can be seen in the cosmic microwave background (CMB). For a long time mainly the power spectrum of the CMB temperature fluctuations has been used to obtain observational constraints, especially on deviations from scale-invariance and pure adiabacity. Non-Gaussian perturbations provide a novel and very promising way to test theoretical predictions. They probe beyond the power spectrum, or two point correlator, since non-Gaussianity involves higher order statistics. The thesis concentrates on the non-Gaussian perturbations arising in several situations involving two scalar fields, namely, hybrid inflation and various forms of preheating. First we go through some basic concepts -- such as the cosmological inflation, reheating and preheating, and the role of scalar fields during inflation -- which are necessary for the understanding of the research papers. We also review the standard linear cosmological perturbation theory. The second order perturbation theory formalism for two scalar fields is developed. We explain what is meant by non-Gaussian perturbations, and discuss some difficulties in parametrisation and observation. In particular, we concentrate on the nonlinearity parameter. The prospects of observing non-Gaussianity are briefly discussed. We apply the formalism and calculate the evolution of the second order curvature perturbation during hybrid inflation. We estimate the amount of non-Gaussianity in the model and find that there is a possibility for an observational effect. The non-Gaussianity arising in preheating is also studied. We find that the level produced by the simplest model of instant preheating is insignificant, whereas standard preheating with parametric resonance as well as tachyonic preheating are prone to easily saturate and even exceed the observational limits. We also mention other approaches to the study of primordial non-Gaussianities, which differ from the perturbation theory method chosen in the thesis work.

Non-Gaussianities and Preheating from N-flation and Magnetogenesis via rotating cosmic string loops

In this thesis we examine multi-field inflationary models of the early Universe. Since non-Gaussianities may allow for the possibility to discriminate between models of inflation, we compute deviations from a Gaussian spectrum of primordial perturbations by extending the delta-N formalism. We use N-flation as a concrete model; our findings show that these models are generically indistinguishable as long as the slow roll approximation is still valid. Besides computing non-Guassinities, we also investigate Preheating after multi-field inflation. Within the framework of N-flation, we find that preheating via parametric resonance is suppressed, an indication that it is the old theory of preheating that is applicable. In addition to studying non-Gaussianities and preheatng in multi-field inflationary models, we study magnetogenesis in the early universe. To this aim, we propose a mechanism to generate primordial magnetic fields via rotating cosmic string loops. Magnetic fields in the micro-Gauss range have been observed in galaxies and clusters, but their origin has remained elusive. We consider a network of strings and find that rotating cosmic string loops, which are continuously produced in such networks, are viable candidates for magnetogenesis with relevant strength and length scales, provided we use a high string tension and an efficient dynamo.

Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

Fracture analysis of stiffened panels under combined tensile, bending, and shear loads

The objective is to present the formulation of numerically integrated modified virtual crack closure integral technique for concentrically and eccentrically stiffened panels for computation of strain-energy release rate and stress intensity factor based on linear elastic fracture mechanics principles. Fracture analysis of cracked stiffened panels under combined tensile, bending, and shear loads has been conducted by employing the stiffened plate/shell finite element model, MQL9S2. This model can be used to analyze plates with arbitrarily located concentric/eccentric stiffeners, without increasing the total number of degrees of freedom, of the plate element. Parametric studies on fracture analysis of stiffened plates under combined tensile and moment loads have been conducted. Based on the results of parametric,studies, polynomial curve fitting has been carried out to get best-fit equations corresponding to each of the stiffener positions. These equations can be used for computation of stress intensity factor for cracked stiffened plates subjected to tensile and moment loads for a given plate size, stiffener configuration, and stiffener position without conducting finite element analysis.