An exploratory study to determine applicability of nano-hardness and micro-compression measurements for yield stress estimation

The superior properties of ferritic/martensitic steels in a radiation environment (low swelling, low activation under irradiation and good corrosion resistance) make them good candidates for structural parts in future reactors and spallation sources. While it cannot substitute for true reactor experiments, irradiation by charged particles from accelerators can reduce the number of reactor experiments and support fundamental research for a better understanding of radiation effects in materials. Based on the nature of low energy accelerator experiments, only a small volume of material can be uniformly irradiated. Micro and nanoscale post irradiation tests thus have to be performed. We show here that nanoindentation and micro-compression testing on T91 and HT-9 stainless steel before and after ion irradiation are useful methods to evaluate the radiation induced hardening.

Reducing uncertainties in estimation of wind effects on tall buildings using aerodynamic wind tunnel tests

Tall buildings are wind-sensitive structures and could experience high wind-induced effects. Aerodynamic boundary layer wind tunnel testing has been the most commonly used method for estimating wind effects on tall buildings. Design wind effects on tall buildings are estimated through analytical processing of the data obtained from aerodynamic wind tunnel tests. Even though it is widely agreed that the data obtained from wind tunnel testing is fairly reliable the post-test analytical procedures are still argued to have remarkable uncertainties. This research work attempted to assess the uncertainties occurring at different stages of the post-test analytical procedures in detail and suggest improved techniques for reducing the uncertainties. Results of the study showed that traditionally used simplifying approximations, particularly in the frequency domain approach, could cause significant uncertainties in estimating aerodynamic wind-induced responses. Based on identified shortcomings, a more accurate dual aerodynamic data analysis framework which works in the frequency and time domains was developed. The comprehensive analysis framework allows estimating modal, resultant and peak values of various wind-induced responses of a tall building more accurately. Estimating design wind effects on tall buildings also requires synthesizing the wind tunnel data with local climatological data of the study site. A novel copula based approach was developed for accurately synthesizing aerodynamic and climatological data up on investigating the causes of significant uncertainties in currently used synthesizing techniques. Improvement of the new approach over the existing techniques was also illustrated with a case study on a 50 story building. At last, a practical dynamic optimization approach was suggested for tuning structural properties of tall buildings towards attaining optimum performance against wind loads with less number of design iterations.

Intracranial Volume Estimation and Graph Theoretical Analysis of Brain Functional Connectivity Networks

Understanding pathways of neurological disorders requires extensive research on both functional and structural characteristics of the brain. This dissertation introduced two interrelated research endeavors, describing (1) a novel integrated approach for constructing functional connectivity networks (FCNs) of brain using non-invasive scalp EEG recordings; and (2) a decision aid for estimating intracranial volume (ICV). The approach in (1) was developed to study the alterations of networks in patients with pediatric epilepsy. Results demonstrated the existence of statistically significant (p

Estimation of Inequality Indices of the Cumulative Distribution Function

Date of Acceptance: 02/03/2015

Estimation of Inequality Indices of the Cumulative Distribution Function

Date of Acceptance: 02/03/2015

A Delay Vector Variance based marker for an output-only assessment of structural changes in tension leg platforms

Although aspects of power generation of many offshore renewable devices are well understood, their dynamic responses under high wind and wave conditions are still to be investigated to a great detail. Output only statistical markers are important for these offshore devices, since access to the device is limited and information about the exposure conditions and the true behaviour of the devices are generally partial, limited, and vague or even absent. The markers can summarise and characterise the behaviour of these devices from their dynamic response available as time series data. The behaviour may be linear or nonlinear and consequently a marker that can track the changes in structural situations can be quite important. These markers can then be helpful in assessing the current condition of the structure and can indicate possible intervention, monitoring or assessment. This paper considers a Delay Vector Variance based marker for changes in a tension leg platform tested in an ocean wave basin for structural changes brought about by single column dampers. The approach is based on dynamic outputs of the device alone and is based on the estimation of the nonlinearity of the output signal. The advantages of the selected marker and its response with changing structural properties are discussed. The marker is observed to be important for monitoring the as- deployed structural condition and is sensitive to changes in such conditions. Influence of exposure conditions of wave loading is also discussed in this study based only on experimental data.

Cognitive and structural aspects of addiction: Relation between iris patterns, time perception, eyeblink rate, impulsivity and cigarette addiction

Objectif : Le but de ce travail est d'étudier les corrélations existantes entre les patterns de l'iris, la perception du temps et la fréquence de clignement des paupières (eye blink rate) et ceci en relation avec l'addiction à la cigarette. Méthodologie: Revue de la littérature existante. Expériences sur une cohorte d'au moins trente sujets fumeurs/non-fumeurs. Analyses statistiques. Résultats: Nos résultats confirment qu'il existe des relations entre l'impulsivité, les patterns d'iris, l'eye blink rate spontané et la perception du temps. Nous observons également que l'addiction à la cigarette et son niveau de dépendance ont une influence sur ces différentes mesures. En effet, les sujets fumeurs tendent à avoir une personnalité plus impulsive par rapport aux sujets contrôles. On remarque également une nette diminution de l'eye blink rate dans le groupe des fumeurs et une tendance à la sur-estimation du temps qui passe. Conclusion : Ce travail nous permet de mieux comprendre les différentes corrélations qui existent entre les différentes variables que nous avons mesurées (patterns d'iris, score d'impulsivité et eye blink rate) ainsi que leur relation à l'addiction à la cigarette. Dès lors qu'il est avéré que les fumeurs peuvent avoir une perception du temps altérée par rapport au groupe contrôle, il serait intéressant d'en étudier l'évolution sur le long terme (aggravation avec la durée du tabagisme actif) ainsi que les conséquences qui en découlent écologiquement au moyen d'études longitudinales et de terrain.

Knowledge about dietary fibres (KADF): development and validation of an evaluation instrument through structural equation modelling (SEM)

Objectives: Because there is scientific evidence that an appropriate intake of dietary fibre should be part of a healthy diet, given its importance in promoting health, the present study aimed to develop and validate an instrument to evaluate the knowledge of the general population about dietary fibres. Study design: The present study was a cross sectional study. Methods: The methodological study of psychometric validation was conducted with 6010 participants, residing in ten countries from 3 continents. The instrument is a questionnaire of self-response, aimed at collecting information on knowledge about food fibres. For exploratory factor analysis (EFA) was chosen the analysis of the main components using varimax orthogonal rotation and eigenvalues greater than 1. In confirmatory factor analysis by structural equation modelling (SEM) was considered the covariance matrix and adopted the Maximum Likelihood Estimation algorithm for parameter estimation. Results: Exploratory factor analysis retained two factors. The first was called Dietary Fibre and Promotion of Health (DFPH) and included 7 questions that explained 33.94 % of total variance ( = 0.852). The second was named Sources of Dietary Fibre (SDF) and included 4 questions that explained 22.46% of total variance ( = 0.786). The model was tested by SEM giving a final solution with four questions in each factor. This model showed a very good fit in practically all the indexes considered, except for the ratio 2/df. The values of average variance extracted (0.458 and 0.483) demonstrate the existence of convergent validity; the results also prove the existence of discriminant validity of the factors (r2 = 0.028) and finally good internal consistency was confirmed by the values of composite reliability (0.854 and 0.787). Conclusions: This study allowed validating the KADF scale, increasing the degree of confidence in the information obtained through this instrument in this and in future studies.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

DEVELOPMENT AND VALIDATION OF THE ANTERIOR CRUCIATE LIGAMENT INJURY-RISK-ESTIMATION QUIZ (ACL-IQ)

Over 2 million Anterior Cruciate Ligament (ACL) injuries occur annually worldwide resulting in considerable economic and health burdens (e.g., suffering, surgery, loss of function, risk for re-injury, and osteoarthritis). Current screening methods are effective but they generally rely on expensive and time-consuming biomechanical movement analysis, and thus are impractical solutions. In this dissertation, I report on a series of studies that begins to investigate one potentially efficient alternative to biomechanical screening, namely skilled observational risk assessment (e.g., having experts estimate risk based on observations of athletes movements). Specifically, in Study 1 I discovered that ACL injury risk can be accurately and reliably estimated with nearly instantaneous visual inspection when observed by skilled and knowledgeable professionals. Modern psychometric optimization techniques were then used to develop a robust and efficient 5-item test of ACL injury risk prediction skill—i.e., the ACL Injury-Risk-Estimation Quiz or ACL-IQ. Study 2 cross-validated the results from Study 1 in a larger representative sample of both skilled (Exercise Science/Sports Medicine) and un-skilled (General Population) groups. In accord with research on human expertise, quantitative structural and process modeling of risk estimation indicated that superior performance was largely mediated by specific strategies and skills (e.g., ignoring irrelevant information), independent of domain general cognitive abilities (e.g., metal rotation, general decision skill). These cognitive models suggest that ACL-IQ is a trainable skill, providing a foundation for future research and applications in training, decision support, and ultimately clinical screening investigations. Overall, I present the first evidence that observational ACL injury risk prediction is possible including a robust technology for fast, accurate and reliable measurement—i.e., the ACL-IQ. Discussion focuses on applications and outreach including a web platform that was developed to house the test, provide a repository for further data collection, and increase public and professional awareness and outreach (www.ACL-IQ.org). Future directions and general applications of the skilled movement analysis approach are also discussed.

Reducing Uncertainties in Estimation of Wind Effects on Tall Buildings Using Aerodynamic Wind Tunnel Tests

Tall buildings are wind-sensitive structures and could experience high wind-induced effects. Aerodynamic boundary layer wind tunnel testing has been the most commonly used method for estimating wind effects on tall buildings. Design wind effects on tall buildings are estimated through analytical processing of the data obtained from aerodynamic wind tunnel tests. Even though it is widely agreed that the data obtained from wind tunnel testing is fairly reliable the post-test analytical procedures are still argued to have remarkable uncertainties. This research work attempted to assess the uncertainties occurring at different stages of the post-test analytical procedures in detail and suggest improved techniques for reducing the uncertainties. Results of the study showed that traditionally used simplifying approximations, particularly in the frequency domain approach, could cause significant uncertainties in estimating aerodynamic wind-induced responses. Based on identified shortcomings, a more accurate dual aerodynamic data analysis framework which works in the frequency and time domains was developed. The comprehensive analysis framework allows estimating modal, resultant and peak values of various wind-induced responses of a tall building more accurately. Estimating design wind effects on tall buildings also requires synthesizing the wind tunnel data with local climatological data of the study site. A novel copula based approach was developed for accurately synthesizing aerodynamic and climatological data up on investigating the causes of significant uncertainties in currently used synthesizing techniques. Improvement of the new approach over the existing techniques was also illustrated with a case study on a 50 story building. At last, a practical dynamic optimization approach was suggested for tuning structural properties of tall buildings towards attaining optimum performance against wind loads with less number of design iterations.

Manipulating the structural and electronic properties of epitaxial NaNbO3 films via strain and stoichiometry

Due to their intriguing dielectric, pyroelectric, elasto-electric, or opto-electric properties, oxide ferroelectrics are vital candidates for the fabrication of most electronics. However, these extraordinary properties exist mainly in the temperature regime around the ferroelectric phase transition, which is usually several hundreds of K away from room temperature. Therefore, the manipulation of oxide ferroelectrics, especially moving the ferroelectric transition towards room temperature, is of great interest for application and also basic research. In this thesis, we demonstrate this using examples of NaNbO3 films. We show that the transition temperature of these films can be modified via plastic strain caused by epitaxial film growth on a structurally mismatched substrate, and this strain can be fixed by controlling the stoichiometry. The structural and electronic properties of Na1+xNbO3+δ thin films are carefully examined by among others XRD (e.g. RSM) and TEM and cryoelectronic measurements. Especially the electronic features are carefully analyzed via specially developed interdigitated electrodes in combination with integrated temperature sensor and heater. The electronic data are interpreted using existing as well as novel theories and models, they are proved to be closely correlated to the structural characteristics. The major results are: -Na1+xNbO3+δ thin films can be grown epitaxially on (110)NdGaO3 with a thickness up to 140 nm (thicker films have not been studied). Plastic relaxation of the compressive strain sets in when the thickness of the film exceeds approximately 10 – 15 nm. Films with excess Na are mainly composed of NaNbO3 with minor contribution of Na3NbO4. The latter phase seems to form nanoprecipitates that are homogeneously distributed in the NaNbO3 film which helps to stabilize the film and reduce the relaxation of the strain. -For the nominally stoichiometric films, the compressive strain leads to a broad and frequency-dispersive phase transition at lower temperature (125 – 147 K). This could be either a new transition or a shift in temperature of a known transition. Considering the broadness and frequency dispersion of the transition, this is actually a transition from the dielectric state at high temperature to a relaxor-type ferroelectric state at low temperature. The latter is based on the formation of polar nano-regions (PNRs). Using the electric field dependence of the freezing temperature, allows a direct estimation of the volume (70 to 270 nm3) and diameter (5.2 to 8 nm, spherical approximation) of the PNRs. The values confirm with literature values which were measured by other technologies. -In case of the off-stoichiometric samples, we observe again the classical ferroelectric behavior. However, the thermally hysteretic phase transition which is observed around 620 – 660 K for unstrained material is shifted to room temperature due to the compressive strain. Beside to the temperature shift, the temperature dependence of the permittivity is nearly identical for strained and unstrained materials. -The last but not least, in all cases, a significant anisotropy in the electronic and structural properties is observed which arises automatically from the anisotropic strain caused by the orthorhombic structure of the substrate. However, this anisotropy cannot be explained by the classical model which tries to fit an orthorhombic film onto an orthorhombic substrate. A novel “square lattice” model in which the films adapt a “square” shaped lattice in the plane of the film during the epitaxial growth at elevated temperature (~1000 K) nicely explains the experimental results. In this thesis we sketch a way to manipulate the ferroelectricity of NaNbO3 films via strain and stoichiometry. The results indicate that compressive strain which is generated by the epitaxial growth of the film on mismatched substrate is able to reduce the ferroelectric transition temperature or induce a phase transition at low temperature. Moreover, by adding Na in the NaNbO3 film a secondary phase Na3NbO4 is formed which seems to stabilize the main phase NaNbO3 and the strain and, thus, is able to engineer the ferroelectric behavior from the expected classical ferroelectric for perfect stoichiometry to relaxor-type ferroelectric for slightly off-stoichiometry, back to classical ferroelectric for larger off-stoichiometry. Both strain and stoichiometry are proven as perfect methods to optimize the ferroelectric properties of oxide films.

Hilbert Space Valued Signal Plus Noise Models: Analysis of Structural Breaks under High Dimensionality and Temporal Dependence

This thesis is concerned with change point analysis for time series, i.e. with detection of structural breaks in time-ordered, random data. This long-standing research field regained popularity over the last few years and is still undergoing, as statistical analysis in general, a transformation to high-dimensional problems. We focus on the fundamental »change in the mean« problem and provide extensions of the classical non-parametric Darling-Erdős-type cumulative sum (CUSUM) testing and estimation theory within highdimensional Hilbert space settings. In the first part we contribute to (long run) principal component based testing methods for Hilbert space valued time series under a rather broad (abrupt, epidemic, gradual, multiple) change setting and under dependence. For the dependence structure we consider either traditional m-dependence assumptions or more recently developed m-approximability conditions which cover, e.g., MA, AR and ARCH models. We derive Gumbel and Brownian bridge type approximations of the distribution of the test statistic under the null hypothesis of no change and consistency conditions under the alternative. A new formulation of the test statistic using projections on subspaces allows us to simplify the standard proof techniques and to weaken common assumptions on the covariance structure. Furthermore, we propose to adjust the principal components by an implicit estimation of a (possible) change direction. This approach adds flexibility to projection based methods, weakens typical technical conditions and provides better consistency properties under the alternative. In the second part we contribute to estimation methods for common changes in the means of panels of Hilbert space valued time series. We analyze weighted CUSUM estimates within a recently proposed »high-dimensional low sample size (HDLSS)« framework, where the sample size is fixed but the number of panels increases. We derive sharp conditions on »pointwise asymptotic accuracy« or »uniform asymptotic accuracy« of those estimates in terms of the weighting function. Particularly, we prove that a covariance-based correction of Darling-Erdős-type CUSUM estimates is required to guarantee uniform asymptotic accuracy under moderate dependence conditions within panels and that these conditions are fulfilled, e.g., by any MA(1) time series. As a counterexample we show that for AR(1) time series, close to the non-stationary case, the dependence is too strong and uniform asymptotic accuracy cannot be ensured. Finally, we conduct simulations to demonstrate that our results are practically applicable and that our methodological suggestions are advantageous.

Structural health monitoring of storage tanks

In this thesis, Ph.D candidate presents a compact sensor node (SN) designed for long-term and real-time acoustic emission (AE) monitoring of above ground storage tanks (ASTs). Each SN exploits up to three inexpensive low-frequency sensors based on piezoelectric diaphragms for effective leakage detection, and it is capable by means of built-in Digital Signal Processing functionalities to process the acquired time waveforms extracting the AE features usually required by testing protocols. Alternatively, capability to plug three high frequency AE sensors to a SN for corrosion simulated phenomena detection is envisaged and demonstrated. Another innovative aspect that the Ph.D candidate presents in this work is an alternative mathematical model of corrosion location on the bottom of the AST. This approach implies considering the three-dimensional localization model versus the two-dimensional commonly used according to the literature. This approach is aimed at significant optimization in the number of sensors in relation to the standard approach for solving localization problems as well as to allow filtering the false AE events related to the condensate droplets from AST ceiling. The technological implementation of this concept required the solution of a number of technical problems, such as the precise time of arrival (ToA) signal estimation, vertical localization of the AE source and multilaration solution that were discussed in detail in this work. To validate the developed prototype, several experimental campaigns were organized that included the simulation of target phenomena both in laboratory conditions and on a real water storage tank. The presented test results demonstrate the successful application of the developed AE system both for simulated leaks and for corrosion processes on the tank bottom. Mathematical and technological algorithms for localization and characterization of AE signals implemented during the development of the prototype are also confirmed by the test results.