Crack identification of functionally graded beams using continuous wavelet transform

© 2018 Elsevier Ltd This paper proposes a new damage index for the crack identification of beams made of functionally graded materials (FGMs) by using the wavelet analysis. The damage index is defined based on the position of the wavelet coefficient modulus maxima in the scale space. The crack is assumed to be an open edge crack and is modeled by a massless rotational spring. It is assumed that the material properties follow exponential distributions along the beam thickness direction. The Timoshenko beam theory is employed to derive the governing equations which are solved analytically to obtain the frequency and mode shape of cracked FGM beams. Then, we apply the continuous wavelet transform (CWT) to the mode shapes of the cracked FGM beams. The locations of the cracks are determined from the sudden changes in the spatial variation of the damage index. An intensity factor, which relates to the size of the crack and the coefficient of the wavelet transform, is employed to estimate the crack depth. The effects of the crack size, the crack location and the Young's modulus ratio on the crack depth detection are investigated

Enhancement of the Feature Extraction Capability in Global Damage Detection Using Wavelet Theory

The main objective of this study is to assess the specific capabilities of the defect energy parameter technique for global damage detection developed by Saleeb and coworkers. The feature extraction is the most important capability in any damage-detection technique. Features are any parameters extracted from the processed measurement data in order to enhance damage detection. The damage feature extraction capability was studied extensively by analyzing various simulation results. The practical significance in structural health monitoring is that the detection at early stages of small-size defects is always desirable. The amount of changes in the structure's response due to these small defects was determined to show the needed level of accuracy in the experimental methods. The arrangement of fine/extensive sensor network to measure required data for the detection is an "unlimited" ability, but there is a difficulty to place extensive number of sensors on a structure. Therefore, an investigation was conducted using the measurements of coarse sensor network. The white and the pink noises, which cover most of the frequency ranges that are typically encountered in the many measuring devices used (e.g., accelerometers, strain gauges, etc.) are added to the displacements to investigate the effect of noisy measurements in the detection technique. The noisy displacements and the noisy damage parameter values are used to study the signal feature reconstruction using wavelets. The enhancement of the feature extraction capability was successfully achieved by the wavelet theory

Fabrication and nanoroughness characterization of specific nanostructures and nanodevice

Nanoroughness is becoming a very important specification for many nanostructures and nanodevices, and its metrology impacts not only the nanodevice properties of interest, but also its material selection and process development. This Ph.D. thesis presents an investigation into fabrication and nanoroughness characterization of nanoscale specimens and MIS (metal-insulator-semiconductor) capacitors with 2 HfO as a high k dielectric. Self-affine curves and Gaussian, non-Gaussian, self-affine as well as complicated rough surfaces were characterized and simulated. The effects of characteristic parameters on the CD (critical dimension) variation and the properties of these rough surfaces were visualized. Compared with experimental investigations, these simulations are flexible, low cost and highly efficient. Relevant conclusions were frequently employed in subsequent investigations. A proposal regarding the thicknesses of the deposited films represented by nominal linewidths and pitch was put forward. The MBE (Molecular Beam Epitaxy) process was introduced and AlGaAs and GaAs were selected to fabricate nanolinewidth and nanopitch specimens on GaAs substrate with nominal linewidths of 2nm, 4nm, 6nm and 8nm, and a nominal pitch of 5nm. HRTEM (High Resolution Transmission Electron Microscopy) image-based characterization of LER/LWR (Line Edge Roughness/Line Width Roughness) in real space and frequency domains demonstrated that the MBE-based process was capable of fabricating the desired nanolinewidth and nanopitch specimens and could be regulated accordingly. MIS capacitors with 2 HfO film as high k dielectric were fabricated, and SEM (Scanning Electron Microscope) image-based nanoroughness characterization, along with measurement of the MIS capacitor electrical properties were performed. It was concluded that the annealing temperature of the deposited 2 HfO film was an important process parameter and 700℃ was an optimal temperature to improve the properties of the MIS capacitor. Also, by quantitative characterization of the relevant nanoroughness, the fabrication process can be further regulated. The uncertainty propagation model of SEM based nanoroughness measurement was presented according to specific requirements of the relevant standards, ISO GPS (Geometric Product Specifications and Verification) and GUM (Guide to the Expression of Uncertainty in Measurement), and the method for implementating uncertainties was evaluated. The case study demonstrated that the total standard uncertainty of the nanoroughness measurement was 0.13nm, while its expanded uncertainty with the coverage factor k as 3 was 0.39nm. They are indispensable parts of LER/LWR measurement results

CHARACTERIZATION OF ARBUCKLE-BASEMENT SYSTEM WITH A FOCUS ON SEISMIC ATTRIBUTES IMAGE OF IGNEOUS INTRUSIONS AND SEISMIC RESOLUTION, PAYNE COUNTY, NORTHERN OKLAHOMA

During the past eight years, north-central Oklahoma has experienced a significant increase in seismicity. Although the disposal of large volumes of wastewater into the Arbuckle Group-basement system has been statistically correlated to this increased seismicity, our understanding of the actual mechanisms involved is somewhat superficial. To address this shortcoming, I served as the geophysicist in an integrated study to characterize and model the Arbuckle-basement system to increase our understanding of the subsurface dynamics during the wastewater-disposal process. I constructed a 3D geological model that integrates 3D seismic data, well logs, core measurements and injection data. Poststack-data conditioning and seismic attributes provided images of faults and the rugose top of the basement, while a modified-Hall analysis provided insights into the injection behavior of the wells. Using a Pareto-based history-matching technique, I calibrated the 3D models using injection rate and pressure data. The history-matching process showed the dominant parameters to be formation-water properties, permeability, porosity, and horizontal anisotropy of the Arbuckle Group. Based on the pressure buildup responses from the calibrated models, I identified sealing and conductive characteristics of the key faults. My analysis shows the average porosity and permeability of Arbuckle Group to be approximately 7% and 10 mD, respectively over the study area. The simulation models also showed pockets of non-uniform and large pressure buildups in these formations indicating that faults play an important role in fluid movement within the Arbuckle Group-basement system. To further improve our understanding of the basement in Oklahoma, its plumbing system and tectono-thermal history, I depth-migrate a 3D pre-stack seismic volume in north central Oklahoma where recent studies have highlighted the presence of basement igneous sills (BIS), expressed as intra-basement seismic reflectors (IBR), possibly associated with the Mid-Continent Rift. The depth-migrated data allows me to better delineate the geophysical characteristics of the BIS, and I integrate it with outcrop observations and well log data to constrain our geological interpretations. Further, I create geologically-realistic 2D seismic forward models of the sills to assess if their synthetic seismic attribute response can be utilized for improving current interpretation workflows for igneous intrusions in other regions. I find that (1) depth-migration of the seismic volume provides better imaging of the geometry of the BIS, (2) 2D forward models show that distinct geometries for fault-controlled basement sill steps can be distinguished in seismic reflection data and (3) salient geometric features of the BIS observed in outcrops are consistent to those in the depth-migrated seismic data. To better delineate such basement intrusions, I evaluate current limits and assumptions of seismic resolution. Beginning in 1973 with Widess’ analysis of reflector wedge models, the conventionally understood limit of vertical seismic resolution has been λ/4 for noise contaminated data. However, this model and resolution limits do not represent the full range of models that might be present in nature. In this dissertation, I examine three algorithms designed to increase the limit or at least quantify vertical seismic resolution: spectral balancing, bandwidth extension and the Hölder exponent. I find that spectral balancing provides a useful, but limited improvement of seismic resolution. I find that although bandwidth extension attempts to resolve beds below tuning frequencies by extending the magnitude spectrum, the corresponding phase spectrum interference patterns are not properly unraveled. Events that were previously resolved appear sharper, while those that were not are now corrupted. The goal of the Hölder exponent is to use the shape of the magnitude spectrum to characterize the underlying reflectivity as being blocky, spikey, or smooth. My work shows that the resolution of thin beds below tuning remains an important problem in the geophysics community that is often poorly understood and for which permanent solutions are still to be found

Characterising evoked potential signals using wavelet transform singularity detection

This research set out to develop a novel technique to decompose Electroencephalograph (EEG) signal into sets of constituent peaks in order to better describe the underlying nature of these signals. It began with the question; can a localised, single stimulation of sensory nervous tissue in the body be detected in the brain? Flash Visual Evoked Potential (VEP) tests were carried out on 3 participants by presenting a flash and recording the response in the occipital region of the cortex. By focussing on analysis techniques that retain a perspective across different domains - temporal (time), spectral (frequency/scale) and epoch (multiple events) - useful information was detected across multiple domains, which is not possible in single domain transform techniques. A comprehensive set of algorithms to decompose evoked potential data into sets of peaks was developed and test ed using wavelet transform singularity detection methods. The set of extracted peaks then forms the basis for a subsequent clustering analysis which identifies sets of localised peaks that contribute the most towards the standard evoked response. The technique is quite novel as no closely similar work in research has been identified. New and valuable insights into the nature of an evoked potential signal have been identified. Although the number of stimuli required to calculate an Evoked Potential response has not been reduced, the amount of data contributing to this response has been effectively reduced by 75%. Therefore better examination of a small subset of the evoked potential data is possible. Furthermore, the response has been meaningfully decomposed into a small number (circa 20) of constituent peaksets that are defined in terms of the peak shape (time location, peak width and peak height) and number of peaks within the peak set. The question of why some evoked potential components appear mor e strongly than others is probed by this technique. Delineation between individual peak sizes and how often they occur is for the first time possible and this representation helps to provide an understanding of how particular evoked potentials components are made up. A major advantage of this techniques is the there are no pre-conditions, constraints or limitations. These techniques are highly relevant to all evoked potential modalities and other brain signal response applications - such as in brain-computer interface applications. Overall, a novel evoked potential technique has been described and tested. The results provide new insights into the nature of evoked potential peaks with potential application across various evoked potential modalities

Smart FRP Composite Sandwich Bridge Decks in Cold Regions

INE/AUTC 12.0