NUMERICAL AND ANALYTICAL VERIFICATION OF A MULTISCALE COMPUTATIONAL MODEL FOR IMPACT PROBLEMS IN HETEROGENEOUS VISCOELASTIC MATERIALS WITH EVOLVING DAMAGE

Composites are engineered materials that take advantage of the particular properties of each of its two or more constituents. They are designed to be stronger, lighter and to last longer which can lead to the creation of safer protection gear, more fuel efficient transportation methods and more affordable materials, among other examples. This thesis proposes a numerical and analytical verification of an in-house developed multiscale model for predicting the mechanical behavior of composite materials with various configurations subjected to impact loading. This verification is done by comparing the results obtained with analytical and numerical solutions with the results found when using the model. The model takes into account the heterogeneity of the materials that can only be noticed at smaller length scales, based on the fundamental structural properties of each of the composite’s constituents. This model can potentially reduce or eliminate the need of costly and time consuming experiments that are necessary for material characterization since it relies strictly upon the fundamental structural properties of each of the composite’s constituents. The results from simulations using the multiscale model were compared against results from direct simulations using over-killed meshes, which considered all heterogeneities explicitly in the global scale, indicating that the model is an accurate and fast tool to model composites under impact loads. Advisor: David H. Allen

The non-ideal problem behavior using a dynamic vibration absorber with nonlinear essential stiffness and timedependent damping properties

The purpose of this study is to develop a dynamic vibration absorber using viscoelastic material with nonlinear essential stiffness and time-dependent damping properties for a non-ideal vibrating system with Sommerfeld effect, resonance capture, and jump phenomenon. The absorber is a mass-bar subsystem that consists of a viscoelastic bar with memory attached to mass, in which the internal dissipative forces depend on current, deformations, and its operational frequency varies with limited temperature. The non-ideal vibrating system consists of a linear (nonlinear) oscillator (plane frame structure) under excitation, via spring connector, of a DC-motor with limited power supply. A viscoelastic dynamic absorber modeled with elastic stiffness essentially nonlinearities was developed to further reduce the Sommerfeld effect and the response of the structure. The numerical results show the performance of the absorber on the non-ideal system response through the resonance curves, time histories, and Poincarésections. Furthermore, the structure responses using the viscoelastic damper with and without memory were studied. © IMechE 2012.

Micromechanics analysis on evolution of crack in viscoelastic materials

A preliminary analysis on crack evolution in viscoelastic materials was presented. Based on the equivalent inclusion concept of micro-mechanics theory, the explicit expressions of crack opening displacement delta and energy release rate G were derived, indicating that both delta and G are increasing with time. The equivalent modulus of the viscoelastic solid comprising cracks was evaluated. It is proved that the decrease of the modulus comes from two mechanisms: one is the viscoelasticity of the material; the other is the crack opening which is getting larger with time.

Analytical techniques for indentation of viscoelastic materials

Indentation of linearly viscoelastic materials is explored using elastic-viscoelastic correspondence analysis for both conical-pyramidal and spherical indentation. Boltzmann hereditary integrals are used to generate displacement-time solutions for loading at constant rate and creep following ramp loading. Experimental data for triangle- and trapezoidal-loading are examined for commercially-available polymers and compared with analytical solutions. Emphasis is given to the use of multiple experiments to test the fidelity and predictive capability of the obtained material creep function. Plastic deformation occurs in sharp indentation of glassy polymers and is found to complicate the viscoelastic analysis. A new method is proposed for estimating a material time-constant from peak displacement or hardness data obtained in pyramidal indentation tests performed at different loading rates.

On the Equivalence of the Riemann-Liouville and the Caputo Fractional Order Derivatives in Modeling of Linear Viscoelastic Materials

Mathematics Subject Classification: 26A33

Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

Development and evaluation of hydrocarbon sorbent materials with the aid of chemometrics

Hydrocarbon spills on roads are a major safety concern for the driving public and can have severe cost impacts both on pavement maintenance and to the economy through disruption to services. The time taken to clean-up spills and re-open roads in a safe driving condition is an issue of increasing concern given traffic levels on major urban arterials. Thus, the primary aim of the research was to develop a sorbent material that facilitates rapid clean-up of road spills. The methodology involved extensive research into a range of materials (organic, inorganic and synthetic sorbents), comprehensive testing in the laboratory, scale-up and field, and product design (i.e. concept to prototype). The study also applied chemometrics to provide consistent, comparative methods of sorbent evaluation and performance. In addition, sorbent materials at every stage were compared against a commercial benchmark. For the first time, the impact of diesel on asphalt pavement has been quantified and assessed in a systematic way. Contrary to conventional thinking and anecdotal observations, the study determined that the action of diesel on asphalt was quite rapid (i.e. hours rather than weeks or months). This significant finding demonstrates the need to minimise the impact of hydrocarbon spills and the potential application of the sorbent option. To better understand the adsorption phenomenon, surface characterisation techniques were applied to selected sorbent materials (i.e. sand, organo-clay and cotton fibre). Brunauer Emmett Teller (BET) and thermal analysis indicated that the main adsorption mechanism for the sorbents occurred on the external surface of the material in the diffusion region (sand and organo-clay) and/or capillaries (cotton fibre). Using environmental scanning electron microscopy (ESEM), it was observed that adsorption by the interfibre capillaries contributed to the high uptake of hydrocarbons by the cotton fibre. Understanding the adsorption mechanism for these sorbents provided some guidance and scientific basis for the selection of materials. The study determined that non-woven cotton mats were ideal sorbent materials for clean-up of hydrocarbon spills. The prototype sorbent was found to perform significantly better than the commercial benchmark, displaying the following key properties: • superior hydrocarbon pick-up from the road pavement; • high hydrocarbon retention capacity under an applied load; • adequate field skid resistance post treatment; • functional and easy to use in the field (e.g. routine handling, transportation, application and recovery); • relatively inexpensive to produce due to the use of raw cotton fibre and simple production process; • environmentally friendly (e.g. renewable materials, non-toxic to environment and operators, and biodegradable); and • rapid response time (e.g. two minutes total clean-up time compared with thirty minutes for reference sorbents). The major outcomes of the research project include: a) development of a specifically designed sorbent material suitable for cleaning up hydrocarbon spills on roads; b) submission of patent application (serial number AU2005905850) for the prototype product; and c) preparation of Commercialisation Strategy to advance the sorbent product to the next phase (i.e. R&D to product commercialisation).

Fabrication of macro-mesoporous zirconia-alumina materials with a 1D hierarchical structure

A series of one dimensional (1D) zirconia/alumina nanocomposites were prepared by the deposition of zirconium species onto the 3D framework of boehmite nanofibres formed by dispersing boehmite nanofibres into butanol solution. The materials were calcined at 773K and characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscope (TEM), N2 adsorption/desorption, infrared emission spectroscopy (IES). The results demonstrated that when the molar percentage X=100*Zr/(Al+Zr) was > 30 %, extremely long ZrO2/Al2O3 composite nanorods with evenly distributed ZrO2 nanocrystals on the surface were formed. The stacking of such nanorods gave rise to a new kind of macroporous material without the use of any organic space filler\template or other specific technologies. The mechanism for the formation of long ZrO2/Al2O3 composite nanorods was proposed in this work.

Studies of the phase evolution of YBCO materials with different additives

Y123 samples with varying amounts of added Y211, PtO 2 and CeO 2 have been melt processed and quenched from temperatures between 960°C and 1100°C. The microstructures of the quenched samples have been characterized using a combination of x-ray diffractometry, optical microscopy, scanning electron microscopy, microprobe analysis, energy-dispersive x-ray spectroscopy and wavelength-dispersive x-ray spectroscopy. The Ba-Cu-O-rich melt undergoes complex changes as a function of temperature and time. A region of stability of BaCuO 2 (BC1) and BaCu 2O 2 (BC2) exists below 1040°C in samples of Y123 + 20 mol% Y211. Ba 2Cu 3O 5 is stabilized by rapid quenching but appears to separate into BC1 and BC2 at lower quenching rates. PtO 2 and CeO 2 additions affect the distribution and volume fractions of the two Ba-Cu-oxide phases.

Thermoelectric Properties of Co4Sb12 Skutterudite Materials with Partial In Filling and Excess In Additions

The properties of Co4Sb12 with various In additions were studied. X-ray diffraction revealed the presence of the pure δ-phase of In0.16Co4Sb12, whereas impurity phases (γ-CoSb2 and InSb) appeared for x = 0.25, 0.40, 0.80, and 1.20. The homogeneity and morphology of the samples were observed by Seebeck microprobe and scanning electron microscopy, respectively. All the quenched ingots from which the studied samples were cut were inhomogeneous in the axial direction. The temperature dependence of the Seebeck coefficient (S), electrical conductivity (σ), and thermal conductivity (κ) was measured from room temperature up to 673 K. The Seebeck coefficient of all In-added Co4Sb12 materials was negative. When the filler concentration increases, the Seebeck coefficient decreases. The samples with In additions above the filling limit (x = 0.22) show an even lower Seebeck coefficient due to the formation of secondary phases: InSb and CoSb2. The temperature variation of the electrical conductivity is semiconductor-like. The thermal conductivity of all the samples decreases with temperature. The central region of the In0.4Co4Sb12 ingot shows the lowest thermal conductivity, probably due to the combined effect of (a) rattling due to maximum filling and (b) the presence of a small amount of fine-dispersed secondary phases at the grain boundaries. Thus, regardless of the non-single-phase morphology, a promising ZT (S 2 σT/κ) value of 0.96 at 673 K has been obtained with an In addition above the filling limit.

Polymorphism in Opto-Electronic Materials with a Benzothiazole-fluorene Core: A Consequence of High Conformational Flexibility of pi-Conjugated Backbone and Alkyl Side Chains

Fluorene and its derivatives are well-known organic semiconducting materials in the field of opto-electronic devices because of their charge transport properties. Three new organic semiconducting materials, namely, 2,2'-((9,9-butyl-9H-fluorene-2,7-diyl)bis(4,1 phenylene))bisbenzod]thiazole, C4; 2,2'-((octyl-9H-fluorene-2,7-diyl)bis(4,1 phenylene))bisbenzod]thiazole, C8; and 2,2'-((9,9-dodecayl-9H-fluorene-2,7-diyl)bis(4,1 phenylene))bisbenzod]thiazole, C12 with a benzothiazole-fluorene backbone, were synthesized and characterized for their photophysical properties. A phenomenon of concomitant polymorphism has been investigated in the first two derivatives (C4 and C8) and has been analyzed systematically in terms of the packing characteristics involving pi ... pi interactions. The conformational flexibility of the pi-conjugated 2,2'-(fluorene-2,7-diyl)bis(4,1 phenylene)bisbenzod]thiazole backbone coupled with orientational freedom of the terminal alkyl chains were found to be the key factors responsible for these polymorphic modifications. Attempts to grow suitable crystals for single crystal X-ray diffraction of compound C12 were unsuccessful.