A meshfree model for plant tissue deformations during drying

Plant tissue has a complex cellular structure which is an aggregate of individual cells bonded by middle lamella. During drying processes, plant tissue undergoes extreme deformations which are mainly driven by moisture removal and turgor loss. Numerical modelling of this problem becomes challenging when conventional grid-based modelling techniques such as Finite Element Methods (FEM) and Finite Difference Methods (FDM) have grid-based limitations. This work presents a meshfree approach to model and simulate the deformations of plant tissues during drying. This method demonstrates the fundamental capabilities of meshfree methods in handling extreme deformations of multiphase systems. A simplified 2D tissue model is developed by aggregating individual cells while accounting for the stiffness of the middle lamella. Each individual cell is simply treated as consisting of two main components: cell fluid and cell wall. The cell fluid is modelled using Smoothed Particle Hydrodynamics (SPH) and the cell wall is modelled using a Discrete Element Method (DEM). During drying, moisture removal is accounted for by reduction of cell fluid and wall mass, which causes local shrinkage of cells eventually leading to tissue scale shrinkage. The cellular deformations are quantified using several cellular geometrical parameters and a favourably good agreement is observed when compared to experiments on apple tissue. The model is also capable of visually replicating dry tissue structures. The proposed model can be used as a step in developing complex tissue models to simulate extreme deformations during drying.

The loss of carbon dioxide from activated perbenzoate anions in the gas phase : Unimolecular rearrangement via epoxidation of the benzene ring

The unimolecular reactivities of a range of perbenzoate anions (X-C6H5CO3-), including the perbenzoate anion itself (X=H), nitroperbenzoates (X=para-, meta-, ortho-NO2), and methoxyperbenzoates (X=para-, meta-OCH3) were investigated in the gas phase by electrospray ionization tandem mass spectrometry. The collision-induced dissociation mass spectra of these compounds reveal product ions consistent with a major loss of carbon dioxide requiring unimolecular rearrangement of the perbenzoate anion prior to fragmentation. Isotopic labeling of the perbenzoate anion supports rearrangement via an initial nucleophilic aromatic substitution at the ortho carbon of the benzene ring, while data from substituted perbenzoates indicate that nucleophilic attack at the ipso carbon can be induced in the presence of electron-withdrawing moieties at the ortho and para positions. Electronic structure calculations carried out at the B3LYP/6311++G(d,p) level of theory reveal two competing reaction pathways for decarboxylation of perbenzoate anions via initial nucleophilic substitution at the ortho and ipso positions, respectively. Somewhat surprisingly, however, the computational data indicate that the reaction proceeds in both instances via epoxidation of the benzene ring with decarboxylation resulting-at least initially-in the formation of oxepin or benzene oxide anions rather than the energetically favored phenoxide anion. As such, this novel rearrangement of perbenzoate anions provides an intriguing new pathway for epoxidation of the usually inert benzene ring.

Pressure state response-based method for evaluating social benefits from smart grid development

In this paper, the inherent mechanism of social benefits associated with smart grid development is examined based on the pressure state response (PSR) model from resource economics. The emerging types of technology brought up by smart grid development are regarded as pressures. The improvements of the performance and efficiency of power system operation, such as the enhanced capability of accommodating renewable energy generation, are regarded as states. The effects of smart grid development on society are regarded as responses. Then, a novel method for evaluating social benefits from smart grid development is presented. Finally, the social benefits from smart grid development in a province in northwest China are carried out by using the developed evaluation system, and reasonable evaluation results are attained.

The construction of social identity in newly recruited nuclear engineering staff : a longitudinal study

This study examines the process by which newly recruited nuclear engineering and technical staff came to understand, define, think, feel and behave within a distinct group that has a direct contribution to the organization's overall emphasis on a culture of reliability and system safety. In the field of organizational behavior the interactive model of social identity formation has been recently proposed to explain the process by which the internalization of shared norms and values occurs, an element critical in identity formation. Using this rich model of organizational behavior we analyzed multiple sources of data from nine new hires over a period of three years. This was done from the time they were employed to investigate the construction of social identity by new entrants entering into a complex organizational setting reflected in the context of a nuclear facility. Informed by our data analyses, we found support for the interactive model of social identity development and report the unexpected finding that a newly appointed member's age and level of experience appears to influence the manner in which they adapt, and assimilate into their surroundings. This study represents an important contribution to the safety and reliability literature as it provides a rich insight into the way newly recruited employees enact the process by which their identities are formed and hence act, particularly under conditions of duress or significant organizational disruption in complex organizational settings.

A sensor fault detection and isolation method in interior permanent-magnet synchronous motor drives based on an extended Kalman filter

Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.

Synthesis and characterization of titanium sol–gels in varied gravity

Two unique test systems were designed and built to allow the effects of varied gravity (high, normal, reduced) during synthesis of titanium sol–gels to be studied. A centrifuge capable of providing high gravity environments of up to 70 g for extended periods while applying a 100 mbar vacuum and a temperature of 40–50 °C to the reaction chambers was developed. The second system was used in the QUT Microgravity Drop Tower Facility also provided the same thermal and vacuum conditions used in the centrifuge, but was required to operate autonomously during free fall. Through the use of post synthesis instrumental characterization, it was found that increased gravity levels during synthesis, had the greatest effect on the final products. Samples produced in reduced and normal gravity appeared to form amorphous gels containing very small particles with moderate surface areas. Whereas crystalline anatase (TiO2), was found to form in samples synthesized above 5 g with significant increases in crystallinity, particle size and surface area observed when samples were produced at gravity levels up to 70 g. It is proposed that for samples produced in higher gravity, an increased concentration gradient of water is forms at the bottom of the reacting film due to forced convection. The particles formed in higher gravity diffuse downward toward this excess of water, which favors the condensation reaction of remaining sol–gel precursors with the particles promoting increased particle growth. Due to the removal of downward convection in reduced gravity, particle growth due to condensation reaction processes are physically hindered hydrolysis reactions favored instead. Another significant finding from this work was that anatase could be produced at relatively low temperatures of 40–50 °C instead of the conventional method of calcination above 450 °C solely through sol–gel synthesis at higher gravity levels.

Risk mitigation of post-earthquake fire in urban buildings

Post-earthquake fire (PEF) is considered one of the most high risk and complicated problems affecting buildings in urban areas and can cause even more damage than the earthquake itself. However, most standards and codes ignore the implications of PEF and so buildings are not normally designed with PEF in mind. What is needed is for PEF factors to be routinely scrutinized and codified as part of the design process. A systematic application is presented as a means of mitigating the risk of PEF in urban buildings. This covers both existing buildings, in terms of retrofit solutions, and those yet to be designed, where a PEF factor is proposed. To ensure the mitigation strategy meets the defined criteria, a minimum time is defined – the safety guaranteed time target – where the safety of the inhabitants in a building is guaranteed.

Non-linear principal components analysis : an alternative method for finding patterns in environmental data

The main purpose of this article is to gain an insight into the relationships between variables describing the environmental conditions of the Far Northern section of the Great Barrier Reef, Australia. Several of the variables describing these conditions had different measurement levels and often they had non-linear relationships. Using non-linear principal component analysis, it was possible to acquire an insight into these relationships. Furthermore, three geographical areas with unique environmental characteristics could be identified.

Computation of ECG signal features using MCMC modelling in software and FPGA reconfigurable hardware

Computational optimisation of clinically important electrocardiogram signal features, within a single heart beat, using a Markov-chain Monte Carlo (MCMC) method is undertaken. A detailed, efficient data-driven software implementation of an MCMC algorithm has been shown. Initially software parallelisation is explored and has been shown that despite the large amount of model parameter inter-dependency that parallelisation is possible. Also, an initial reconfigurable hardware approach is explored for future applicability to real-time computation on a portable ECG device, under continuous extended use.

Thermal stability and decomposition kinetics of styrene-butadiene rubber nanocomposites filled with different particle sized kaolinites

A series of styrene-butadiene rubber (SBR) nanocomposites filledwith different particle sized kaolinites are prepared via a latex blending method. The thermal stabilities of these clay polymer nanocomposites (CPN) are characterized by a range of techniques including thermogravimetry (TG), digital photos, scanning electron microscopy (SEM) and Raman spectroscopy. These CPN show some remarkable improvement in thermal stability compared to that of the pure SBR. With the increase of kaolinite particle size, the residual char content and the average activation energy of kaolinite SBR nanocomposites all decrease; the pyrolysis residues become porous; the crystal carbon in the pyrolysis residues decrease significantly from 58.23% to 44.41%. The above results prove that the increase of kaolinite particle size is not beneficial in improving the thermal stability of kaolinite SBR nanocomposites.

A novel identification method for ultra trace detection of biomolecules using functionalised Surface Enhanced Raman Spectroscopy (SERS)

This thesis developed a new method for measuring extremely low amounts of organic and biological molecules, using Surface enhanced Raman Spectroscopy. This method has many potential applications, e.g. medical diagnosis, public health, food provenance, antidoping, forensics and homeland security. The method development used caffeine as the small molecule example, and erythropoietin (EPO) as the large molecule. This method is much more sensitive and specific than currently used methods; rapid, simple and cost effective. The method can be used to detect target molecules in beverages and biological fluids without the usual preparation steps.

A finite volume scheme with preconditioned Lanczos method for two-dimensional space-fractional reaction–diffusion equations

Fractional differential equations have been increasingly used as a powerful tool to model the non-locality and spatial heterogeneity inherent in many real-world problems. However, a constant challenge faced by researchers in this area is the high computational expense of obtaining numerical solutions of these fractional models, owing to the non-local nature of fractional derivatives. In this paper, we introduce a finite volume scheme with preconditioned Lanczos method as an attractive and high-efficiency approach for solving two-dimensional space-fractional reaction–diffusion equations. The computational heart of this approach is the efficient computation of a matrix-function-vector product f(A)bf(A)b, where A A is the matrix representation of the Laplacian obtained from the finite volume method and is non-symmetric. A key aspect of our proposed approach is that the popular Lanczos method for symmetric matrices is applied to this non-symmetric problem, after a suitable transformation. Furthermore, the convergence of the Lanczos method is greatly improved by incorporating a preconditioner. Our approach is show-cased by solving the fractional Fisher equation including a validation of the solution and an analysis of the behaviour of the model.

Modelling airport passenger group dynamics using an agent-based method

This thesis investigates the influence of passenger group dynamics on passengers' behaviour in an international airport. A simulation model is built to analyse passengers' behaviour during airport departure processes and during an emergency event. Results from the model showed that passengers' group dynamics have significant influences on the performance and utilisation of airport services. The agent-based model also provides a convenient way to investigate the effectiveness of space design and service allocations, which may contribute to the enhancement of passenger airport experiences.

Moving from outsider to insider : peer status and partnerships between electricity utilities and residential consumers

An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008. By 2011, both the peak demand and grid supplied electricity consumption had decreased to below pre-intervention levels. This case study research explored the relationship developed between the utility, community and individual consumer from the residential customer perspective through qualitative research of 22 residential households. It is proposed that an energy utility can be highly successful at peak demand reduction by becoming a community member and a peer to residential consumers and developing the necessary trust, access, influence and partnership required to create the responsive environment to change. A peer-community approach could provide policymakers with a pathway for implementing pro-environmental behaviour for low carbon communities, as well as peak demand reduction, thereby addressing government emission targets while limiting the cost of living increases from infrastructure expenditure.

Two dynamic discrete choice estimation problems and simulation method solutions

This paper considers two problems that frequently arise in dynamic discrete choice problems but have not received much attention with regard to simulation methods. The first problem is how to simulate unbiased simulators of probabilities conditional on past history. The second is simulating a discrete transition probability model when the underlying dependent variable is really continuous. Both methods work well relative to reasonable alternatives in the application discussed. However, in both cases, for this application, simpler methods also provide reasonably good results.