Application of meshfree methods to numerically simulate microscale deformations of different plant food materials during drying

Plant food materials have a very high demand in the consumer market and therefore, improved food products and efficient processing techniques are concurrently being researched in food engineering. In this context, numerical modelling and simulation techniques have a very high potential to reveal fundamentals of the underlying mechanisms involved. However, numerical modelling of plant food materials during drying becomes quite challenging, mainly due to the complexity of the multiphase microstructure of the material, which undergoes excessive deformations during drying. In this regard, conventional grid-based modelling techniques have limited applicability due to their inflexible grid-based fundamental limitations. As a result, meshfree methods have recently been developed which offer a more adaptable approach to problem domains of this nature, due to their fundamental grid-free advantages. In this work, a recently developed meshfree based two-dimensional plant tissue model is used for a comparative study of microscale morphological changes of several food materials during drying. The model involves Smoothed Particle Hydrodynamics (SPH) and Discrete Element Method (DEM) to represent fluid and solid phases of the cellular structure. Simulation are conducted on apple, potato, carrot and grape tissues and the results are qualitatively and quantitatively compared and related with experimental findings obtained from the literature. The study revealed that cellular deformations are highly sensitive to cell dimensions, cell wall physical and mechanical properties, middle lamella properties and turgor pressure. In particular, the meshfree model is well capable of simulating critically dried tissues at lower moisture content and turgor pressure, which lead to cell wall wrinkling. The findings further highlighted the potential applicability of the meshfree approach to model large deformations of the plant tissue microstructure during drying, providing a distinct advantage over the state of the art grid-based approaches.

Numerical simulation of micro-scale morphological changes of plant food materials during drying - a meshfree approach

This thesis developed a high preforming alternative numerical technique to investigate microscale morphological changes of plant food materials during drying. The technique is based on a novel meshfree method, and is more capable of modeling large deformations of multiphase problem domains, when compared with conventional grid-based numerical modeling techniques. The developed cellular model can effectively replicate dried tissue morphological changes such as shrinkage and cell wall wrinkling, as influenced by moisture reduction and turgor loss.

Can bone tissue engineering contribute to therapy concepts after resection of musculoskeletal sarcoma?

Resection of musculoskeletal sarcoma can result in large bone defects where regeneration is needed in a quantity far beyond the normal potential of self-healing. In many cases, these defects exhibit a limited intrinsic regenerative potential due to an adjuvant therapeutic regimen, seroma, or infection. Therefore, reconstruction of these defects is still one of the most demanding procedures in orthopaedic surgery. The constraints of common treatment strategies have triggered a need for new therapeutic concepts to design and engineer unparalleled structural and functioning bone grafts. To satisfy the need for long-term repair and good clinical outcome, a paradigm shift is needed from methods to replace tissues with inert medical devices to more biological approaches that focus on the repair and reconstruction of tissue structure and function. It is within this context that the field of bone tissue engineering can offer solutions to be implemented into surgical therapy concepts after resection of bone and soft tissue sarcoma. In this paper we will discuss the implementation of tissue engineering concepts into the clinical field of orthopaedic oncology.

Colloidal drug probe : Method development and validation for adhesion force measurement using Atomic Force Microscopy

This study demonstrates a novel technique of preparing drug colloid probes to determine the adhesion force between a model drug salbutamol sulphate (SS) and the surfaces of polymer microparticles to be used as carriers for the dispersion of drug particles from dry powder inhaler (DPI) formulations. Model silica probes of approximately 4 lm size, similar to a drug particle used in DPI formulations, were coated with a saturated SS solution with the aid of capillary forces acting between the silica probe and the drug solution. The developed method of ensuring a smooth and uniform layer of SS on the silica probe was validated using X-ray Photoelectron Spectroscopy (XPS) and Scanning Electron Microscopy (SEM). Using the same technique, silica microspheres pre-attached on the AFM cantilever were coated with SS. The adhesion forces between the silica probe and drug coated silica (drug probe) and polymer surfaces (hydrophilic and hydrophobic) were determined. Our experimental results showed that the technique for preparing the drug probe was robust and can be used to determine the adhesion force between hydrophilic/ hydrophobic drug probe and carrier surfaces to gain a better understanding on drug carrier adhesion forces in DPI formulations.

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.

Size dependent photodegradation of CdS particles deposited onto TiO2 mesoporous films by SILAR method

The properties of CdS nanoparticles incorporated onto mesoporous TiO2 films by a successive ionic layer adsorption and reaction (SILAR) method were investigated by Raman spectroscopy, UV-visible spectroscopy, transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS). High resolution TEM indicated that the synthesized CdS particles were hexagonal phase and the particle sizes were less than 5 nm when SILAR cycles were fewer than 9. Quantum size effect was found with the CdS sensitized TiO2 films prepared with up to 9 SILAR cycles. The band gap of CdS nanoparticles decreased from 2.65 eV to 2.37 eV with the increase of the SILAR cycles from 1 to 11. The investigation of the stability of the CdS/TiO2 films in air under illumination (440.6 µW/cm2) showed that the photodegradation rate was up to 85% per day for the sample prepared with 3 SILAR cycles. XPS analysis indicated that the photodegradation was due to the oxidation of CdS, leading to the transformation from sulphide to sulphate (CdSO4). Furthermore, the degradation rate was strongly dependent upon the particle size of CdS. Smaller particles showed faster degradation rate. The size-dependent photo-induced oxidization was rationalized with the variation of size-dependent distribution of surface atoms of CdS particles. Molecular Dynamics (MD) simulation has indicated that the surface sulphide anion of a large CdS particle such as CdS made with 11 cycles (CdS11, particle size = 5.6 nm) accounts for 9.6% of the material whereas this value is increased to 19.2% for (CdS3) based smaller particles (particle size: 2.7 nm). Nevertheless, CdS nanoparticles coated with ZnS material showed a significantly enhanced stability under illumination in air. A nearly 100% protection of CdS from photon induced oxidation with a ZnS coating layer prepared using four SILAR cycles, suggesting the formation of a nearly complete coating layer on the CdS nanoparticles.

Including nonequilibrium interface kinetics in a continuum model for melting nanoscaled particles

The melting temperature of a nanoscaled particle is known to decrease as the curvature of the solid-melt interface increases. This relationship is most often modelled by a Gibbs--Thomson law, with the decrease in melting temperature proposed to be a product of the curvature of the solid-melt interface and the surface tension. Such a law must break down for sufficiently small particles, since the curvature becomes singular in the limit that the particle radius vanishes. Furthermore, the use of this law as a boundary condition for a Stefan-type continuum model is problematic because it leads to a physically unrealistic form of mathematical blow-up at a finite particle radius. By numerical simulation, we show that the inclusion of nonequilibrium interface kinetics in the Gibbs--Thomson law regularises the continuum model, so that the mathematical blow up is suppressed. As a result, the solution continues until complete melting, and the corresponding melting temperature remains finite for all time. The results of the adjusted model are consistent with experimental findings of abrupt melting of nanoscaled particles. This small-particle regime appears to be closely related to the problem of melting a superheated particle.

Design, manufacturing and maintenance of sugar milling equipment : observations from the 2008 ISSCT Engineering Workshop

An International Society of Sugar Cane Technologists (ISSCT) Engineering Workshop was held in Piracicaba, Brazil from 30 June to 4 July 2008. The theme of the workshop was Design, manufacturing and maintenance of sugar mill equipment. The workshop consisted of a series of technical sessions and site visits. The Brazilian sugar industry is growing rapidly. The growth has occurred as the result of the sugar industry’s position as a key provider of renewable energy in the form of ethanol and, more recently, electricity. The increased focus on electricity is seeing investment in high pressure (100 bar) boilers, cane cleaning plants that allow an increased biomass supply from trash and digesters that produce biogas from dunder. It is clear that the Brazilian sugar industry has a well defined place in the country’s future. The ISSCT workshop provided a good opportunity to gain information from equipment suppliers and discuss new technology that may have application in Australia. The new technologies of interest included IMCO sintered carbide shredder hammer tips, Fives Cail MillMax mills, planetary mill gearboxes, Bosch Projects chainless diffusers, Fives Cail Zuka centrifugals and Vaperma Siftek membrane systems.

An efficient and robust system for multi-person event detection in real world indoor surveillance scenes

Due to the popularity of security cameras in public places, it is of interest to design an intelligent system that can efficiently detect events automatically. This paper proposes a novel algorithm for multi-person event detection. To ensure greater than real-time performance, features are extracted directly from compressed MPEG video. A novel histogram-based feature descriptor that captures the angles between extracted particle trajectories is proposed, which allows us to capture motion patterns of multi-person events in the video. To alleviate the need for fine-grained annotation, we propose the use of Labelled Latent Dirichlet Allocation, a “weakly supervised” method that allows the use of coarse temporal annotations which are much simpler to obtain. This novel system is able to run at approximately ten times real-time, while preserving state-of-theart detection performance for multi-person events on a 100-hour real-world surveillance dataset (TRECVid SED).

Frequency-motivated observer design for the prediction of parametric roll resonance control applications in marine systems

This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.