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.

Effective diffusivity and evaporative cooling in convective drying of food material

This article presents mathematical models to simulate coupled heat and mass transfer during convective drying of food materials using three different effective diffusivities: shrinkage dependent, temperature dependent and average of those two. Engineering simulation software COMSOL Multiphysics was utilized to simulate the model in 2D and 3D. The simulation results were compared with experimental data. It is found that the temperature dependent effective diffusivity model predicts the moisture content more accurately at the initial stage of the drying, whereas, the shrinkage dependent effective diffusivity model is better for the final stage of the drying. The model with shrinkage dependent effective diffusivity shows evaporative cooling phenomena at the initial stage of drying. This phenomenon was investigated and explained. Three dimensional temperature and moisture profiles show that even when the surface is dry, inside of the sample may still contain large amount of moisture. Therefore, drying process should be carefully dealt with otherwise microbial spoilage may start from the centre of the ‘dried’ food. A parametric investigation has been conducted after the validation of the model.

Online estimation of Allan variance parameters

A new online method is presented for estimation of the angular randomwalk and rate randomwalk coefficients of inertial measurement unit gyros and accelerometers. In the online method, a state-space model is proposed, and recursive parameter estimators are proposed for quantities previously measured from offline data techniques such as the Allan variance method. The Allan variance method has large offline computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of approximately 100 calculations per data sample.

Reduced complexity on-line estimation of hidden Markov model parameters

In this paper we propose and study low complexity algorithms for on-line estimation of hidden Markov model (HMM) parameters. The estimates approach the true model parameters as the measurement noise approaches zero, but otherwise give improved estimates, albeit with bias. On a nite data set in the high noise case, the bias may not be signi cantly more severe than for a higher complexity asymptotically optimal scheme. Our algorithms require O(N3) calculations per time instant, where N is the number of states. Previous algorithms based on earlier hidden Markov model signal processing methods, including the expectation-maximumisation (EM) algorithm require O(N4) calculations per time instant.

On-line estimation of Allan variance parameters

A new online method is presented for estimation of the angular random walk and rate random walk coefficients of IMU (inertial measurement unit) gyros and accelerometers. The online method proposes a state space model and proposes parameter estimators for quantities previously measured from off-line data techniques such as the Allan variance graph. Allan variance graphs have large off-line computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of O(100) calculations per data sample.

Significance of drying periods on nitrate removal in experimental biofilters

Nitrogen is an important nutrient that can impact the quality of aquatic environments when present in high concentration. Even though low concentration levels of ammonium-nitrogen have been observed in laboratory studies in bioretention basins, poor removal or even the production of nitrate-nitrogen within the filter is often recorded in such studies. Ten Perspex biofilter columns of 94 mm (internal diameter) were packed with a filter layer, transition layer and a gravel layer. While the filter layer was packed to a height of 800 mm, transition and gravel layers were packed to a composite height of 220 mm and operated with simulated stormwater in the laboratory. The filter layer contained 8% organic material by weight. A free board of 350 mm provided detention storage and head to facilitate infiltration. The columns were operated with different antecedent dry days (0 d to 21 d) and constant inflow concentration at a feed rate of 100 mL/min. Samples were collected from the outflow at different time intervals, between 2 min and 150 min from the start of outflow, and were tested for nitrate-nitrogen and total organic carbon. Washoff of organic carbon from the filter layer was observed to occur for 30 min of outflow. This indicated washoff of organic carbon from the filter itself. At the same time, a very low concentration of nitrate-nitrogen was recorded at the beginning of the outflow, indicating the effective removal of nitrate-nitrogen. We conclude that the removal of nitrate-nitrogen is insignificant during the wetting phase of a rainfall event and the process of denitrification is more pronounced during the drying phase of a rainfall event. Thus intermittent wetting and drying is crucial for the removal of nitrate-nitrogen in bioretention basins.

Multiphase porous media model for heat and mass transfer during drying of agricultural products

Modelling of food processing is complex because it involves sophisticated material and transport phenomena. Most of the agricultural products such fruits and vegetables are hygroscopic porous media containing free water, bound water, gas and solid matrix. Considering all phase in modelling is still not developed. In this article, a comprehensive porous media model for drying has been developed considering bound water, free water separately, as well as water vapour and air. Free water transport was considered as diffusion, pressure driven and evaporation. Bound water assumed to be converted to free water due to concentration difference and also can diffuse. Binary diffusion between water vapour and air was considered. Since, the model is fundamental physics based it can be applied to any drying applications and other food processing where heat and mass transfer takes place in porous media with significant evaporation and other phase change.

Dynamics of nitrogen and suspended solids removal in experimental stormwater biofilters under intermittent wetting and drying

This research study comprehensively analyses the dynamics of nitrogen and suspended solids removal in stormwater biofilters. The study focuses on pollutant removal during an event with time, rather than the conventional event-mean analysis. Antecedent dry days (number of days in between rainfall) during which biofilters remain dry and the inflow concentration of pollutants were two other important variables analysed in this study. The research outcome highlights the significance of dry-phase processes and the process of stabilization on filter performance and sets a paradigm shift from the current approach towards an innovative way of performance analysis of biofilters.

Melanoma cell colony expansion parameters revealed by approximate Bayesian computation

In vitro studies and mathematical models are now being widely used to study the underlying mechanisms driving the expansion of cell colonies. This can improve our understanding of cancer formation and progression. Although much progress has been made in terms of developing and analysing mathematical models, far less progress has been made in terms of understanding how to estimate model parameters using experimental in vitro image-based data. To address this issue, a new approximate Bayesian computation (ABC) algorithm is proposed to estimate key parameters governing the expansion of melanoma cell (MM127) colonies, including cell diffusivity, D, cell proliferation rate, λ, and cell-to-cell adhesion, q, in two experimental scenarios, namely with and without a chemical treatment to suppress cell proliferation. Even when little prior biological knowledge about the parameters is assumed, all parameters are precisely inferred with a small posterior coefficient of variation, approximately 2–12%. The ABC analyses reveal that the posterior distributions of D and q depend on the experimental elapsed time, whereas the posterior distribution of λ does not. The posterior mean values of D and q are in the ranges 226–268 µm2h−1, 311–351 µm2h−1 and 0.23–0.39, 0.32–0.61 for the experimental periods of 0–24 h and 24–48 h, respectively. Furthermore, we found that the posterior distribution of q also depends on the initial cell density, whereas the posterior distributions of D and λ do not. The ABC approach also enables information from the two experiments to be combined, resulting in greater precision for all estimates of D and λ.

Modal parameters identification of heavy-haul railway RC bridges: Experience acquired

Traditionally, it is not easy to carry out tests to identify modal parameters from existing railway bridges because of the testing conditions and complicated nature of civil structures. A six year (2007-2012) research program was conducted to monitor a group of 25 railway bridges. One of the tasks was to devise guidelines for identifying their modal parameters. This paper presents the experience acquired from such identification. The modal analysis of four representative bridges of this group is reported, which include B5, B15, B20 and B58A, crossing the Carajás railway in northern Brazil using three different excitations sources: drop weight, free vibration after train passage, and ambient conditions. To extract the dynamic parameters from the recorded data, Stochastic Subspace Identification and Frequency Domain Decomposition methods were used. Finite-element models were constructed to facilitate the dynamic measurements. The results show good agreement between the measured and computed natural frequencies and mode shapes. The findings provide some guidelines on methods of excitation, record length of time, methods of modal analysis including the use of projected channel and harmonic detection, helping researchers and maintenance teams obtain good dynamic characteristics from measurement data.

Modelling intermittent microwave convective drying (IMCD) of food materials

This thesis develops comprehensive mathematical models for an advanced drying technology Intermittent Microwave Convective Drying (IMCD). The models provide an improved physical understanding of the heat and mass transport during the drying process, which will help to improve the quality of dried food and energy efficiency of the process, as well as will increase the ability of automation and optimization. The final model in this thesis represents the most comprehensive fundamental multiphase model for IMCD that considers 3D electromagnetics coupled with multiphase porous media transport processes. The 3D electromagnetics considers Maxwell's equation and multiphase transport model considers three different phases: solid matrix, liquid water and gas consisting water vapour and air. The multiphase transport includes pressure-driven flow, capillary diffusion, binary diffusion, and evaporation. The models developed in this thesis were validated with extensive experimental investigations.