A microscopic simulation model to estimate Bus Rapid Transit (BRT) station service capacity with mixed stopping and non-stopping bus operation

Bus Rapid Transit (BRT) station is the interface between passenger and service. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses maneuvering into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. However, some systems include operation where express buses pass the critical station, resulting in a proportion of non stopping buses. It is important to understand the operation of the critical busway station under this type of operation, as it affects busway line capacity. This study uses micro simulation to treat the BRT station operation and to analyze the relationship between station Limit state bus capacity (B_ls), Total Bus Capacity (B_ttl). First, the simulation model is developed for Limit state scenario and then a mathematical model is defined, calibrated for a specified range of controlled scenarios of mean and coefficient of variation of dwell time. Thereafter, the proposed B_ls model is extended to consider non stopping buses and B_ttlmodel is defined. The proposed models provides better understanding to the BRT line capacity and is useful for transit authorities for designing better BRT operation.

A tensor encoding model of word meaning : theory and application to information retrieval

This project was a step forward in developing and evaluating a novel, mathematical model that can deduce the meaning of words based on their use in language. This model can be applied to a wide range of natural language applications, including the information seeking process most of us undertake on a daily basis.

Mathematical modelling of LiFePO4 cathodes

LiFePO4 is a commercially available battery material with good theoretical discharge capacity, excellent cycle life and increased safety compared with competing Li-ion chemistries. It has been the focus of considerable experimental and theoretical scrutiny in the past decade, resulting in LiFePO4 cathodes that perform well at high discharge rates. This scrutiny has raised several questions about the behaviour of LiFePO4 material during charge and discharge. In contrast to many other battery chemistries that intercalate homogeneously, LiFePO4 can phase-separate into highly and lowly lithiated phases, with intercalation proceeding by advancing an interface between these two phases. The main objective of this thesis is to construct mathematical models of LiFePO4 cathodes that can be validated against experimental discharge curves. This is in an attempt to understand some of the multi-scale dynamics of LiFePO4 cathodes that can be difficult to determine experimentally. The first section of this thesis constructs a three-scale mathematical model of LiFePO4 cathodes that uses a simple Stefan problem (which has been used previously in the literature) to describe the assumed phase-change. LiFePO4 crystals have been observed agglomerating in cathodes to form a porous collection of crystals and this morphology motivates the use of three size-scales in the model. The multi-scale model developed validates well against experimental data and this validated model is then used to examine the role of manufacturing parameters (including the agglomerate radius) on battery performance. The remainder of the thesis is concerned with investigating phase-field models as a replacement for the aforementioned Stefan problem. Phase-field models have recently been used in LiFePO4 and are a far more accurate representation of experimentally observed crystal-scale behaviour. They are based around the Cahn-Hilliard-reaction (CHR) IBVP, a fourth-order PDE with electrochemical (flux) boundary conditions that is very stiff and possesses multiple time and space scales. Numerical solutions to the CHR IBVP can be difficult to compute and hence a least-squares based Finite Volume Method (FVM) is developed for discretising both the full CHR IBVP and the more traditional Cahn-Hilliard IBVP. Phase-field models are subject to two main physicality constraints and the numerical scheme presented performs well under these constraints. This least-squares based FVM is then used to simulate the discharge of individual crystals of LiFePO4 in two dimensions. This discharge is subject to isotropic Li+ diffusion, based on experimental evidence that suggests the normally orthotropic transport of Li+ in LiFePO4 may become more isotropic in the presence of lattice defects. Numerical investigation shows that two-dimensional Li+ transport results in crystals that phase-separate, even at very high discharge rates. This is very different from results shown in the literature, where phase-separation in LiFePO4 crystals is suppressed during discharge with orthotropic Li+ transport. Finally, the three-scale cathodic model used at the beginning of the thesis is modified to simulate modern, high-rate LiFePO4 cathodes. High-rate cathodes typically do not contain (large) agglomerates and therefore a two-scale model is developed. The Stefan problem used previously is also replaced with the phase-field models examined in earlier chapters. The results from this model are then compared with experimental data and fit poorly, though a significant parameter regime could not be investigated numerically. Many-particle effects however, are evident in the simulated discharges, which match the conclusions of recent literature. These effects result in crystals that are subject to local currents very different from the discharge rate applied to the cathode, which impacts the phase-separating behaviour of the crystals and raises questions about the validity of using cathodic-scale experimental measurements in order to determine crystal-scale behaviour.

Segmental torso masses and coronal plane joint torques in the adolescent scoliotic spine

Introduction. Calculating segmental (vertebral level-by-level) torso masses in Adolescent Idiopathic Scoliosis (AIS) patients allows the gravitational loading on the scoliotic spine during relaxed standing to be determined. This study used CT scans of AIS patients to measure segmental torso masses and explores how joint moments in the coronal plane are affected by changes in the position of the intervertebral joint’s axis of rotation; particularly at the apex of a scoliotic major curve. Methods. Existing low dose CT data from the Paediatric Spine Research Group was used to calculate vertebral level-by-level torso masses and joint torques occurring in the spine for a group of 20 female AIS patients (mean age 15.0 ± 2.7 years, mean Cobb angle 53 ± 7.1°). Image processing software, ImageJ (v1.45 NIH USA) was used to threshold the T1 to L5 CT images and calculate the segmental torso volume and mass corresponding to each vertebral level. Body segment masses for the head, neck and arms were taken from published anthropometric data. Intervertebral (IV) joint torques at each vertebral level were found using principles of static equilibrium together with the segmental body mass data. Summing the torque contributions for each level above the required joint, allowed the cumulative joint torque at a particular level to be found. Since there is some uncertainty in the position of the coronal plane Instantaneous Axis of Rotation (IAR) for scoliosis patients, it was assumed the IAR was located in the centre of the IV disc. A sensitivity analysis was performed to see what effect the IAR had on the joint torques by moving it laterally 10mm in both directions. Results. The magnitude of the torso masses from T1-L5 increased inferiorly, with a 150% increase in mean segmental torso mass from 0.6kg at T1 to 1.5kg at L5. The magnitudes of the calculated coronal plane joint torques during relaxed standing were typically 5-7 Nm at the apex of the curve, with the highest apex joint torque of 7Nm being found in patient 13. Shifting the assumed IAR by 10mm towards the convexity of the spine, increased the joint torque at that level by a mean 9.0%, showing that calculated joint torques were moderately sensitive to the assumed IAR location. When the IAR midline position was moved 10mm away from the convexity of the spine, the joint torque reduced by a mean 8.9%. Conclusion. Coronal plane joint torques as high as 7Nm can occur during relaxed standing in scoliosis patients, which may help to explain the mechanics of AIS progression. This study provides new anthropometric reference data on vertebral level-by-level torso mass in AIS patients which will be useful for biomechanical models of scoliosis progression and treatment. However, the CT scans were performed in supine (no gravitational load on spine) and curve magnitudes are known to be smaller than those measured in standing.

Preferential invasion by Plasmodium merozoites and the self-regulation of parasite burden

The preferential invasion of particular red blood cell (RBC) age classes may offer a mechanism by which certain species of Plasmodia regulate their population growth. Asexual reproduction of the parasite within RBCs exponentially increases the number of circulating parasites; limiting this explosion in parasite density may be key to providing sufficient time for the parasite to reproduce, and for the host to develop a specific immune response. It is critical that the role of preferential invasion in infection is properly understood to model the within-host dynamics of different Plasmodia species. We develop a simulation model to show that limiting the range of RBC age classes available for invasion is a credible mechanism for restricting parasite density, one which is equally as important as the maximum parasite replication rate and the duration of the erythrocytic cycle. Different species of Plasmodia that regularly infect humans exhibit different preferences for RBC invasion, with all species except P. falciparum appearing to exhibit a combination of characteristics which are able to selfregulate parasite density.

Towards a model of spray-canopy interactions : interception, shatter, bounce and retention of droplets on horizontal leaves

Pesticides used in agricultural systems must be applied in economically viable and environmentally sensitive ways, and this often requires expensive field trials on spray deposition and retention by plant foliage. Computational models to describe whether a spray droplet sticks (adheres), bounces or shatters on impact, and if any rebounding parent or shatter daughter droplets are recaptured, would provide an estimate of spray retention and thereby act as a useful guide prior to any field trials. Parameter-driven interactive software has been implemented to enable the end-user to study and visualise droplet interception and impaction on a single, horizontal leaf. Living chenopodium, wheat and cotton leaves have been scanned to capture the surface topography and realistic virtual leaf surface models have been generated. Individual leaf models have then been subjected to virtual spray droplets and predictions made of droplet interception with the virtual plant leaf. Thereafter, the impaction behaviour of the droplets and the subsequent behaviour of any daughter droplets, up until re-capture, are simulated to give the predicted total spray retention by the leaf. A series of critical thresholds for the stick, bounce, and shatter elements in the impaction process have been developed for different combinations of formulation, droplet size and velocity, and leaf surface characteristics to provide this output. The results show that droplet properties, spray formulations and leaf surface characteristics all influence the predicted amount of spray retained on a horizontal leaf surface. Overall the predicted spray retention increases as formulation surface tension, static contact angle, droplet size and velocity decreases. Predicted retention on cotton is much higher than on chenopodium. The average predicted retention on a single horizontal leaf across all droplet size, velocity and formulations scenarios tested, is 18, 30 and 85% for chenopodium, wheat and cotton, respectively.

Understanding mild acid pretreatment of sugarcane bagasse through particle scale modeling

Sugarcane bagasse is an abundant and sustainable resource, generated as a by-product of sugarcane milling. The cellulosic material within bagasse can be broken down into glucose molecules and fermented to produce ethanol, making it a promising feedstock for biofuel production. Mild acid pretreatment hydrolyses the hemicellulosic component of biomass, thus allowing enzymes greater access to the cellulosic substrate during saccharification. A particle-scale mathematical model describing the mild acid pretreatment of sugarcane bagasse has been developed, using a volume averaged framework. Discrete population-balance equations are used to characterise the polymer degradation kinetics, and diffusive effects account for mass transport within the cell wall of the bagasse. As the fibrous material hydrolyses over time, variations in the porosity of the cell wall and the downstream effects on the reaction kinetics are accounted for using conservation of volume arguments. Non-dimensionalization of the model equations reduces the number of parameters in the system to a set of four dimensionless ratios that compare the timescales of different reaction and diffusion events. Theoretical yield curves are compared to macroscopic experimental observations from the literature and inferences are made as to constraints on these “unknown” parameters. These results enable connections to be made between experimental data and the underlying thermodynamics of acid pretreatment. Consequently, the results suggest that data-fitting techniques used to obtain kinetic parameters should be carefully applied, with prudent consideration given to the chemical and physiological processes being modeled.

Optimal catalyst thickness in titanium dioxide fixed film reactors: Mathematical modelling and experimental validation

The use of immobilised TiO2 for the purification of polluted water streams introduces the necessity to evaluate the effect of mechanisms such as the transport of pollutants from the bulk of the liquid to the catalyst surface and the transport phenomena inside the porous film. Experimental results of the effects of film thickness on the observed reaction rate for both liquid-side and support-side illumination are here compared with the predictions of a one-dimensional mathematical model of the porous photocatalytic slab. Good agreement was observed between the experimentally obtained photodegradation of phenol and its by-products, and the corresponding model predictions. The results have confirmed that an optimal catalyst thickness exists and, for the films employed here, is 5 μm. Furthermore, the modelling results have highlighted the fact that porosity, together with the intrinsic reaction kinetics are the parameters controlling the photocatalytic activity of the film. The former by influencing transport phenomena and light absorption characteristics, the latter by naturally dictating the rate of reaction.

Incorporating spatial correlations into multispecies mean-field models

In biology, we frequently observe different species existing within the same environment. For example, there are many cell types in a tumour, or different animal species may occupy a given habitat. In modelling interactions between such species, we often make use of the mean field approximation, whereby spatial correlations between the locations of individuals are neglected. Whilst this approximation holds in certain situations, this is not always the case, and care must be taken to ensure the mean field approximation is only used in appropriate settings. In circumstances where the mean field approximation is unsuitable we need to include information on the spatial distributions of individuals, which is not a simple task. In this paper we provide a method that overcomes many of the failures of the mean field approximation for an on-lattice volume-excluding birth-death-movement process with multiple species. We explicitly take into account spatial information on the distribution of individuals by including partial differential equation descriptions of lattice site occupancy correlations. We demonstrate how to derive these equations for the multi-species case, and show results specific to a two-species problem. We compare averaged discrete results to both the mean field approximation and our improved method which incorporates spatial correlations. We note that the mean field approximation fails dramatically in some cases, predicting very different behaviour from that seen upon averaging multiple realisations of the discrete system. In contrast, our improved method provides excellent agreement with the averaged discrete behaviour in all cases, thus providing a more reliable modelling framework. Furthermore, our method is tractable as the resulting partial differential equations can be solved efficiently using standard numerical techniques.

The impact of the clean development mechanism (CDM) on the cost price of wind power electricity : a China study

As a renewable energy source, wind power is playing an increasingly important role in China’s electricity supply. Meanwhile, China is also the world’s largest market for Clean Development Mechanism (CDM) wind power projects. Based on the data of 27 wind power projects of Inner Mongolia registered with the Executive Board of the United Nations (EB) in 2010, this paper constructs a financial model of Net Present Value (NPV) to analyze the cost of wind power electricity. A sensitivity analysis is then conducted to examine the impact of different variables with and without Certified Emission Reduction (CER) income brought about by the CDM. It is concluded that the CDM, along with static investment and annual wind electricity production, is one of the most significant factors in promoting the development of wind power in China. Additionally, wind power is envisaged as a practical proposition for competing with thermal power if the appropriate actions identified in the paper are made.

Do pioneer cells exist?

Most mathematical models of collective cell spreading make the standard assumption that the cell diffusivity and cell proliferation rate are constants that do not vary across the cell population. Here we present a combined experimental and mathematical modeling study which aims to investigate how differences in the cell diffusivity and cell proliferation rate amongst a population of cells can impact the collective behavior of the population. We present data from a three–dimensional transwell migration assay which suggests that the cell diffusivity of some groups of cells within the population can be as much as three times higher than the cell diffusivity of other groups of cells within the population. Using this information, we explore the consequences of explicitly representing this variability in a mathematical model of a scratch assay where we treat the total population of cells as two, possibly distinct, subpopulations. Our results show that when we make the standard assumption that all cells within the population behave identically we observe the formation of moving fronts of cells where both subpopulations are well–mixed and indistinguishable. In contrast, when we consider the same system where the two subpopulations are distinct, we observe a very different outcome where the spreading population becomes spatially organized with the more motile subpopulation dominating at the leading edge while the less motile subpopulation is practically absent from the leading edge. These modeling predictions are consistent with previous experimental observations and suggest that standard mathematical approaches, where we treat the cell diffusivity and cell proliferation rate as constants, might not be appropriate.

Angiogenesis is an independent prognostic factor in malignant mesothelioma

Angiogenesis is essential for tumour growth beyond 1 to 2 mm in diameter. The clinical relevance of angiogenesis, as assessed by microvessel density (MVD), is unclear in malignant mesothelioma (MM). Immunohistochemistry was performed on 104 archival, paraffin-embedded, surgically resected MM samples with an anti-CD34 monoclonal antibody, using the Streptavidin-biotin complex immunoperoxidase technique. 93 cases were suitable for microvessel quantification. MVD was obtained from 3 intratumoural hotspots, using a Chalkley eyepiece graticule at × 250 power. MVD was correlated with survival by Kaplan-Meier and log-rank analysis. A stepwise, multivariate Cox model was used to compare MVD with known prognostic factors and the EORTC and CALGB prognostic scoring systems. Overall median survival from the date of diagnosis was 5.0 months. Increasing MVD was a poor prognostic factor in univariate analysis (P = 0.02). Independent indicators of poor prognosis in multivariate analysis were non-epithelial cell type (P = 0.002), performance status > 0 (P = 0.003) and increasing MVD (P = 0.01). In multivariate Cox analysis, MVD contributed independently to the EORTC (P = 0.006), but not to the CALGB (P = 0.1), prognostic groups. Angiogenesis, as assessed by MVD, is a poor prognostic factor in MM, independent of other clinicopathological variables and the EORTC prognostic scoring system. Further work is required to assess the prognostic importance of angiogenic regulatory factors in this disease. © 2001 Cancer Research Campaign.

A variable diffusivity model for the drying of spherical food particulates

An investigation of the drying of spherical food particles was performed, using peas as the model material. In the development of a mathematical model for drying curves, moisture diffusion was modelled using Fick’s second law for mass transfer. The resulting partial differential equation was solved using a forward-time central-space finite difference approximation, with the assumption of variable effective diffusivity. In order to test the model, experimental data was collected for the drying of green peas in a fluidised bed at three drying temperatures. Through fitting three equation types for effective diffusivity to the data, it was found that a linear equation form, in which diffusivity increased with decreasing moisture content, was most appropriate. The final model accurately described the drying curves of the three experimental temperatures, with an R2 value greater than 98.6% for all temperatures.

Mathematical modelling of counter flow v-grove solar air collector

Double-pass counter flow v-grove collector is considered one of the most efficient solar air-collectors. In this design of the collector, the inlet air initially flows at the top part of the collector and changes direction once it reaches the end of the collector and flows below the collector to the outlet. A mathematical model is developed for this type of collector and simulation is carried out using MATLAB programme. The simulation results were verified with three distinguished research results and it was found that the simulation has the ability to predict the performance of the air collector accurately as proven by the comparison of experimental data with simulation. The difference between the predicted and experimental results is, at maximum, approximately 7% which is within the acceptable limit considering some uncertainties in the input parameter values to allow comparison. A parametric study was performed and it was found that solar radiation, inlet air temperature, flow rate and length have a significant effect on the efficiency of the air collector. Additionally, the results are compared with single flow V-groove collector.

Multi-criteria optimization of group replacement schedules for distributed water pipeline assets

This thesis presents a multi-criteria optimisation study of group replacement schedules for water pipelines, which is a capital-intensive and service critical decision. A new mathematical model was developed, which minimises total replacement costs while maintaining a satisfactory level of services. The research outcomes are expected to enrich the body of knowledge of multi-criteria decision optimisation, where group scheduling is required. The model has the potential to optimise replacement planning for other types of linear asset networks resulting in bottom-line benefits for end users and communities. The results of a real case study show that the new model can effectively reduced the total costs and service interruptions.