Mathematical Modelling of a Reciprocating Piston Expander

Modern internal combustion (IC) engines reject around two thirds of the energy provided by the fuel as low-grade waste heat. Capturing a portion of this waste heat energy and transforming it into a more useful form of energy could result in a significant reduction in fuel consumption. By using the low-grade heat, an organic Rankine cycle (ORC) can produce mechanical work from a pressurised organic fluid with the use of an expander.
Ideal gas assumptions are shown to produce significant errors in expander performance predictions when using an organic fluid. This paper details the mathematical modelling technique used to accurately model the thermodynamic processes for both ideal and non-ideal fluids within the reciprocating expander. A comparison between the two methods illustrates the extent of the errors when modelling a reciprocating piston expander. Use of the ideal gas assumptions are shown to produce an error of 55% in the prediction of power produced by the expander when operating on refrigerant R134a.

Mathematical modelling of quantum yield enhancements of methyl orange photooxidation in aqueous TiO2 suspensions under controlled periodic UV LED illumination

Quantum yields of the photocatalytic degradation of methyl orange under controlled periodic illumination (CPI) have been modelled using existing models. A modified Langmuir-Hinshelwood (L-H) rate equation was used to predict the degradation reaction rates of methyl orange at various duty cycles and a simple photocatalytic model was applied in modelling quantum yield enhancement of the photocatalytic process due to the CPI effect. A good agreement between the modelled and experimental data was observed for quantum yield modelling. The modified L-H model, however, did not accurately predict the photocatalytic decomposition of the dye under periodic illumination.

Dynamic modelling of die melt temperature profile in polymer extrusion: Effects of process settings, screw geometry and material

Extrusion is one of the major methods for processing polymeric materials and the thermal homogeneity of the process output is a major concern for manufacture of high quality extruded products. Therefore, accurate process thermal monitoring and control are important for product quality control. However, most industrial extruders use single point thermocouples for the temperature monitoring/control although their measurements are highly affected by the barrel metal wall temperature. Currently, no industrially established thermal profile measurement technique is available. Furthermore, it has been shown that the melt temperature changes considerably with the die radial position and hence point/bulk measurements are not sufficient for monitoring and control of the temperature across the melt flow. The majority of process thermal control methods are based on linear models which are not capable of dealing with process nonlinearities. In this work, the die melt temperature profile of a single screw extruder was monitored by a thermocouple mesh technique. The data obtained was used to develop a novel approach of modelling the extruder die melt temperature profile under dynamic conditions (i.e. for predicting the die melt temperature profile in real-time). These newly proposed models were in good agreement with the measured unseen data. They were then used to explore the effects of process settings, material and screw geometry on the die melt temperature profile. The results showed that the process thermal homogeneity was affected in a complex manner by changing the process settings, screw geometry and material.

The occurrence and significance of triploidy in the liver fluke, Fasciola hepatica.

Karyotyping of Fasciola hepatica samples from Britain and Ireland has identified a triploid isolate which is effectively aspermic, rendering it necessarily asexually reproducing. Considering the extensive presence of asexually reproducing diploid and triploid Fasciola in Asia it is suggested that facultative gynogenesis is widespread in this parasite. This has important implications for the population genetics and evolution of Fasciola, especially in relation to the development and spread of drug resistance, and must be considered in the mathematical modelling of this process.

Analysis of compressive membrane action in concrete slabs

This paper summarises the results obtained from non-linear finite-element analysis (NLFEA) of a series of reinforced-concrete one-way slabs with various boundary conditions representative of a bridge deck slab strip in which compressive membrane action governs the structural behaviour. The application of NLFEA for the optimum analysis and design of in-plane restrained concrete slabs is explored. An accurate material model and various equation solution methods were assessed to find a suitable finite-element method for the analysis of concrete slabs in which arching action occurs. Finally, the results from the NLFEA are compared and validated with those from various experimental test data. Significantly, the numerical analysis was able to model the arching action that occurred as a result of external in-plane restraint at the supports and which enhanced the ultimate strength of the slab. The NLFEA gave excellent predictions for the ultimate load-carrying capacity and far more accurate predictions than those obtained using standard flexural or elastic theory.

Investigating the Potential Impact of Four-dimensional Computed Tomography (4DCT) on Toxicity, Outcomes and Dose Escalation for Radical Lung Cancer Radiotherapy

AIMS: To investigate the potential dosimetric and clinical benefits predicted by using four-dimensional computed tomography (4DCT) compared with 3DCT in the planning of radical radiotherapy for non-small cell lung cancer.

MATERIALS AND METHODS:
Twenty patients were planned using free breathing 4DCT then retrospectively delineated on three-dimensional helical scan sets (3DCT). Beam arrangement and total dose (55 Gy in 20 fractions) were matched for 3D and 4D plans. Plans were compared for differences in planning target volume (PTV) geometrics and normal tissue complication probability (NTCP) for organs at risk using dose volume histograms. Tumour control probability and NTCP were modelled using the Lyman-Kutcher-Burman (LKB) model. This was compared with a predictive clinical algorithm (Maastro), which is based on patient characteristics, including: age, performance status, smoking history, lung function, tumour staging and concomitant chemotherapy, to predict survival and toxicity outcomes. Potential therapeutic gains were investigated by applying isotoxic dose escalation to both plans using constraints for mean lung dose (18 Gy), oesophageal maximum (70 Gy) and spinal cord maximum (48 Gy).

RESULTS:
4DCT based plans had lower PTV volumes, a lower dose to organs at risk and lower predicted NTCP rates on LKB modelling (P < 0.006). The clinical algorithm showed no difference for predicted 2-year survival and dyspnoea rates between the groups, but did predict for lower oesophageal toxicity with 4DCT plans (P = 0.001). There was no correlation between LKB modelling and the clinical algorithm for lung toxicity or survival. Dose escalation was possible in 15/20 cases, with a mean increase in dose by a factor of 1.19 (10.45 Gy) using 4DCT compared with 3DCT plans.

CONCLUSIONS:
4DCT can theoretically improve therapeutic ratio and dose escalation based on dosimetric parameters and mathematical modelling. However, when individual characteristics are incorporated, this gain may be less evident in terms of survival and dyspnoea rates. 4DCT allows potential for isotoxic dose escalation, which may lead to improved local control and better overall survival.

Dose, dose-rate and field size effects on cell survival following exposure to non-uniform radiation fields

For the delivery of intensity-modulated radiation therapy (IMRT), highly modulated fields are used to achieve dose conformity across a target tumour volume. Recent in vitro evidence has demonstrated significant alterations in cell survival occurring out-of-field which cannot be accounted for on the basis of scattered dose. The radiobiological effect of area, dose and dose-rate on out-of-field cell survival responses following exposure to intensity-modulated radiation fields is presented in this study. Cell survival was determined by clonogenic assay in human prostate cancer (DU-145) and primary fibroblast (AG0-1522) cells following exposure to different modulated field configurations delivered using a X-Rad 225 kVp x-ray source. Uniform survival responses were compared to in- and out-of-field responses in which 25-99% of the cell population was shielded. Dose delivered to the out-of-field region was varied from 1.6-37.2% of that delivered to the in-field region using different levels of brass shielding. Dose rate effects were determined for 0.2-4 Gy min⁻¹ for uniform and modulated exposures with no effect seen in- or out-of-field. Survival responses showed little dependence on dose rate and area in- and out-of-field with a trend towards increased survival with decreased in-field area. Out-of-field survival responses were shown to scale in proportion to dose delivered to the in-field region and also local dose delivered out-of-field. Mathematical modelling of these findings has shown survival response to be highly dependent on dose delivered in- and out-of-field but not on area or dose rate. These data provide further insight into the radiobiological parameters impacting on cell survival following exposure to modulated irradiation fields highlighting the need for refinement of existing radiobiological models to incorporate non-targeted effects and modulated dose distributions.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

Finite element modelling of cyclic behaviour of cold-formed steel bolted moment-resisting connections

This paper investigates the accuracy of new finite element modelling approaches to predict the behaviour of bolted moment-connections between cold-formed steel members, formed by using brackets bolted to the webs of the section, under low cycle fatigue. ABAQUS software is used as a modelling platform. Such joints are used for portal frames and potentially have good seismic resisting capabilities, which is important for construction in developing countries. The modelling implications of a two-dimensional beam element model, a three-dimensional shell element model and a three-dimensional solid element model are reported. Quantitative and qualitative results indicate that the three-dimensional quadratic S8R shell element model most accurately predicts the hysteretic behaviour and energy dissipation capacity of the connection when compared to the test results.