Fasciola hepatica vaccine: We may not be there yet but we're on the right road

Major advances have been made in identifying potential vaccine molecules for the control of fasciolosis in livestock but we have yet to reach the level of efficacy required for commercialisation. The pathogenesis of fasciolosis is associated with liver damage that is inflicted by migrating and feeding immature flukes as well as host inflammatory immune responses to parasite-secreted molecules and tissue damage alarm signals. Immune suppression/modulation by the parasites prevents the development of protective immune responses as evidenced by the lack of immunity observed in naturally and experimentally infected animals. In our opinion, future efforts need to focus on understanding how parasites invade and penetrate the tissues of their hosts and how they potentiate and control the ensuing immune responses, particularly in the first days of infection. Emerging 'omics' data employed in an unbiased approach are helping us understand liver fluke biology and, in parallel with new immunological data, to identify molecules that are essential to parasite development and accessible to vaccine-induced immune responses.

A Numerical Study of Inlet Geometry for a Low Inertia Mixed Flow Turbocharger Turbine

Mixed flow turbines can offer improvements over typical radial turbines used in automotive turbochargers, with regards to transient performance and low velocity ratio efficiency. Turbine rotor mass dominates the rotating inertia of the turbocharger, and any reductions of mass in the outer radii of the wheel, including the rotor back-disk, can significantly reduce this inertia and improve the acceleration of the assembly. Off-design, low velocity ratio conditions are typified by highly tangential flow at the rotor inlet and a non-zero inlet blade angle is preferred for such operating conditions. This is achievable in a Mixed Flow Turbine without increasing bending stresses within the rotor blade, which is beneficial in high speed and high inlet temperature turbine design. A range of mixed flow turbine rotors was designed with varying cone angle and inlet blade angle and each was assessed at a number of operating points. These rotors were based on an existing radial flow turbine, and both the hub and shroud contours and exducer geometry were maintained. The inertia of each rotor was also considered. The results indicated that there was a trade-off between efficiency and inertia for the rotors and certain designs may be beneficial for the transient performance of downsized, turbocharged engines.

A numerical study of trailing edge geometry for low inertia automotive mixed flow turbines

Abstract. Mixed flow turbines can offer improvements over typical radial turbines used in automotive turbochargers, with respect to transient performance and low velocity ratio efficiency. Turbine rotor mass dominates the rotating inertia of the turbocharger’s rotating assembly, and any reductions of mass in the outer radii of the wheel, including the rotor back-disk, can significantly reduce this inertia and improve the acceleration of the assembly. Off-design, low velocity ratio conditions are typified by highly tangential flow at the rotor inlet and a non-zero inlet blade angle is desirable for such operating conditions. This is achievable in a Mixed Flow Turbine without increasing bending stresses within the rotor blade, which is beneficial in high speed and high inlet temperature turbine designs.
This study considers the meridional geometry of Mixed Flow Turbines using a multi-disciplinary study to assess both the structural and aerodynamic performance of each rotor, incorporating both CFD and FEA. Variations of rotor trailing edge were investigated at different operating conditions representing both on- and off-design operation within the constraints of existing hardware geometries. In all cases, the performance is benchmarked against an existing state-of-the-art radial turbocharger turbine with consideration of rotor inertia and its benefit for engine transient performance. The results indicate the influence of these parameters and this report details their benefits with respect to turbocharging a downsized, automotive engine.

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.

A Numerical and Experimental Assessment of the Use of a Turbine Utilizing Splitter Blades for an Automotive Variable Geometry Turbocharger

Automotive manufacturers require improved part load engine performance to further improve fuel economy. For a swing vane VGS (Variable Geometry Stator) turbine this means a more closed stator vane, to deal with the low MFRs (Mass Flow Rates), high PRs (Pressure Ratios) and low rotor rotational speeds. During these conditions the turbine is operating at low velocity ratios. As more energy is available at high pressure ratios and during lower turbocharger rotational speeds, a turbine which is efficient at these conditions is desirable. Another key aspect for automotive manufacturers is engine responsiveness. High inertia designs result in “turbo lag” which means an increased time before the target boost pressure is reached. Therefore, designs with improved performance at low velocity ratios, reduced inertia or an increased swallowing capacity are the current targets for turbocharger manufacturers.

To try to meet these design targets a CFD (Computational Fluid Dynamics) study was performed on a turbine wheel using splitter blades. A number of parameters were investigated. These included splitter blade merdional length, blade number and blade angle distribution.

The numerical study was performed on a scaled automotive VGS. Three different stator vane positions have been analysed. A single passage CFD model was developed and used to provide information on the flow features affecting performance in both the stator vanes and turbine.

Following the CFD investigation the design with the best compromise in terms of performance, inertia and increased MFP (Mass Flow Parameter) was selected for manufacture and testing. Tests were performed on a scaled, low temperature turbine test rig. The aerodynamic flow path of the gas stand was the same as that investigated during the CFD. The test results revealed a design which had similar performance at the closed stator vane positions when compared to the baseline wheel. At the maximum MFR stator vane condition a drop of −0.6% pts in efficiency was seen. However, 5.5% increase in MFP was obtained with the additional benefit of a drop in rotor inertia of 3.7%, compared to the baseline wheel.

A numerical study of automotive turbocharger mixed flow turbine inlet geometry for off design performance

Mixed flow turbines represent a potential solution to the increasing requirement for high pressure, low velocity ratio operation in turbocharger applications. While literature exists for the use of these turbines at such operating conditions, there is a lack of detailed design guidance for defining the basic geometry of the turbine, in particular, the cone angle – the angle at which the inlet of the mixed flow turbine is inclined to the axis. This investigates the effect and interaction of such mixed flow turbine design parameters.
Computational Fluids Dynamics was initially used to investigate the performance of a modern radial turbine to create a baseline for subsequent mixed flow designs. Existing experimental data was used to validate this model.
Using the CFD model, a number of mixed flow turbine designs were investigated. These included studies varying the cone angle and the associated inlet blade angle.
The results of this analysis provide insight into the performance of a mixed flow turbine with respect to cone and inlet blade angle.

A Numerical Study of the Flow Fields in a Highly Off-Design Variable Geometry Turbine

Conventionally, radial turbines have almost exclusively used radially fibred blades. While issues of mechanical integrity are paramount, there may be opportunities for improving turbine efficiency through a 3D blade design without exceeding mechanical limits. Off-design performance and understanding of the secondary flow structures now plays a vital role in the design decisions made for automotive turbocharger turbines. Of particular interest is extracting more energy at high pressure ratios and lower rotational speeds. Operating in this region means the rotor will experience high values of positive incidence at the inlet. A CFD analysis has been carried out on a scaled automotive turbine utilizing a swing vane stator system. To date no open literature exists on the flow structures present in a standard VGT system. Investigations were carried out on a 90 mm diameter rotor with the stator vane at the maximum, minimum and 25% mass flow rate positions. In addition stator vane endwall clearance existed at the hub side. From investigation of the internal flow fields of the baseline rotor, a number of areas that could be optimized in the future with three dimensional blading were identified. The blade loading and tip leakage flow near inlet play a significant role in the flow development further downstream at all stator vane positions. It was found that tip leakage flow and flow separation at off-design conditions could be reduced by employing back swept blading and redistributing the blade loading. This could potentially reduce the extent of the secondary flow structures found in the present study.

Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.

Evolving techniques for monitoring geotechnical risk on the Antrim Coast Road.

The interaction between problematic geology and environmental variables along the Antrim Coast Road results in frequent instances of geotechnical instability. During such instances of instability, mudslide debris encroaches on the carriageway posing a hazard to motorists, causing lengthily tailbacks. This paper examines some of the geotechnical and spatial analysis techniques currently being implemented to monitor slope stability on this key transport route.

Identification of Road Irregularities via Vehicle Accelerations

A periodic monitoring of the pavement condition facilitates a cost-effective distribution of the resources available for maintenance of the road infrastructure network. The task can be accurately carried out using profilometers, but such an approach is generally expensive. This paper presents a method to collect information on the road profile via accelerometers mounted in a fleet of non-specialist vehicles, such as police cars, that are in use for other purposes. It proposes an optimisation algorithm, based on Cross Entropy theory, to predict road irregularities. The Cross Entropy algorithm estimates the height of the road irregularities from vehicle accelerations at each point in time. To test the algorithm, the crossing of a half-car roll model is simulated over a range of road profiles to obtain accelerations of the vehicle sprung and unsprung masses. Then, the simulated vehicle accelerations are used as input in an iterative procedure that searches for the best solution to the inverse problem of finding road irregularities. In each iteration, a sample of road profiles is generated and an objective function defined as the sum of squares of differences between the ‘measured’ and predicted accelerations is minimized until convergence is reached. The reconstructed profile is classified according to ISO and IRI recommendations and compared to its original class. Results demonstrate that the approach is feasible and that a good estimate of the short-wavelength features of the road profile can be detected, despite the variability between the vehicles used to collect the data.

Dynamic axle force and road profile identification using a moving vehicle

The axle forces applied by a vehicle through its wheels are a critical part of the interaction between vehicles, pavements and bridges. Therefore, the minimisation of these forces is important in order to promote long pavement life spans and ensure that bridge loads are small. Moreover, as the road surface roughness affects the vehicle dynamic forces, the monitoring of pavements for highways and bridges is an important task. This paper presents a novel algorithm to identify these dynamic interaction forces which involves direct instrumentation of a vehicle with accelerometers. The ability of this approach to predict the pavement roughness is also presented. Moving force identification theory is applied to a vehicle model in theoretical simulations in order to obtain the interaction forces and pavement roughness from the measured accelerations. The method is tested for a range of bridge spans in simulations and the influence of road roughness level on the accuracy of the results is investigated. Finally, the challenge for the real-world problem is addressed in a laboratory experiment.