An Investigation of the Flow Field through a Variable Geometry Turbine Stator with Vane Endwall Clearance

Variable geometry turbines provide an extra degree of flexibility in air management in turbocharged engines. The pivoting stator vanes used to achieve the variable turbine geometry necessitate the inclusion of stator vane endwall clearances. The consequent leakage flow through the endwall clearances impacts the flow in the stator vane passages and an understanding of the impact of the leakage flow on stator loss is required. A numerical model of a typical variable geometry turbine was developed using the commercial CFX-10 computational fluid dynamics software, and validated using laser doppler velocimetry and static pressure measurements from a variable geometry turbine with stator vane endwall clearance. Two different stator vane positions were investigated, each at three different operating conditions representing different vane loadings. The vane endwall leakage was found to have a significant impact on the stator loss and on the uniformity of flow entering the turbine rotor. The leakage flow changed considerably at different vane positions and flow incidence at vane inlet was found to have a significant impact.

A hierarchical physical model-based approach to predictive control of a thermal power plant for efficient plant-wide disturbance rejection

Extending the work presented in Prasad et al. (IEEE Proceedings on Control Theory and Applications, 147, 523-37, 2000), this paper reports a hierarchical nonlinear physical model-based control strategy to account for the problems arising due to complex dynamics of drum level and governor valve, and demonstrates its effectiveness in plant-wide disturbance handling. The strategy incorporates a two-level control structure consisting of lower-level conventional PI regulators and a higher-level nonlinear physical model predictive controller (NPMPC) for mainly set-point manoeuvring. The lower-level PI loops help stabilise the unstable drum-boiler dynamics and allow faster governor valve action for power and grid-frequency regulation. The higher-level NPMPC provides an optimal load demand (or set-point) transition by effective handling of plant-wide interactions and system disturbances. The strategy has been tested in a simulation of a 200-MW oil-fired power plant at Ballylumford in Northern Ireland. A novel approach is devized to test the disturbance rejection capability in severe operating conditions. Low frequency disturbances were created by making random changes in radiation heat flow on the boiler-side, while condenser vacuum was fluctuating in a random fashion on the turbine side. In order to simulate high-frequency disturbances, pulse-type load disturbances were made to strike at instants which are not an integral multiple of the NPMPC sampling period. Impressive results have been obtained during both types of system disturbances and extremely high rates of load changes, right across the operating range, These results compared favourably with those from a conventional state-space generalized predictive control (GPC) method designed under similar conditions.

Ocular blood flow analysis detects microvascular abnormalities in impaired glucose tolerance.

Objective: Waveform analysis has been used to assess vascular resistance and predict cardiovascular events. We aimed to identify microvascular abnormalities in patients with impaired glucose tolerance (IGT) using ocular waveform analysis. The effects of pioglitazone were also assessed. Methods: Forty patients with IGT and twenty-four controls were studied. Doppler velocity recordings were obtained from the central retinal, ophthalmic and common carotid arteries, and sampled at 200 Hz. A discrete wavelet-based analysis method was employed to quantify waveforms. The resistive index (RI),was also determined. Patients with IGT were randomised to pioglitazone or placebo and measurements repeated after 12 weeks treatment. Results: In the ocular waveforms, significant differences in power spectra were observed in frequency band four (corresponding to frequencies between 6.25 and 12.50 Hz) between groups (p

Effect of Turbine Inlet Temperature on Rotor Blade Tip Leakage Flow and Heat Transfer

One of the most critical gas turbine engine components, the rotor blade tip and casing, is exposed to high thermal load. It becomes a significant design challenge to protect the turbine materials from this severe situation. The purpose of this paper is to study numerically the effect of turbine inlet temperature on the tip leakage flow structure and heat transfer. In this paper, the effect of turbine inlet temperature on the tip leakage flow structure and heat transfer has been studied numerically. Uniform low (LTIT: 444 K) and high (HTIT: 800 K) turbine inlet temperature, as well as non-uniform inlet temperature have been considered. The results showed the higher turbine inlet temperature yields the higher velocity and temperature variations in the leakage flow aerodynamics and heat transfer. For a given turbine geometry and on-design operating conditions, the turbine power output can be increased by 1.33 times, when the turbine inlet temperature increases 1.80 times. Whereas the averaged heat fluxes on the casing and the blade tip become 2.71 and 2.82 times larger, respectively. Therefore, about 2.8 times larger cooling capacity is required to keep the same turbine material temperature. Furthermore, the maximum heat flux on the blade tip of high turbine inlet temperature case reaches up to 3.348 times larger than that of LTIT case. The effect of the interaction of stator and rotor on heat transfer features is also explored using unsteady simulations. The non-uniform turbine inlet temperature enhances the heat flux fluctuation on the blade tip and casing.

Combination of CFD and DOE to analyze and improve the mass flow rate in urinary catheters

The urinary catheter is a thin plastic tube that has been designed to empty the bladder artificially, effortlessly, and with minimum discomfort. The current CH14 male catheter design was examined with a view to optimizing the mass flow rate. The literature imposed constraints to the analysis of the urinary catheter to ensure that a compromise between optimal flow, patient comfort, and everyday practicality from manufacture to use was achieved in the new design. As a result a total of six design characteristics were examined. The input variables in question were the length and width of eyelets 1 and 2 (four variables), the distance between the eyelets, and the angle of rotation between the eyelets. Due to the high number of possible input combinations a structured approach to the analysis of data was necessary. A combination of computational fluid dynamics (CFD) and design of experiments (DOE) has been used to evaluate the "optimal configuration." The use of CFD couple with DOE is a novel concept, which harnesses the computational power of CFD in the most efficient manner for prediction of the mass flow rate in the catheter. Copyright © 2009 by ASME.

The Impact of Vehicle-to-Grid on Electric Power Systems: A Review

Environmental concerns and fossil fuel shortage put pressure on both power and transportation systems. Electric vehicles (EVs) are thought to be a good solution to these problems. With EV adoption, energy flow is two way: from grid to vehicle and from vehicle to grid, which is known as vehicle-to-grid (V2G) today. This paper considers electric power systems and provides a review of the impact of V2G on power system stability. The concept and basics of V2G technology are introduced at first, followed by a description of EV application in the world. Several technical issues are detailed in V2G modeling and capacity forecasting, steady-state analysis and stability analysis. Research trends of such topics are declared at last.

Analysis of Load Impact on Small-signal Stability based on Load Active Power Sensitivity

While load flow conditions vary with different loads, the small-signal stability of the entire system is closely related with to the locations, capacities and models of loads. In this paper, load impacts with different capacities and models on the small-signal stability are analysed. In the real large-scale power system case, the load sensitivity which denotes the sensitivity of the eigenvalue with respect to the load active power is introduced and applied to rank the loads. The loads with high sensitivity are also considered.

Energy monitoring and quality control of a single screw extruder

Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.

Efficiency improvement study for small wind turbines through flow control

In this study, a constant suction technique for controlling boundary layer separation at low Reynolds numbers was designed and tested. This was later implemented on small wind turbines. Small wind turbines need to operate in low wind speeds, that is, in low Reynolds number regimes – typically in the range 104–105. Airfoils are prone to boundary layer separation in these conditions, leading to a substantial drop in aerodynamic performance of the blades. Under these conditions turbines will have reduced energy output. This paper presents experimental results of applying surface-suction over the suction-surface of airfoils for controlling boundary layer separation. The Reynolds numbers for the experiments are kept in the range 8×104–5×105. The air over the surface of the airfoil is drawn into the airfoil through a slit. It is found that the lift coefficient of the airfoils increases and the drag reduces. Based on the improved airfoil characteristics, an analysis of increase in Coefficient of Power (CP), versus input power for a small wind turbine blade with constant suction is presented.

Enhanced AIMD based decentralized residential charging of EVs

Moving from combustion engine to electric vehicle (EV)-based transport is recognized as having a major role to play in reducing pollution, combating climate change and improving energy security. However, the introduction of EVs poses major challenges for power system operation. With increasing penetration of EVs, uncontrolled coincident charging may overload the grid and substantially increase peak power requirements. Developing smart grid technologies and appropriate charging strategies to support the role out of EVs is therefore a high priority. In this paper, we investigate the effectiveness of distributed additive increase and multiplicative decrease (AIMD) charging algorithms, as proposed by Stu¨dli et al. in 2012, at mitigating the impact of domestic charging of EVs on low-voltage distribution networks. In particular, a number of enhancements to the basic AIMD implementation are introduced to enable local power system infrastructure and voltage level constraints to be taken into account and to reduce peak power requirements. The enhanced AIMD EV charging strategies are evaluated using power system simulations for a typical low-voltage residential feeder network in Ireland. Results show that by using the proposed AIMD-based smart charging algorithms, 50% EV penetration can be accommodated, compared with only 10% with uncontrolled charging, without exceeding network infrastructure constraints.

Topology of megagauss magnetic fields and of heat-carrying electrons produced in a high-power laser-solid interaction

The intricate spatial and energy distribution of magnetic fields, self-generated during high power laser irradiation (at Iλ2∼1013-1014W.cm-2.μm2) of a solid target, and of the heat-carrying electron currents, is studied in inertial confinement fusion (ICF) relevant conditions. This is done by comparing proton radiography measurements of the fields to an improved magnetohydrodynamic description that fully takes into account the nonlocality of the heat transport. We show that, in these conditions, magnetic fields are rapidly advected radially along the target surface and compressed over long time scales into the dense parts of the target. As a consequence, the electrons are weakly magnetized in most parts of the plasma flow, and we observe a reemergence of nonlocality which is a crucial effect for a correct description of the energetics of ICF experiments.

Molecular pedigree reconstruction and estimation of evolutionary parameters in a wild Atlantic salmon river system with incomplete sampling: a power analysis

Background: Pedigree reconstruction using genetic analysis provides a useful means to estimate fundamental population biology parameters relating to population demography, trait heritability and individual fitness when combined with other sources of data. However, there remain limitations to pedigree reconstruction in wild populations, particularly in systems where parent-offspring relationships cannot be directly observed, there is incomplete sampling of individuals, or molecular parentage inference relies on low quality DNA from archived material. While much can still be inferred from incomplete or sparse pedigrees, it is crucial to evaluate the quality and power of available genetic information a priori to testing specific biological hypotheses. Here, we used microsatellite markers to reconstruct a multi-generation pedigree of wild Atlantic salmon (Salmo salar L.) using archived scale samples collected with a total trapping system within a river over a 10 year period. Using a simulation-based approach, we determined the optimal microsatellite marker number for accurate parentage assignment, and evaluated the power of the resulting partial pedigree to investigate important evolutionary and quantitative genetic characteristics of salmon in the system.

Results: We show that at least 20 microsatellites (ave. 12 alleles/locus) are required to maximise parentage assignment and to improve the power to estimate reproductive success and heritability in this study system. We also show that 1.5 fold differences can be detected between groups simulated to have differing reproductive success, and that it is possible to detect moderate heritability values for continuous traits (h(2) similar to 0.40) with more than 80% power when using 28 moderately to highly polymorphic markers.

Conclusion: The methodologies and work flow described provide a robust approach for evaluating archived samples for pedigree-based research, even where only a proportion of the total population is sampled. The results demonstrate the feasibility of pedigree-based studies to address challenging ecological and evolutionary questions in free-living populations, where genealogies can be traced only using molecular tools, and that significant increases in pedigree assignment power can be achieved by using higher numbers of markers.

Effect of turbine inlet temperature on blade tip leakage flow and heat transfer

One of the most critical gas turbine engine components, rotor blade tip and casing, are exposed to high thermal load. It becomes a significant design challenge to protect the turbine materials from this severe situation. As a result of geometric complexity and experimental limitations, Computational Fluid Dynamics (CFD) tools have been used to predict blade tip leakage flow aerodynamics and heat transfer at typical engine operating conditions. In this paper, the effect of turbine inlet temperature on the tip leakage flow structure and heat transfer has been studied numerically. Uniform low (LTIT: 444 K) and high (HTIT: 800 K) turbine inlet temperature have been considered. The results showed the higher turbine inlet temperature yields the higher velocity and temperature variations in the leakage flow aerodynamics and heat transfer. For a given turbine geometry and on-design operating conditions, the turbine power output can be increased by 1.48 times, when the turbine inlet temperature increases 1.80 times. Whereas the averaged heat fluxes on the casing and the blade tip become 2.71 and 2.82 times larger, respectively. Therefore, about 2.8 times larger cooling capacity is required to keep the same turbine material temperature. Furthermore, the maximum heat flux on the blade tip of high turbine inlet temperature case reaches up to 3.348 times larger than that of LTIT case. The effect of the interaction of stator and rotor on heat transfer features is also explored using unsteady simulations.

High-resolution genetic analysis reveals extensive gene flow within the jellyfish Pelagia noctiluca (Scyphozoa) in the North Atlantic and Mediterranean Sea

Despite the importance of gelatinous zooplankton as components of marine ecosystems, both ecologically and socio-economically, relatively little is known about population persistence or connectivity in jellyfish. In the present study, we employed a combination of nuclear microsatellite markers and sequence data from the mitochondrial cytochrome oxidase I (COI) gene to determine levels and patterns of population genetic structuring in the holoplanktonic jellyfish Pelagia noctiluca across the northeast Atlantic Ocean and Mediterranean Sea. Our results indicate a high degree of connectivity in P. noctiluca, with little evidence of geographical structuring of genetic variation. A small but significant differentiation of Atlantic Ocean and Mediterranean stocks was detected based on the microsatellite data, but no evidence of differentiation was observed with the mtDNA, probably due to the higher power of the microsatellites to detect low levels of genetic structuring. Two clearly distinct groups of genotypes were observed within the mtDNA COI, which probably diverged in the early Pleistocene, but with no evidence of geographical structuring. Palaeodistribution modelling of P. noctiluca at the Last Glacial Maximum (LGM; ca. 21 KYA) indicated large areas of suitable habitat south of the species’ current-day distribution, with little reduction in area. The congruent evidence for minimal genetic differentiation from the nuclear microsatellites and the mtDNA, coupled with the results of the palaeodistribution modelling, supports the idea of long-term population stability and connectivity, thus providing key insights into the population dynamics and demography of this important species