Numerical investigation of secondary flows in a high-lift low pressure turbine

In turbomachines, secondary flows (or endwall flows) typically originate at the junction between endwalls and the blade surface. Within the blade passage, the strength of the secondary flows is amplified by the crossflow from the pressure to the suction surface of the blade. The enhanced mixing due to secondary flows induce additional losses into the system. This decreases the overall work output and also changes the flow incidence onto the downstream blade rows. Using a series of high-fidelity eddy resolving simulations, the current study attempts to provide an improved understanding for the complex flow physics over the endwalls of a high-lift Low Pressure Turbine (LPT) blade. The effect of three different inflow conditions has been studied. These include a laminar boundary layer (LBL), a turbulent boundary layer (TBL) and wakes with secondary flow (W&S) from an upstream blade row. For the simulations with TBL and W&S, precursor eddy resolving simulations were used to prescribe realistic inflows. The loss generation mechanisms were subsequently studied both at the endwall and the midspan, which includes evaluating the mass-averaged total pressure loss coefficient (Y$_p$) and the loss generation rate. When compared to LBL, additional disturbances from an incoming TBL and wakes with secondary flows enhanced the mixing within the blade passage resulting in a substantial increase in the total pressure loss. Prior to flow transition, incoming wakes with secondary flows increased the local loss generation rate at both the endwall and the midspan in the front portion of the blade passage ($\textit{x}$/C$_x$ 0.8), the incoming wakes effectively suppressed the separation bubble at the midspan thereby decreasing the local loss generation rate. It is also demonstrated that the wakes shed from the trailing edge at the mid-span mix out rapidly when compared to the passage vortex at the endwall.Cambridge Overseas TrustThis is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.ijheatfluidflow.2016.05.01

Climatic shift over Mahanadi river basin

The inter-annual variability and the long-term trends in the monsoon rainfall and in two derived climatic parameters, aridity index (I(a)) and moisture index (I(m)), have been examined for the Mahanadi basin using the rainfall and temperature data for the 80-year period (1901-80). The study shows that the basin has experienced a good number of deficit years during the last two decades of the study period. The yearly values of aridity and moisture indices show increase in the aridity conditions over the basin, with the semi-arid type climate in as many as five years during 1965-80. The trend analysis shows that the increasing and decreasing trends in the aridity index and moisture index respectively are statistically significant. The trend in the seasonal rainfall, though negative, is not statistically significant

Pre-transplant CDKN2A expression in kidney biopsies predicts renal function and is a future component of donor scoring criteria

CDKN2A is a proven and validated biomarker of ageing which acts as an off switch for cell proliferation. We have demonstrated previously that CDKN2A is the most robust and the strongest pre-transplant predictor of post- transplant serum creatinine when compared to “Gold Standard” clinical factors, such as cold ischaemic time and donor chronological age. This report shows that CDKN2A is better than telomere length, the most celebrated biomarker of ageing, as a predictor of post-transplant renal function. It also shows that CDKN2A is as strong a determinant of post-transplant organ function when compared to extended criteria (ECD) kidneys. A multivariate analysis model was able to predict up to 27.1% of eGFR at one year post-transplant (p = 0.008). Significantly, CDKN2A was also able to strongly predict delayed graft function. A pre-transplant donor risk classification system based on CDKN2A and ECD criteria is shown to be feasible and commendable for implementation in the near future

Alpha 1 antitrypsin gene: A case-control study in chronic obstructive pulmonary disease

Alpha-1 antitrypsin (AAT) deficiency is an inherited disorder that causes low levels of, or no AAT in the blood. The most common illness in adults with AAT deficiency is lung disease during the third and fourth decades of life. Most commonly, it is associated with chronic obstructive pulmonary disease (COPD). Mutations in the protease inhibitor (PI) gene, located on chromosome 14, are associated with this genetic disorder. The Z protein is due to a single amino acid substitution of 342 glutamine lysine. Although cigarette smoking is the main environmental risk factor, only about 15% of smokers develop clinically significant disease suggesting other influences on disease expression. The study included hospital based age and sex matched 100 cases of COPD and 100 controls without COPD recruited from Christian Medical Centre, Jorhat, Assam. These cases were recruited from February 2009 to December 2009. Subjects were included in the COPD group on the basis of lung function test. DNA extraction was done by DNA extraction kit and amplification for AAT gene was done by site directed mutagenesis polymerase chain reaction (PCR) method as described by Tazellar et al. (1992). We found that smoking was the prior cause of COPD. A1AT deficiency is not prevalent in our population subset but certain other genes could be the attributable factor for COPD.Key words: Alpha 1-antitrypsin, chronic obstructive pulmonary disorder (COPD)

Chemotaxis When Bacteria Remember: Drift versus Diffusion

{\sl Escherichia coli} ({\sl E. coli}) bacteria govern their trajectories by switching between running and tumbling modes as a function of the nutrient concentration they experienced in the past. At short time one observes a drift of the bacterial population, while at long time one observes accumulation in high-nutrient regions. Recent work has viewed chemotaxis as a compromise between drift toward favorable regions and accumulation in favorable regions. A number of earlier studies assume that a bacterium resets its memory at tumbles -- a fact not borne out by experiment -- and make use of approximate coarse-grained descriptions. Here, we revisit the problem of chemotaxis without resorting to any memory resets. We find that when bacteria respond to the environment in a non-adaptive manner, chemotaxis is generally dominated by diffusion, whereas when bacteria respond in an adaptive manner, chemotaxis is dominated by a bias in the motion. In the adaptive case, favorable drift occurs together with favorable accumulation. We derive our results from detailed simulations and a variety of analytical arguments. In particular, we introduce a new coarse-grained description of chemotaxis as biased diffusion, and we discuss the way it departs from older coarse-grained descriptions.Comment: Revised version, journal reference adde

Solutions of Several Coupled Discrete Models in terms of Lame Polynomials of Order One and Two

Coupled discrete models abound in several areas of physics. Here we provide an extensive set of exact quasiperiodic solutions of a number of coupled discrete models in terms of Lame polynomials of order one and two. Some of the models discussed are (i) coupled Salerno model, (ii) coupled Ablowitz-Ladik model, (iii) coupled saturated discrete nonlinear Schrodinger equation, (iv) coupled phi4 model, and (v) coupled phi6 model. Furthermore, we show that most of these coupled models in fact also possess an even broader class of exact solutions.Comment: 31 pages, to appear in Pramana (Journal of Physics) 201

Exploring the Free Energy Landscape: From Dynamics to Networks and Back

The knowledge of the Free Energy Landscape topology is the essential key to understand many biochemical processes. The determination of the conformers of a protein and their basins of attraction takes a central role for studying molecular isomerization reactions. In this work, we present a novel framework to unveil the features of a Free Energy Landscape answering questions such as how many meta-stable conformers are, how the hierarchical relationship among them is, or what the structure and kinetics of the transition paths are. Exploring the landscape by molecular dynamics simulations, the microscopic data of the trajectory are encoded into a Conformational Markov Network. The structure of this graph reveals the regions of the conformational space corresponding to the basins of attraction. In addition, handling the Conformational Markov Network, relevant kinetic magnitudes as dwell times or rate constants, and the hierarchical relationship among basins, complete the global picture of the landscape. We show the power of the analysis studying a toy model of a funnel-like potential and computing efficiently the conformers of a short peptide, the dialanine, paving the way to a systematic study of the Free Energy Landscape in large peptides.Comment: PLoS Computational Biology (in press

Evaluation of the impact of high-resolution winds on the coastal waves

This study discusses the impact of high-resolution winds on the coastal waves and analyses the effectiveness of the high-resolution winds in recreating the fine-scale features along the coastal regions during the pre-monsoon season (March–May). The influence of the diurnal variation of winds on waves is studied for the Tamil Nadu coastal region using wind fields from weather research and forecast (WRF) (3 km) and European Centre for Medium-Range Weather Forecasts (ECMWF) (27.5 km). The improvement in the coastal forecast is then quantified with wave rider buoy observations. The high-resolution wind fields simulated fine-scale features like land–sea breeze events and showed good agreement with observation results. The error in the wave height and period is reduced by 8% and 46%, respectively, with the use of high-resolution forcing winds WRF over ECMWF, although the overestimation of wave energy on high frequencies due to overestimated WRF winds remains as a challenge in forecasting. The analysis also shows the importance of accurate wave forecast during a short-duration sudden wind (~12 m/s) occurrence in southern Tamil Nadu near Rameswaram during the pre-monsoon period. Low pressure forms over Tamil Nadu due to the land surface heating, resulting in a sudden increase of winds. High winds and steep waves which cause damage to the property of the coastal community near Rameswaram also were well simulated in the high-resolution forecast system with WRF winds