An Experimental Study of Synthetic Jet Actuators with Application in Airfoil LCO Control

An experimental study on the development and implementation of Synthetic Jet Actuators (SJAs) is conducted for eliminating aeroelastic phenomenon such as Limit Cycle Oscillations (LCO). One of the biggest challenges involved in the design of UAVs operating in unsteady atmosphere conditions is the susceptibility of the airframe to aeroelastic instabilities, such as flutter or LCO. Suppression of such instabilities can be achieved through the implementation of Active Flow Control (AFC) techniques, however to this day, a limited amount of experimental studies exist. Thus, the focus of this work is to develop a new AFC method consisting of an actuator that is directly instrumented in the internal volume of the airfoil. Due to the complex geometry of airfoil/actuator integration, advanced manufacturing technique has been employed for rapid manufacturing of these complex parts. In addition, a newly designed experimental test facility is fabricated to study the effect of the developed actuator on aerodynamic performance. Parametric analysis are conducted to investigate the effect of actuator along the airfoil surface, Reynolds number, and angle of attack. Results of this study demonstrated the actuator effectiveness on overall aerodynamic performance and show consistent trends with high-order Computational Fluid Dynamics (CFD)

Why Are Outcomes Different for Registry Patients Enrolled Prospectively and Retrospectively? Insights from the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF).

Background: Retrospective and prospective observational studies are designed to reflect real-world evidence on clinical practice, but can yield conflicting results. The GARFIELD-AF Registry includes both methods of enrolment and allows analysis of differences in patient characteristics and outcomes that may result. Methods and Results: Patients with atrial fibrillation (AF) and ≥1 risk factor for stroke at diagnosis of AF were recruited either retrospectively (n = 5069) or prospectively (n = 5501) from 19 countries and then followed prospectively. The retrospectively enrolled cohort comprised patients with established AF (for a least 6, and up to 24 months before enrolment), who were identified retrospectively (and baseline and partial follow-up data were collected from the emedical records) and then followed prospectively between 0-18 months (such that the total time of follow-up was 24 months; data collection Dec-2009 and Oct-2010). In the prospectively enrolled cohort, patients with newly diagnosed AF (≤6 weeks after diagnosis) were recruited between Mar-2010 and Oct-2011 and were followed for 24 months after enrolment. Differences between the cohorts were observed in clinical characteristics, including type of AF, stroke prevention strategies, and event rates. More patients in the retrospectively identified cohort received vitamin K antagonists (62.1% vs. 53.2%) and fewer received non-vitamin K oral anticoagulants (1.8% vs . 4.2%). All-cause mortality rates per 100 person-years during the prospective follow-up (starting the first study visit up to 1 year) were significantly lower in the retrospective than prospectively identified cohort (3.04 [95% CI 2.51 to 3.67] vs . 4.05 [95% CI 3.53 to 4.63]; p = 0.016). Conclusions: Interpretations of data from registries that aim to evaluate the characteristics and outcomes of patients with AF must take account of differences in registry design and the impact of recall bias and survivorship bias that is incurred with retrospective enrolment. Clinical Trial Registration: - URL: http://www.clinicaltrials.gov . Unique identifier for GARFIELD-AF (NCT01090362)

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Floating Drug Delivery System

Floating drug delivery system (FDDS) helps to improve the buoyancy property of the drug over the gastric fluids and hence maintain the longer duration of action. It is helpful in minimizing the dosing frequency. The density of dosage form must be less than the density of gastric contents (1.004 gm/ml) in FDDS. It may effervescent or non-effervescent system. The drugs having narrow absorption window in GIT is good candidate for the floating drug delivery system. The main objective of writing this review article is to compile the recent literature with special focus on classification, method of preparation, mechanism of action advantages and disadvantages.&nbsp; Keywords: Floating drug delivery system, Sustained release, controlled release, Floating tablet, Evaluation, Application, Gastro-retentive drug delivery system

An Experimental Study of Synthetic Jet Actuators with Application in Airfoil Limit Cycle Oscillations Control

Micro Air Vehicles (MAVs) operating in tight urban environments often encounter gust-induced limit-cycleoscillations. Based on our previous simulation studies on controller designs, this paper focuses on experimentalstudies to utilizing synthetic jet actuators (SJAs) that would be used to suppress LCO in small MAVs withuncertain actuator dynamics. The proposed robust nonlinear flight control technology employs an array of SJAsembedded in a wing design in order to completely eliminate moving parts. The benchmark case studies oncontrolling the longitudinal dynamics of a lifting surface using embedded synthetic jet actuators (SJAs) enteringlimit-cycle oscillations (LCOs) due to impinging upstream vertical flow disturbances including deterministicgust and stochastic turbulence. In this experimental study a symmetric-Glauert (SG) airfoil with embeddedsynthetic jet actuators (SJAs) is developed and parametric analysis are conducted to investigate the effect ofactuator location along the airfoil surface, Reynolds number, and angle of attack. Results of this studydemonstrated the actuator effectiveness on overall aerodynamic performance and show consistent trend withhigher-order computational fluid dynamics (CFD)

Next generation broadband network

In this report, a set of two QoS control schemes - a packet scheduling scheme and an adaptive admission control scheme - are proposed to achieve end-to-end QoS for interactive real-time applications with good network resource utilization.RGM 1/9

Utilization of additives in biodiesel blends for improving the diesel engine performance and minimizing emissions through a modified Taguchi approach

Biodiesel from Jatropha oil is produced through catalyzed homogeneous transesterification. Hydrogen peroxide (H2O2) is considered as additive. Blends of Jatropha considered in the present study are 60% diesel, (40-A)% biodiesel and A% additive, varying A from 0 to 10. Identifying optimal input variables (such as additive volume percentage, injection pressure, and load) is important for improving the engine performance and reducing emissions. Air-fuel ratio; brake specific fuel consumption (BSFC); and brake thermal efficiency (BTE) are the engine performance characteristics. Carbon monoxide (CO); carbon dioxide (CO2); exhaust gas temperature (EGT); nitrogen oxide (NOx); and smoke opacity are the emission characteristics. 27 experiments need to be performed for the assigned 3 levels and 3 input variables. The Taguchi's L9 orthogonal array (OA) is chosen to perform only 9 experiments to obtain the optimal solution. The expected range of performance characteristics and emissions was obtained following a modified Taguchi approach. Empirical relationships are developed and verified through engine performance and emission characteristics

Development and QOS of interactive network applications

In this project, a set of two QoS control scheme and an adaptive admission control scheme are proposed to achieve end-to-end QoS for interactive real-time applications with good network resource utilization.RG 17/9

Essence of Thermal Analysis to Assess Biodiesel Combustion Performance

The combustion phenomena are always complex in nature due to the involvement of complex series and parallel reactions. There are various methods that are involved in analyzing combustion phenomena. Viscosity is the first and foremost factor that acts as the DNA of fuel. By evaluating the viscosity, it is possible initially to understand the combustion phenomena. Thermophysical and transport properties are helpful during the intensification of the combustion process. Combustion experiments are economically infeasible and time-consuming processes. Combustion simulations demand excellent computational facilities with detailed knowledge of chemical kinetics. So far, the majority of researchers have focused on analyzing coal combustion phenomena, whereas less work has been carried out on liquid fuels, especially biodiesel combustion analysis. Traditional engine testing provides only performance parameters, and it fails to have oversight of the thermodynamic aspects. The application of thermal analysis methods in combustion research is useful in the design, modeling, and operation of the systems. Such investigations are carried out extensively in the combustor, engine, and process industries. The use of differential scanning calorimetry (DSC) and thermogravimetry (TG) to assess the properties of biofuels has been attracting researchers in recent years. The main objective of this paper is to discuss the application of TGA and DSC to analyze heat flow, enthalpy, thermal stability, and combustion indexes. Moreover, this paper reviews some of the other aspects of the kinetics of combustion, transport properties’ evaluation, and combustion simulations for biodiesels and their blends. TG curves indicate two phases of decomposition for diesel and three phases for biofuel. The B-20 blend’s (20% biodiesel and 80% diesel) performance was found to be similar to that of diesel with the combustion index and intensity of combustion nearly comparable with diesel. It is thermally more stable with a high offset temperature, confirming a longer combustion duration. A case study reported in this work showed diesel and B20 JOME degradation start from 40 °C, whereas jatropha oil methyl ester (JOME) degradation starts from 140 °C. JOME presents more decomposition steps with high decomposition temperatures, indicative of more stable compound formation due to the oxidation process. The peak temperature of combustion for diesel, JOME, and B20 JOME are 250.4 °C, 292.1 °C, and 266.5 °C, respectively. The ignition index for the B-20 blend is 73.73% more than that of diesel. The combustion index for the B20 blend is 37.81% higher than diesel. The B20 blend exhibits high enthalpy, better thermal stability, and a reduced peak temperature of combustion with an improved combustion index and intensity of combustion nearly comparable to diesel

Machine Learning Prediction and Optimization of Performance and Emissions Characteristics of IC Engine

In this work, a study was conducted to investigate the effects of different biodiesel blends with hydrogen peroxide additive on the performance and emissions of an internal combustion engine under various operating parameters. A CI engine was operated with diesel, four dissimilar biodiesels, and H2O2 at various proportions. The biodiesel blends used were Jatropha (D60JB30A10, D60JB34A6, D60JB38A2, D60JB40), Honge (D60HB30A10, D60HB34A6, D60HB38A2, D60HB40), Simarouba (D60SB30A10, D60SB34A6, D60SB38A2, D60SB40), and Neem (D60NB30A10, D60NB34A6, D60NB38A2, D60NB40). The engine was tested at different injection operating pressures (200, 205, and 210 bar), a speed of 1500 rpm, and a CR of 17.5:1. From the experiments conducted, it was highlighted that, under specific conditions, i.e., with an injection pressure of 205 bar, 80% load, a compression ratio of 17.5, an injection timing set at 230 before top dead center, and an engine speed of 1500 rpm, the biodiesel blends D60JB30A10, D60HB30A10, D60SB30A10, and D60NB30A10 achieved the highest brake thermal efficiencies of 24%, 23.9675%, 23.935%, and 23.9025%, respectively. Notably, the blend D60JB30A10 stood out with the highest brake thermal efficiency of 24% among these tested blends. Similarly, when evaluating emissions under the same operational conditions, the D60JB30A10 blend exhibited the lowest emissions levels: CO (0.16% Vol), CO2 (7.8% Vol), HC (59 PPM), and Smoke (60 HSU), while NOx (720 PPM) emissions showed a relative increase with higher concentrations of the hydrogen-based additive. The D60HB30A10, D60SB30A10, and D60NB30A10 blends showed higher emissions in comparison. Additionally, the study suggests that machine learning techniques can be employed to predict engine performance and emission characteristics, thereby cutting down on time and costs associated with traditional engine trials. Specifically, machine learning methods, like XG Boost, random forest regressor, decision tree regressor, and linear regression, were utilized for prediction purposes. Among these techniques, the XG Boost model demonstrated highly accurate predictions, followed by the random forest regressor, decision tree regressor, and linear regression models. The accuracy of the predictions for XG Boost model was assessed through evaluation metrics such as R2-Score (0.999), Root Mean Squared Error (0.540), Mean Squared Error (0.248), and Mean Absolute Error (0.292), which allowed for a thorough analysis of the algorithm’s performance compared to actual values