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The reliance on Computational Fluid Dynamics (CFD) simulations has drastically increased over time to evaluate the aerodynamic performance of small-scale wind turbines. With the rapid variability in customer demand, industrial requirements, economic constraints, and time limitations associated with the design and development of small-scale wind turbines, the trade-off between computational resources and the simulation’s numerical accuracy may vary significantly. In the context of wind turbine design and analysis, high fidelity simulation under full geometric and numerical complexity is more accurate but pose significant demands from a computational standpoint. There is a need to understand and quantify performance deterioration of high fidelity simulations under reduced geometric or numerical approximation on a single small scale turbine model. In the present work, the flow past a small-scale Horizontal Axis Wind Turbine (HAWT) was simulated under various geometric and numerical configurations. The geometric complexity was varied based on stationary and rotating turbine conditions. In the stationary case, simple 2D airfoil, 2.5D blade, 3D blade sections are evaluated, while rotational effects are introduced for the configuration 3D blade, rotor only, and the full-scale wind turbine with and without the inclusion of a nacelle and tower. In terms of numerical complexity, the Single Reference Frame (SRF), Multiple Reference Frames (MRF), and the Sliding Meshing Interface (SMI) is analyzed over Tip Speed Ratios (TSR) of 3, 6, 10. The quantification of aerodynamic coefficients of the blade (Cl, Cd) and turbine (Cp, Ct) was conducted along with the discussion on wake patterns in comparison with experimental data.

The main objective of our study was to determine the prevalence of burnout and to identify various socio-demographic factors which are associated with resident burnout. As a secondary objective, we aimed to assess levels of empathy among the residents. A descriptive cross-sectional study was performed among residents working in Holy Family Hospital, Benazir Bhutto Hospital, and District Headquarter Hospital, all of which are situated in district Rawalpindi of Punjab, Pakistan. Data were collected from January 2019 to April 2019 using a convenient sampling technique. The participants were requested to complete Maslach Burnout Inventory to measure burnout and Jefferson Scale of Physician Empathy to measure empathy from January 2019 to April 2019. For data analysis IBM SPSS © version 25.0 was used. Descriptive statistics were used to summarize the quantitative variables. Chi-square test was used to determine the association between burnout and categorical variables. Then, those independent variables with p-value < 0.05 were subjected to binary logistic regression to identify predictors of burnout. A P-value of < 0.05 was used as the criterion for statistical significance and OR with 95% confidence interval was used to indicate the strength of association. Independent sample t-test was used to assess empathy among the groups. The prevalence of burnout in our sample was 78%. The average burnout score of the sample was 81±13.45. Weekly working hours (p-value < 0.05) and the type of specialty (p-value < 0.05) were significantly associated with resident burnout. Residents working more than 80 hours were more prone to develop burnout [AOR 2.700(1.42-5.120)]. Medical residents were found to be at a higher risk of developing burnout as compared to surgical residents [(AOR 2.097(1.16-3.78)]. Residents working less than 80 hours per week had more empathy scores as compared to residents working more than 80 hours and this result was statistically significant (p-value < 0.05). However, no significant difference in empathy was found for age, gender, marital status, and posts. Therefore, weekly working hours should be reduced to diminish burnout and increase empathy, thereby, promoting the quality of care being delivered to the patient. Moreover, efforts should be made to reduce burnout in medicine residents so that we may promote the doctor-patient relationship.

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