Comparison of three buoyancy extended versions of the k–ϵ–t′2 model in predicting turbulent plane plume

AbstractIn the present paper, turbulent plane plume in a quiescent ambience has been numerically studied using three different versions of the buoyancy extended k–ϵ–t′2 model. The performance of models is analysed by means of a detailed comparison between the predictions and the experimental observations reported in the literature. In addition, the predictions by the Reynolds stress and the heat flux transport (RSHFT) model reported in the literature are also included in the comparison to examine the effectiveness of k–ϵ–t′2 models relative to the higher order RSHFT model. The comparison shows that the mean flow quantities predicted by all the models agree well with the experimental observations. However, considerable differences are observed in the predicted turbulent quantities

A study of turbulent heat transfer in convergent-divergent shaped microchannel with ribs and cavities using CFD

This paper presents the effects of microchannel shape with ribs and cavities on turbulent heat transfer. Three-dimensional conjugate heat transfer using the SST k-ω turbulence model has been investigated for four different microchannels, namely, rectangular, rectangular with ribs and cavities, convergent-divergent (CD) and convergent-divergent with Ribs and Cavities (CD-RC). The flow field, pressure and temperature distributions and friction factor are analyzed, and thermal resistance and average Nusselt number are compared. The thermal performance of the CD-RC microchannel is found to be better than that of other microchannels considered in terms of an average Nusselt number increased from 16% to 40%. Heat transfer increases due to a strong fluid mixing and periodic interruption of boundary-layer. It is observed that with an increase in Reynolds number (Re), the thermal resitance drops rapidly. The thermal resistance of the CD-RC microchannel is decreased by 30% than that of the rectangular microchannel for Re ranging from 2500 to 7000. However, such design of microchannel loses its heat transfer effectiveness due to a high pumping power at high values of Re

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Use of k-ε-γ model to predict intermittency in turbulent boundary-layers

The intermittency profile in the turbulent flat-plate zero pressure-gradient boundary-layer and a thick axisymmetric boundary-layer has been computed using the Reynolds-averaged k-ε-γ model, where k denotes turbulent kinetic energy, ε its rate of dissipation, and γ intermittency. The Reynolds-averaged model is simpler compared to the conditional model used in the literature. The dissipation equation of the Reynolds-averaged model is modified to account for the effect of entrainment. It has been shown that the model correctly predicts the observed intermittency of the flows

Large Eddy simulation of passive noise reduction in subsonic jets

by Kamal Tewari , Vinod Narayanan and Anupam Dewa

Understanding Atmospheric Convection Using Large Eddy Simulation

Cloud formation is based on the fundamental principle of atmospheric convection, which involves the vertical transport of heat and moisture into an unstable environment. Convective transfer of moisture and heat in the form of turbulent fluxes over the Bay of Bengal (BoB) has not been explored much and is not resolved in global and regional climate models (GCMs and RCMs) due to the coarser grid resolutions used. Therefore, the present study is an attempt to understand the convection phenomenon over the BoB using a high-resolution cloud-resolving large eddy simulation. Due to the lack of observational data over the BoB, initial and boundary conditions were generated using reanalysis data. We found that the LES successfully captured the cloud formation and convection phenomenon. The turbulence in the convection was analyzed by using Reynolds averaging to obtain variances and covariances. The presence of turbulence over the region was observed. The cloud characteristics were verified by conditionally averaging the output fields. The present study paves a pathway to perform various simulations at different atmospheric conditions over the region in order to create a library of high-resolution simulations

Understanding Atmospheric Convection Using Large Eddy Simulation

Cloud formation is based on the fundamental principle of atmospheric convection, which involves the vertical transport of heat and moisture into an unstable environment. Convective transfer of moisture and heat in the form of turbulent fluxes over the Bay of Bengal (BoB) has not been explored much and is not resolved in global and regional climate models (GCMs and RCMs) due to the coarser grid resolutions used. Therefore, the present study is an attempt to understand the convection phenomenon over the BoB using a high-resolution cloud-resolving large eddy simulation. Due to the lack of observational data over the BoB, initial and boundary conditions were generated using reanalysis data. We found that the LES successfully captured the cloud formation and convection phenomenon. The turbulence in the convection was analyzed by using Reynolds averaging to obtain variances and covariances. The presence of turbulence over the region was observed. The cloud characteristics were verified by conditionally averaging the output fields. The present study paves a pathway to perform various simulations at different atmospheric conditions over the region in order to create a library of high-resolution simulations