Turbulence modeling for film cooling flows

An improved two equation turbulence model has been developed in this dissertation to better predict the complex film cooling flow field that is formed from the interaction of a coolant jet and a crossflow over a modeled turbine blade surface. Film cooling of turbine blades is commonly employed to effectively protect turbine blades from thermal failure and thereby to allow higher inlet temperatures in order to increase the efficiency of gas turbine engines. Film cooling involves the injection of rows of coolant jets from slots on the surface of a turbine blade which is then bent over by the crossflow gases to form a protective coolant film on the blade surface. The highly complex flow field arising from the impact of the coolant jet on the crossflow is the focus of the numerical investigation undertaken in this study. A systematic, step by step approach has been adopted in this work to analyze the flow physics of the film cooling problem and to get an accurate representation of the flow field through numerical simulations that employ Reynolds Averaged Navier Stokes (RANS) turbulence models. Towards this end, numerical predictions have been obtained for the flow problem at hand by employing available models in order to assess the present modeling capabilities. A wide range of turbulence models have been used and their deficiencies have been underscored in order to isolate avenues of model development. The exhaustive numerical investigation with existing models has then been followed by the development of an improved two equation model. The newly developed model has been validated for a wide range of flow problems and has thereafter been applied to the film cooling flow configuration under investigation in this study. Improvements in predictions obtained by the newly developed model have been highlighted and avenues of future work have been identified

A numerical investigation of explicit pressure-correction projection methods for incompressible flows

A numerical investigation is performed on an explicit pressure-correction projection method. The schemes are fully explicit in time in the framework of the finite difference method. They are tested on benchmark cases of a lid-driven cavity flow, flow past a cylinder and flow over a backward facing step. Comparisons of the numerical simulations have been made with benchmark experimental and DNS data. Based on the results obtained, several numerical issues are discussed; namely, the handling of the pressure term, time discretization and spatial discretization of convective and diffusive terms. The fully explicit projection method is also compared with the fully implicit SIMPLE algorithm. It is observed that the SIMPLE algorithm performs better (faster and produces more accurate results) for laminar flows while the projection method works better for unsteady turbulent flows. Although there have been much research performed using the higher-order pressure incremental projection method, this research work is novel because the schemes employed here are fully explicit, developed in the framework of a finite difference method, and applied to turbulent flows using k- model. The major difficulty and challenges of this research work is to identify the sources of instability for the higher-order pressure incremental projection method scheme

A comparative study of natural gas and biogas combustion in a swirling flow gas turbine combustor

In this study, non-premixed combustion of traditional fuel-natural gas, and an alternative fuel-biogas, is simulated in a swirling flow industrial gas turbine combustor geometry which includes the combustor liner and the outside casing in order to replicate the flow and combustion in a real gas turbine combustor. The 3D combustion simulations are validated and the results for combustion of both gases are analyzed to compare and evaluate the viability of biogas as an alternative fuel for use in industrial gas turbine combustors. The combustion performance is evaluated based on multiple combustion performance optimization parameters, namely, the combustion efficiency, pattern factor, and pollutant emissions (CO and NO). The effects of two design parameters: swirl number and fuel injector diameter on the combustion performance optimization parameters is examined. The results have been analyzed to identify the best case for each combustion performance optimization parameter and a suitable trade-off case for both gases is proposed. Additionally, the comparison of the combustion performances of both gases revealed that despite possessing much lower methane and hence lower heating value (LHV), a combination of swirl number and fuel injector diameter for biogas of a specific composition results in a combustion performance comparable to natural gas along with lower NO emission, although at the expense of higher CO emission. Therefore, biogas can potentially be utilized as an alternative fuel in industrial gas turbine combustors, and methods for reducing CO emission can be devise

The application of multiphase DEM for the prediction of fat, oil and grease (FOG) deposition in sewer pipe lines

Fat oil and grease (FOG) deposition into sewer pipes can block the pipes and restrict the wastewater flow causing backflows and sanitary sewer overflows (SSOs). Understanding the wastewater flow and transport of FOG particles is a key step for predicting the particles deposition and blockage formation. ANSYS FLUENT was used for simulating the flow of FOG particles and its deposition onto the sewer pipe. The multiphase Eularian-Lagrangian model with discrete Phase method (DPM) was utilized for developing the CFD model. The kinetic parameters and physical values are based on previous experimental work and literature. The CFD Eularian-DEM multiphase model has shown a good potential for simulating the wastewater flow and demonstrated the applicability of CFD to simulate and track the transport and deposition of FOG particles into the sewer pipe walls

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation