Two-phase flow boiling in small to micro-diameter tubes

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis is dedicated to the experimental and theoretical study of flow boiling in small to micro diameter tubes using R 134a. Flow pattern, heat transfer and pressure drop studies were conducted in stainless steel cold drawn tubes with internal diameter 2.88,1.1, and 0.52 mm using an existing facility that was designed with a long term research objective of improving the fundamental understanding of flow boiling in small metallic tubes. The facility was moved to the present location from London South Bank University and re-commissioned before carrying out the experiments. The test sections were heated by a direct passage of alternating current and wall temperatures were measured at 15 axial locations by miniature thermocouples that were directly spotwelded at the tube outer wall. A digital high-speed camera was used to simultaneously observe the flow patterns (during the heat transfer tests) directly at a borosilicate glass tube located immediately downstream of the heat transfer test section. The purpose of the flow visualization study was to support understanding of the heat transfer characteristics and development of flow regime-specific models. The heat transfer and pressure drop data of X. Huo (2005) in the 4.26 and 2.01 mm tubes and the flow visualization results of Chen (2006) for the tubes of diameter 4.26,2.88,2.01, and 1.1 mm were included with the new data in an extensive analysis of flow boiling heat transfer and pressure drop in five vertical tubes with internal diameters 4.26, 2.88,2.01, 1.1 and 0.52 mm. The wide range of tube diameter was chosen to investigate the influence of tube size and possibly identify the threshold where the effect of small or micro diameter effects become significant. In the experiments, parameters were varied in the ranges: mass flux 100 to 700 kg/m2s; heat flux 1.6 to 150 kW/m; pressure 6 to 14 bar; quality up to 0.9 and the inlet temperature was controlled at a subcooling of 1-5K. There was no clear significant difference between the characteristics and magnitude of the heat transfer coefficients in the 4.26 mm and 2.88 mm tubes but the coefficients in the 2.01 and 1.1 mm tube were higher. The heat transfer results suggested that a tube size of about 2 mm might be considered as a critical diameter to distinguish small and conventional tubes. Further differences have now been observed in the 0.52 mm tube. These differences, both in flow patterns and heat transfer, indicate a possible second change from small to micro behaviour at diameters less than 1 mm for R 134a. Also, the results showed axial variations in heat transfer characteristics marking the importance of surface conditions on heat transfer. This calls for a further detail investigation to understand the underlying physics in the initiation of boiling, effect of surface condition on nucleation, and structure of newly emerging flow patterns, particularly in very small tubes. Existing correlations were examined using the results of the five tubes and indicated that these correlations do not predict the present small diameter data to a satisfactory degree. Therefore, two new correlations that take into account both magnitude and characteristic effect of tube diameter have been proposed covering the 4.26 mm-1.1 mm and the smallest 0.52 mm tube, respectively. A detailed comparison was also made with the state-of-the-art flow regime-specific model of Thome et al. (2004) and verified that the mechanistic modelling approach has a promising capability of predicting two phase heat transfer in small diameter tubes, although it still requires further development. Some improvements have been proposed and tested against the current data. Using a similar approach, a new two phase pressure drop model has been proposed and compared with the current data with encouraging results.Funding was obtained from the School of Engineering and Design, Brunel Universit

Short Term Load Forecast In Jimma City By Using Artificial Neural Network

For optimal power system operation, electrical generation must follow electrical load demand. The generation, transmission, and distribution utilities require forecasting the electrical load so they can utilize their electrical infrastructure efficiently, securely, and economically. The short-term load forecast (STLF) represents the electric load forecast for a time interval of a few hours to a few days. This thesis is a study of short-term electric power forecasting in the jimma power system using artificial neural network model. The model is created in the form of a simulation program written with MATLAB tool. The model, a feed forward neural network, for radial basis neural network and recurrent current artificial neural network trained with error, was made to study the pre-historical load pattern of a typical jimma power system in a supervised training manner. After presenting the model with a reasonable number of training samples, the model could forecast correctly electric power supply in the jimma power system 24 hours in advance. An absolute mean error was obtained and compares three neural networks feed forward neural network 0.5180 to 6.3868, for radial basis neural network 0.0861 to 2.8703 and recurrent current 0.2811 to 13.8851 from this choose the least absolute mean error radial basis neural network 0.0861 to 2.8703. The trained neural network model was tested on one week, daily hourly load data of a typical jimma power station. This result demonstrates that ANN is a powerful tool for load forecasting. One week (winter Monday 22/9/07 – Sunday 28/9/07) , One week (Summer Monday 25/12/07 – Sunday 1/13/07) and One day (Holiday Wednesday 1/1/08) of electrical load. Load data was recorded for JIMMA CITY, so there are 15 days of data collected

Impact of demand-side management on the sizing of autonomous solar PV-based mini-grids

Solar PV-based autonomous mini-grids represent an economically affordable and robust electrification option for rural communities. However, the initial investment cost for renewable energy technologies such as solar PV remains high for rural communities. Implementation of demand-side management (DSM) could increase the cost-efficiency of mini-grids in rural areas. This requires demand-side knowledge, but little is still known of electricity demands in recently electrified areas and, in particular, of how DSM implementation could impact mini-grids. The few studies available focus either on systems or on appliance levels while this study aims to determine cost-efficiency impacts of DSM implementation at a category level. A shifting strategy is applied based on classification into high priority loads and low priority loads. Autonomous rural mini-grid components sizing for four different load categories and load flexibility are carried out using particle swarm optimization. The results show that different load category combinations result in large variations in terms of possible levelized energy cost reductions and, thus, in terms of the cost-optimal sizing of the mini-grid components. The DSM implementation on the household and productive use categories have the largest capacity of reducing the levelized energy cost, by 45.8% and 20.7%, respectively, compared to the no demand-side management case

What factors affect households’ decision to allocate credit for livestock production? Evidence from Ethiopia

Access to credit is often viewed as a key to transform semi-subsistence smallholders into market oriented producers. However only few studies have examined factors that affect farmers’ decision to allocate credit on farm activities in general and livestock production in particular. A trivariate probit model with double selection is employed to identify factors that affect farmers’ decision to allocate credit on livestock production using data collected from smallholder farmers in Ethiopia. After controlling for two sample selection bias – taking credit in the production season and decision to allocate credit on farm activities – land ownership and access to a livestock centered extension service are found to have a significant (p<0.001) effect on farmers decision to use credit for livestock production. The result showed farmers with large land holding, and access to a livestock centered extension services are more likely to utilize credit for livestock production. However since the effect of land ownership squared is negative the effect of land ownership for those who own a large plot of land lessens. The study highlights the fact that improving access to credit does not automatically translate into more productive households. Improving farmers’ access to credit should be followed by a focused extension services

What factors affect households’ decision to allocate credit for livestock production? Evidence from Ethiopia

Access to credit is often viewed as a key to transform semi-subsistence smallholders into market oriented producers. However only few studies have examined factors that affect farmers’ decision to allocate credit on farm activities in general and livestock production in particular. A trivariate probit model with double selection is employed to identify factors that affect farmers’ decision to allocate credit on livestock production using data collected from smallholder farmers in Ethiopia. After controlling for two sample selection bias – taking credit in the production season and decision to allocate credit on farm activities – land ownership and access to a livestock centered extension service are found to have a significant (p<0.001) effect on farmers decision to use credit for livestock production. The result showed farmers with large land holding, and access to a livestock centered extension services are more likely to utilize credit for livestock production. However since the effect of land ownership squared is negative the effect of land ownership for those who own a large plot of land lessens. The study highlights the fact that improving access to credit does not automatically translate into more productive households. Improving farmers’ access to credit should be followed by a focused extension services

Maternal Death Review at a Tertiary Hospital in Ethiopia

BACKGROUND፡ There is conflicting data on the rate and trends of maternal mortality in Ethiopia. There is no previous study done on the magnitude and trends of maternal death at Saint Paul's Hospital, an institution providing the largest labor and delivery services in Ethiopia. The objective of this study is to determine the magnitude, causes and contributing factors for maternal deaths in the institution.METHODS: We conducted a retrospective review of maternal deaths from January 2016 to December 2017. Data were analyzed using SPSS version 20.RESULTS: The maternal mortality ratio of the institution was 228.3 per 100,000 live births. Direct maternal death accounted for 90% (n=36) of the deceased. The leading causes of the direct maternal deaths were hypertensive disorders of pregnancy (n=13,32.5%), postpartum hemorrhage (n=10, 25%), sepsis (n=4, 10%), pulmonary thromboembolism (n=3, 7.5%) and amniotic fluid embolism (n=3, 7.5%).CONCLUSION: The maternal mortality ratio was lower than the ratios reported from other institutions in Ethiopia. Hypertensive disorders of pregnancy and malaria were the leading cause of direct and indirect causes of maternal deaths respectively. Embolism has become one of the top causes of maternal death in a rate like the developed nations. This might show the double burden of embolism and other causes of maternal mortality that developing countries might be facing

Application of Linear Programming to Analyze Profit of Flour Factory, in the Case of Sanate Flour Factory, at Robe Town

The purpose of this study was to analyze the total production and profit of Sanate flour factory located in Ethiopia, Oromia regional state, Bale zone, Robe town, by applying linear programming. A factory is situated within Robe town about 430 KM, from Addis Ababa (Capital of Ethiopia). Today linear programming was the most popular method of manipulating a large amount of data. Hence, Different studies bring out the necessity of using quantitative techniques for utilization in the factory. So, in this paper to analyze the production and profit of this factory, the study incorporates different steps; the first step is collecting data. A data collecting formats prepared and circulated among factory staff to executive managers, co-managers, sellers, machine operators, and technicians to determine the production, sales, and profit during five months of November 30, 2018- June 18, 2019. In the second step, a collected data is modeled to mathematical form, particularly modeled to linear program. In the third step the mathematical modeled data was solved (analyzed). Finally, depending on the empirical results (the solution of a modeled data) some problem facing the factory was indicated and the solution for the problem has been recommended

Synthesis, structural characterization, and computational studies of novel Co(II) and Zn(II) fluoroquinoline complexes for antibacterial and antioxidant activities

Research into heterocyclic ligands has increased in popularity due to their versatile applications in the biomedical field. Quinoline derivatives with their transition metal complexes are popular scaffolding molecules in the ongoing pursuit of newer and more effective bioactive molecules. Subsequently, this work reports on the synthesis and possible biological application of new Zn(II) and Co(II) complexes with a bidentate quinoline derivative ligand (H2L), [(H2L):(E)-2-(((6-fluoro-2-((2-hydroxyethyl)amino)quinolin-3-yl)methylene)amino)ethanol]. The ligand and its metal complexes were structurally characterized by spectroscopic methods (1H NMR, 13C NMR, Fourier transform infrared (FTIR), UV–vis, fluorescence, and mass spectroscopy), as well as by thermogravimetric and elemental analysis methods. The spectroscopic findings were further supported by density functional theory (DFT) and time-dependent (TD)-DFT calculations. The biological application was examined by investigating the inhibitory action of the complexes against bacterial strains using diffusion and agar dilution methods, and their profiles against two Gram-positive and Gram-negative bacterial strains were supported by molecular docking analysis. To rationalize the in vitro activity and establish the possible mechanism of action, the interactions and binding affinity of the ligand and complexes were investigated against three different bacterial enzymes (Escherichia coli DNA gyrase (PDB ID 6f86), E. coli dihydrofolate reductase B (PDB ID: 7r6g), and Staphylococcus aureus tyrosyl-tRNA synthetase (PDB ID: 1JIJ)) using AutoDock with the standard protocol. The MIC value of 0.20 μg/mL for zinc complex against E. coli and associated binding affinities −7.2 and −9.9 kcal/mol with DNA gyrase (PDB ID 6f86) and dihydrofolate reductase B (PDB ID: 7r6g), as well as the MIC value of 2.4 μg/mL for cobalt(II) complex against Staphylococcus aureus and the associated binding affinity of −10.5 kcal/mol with tyrosyl-tRNA synthetase (PDB ID: 1JIJ), revealed that the complexes’ inhibitory actions were strong and comparable with those of the standard drug in the experiments. In addition, the ability of the new quinoline-based complexes to scavenge 1,1-diphenyl-picrylhydrazyl radicals was investigated; the findings suggested that the complexes exhibit potent antioxidant activities, which may be of therapeutic significance.https://pubs.acs.org/journal/acsodfPhysicsSDG-09: Industry, innovation and infrastructur

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk outcome pairs, and new data on risk exposure levels and risk outcome associations. Methods: We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings: In 2017,34.1 million (95% uncertainty interval [UI] 33.3-35.0) deaths and 121 billion (144-1.28) DALYs were attributable to GBD risk factors. Globally, 61.0% (59.6-62.4) of deaths and 48.3% (46.3-50.2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10.4 million (9.39-11.5) deaths and 218 million (198-237) DALYs, followed by smoking (7.10 million [6.83-7.37] deaths and 182 million [173-193] DALYs), high fasting plasma glucose (6.53 million [5.23-8.23] deaths and 171 million [144-201] DALYs), high body-mass index (BMI; 4.72 million [2.99-6.70] deaths and 148 million [98.6-202] DALYs), and short gestation for birthweight (1.43 million [1.36-1.51] deaths and 139 million [131-147] DALYs). In total, risk-attributable DALYs declined by 4.9% (3.3-6.5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23.5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18.6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning