Direct Numerical Simulation of supercritical CO2 mixing and combustion

The supercritical CO2 power cycle (sCO2 ) is a relatively new technology, which promises to reduce CO2 emissions with potentially higher efficiencies. However due to challenging conditions posed by supercritical pressures, the mixing and ignition phenomena in sCO2 combustion is relatively less understood and studied. The primary objective of the current study is to investigate these fundamental processes using homogeneous ignition calculations (HMI) and direct numerical simulations (DNS). Broadly, the study is divided into two major parts. In the first part supercritical mixing in sCO2 relevant conditions is investigated. To achieve this, DNS of temporally developing, three dimensional, CH4 /CO2, CH4 /O2 and CO2 /O2 mixing layers, are conducted at a supercritical pressure of 300 atm. To effectively model the supercritical regime, the employed formulation includes the compressible form of the governing equations, the cubic Peng-Robinson equation of state and a generalized formulation for heat and mass flux vectors derived from non-equilibrium thermodynamics and fluctuation theory. A linear inviscid stability analysis is also performed for each case, to determine its most unstable wavelength. Flow visualizations reveal the presence of high density gradient magnitude regions for all three mixing layers, with conditional averages indicating increased presence of heavier fluid species within these regions. No significant departures are observed from perfect gas behavior, with compressibility factors very close to unity for all three mixing cases. Applicability of presumed probability density function methods (PDF) is examined for the three supercritical mixing layers. An a priori analysis is also conducted to investigate various simplifying assumptions employed in modeling various subgrid scale (SGS) flux models. Two additional terms are identified in the large eddy simulations (LES) equations, the gradient of SGS contribution of pressure in the momentum equation and the gradient of SGS contribution of heat flux in energy equation, whose magnitudes are similar and comparable with their respective resolved terms. The performance of the scale similarity model to represent these additional terms is investigated. The performance of Smagorinsky, gradient and scale similarity models is also investigated to model the conventional SGS fluxes. In the second part, the ignition process in sCO2 combustion is investigated using homogeneous ignition calculations (HMI) and two-dimensional direct numerical simulations (DNS). For selection of a suitable chemical mechanism, HMI calculations are first employed, to investigate the performance of existing skeletal mechanisms against shock- tube experimental data. The chemical characteristics of ignition are further studied using path-flux and sensitivity analysis, with CH3O2 chemistry exhibiting the largest effect on accelerating the ignition process. Different chemical pathways of fuel breakdown are also discussed to aid in interpretation of subsequent DNS case. In the DNS case, autoignition of a two dimensional mixing layer perturbed with pseudo-turbulence is simulated. The ignition is found to be delayed compared to the HMI case, with the ignition kernels forming in a spotty manner. The two phenomena are primarily attributed to variation of scalar dissipation within the mixing layer. The ignition kernels expand and evolve into a tribrachial edge flame propagating along the stoichiometric isosurface. Further investigation on the structure of edge flame revealed an asymmetrical structure, with CH4 molecules being entirely consumed in the triple point region of the flame along the stoichiometric isosurface, and more stable fuels like CO burning in the non-premixed branch of the edge flame. The edge flame propagation speeds are also calculated, with variations found to be correlated with scalar dissipation and upstream progress variable of the reacting mixture

Express TV: Competing In a Cluttered World of Media for Consumer Preferences and Viewership Patterns

Express News TV Channel found some reports that their TV channel viewership was declining. In Pakistan, however, the viewership data is managed, still the system is not properly managed and has many loopholes. This can be imagined through the information that one of the most populated area of Karachi, Gulshan Iqbal, TV viewing patterns are evaluated through less than ten people meters. Express news therefore decided to conduct a full survey that included the viewership patterns, the most preferred TV shows, and hosts, morning shows, and anchors. The study revealed interesting facts about the standing of Express News programs and TV viewers’ preferences of the same

Patients\u27 satisfaction and opinions of their experiences during admission in a tertiary care hospital in Pakistan - a cross sectional study

Background: It is often felt that developing countries need to improve their quality of healthcare provision. This study hopes to generate data that can help managers and doctors to improve the standard of care they provide in line with the wishes of the patients.Methods: It was a cross sectional study carried out at a major tertiary care hospital of Karachi. Patients between the ages of 18 and 80 years admitted to the hospital for at least one day were included. Patients in the maternity, psychiatry and chemotherapy wards and those in the ICU/CCU were excluded. A pretested, peer reviewed translation of a validated patient satisfaction scale developed by the Picker Institute of Europe was administered.Results: A total of 173 patients (response rate: 78.6 %) filled the questionnaire. Patient satisfaction was at levels comparable to European surveys for most aspects of hospital care. However, nearly half the patients (48%) felt they had to wait too long to get a bed in the hospital after presenting to the ER. 68.6% of the patients said that they were never asked for views on the quality of care provided. 20% of the patients did not find anyone in the staff to talk to about their worries and fears while 27.6% felt that they were given emotional support to only some extent. Up to one third of the patients said they were not provided enough information regarding their operative procedures beforehand.CONCLUSION: Although several components of patient care equal the quality levels of the west, many sections require considerable improvement in order to improve health care provision. The healthcare team needs to get more involved with the patients, providing them greater support and keeping them informed and involved with their medical treatment. Efforts should be made to get regular feedback from the patients

Patients' satisfaction and opinions of their experiences during admission in a tertiary care hospital in Pakistan – a cross sectional study

<p>Abstract</p> <p>Background</p> <p>It is often felt that developing countries need to improve their quality of healthcare provision. This study hopes to generate data that can help managers and doctors to improve the standard of care they provide in line with the wishes of the patients.</p> <p>Methods</p> <p>It was a cross sectional study carried out at a major tertiary care hospital of Karachi. Patients between the ages of 18 and 80 years admitted to the hospital for at least one day were included. Patients in the maternity, psychiatry and chemotherapy wards and those in the ICU/CCU were excluded. A pretested, peer reviewed translation of a validated patient satisfaction scale developed by the Picker Institute of Europe was administered.</p> <p>Results</p> <p>A total of 173 patients (response rate: 78.6 %) filled the questionnaire. Patient satisfaction was at levels comparable to European surveys for most aspects of hospital care. However, nearly half the patients (48%) felt they had to wait too long to get a bed in the hospital after presenting to the ER. 68.6% of the patients said that they were never asked for views on the quality of care provided. 20% of the patients did not find anyone in the staff to talk to about their worries and fears while 27.6% felt that they were given emotional support to only some extent. Up to one third of the patients said they were not provided enough information regarding their operative procedures beforehand.</p> <p>Conclusion</p> <p>Although several components of patient care equal the quality levels of the west, many sections require considerable improvement in order to improve health care provision. The healthcare team needs to get more involved with the patients, providing them greater support and keeping them informed and involved with their medical treatment. Efforts should be made to get regular feedback from the patients.</p

Direct Numerical Simulation of supercritical CO2 mixing and combustion

The supercritical CO2 power cycle (sCO2 ) is a relatively new technology, which promises to reduce CO2 emissions with potentially higher efficiencies. However due to challenging conditions posed by supercritical pressures, the mixing and ignition phenomena in sCO2 combustion is relatively less understood and studied. The primary objective of the current study is to investigate these fundamental processes using homogeneous ignition calculations (HMI) and direct numerical simulations (DNS). Broadly, the study is divided into two major parts. In the first part supercritical mixing in sCO2 relevant conditions is investigated. To achieve this, DNS of temporally developing, three dimensional, CH4 /CO2, CH4 /O2 and CO2 /O2 mixing layers, are conducted at a supercritical pressure of 300 atm. To effectively model the supercritical regime, the employed formulation includes the compressible form of the governing equations, the cubic Peng-Robinson equation of state and a generalized formulation for heat and mass flux vectors derived from non-equilibrium thermodynamics and fluctuation theory. A linear inviscid stability analysis is also performed for each case, to determine its most unstable wavelength. Flow visualizations reveal the presence of high density gradient magnitude regions for all three mixing layers, with conditional averages indicating increased presence of heavier fluid species within these regions. No significant departures are observed from perfect gas behavior, with compressibility factors very close to unity for all three mixing cases. Applicability of presumed probability density function methods (PDF) is examined for the three supercritical mixing layers. An a priori analysis is also conducted to investigate various simplifying assumptions employed in modeling various subgrid scale (SGS) flux models. Two additional terms are identified in the large eddy simulations (LES) equations, the gradient of SGS contribution of pressure in the momentum equation and the gradient of SGS contribution of heat flux in energy equation, whose magnitudes are similar and comparable with their respective resolved terms. The performance of the scale similarity model to represent these additional terms is investigated. The performance of Smagorinsky, gradient and scale similarity models is also investigated to model the conventional SGS fluxes. In the second part, the ignition process in sCO2 combustion is investigated using homogeneous ignition calculations (HMI) and two-dimensional direct numerical simulations (DNS). For selection of a suitable chemical mechanism, HMI calculations are first employed, to investigate the performance of existing skeletal mechanisms against shock- tube experimental data. The chemical characteristics of ignition are further studied using path-flux and sensitivity analysis, with CH3O2 chemistry exhibiting the largest effect on accelerating the ignition process. Different chemical pathways of fuel breakdown are also discussed to aid in interpretation of subsequent DNS case. In the DNS case, autoignition of a two dimensional mixing layer perturbed with pseudo-turbulence is simulated. The ignition is found to be delayed compared to the HMI case, with the ignition kernels forming in a spotty manner. The two phenomena are primarily attributed to variation of scalar dissipation within the mixing layer. The ignition kernels expand and evolve into a tribrachial edge flame propagating along the stoichiometric isosurface. Further investigation on the structure of edge flame revealed an asymmetrical structure, with CH4 molecules being entirely consumed in the triple point region of the flame along the stoichiometric isosurface, and more stable fuels like CO burning in the non-premixed branch of the edge flame. The edge flame propagation speeds are also calculated, with variations found to be correlated with scalar dissipation and upstream progress variable of the reacting mixture

Sensitivity and specificity of bedside troponin I kit (qualitative) test as compared with the standardized quantitative lab test for troponin I

Objective: Our aim was to find out the sensitivity and specificity of (qualitative) troponin I kit against the quantitative lab kit for Troponin I. Material And Method: Admitted patients of ACS/NSTEMI at Karachi Institute of Heart Diseases of both gender, were administered a standardized questionnaire. Quantitative analysis of Trop I was carried out by the hospital laboratory. At the same time sample was used for qualitative analysis of Troponin I by using Troponin I test kit. Results: We recruited 50 patients in which 37 (74%) were male. Hypertensive 32 (64%), dyslipidemia in 13 (26%), family history in 15 (30%), DM in 16 (32%) smoking was prevalent in 11 (22%), previous MI in 10 (20%). The kit showed 97% sensitivity and 100% specificity as compared to the quantitative test with a cutoff of 0.30 ng/dl, i.e.; quantitative test showed 32 positive and 18 negative cases, whereas qualitative test shows 31 positive and 19 negative. The difference in test results was on a value of 0.40 ng/dl , as qualitative test showed it as negative result. Conclusion: Study showed that qualitative kit is highly sensitive and specific at higher values of Troponin I, i.e., ≥ 0.5 ng/dl. The qualitative test could be very beneficial in cost and time saving for the non-conclusive patients, like NSTEMI and ACS in emergency department and patients coming to outreach chest pain centers where laboratory services are not adequate, and whose Trop I values are not very close to the minimum cut off values. Keywords: Troponin I, specificity, M

Optimizing Pretrained Convolutional Neural Networks for Tomato Leaf Disease Detection

Vegetable and fruit plants facilitate around 7.5 billion people around the globe, playing a crucial role in sustaining life on the planet. The rapid increase in the use of chemicals such as fungicides and bactericides to curtail plant diseases is causing negative effects on the agro-ecosystem. The high scale prevalence of diseases in crops affects the production quantity and quality. Solving the problem of early identification/diagnosis of diseases by exploiting a quick and consistent reliable method will benefit the farmers. In this context, our research work focuses on classification and identification of tomato leaf diseases using convolutional neural network (CNN) techniques. We consider four CNN architectures, namely, VGG-16, VGG-19, ResNet, and Inception V3, and use feature extraction and parameter-tuning to identify and classify tomato leaf diseases. We test the underlying models on two datasets, a laboratory-based dataset and self-collected data from the field. We observe that all architectures perform better on the laboratory-based dataset than on field-based data, with performance on various metrics showing variance in the range 10%–15%. Inception V3 is identified as the best performing algorithm on both datasets.</jats:p

Optimizing Pretrained Convolutional Neural Networks for Tomato Leaf Disease Detection

Vegetable and fruit plants facilitate around 7.5 billion people around the globe, playing a crucial role in sustaining life on the planet. The rapid increase in the use of chemicals such as fungicides and bactericides to curtail plant diseases is causing negative effects on the agro-ecosystem. The high scale prevalence of diseases in crops affects the production quantity and quality. Solving the problem of early identification/diagnosis of diseases by exploiting a quick and consistent reliable method will benefit the farmers. In this context, our research work focuses on classification and identification of tomato leaf diseases using convolutional neural network (CNN) techniques. We consider four CNN architectures, namely, VGG-16, VGG-19, ResNet, and Inception V3, and use feature extraction and parameter-tuning to identify and classify tomato leaf diseases. We test the underlying models on two datasets, a laboratory-based dataset and self-collected data from the field. We observe that all architectures perform better on the laboratory-based dataset than on field-based data, with performance on various metrics showing variance in the range 10%–15%. Inception V3 is identified as the best performing algorithm on both datasets