Modeling and Numerical Simulations Of The Michigan Tech Convection Cloud Chamber

Understanding atmospheric clouds is essential for human progress, ranging from short-term effects such as when and how much it rains to long-term effects such as how much temperatures would rise due to global climate change. Clouds vary globally and seasonally; also they have length scales ranging from a few nanometers to a few kilometers and timescales from a few nanoseconds to a few weeks. Knowledge gaps in aerosol-cloud-turbulence interactions and a lack of sufficient resolution in observations pose a challenge in understanding cloud systems. Experimental facilities like the Michigan Tech Cloud Chamber can provide a suitable platform for studying aerosol-cloud interactions in the presence of turbulence without any feedback processes, within a steady state environment. In the current thesis, we modify an atmospheric model to simulate the Michigan Tech Cloud Chamber and validate against the turbulence measured from the experiments. The modified atmospheric model is used to gain insights into the cloud chamber processes, and to predict and interpret the experimental results. This model is used to validate theoretical results, such as the presence of a constant microphysics independent heat flux. Further, the model results helps us to identify the non-Gaussian nature of supersaturation during isobaric mixing processes. Finally, this model serves as the first-order approximation for insights into the physics governing the cloud-turbulence interactions for a larger cloud chamber

Assessment of Coronary Artery Disease using multiparametric cardiac Magnetic Resonance Imaging

OBJECTIVES : We wanted to assess the burden of coronary artery disease (CAD) in patients with suspected or known CAD who are referred for adenosine stress cardiac MRI. MATERIALS AND METHODS : Consecutive patients with suspected/diagnosed coronary artery disease, who are advised to undergo adenosine stress MRI, were enrolled in the study. Demographic detail and relevant past history was collected. Multiparametric cardiac MRI included adenosine-stress and rest perfusion scans, cine images and delayed enhancement scan for infarction imaging. Adenosine was infused at the rate of 140ug/kg/min. Before and during the infusion, the heart rate, systemic blood pressure, and oxygen saturation were monitored using an MRI-compatible system. Matched stress-rest perfusion defects in the absence of delayed enhancement were considered artifactual. ECHO and coronary angiography of a recruited patient was performed and reported by the cardiologist. RESULTS : 84 patients underwent adenosine stress cardiac MRI and 25 had subsequent invasive coronary angiogram (CAG). Out of 84, 50 showed evidence of CAD on MRI – 34 with only infarction, 6 with only ischemia and 10 with both ischemia and infarction. 23 of these patients underwent CAG all of which were positive for significant CAD. MRI accurately identified 22 out of 23 diseased LADs and 12 out of 13 RCAs. However, only 6 out of 10 diseased LCx were identified, 3 of which had co-existing RCA involvement as well. With adenosine, there were no major adverse effects. CONCLUSION : Adenosine stress cardiac MRI shows good positive correlation with CAG in patients with significant CAD. Diseased LADs and RCAs are best detected by MRI. However, LCx has poorer correlation but this can be explained by the significant overlap between LCx and RCA territories. Adenosine is a safe stressor

Scaling of Turbulence and Microphysics in a Convection–Cloud Chamber of Varying Height

The convection–cloud chamber enables measurement of aerosol and cloud microphysics, as well as their interactions, within a turbulent environment under steady-state conditions. Increasing the size of a convection–cloud chamber, while holding the imposed temperature difference constant, leads to increased Rayleigh, Reynolds and Nusselt numbers. Large–eddy simulation coupled with a bin microphysics model allows the influence of increased velocity, time, and spatial scales on cloud microphysical properties to be explored. Simulations of a convection–cloud chamber, with fixed aspect ratio and increasing heights of H = 1, 2, 4, and (for dry conditions only) 8 m are performed. The key findings are: Velocity fluctuations scale as H1/3, consistent with the Deardorff expression for convective velocity, and implying that the turbulence correlation time scales as H2/3. Temperature and other scalar fluctuations scale as H−3/7. Droplet size distributions from chambers of different sizes can be matched by adjusting the total aerosol injection rate as the horizontal cross-sectional area (i.e., as H2 for constant aspect ratio). Injection of aerosols at a point versus distributed throughout the volume makes no difference for polluted conditions, but can lead to cloud droplet size distribution broadening in clean conditions. Cloud droplet growth by collision and coalescence leads to a broader right tail of the distribution compared to condensation growth alone, and this tail increases in magnitude and extent monotonically as the increase of chamber height. These results also have implications for scaling within turbulent, cloudy mixed-layers in the atmosphere, such as fog layers

Effects of the Large-Scale Circulation on Temperature and Water Vapor Distributions in the Π Chamber

Microphysical processes are important for the development of clouds and thus Earth\u27s climate. For example, turbulent fluctuations in the water vapor concentration, r, and temperature, T, cause fluctuations in the saturation ratio, S. Because S is the driving factor in the condensational growth of droplets, fluctuations may broaden the cloud droplet size distribution due to individual droplets experiencing different growth rates. The small scale turbulent fluctuations in the atmosphere that are relevant to cloud droplets are difficult to quantify through field measurements. We investigate these processes in the laboratory, using Michigan Tech\u27s Π Chamber. The Π Chamber utilizes Rayleigh-Benard convection (RBC) to create the turbulent conditions inherent in clouds. In RBC it is common for a large scale circulation (LSC) to form. As a consequence of the LSC, the temperature field of the chamber is not spatially uniform. In this paper, we characterize the LSC in the Π chamber and show how it affects the shape of the distributions of r, T and S. The LSC was found to follow a single roll with an updraft and downdraft along opposing walls of the chamber. Near the updraft (downdraft), the distributions of T and r were positively (negatively) skewed. S consistently had a negatively skewed distribution, with the downdraft being the most negative

Fast and slow microphysics regimes in a minimalist model of cloudy Rayleigh-Bénard convection

A minimalist model of microphysical properties in cloudy Rayleigh-Bénard convection is developed based on mass and number balances for cloud droplets growing by vapor condensation. The model is relevant to a turbulent mixed-layer in which a steady forcing of supersaturation can be defined, e.g., a model of the cloudy boundary layer or a convection-cloud chamber. The model assumes steady injection of aerosol particles that are activated to form cloud droplets, and the removal of cloud droplets through sedimentation. Simplifying assumptions include the consideration of mean properties in steady state, neglect of coalescence growth, and no detailed representation of the droplet size distribution. Closed-form expressions for cloud droplet radius, number concentration, and liquid water content are derived. Limits of fast and slow microphysics, compared to the turbulent mixing time scale, are explored, and resulting expressions for the scaling of microphysical properties in fast and slow regimes are obtained. Scaling of microphysics with layer thickness is also explored, suggesting that liquid water content and cloud droplet number concentration increase, and mean droplet radius decreases with increasing layer thickness. Finally, the analytical model is shown to compare favorably to solutions of the fully-coupled set of governing ordinary differential equations that describe the system, and the predicted power law for liquid water mixing ratio versus droplet activation rate is observed to be consistent with measurements from the Pi convection-cloud chamber

Light scattering in a turbulent cloud: Simulations to explore cloud-chamber experiments

Radiative transfer through clouds can be impacted by variations in particle number size distribution, but also in particle spatial distribution. Due to turbulent mixing and inertial effects, spatial correlations often exist, even on scales reaching the cloud droplet separation distance. The resulting clusters and voids within the droplet field can lead to deviations from exponential extinction. Prior work has numerically investigated these departures from exponential attenuation in absorptive and scattering media; this work takes a step towards determining the feasibility of detecting departures from exponential behavior due to spatial correlation in turbulent clouds generated in a laboratory setting. Large Eddy Simulation (LES) is used to mimic turbulent mixing clouds generated in a laboratory convection cloud chamber. Light propagation through the resulting polydisperse and spatially correlated particle fields is explored via Monte Carlo ray tracing simulations. The key finding is that both mean radiative flux and standard deviation about the mean differ when correlations exist, suggesting that an experiment using a laboratory convection cloud chamber could be designed to investigate non-exponential behavior. Total forward flux is largely unchanged (due to scattering being highly forward-dominant for the size parameters considered), allowing it to be used for conditional sampling based on optical thickness. Direct and diffuse forward flux means are modified by approximately one standard deviation. Standard deviations of diffuse forward and backward fluxes are strongly enhanced, suggesting that fluctuations in the scattered light are a more sensitive metric to consider. The results also suggest the possibility that measurements of radiative transfer could be used to infer the strength and scales of correlations in a turbulent cloud, indicating entrainment and mixing effects

DETAILED VIEW ON REPURPOSED DRUGS, TRACKING OF VACCINES,AND BRIEF VIEW ON PROPHYLACTIC NANOMEDICINES AS AN ALTERNATIVE APPROACH AND PATIENT CARE FOR COVID-19

In December 2019, a rare case of pneumonia was reported in Wuhan, China. This was later analyzed and known to have similar characteristics as viral pneumonia caused by a novel coronavirus. Later, on 11 February 2020, the World Health Organization (WHO) officially named the disease as COVID19. The Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) ought to taint both the upper respiratory tract and the lower respiratory tract. This COVID-19 is spreading quickly with an immense rise in cases around the world. This infection's mechanism stays obscure, and the medications explicit for the infection were not grown at this point. Infection is highly contagious. Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2) is one of seven kinds of crown infection, including the one which causes severe maladies like Middle East respiratory disorder (MERS) and abrupt, intense respiratory syndrome(SARS). Since its revelation, the infection has spread and has caused anxiety and fear among people. Recent vaccines are tracked, and clinical trials can bring an immediate protocol on a medication approach. By including different therapeutic approaches, it is easier to combat the disease quickly. With very low mortality and high transmission rate, new approaches to vaccines and nanomedicines bring down the spread. Controlled patient care is also crucial. On 11 March, the World Health Organization (WHO) declared the disease as 'global pandemic’. COVID-19, therefore, poses a significant threat to global public health. This article reviews the epidemiology, pathogenesis, and diagnostic methods. The review also focuses on repurposed drugs, traced vaccines, and a quick view of prophylactic nanomedicines as an alternative for COVID 19. For this review, the complete database has been collected from various search engines such as PubMed, ScienceDirect, Scopus, Elsevier, etc., from the year 2001-2020 using the following keywords

Large-Eddy Simulations of a Convection Cloud Chamber: Sensitivity to Bin Microphysics and Advection

Bin microphysics schemes are useful tools for cloud simulations and are often considered to provide a benchmark for model intercomparison. However, they may experience issues with numerical diffusion, which are not well quantified, and the transport of hydrometeors depends on the choice of advection scheme, which can also change cloud simulation results. Here, an atmospheric large-eddy simulation model is adapted to simulate a statistically steady-state cloud in a convection cloud chamber under well-constrained conditions. Two bin microphysics schemes, a spectral bin method and the method of moments, as well as several advection methods for the transport of the microphysical variables are employed for model intercomparison. Results show that different combinations of microphysics and advection schemes can lead to considerable differences in simulated cloud properties, such as cloud droplet number concentration. We find that simulations using the advection scheme that suffers more from numerical diffusion tends to have a smaller droplet number concentration and liquid water content, while simulation with the microphysics scheme that suffers more from numerical diffusion tends to have a broader size distribution and thus larger mean droplet sizes. Sensitivities of simulations to bin resolution, spatial resolution, and temporal resolution are also tested. We find that refining the microphysical bin resolution leads to a broader cloud droplet size distribution due to the advection of hydrometeors. Our results provide insight for using different advection and microphysics schemes in cloud chamber simulations, which might also help understand the uncertainties of the schemes used in atmospheric cloud simulations

River Cleaning Robot

This Robot is a manually controlled river cleaning intelligent to achieve a sustainable environment. The work has done looking at the current situation of our national rivers which are dump with crore liters of sewage and loaded with pollutants, toxic materials, debris etc. This “River clean-up Robo” is places where there is waste debris in the water body which are to be removed. This machine consists of waterwheel controlled by a joystick which is having lift buttons that collect & remove the wastage, garbage & plastic wastages from water bodies. This also reduce the difficulties which we face when collection of debris take place. A machine will lift the waste surface debris from the water bodies, this will ultimately result in reduction of water pollution and lastly the aquatic animal's death to these problems will be reduced

Scaling of an atmospheric model to simulate turbulence and cloud microphysics in the Pi Chamber

The Pi Cloud Chamber offers a unique opportunity to study aerosol-cloud microphysics interactions in a steady-state, turbulent environment. In this work, an atmospheric large-eddy simulation (LES) model with spectral bin microphysics is scaled down to simulate these interactions, allowing comparison with experimental results. A simple scalar flux budget model is developed and used to explore the effect of sidewalls on the bulk mixing temperature, water vapor mixing ratio, and supersaturation. The scaled simulation and the simple scalar flux budget model produce comparable bulk mixing scalar values. The LES dynamics results are compared with particle image velocimetry measurements of turbulent kinetic energy, energy dissipation rates, and large-scale oscillation frequencies from the cloud chamber. These simulated results match quantitatively to experimental results. Finally, with the bin microphysics included the LES is able to simulate steady-state cloud conditions and broadening of the cloud droplet size distributions with decreasing droplet number concentration, as observed in the experiments. The results further suggest that collision-coalescence does not contribute significantly to this broadening. This opens a path for further detailed intercomparison of laboratory and simulation results for model validation and exploration of specific physical processes