Large Scale GPU Based Simulations of Turbulent Bubbly Flow in a Square Duct

In this paper, we present the results of a numerical study of air-water turbulent bubbly flow in a periodic vertical square duct. The study is conducted using a novel numerical technique which leverages Volume of Fluid method for interface capturing and Sharp Surface Force method for accurate representation of the surface tension forces. A three-dimensional geometry construction method is employed during solution of interface equation which gives absolute conservation of mass and sharp interface between gas and liquid phases. The entire algorithm has been implemented on a data parallel mode on multiple graphics processing units (GPU) taking advantage of the large number of available cores. We have studied the dynamics of a swarm of spherical bubbles co-flowing with the upward turbulent flow and compared results with an unladen turbulent flow. The frictional Reynolds number of the unladen $Re_{\tau}$ is 360, which is sufficient to sustain a turbulent flow. We observe the turbulence-driven secondary flows in the mean flow, with complex instantaneous turbulent vortical structures. The interaction of these secondary flows with the upwards rising bubbles is very complex and leads to significant changes in the instantaneous and time-averaged flow field. We present the results of mean void fraction distribution, mean velocities, longitudinal and transverse turbulence intensities along the wall, corner bisector, and wall bisector. A peak in the void fraction distribution near the walls is observed representing the migration of bubbles to a preferred section of the duct. The effects of turbulence-driven secondary flows and instantaneous large eddies on preferential concentration of the bubbles are discussed. The dispersed bubbles are seen to break the long elongated turbulent structures commonly observed in the unladen turbulent flow

Development and application of Lattice Boltzmann and accurate volume of fluid numerical techniques on graphics processing units

The research work presented in this dissertation is concerned with development and applications of two computational techniques for high density ratio two-phase flow as encountered in air conditioning and refrigeration equipment. In this research work, we have examined mesoscopic and macroscopic approaches of CFD modeling for multiphase calculations. We have examined two variants of two-phase Lattice Boltzmann methods (LBM) namely the Shan and Chen (SC) and He and Chen (HC) and applied them to study various flows including droplet impingement on solid and liquid surfaces, head-on and oblique droplet collisions, droplet deformation in a square duct, and displacement flow in complex micro-channels. Both SC and HC methods were able to model liquid-liquid flow, whose density ratio is less than 2, but both methods were unstable for gas-liquid flow. To handle large density ratios, we have developed an alternate finite volume based computational technique where continuity, momentum, and interface tracking equations are solved. The volume of fluid (VOF) method is used for accurate representation and tracking of the interface, and a pressure balance method is used for pressure gradient and other discontinuous body forces in the Navier-Stokes equation. The interfacial force is modeled using the sharp surface force (SSF) method, and an additional Poisson equation is derived for the pressure due to surface tension forces. This method is stable for flow involving density and viscosity ratios up to 1000 and 100 respectively. We have applied the computational technique to various fundamental problems to verify its accuracy and robustness. The study of an air bubble rising in a viscous liquid is used to validate the computational technique with experimental results. The effects various dimensionless parameters (Bond number, Morton number, and confinement ratio) were investigated to understand the terminal velocity and shape of a bubble. Subsequently, bubble dynamics in variable viscosity fluid were investigated where the effects of power-law index, Bond number, and confinement ratio have been analyzed on the bubble deformation, rise velocity, and rise path. Finally, the dynamics of a bubble swarm in a square duct is simulated. The modification of turbulence due to the introduction of bubbles is studied. This problem required handling of multiple interfaces, wall-interface interaction, and interface-interface interaction, and tested the robustness of the VOF method. We validated the turbulence implementation by comparing the mean quantities with literature for unladen flow. A sizable number of spherical bubbles are introduced in the unladen flow, and their movement is tracked until a stationary state is reached. We compared flow structures, mean and instantaneous velocities, and various turbulence quantities between unladen and laden flows. We also investigated the mechanism for preferential distribution of bubbles in an upward turbulent bubbly flow. Both LBM procedures and VOF are implemented to run on graphics processing units (GPU) including multiple CPU-GPU platforms. The throughput of a single GPU LBM code is approximately 16 times higher that of a single CPU code. The scaling of a multi-GPU VOF code is nearly linear on the Blue Waters computing facility. The numerical method developed in this study is useful for the study of a variety of two-phase flow, including those with heat transfer and phase change. Such flow will be considered in the future

DEVELOPMENT AND VALIDATION OF STABILITY INDICATING HPTLC METHOD FOR DETERMINATION OF APIXABAN AS BULK DRUG

Objective: To develop and validate simple, sensitive stability indicating HPTLC (High performance thin layer chromatography) method for apixaban. Methods: The chromatographic separation was performed on aluminium plates precoated with silica gel 60 F254 using toluene: ethyl acetate: methanol (3:6:1 v/v/v) as mobile phase followed by densitometric scanning at 279 nm. Results: The chromatographic condition shows sharp peak of apixaban at Rf value of 0.38±0.03. Stress testing was carried out according to international conference on harmonization (ICH)Q1A (R2) guidelines and the method was validated as per ICH Q2(R1) guidelines. The calibration curve was found to be linear in the concentration range of 100-500 ng/band for apixaban. The limit of detection and quantification was found to be 11.66ng/bandand35.33ng/band, respectively. Conclusion: A new simple, sensitive, stability indicating high performance thin layer chromatographic (HPTLC) method has been developed and validated for the determination of apixaban

Isolated saccular aneurysm of the external jugular vein

Venous aneurysm of the head and neck is a rare clinical entity due to its asymptomatic nature and tendency of clinicians to report only surgical results. Whereas the primary aneurysm of internal jugular vein (IJV) in children is being increasingly recognized, secondary aneurysms of veins of the head and neck in adults, notably the external jugular vein (EJV) aneurysm remains only in anecdotal case reports. We present the case of a 63-year-old previously healthy woman who presented with a gradually progressive right lateral neck swelling over the last 18 months. Following the evaluation, she was diagnosed as a case of isolated spontaneous right-sided EJV aneurysm and was managed by surgical excision of the aneurysm

Crop Yield Prediction Using Gradient Boosting Neural Network Regression Model

The finest utility sector is agriculture, especially in emerging nations like India. Utilizing historical data in agriculture can change the context of decision-making and increase farmer productivity. Approximately a part of India's population is employed in agriculture, however this sector contributes just 14% of the country's GDP. This can be explained in part by farmers not making sufficient decisions on yield forecast. By examining numerous climatic elements, such as rainfall, and land characteristics, such as soil type and ground water salinity, as well as historical records of crops cultivated, the suggested machine learning technique tries to estimate the agricultural yield for a certain location. Finally, we anticipate that our proposed Machine Learning Gradient Boosting Neural Network Regression (Grow Net) model was predicting the accurate yield. Finally our system is expected to predict the yield based on dataset we have taken. We were compared our proposed algorithm with various Machine Learning algorithms such as Random Forest, Support Vector Machine, KNN, Multi-layer Perceptron Regressor, Gradient Boosting Regressor and results shows that proposed was given best RMSE ,MAE and R2 value

Current allergy educational needs in primary care. Results of the EAACI working group on primary care survey exploring the confidence to manage and the opportunity to refer patients with allergy

The aim of this survey was to explore the specific educational needs of a cohort of European GPs with regards to allergy training so that future educational initiatives may better support the delivery of allergy services in primary care. Method: This study took the form of a cross-sectional observational study in which a structured electronic questionnaire was distributed to primary care providers, in eight languages, across 8 European countries between September 2019 and November 2019. Data associated with demographic parameters, professional qualifications, type of employment, level of confidence regarding competencies for diagnosis and treatment of allergic diseases, referral of patients to allergist and preferred method of learning and assessment were collected. A 5-point Likert scale was used to assess level of confidence. Exploratory analysis was carried out. Results: A total of 687 responses were available for analysis, with 99.3% of responders working within Europe. 70.1% of participants were female; and 48.0% and 48.0% of participants respectively had received some undergraduate and/or postgraduate allergy education. Confidence in dealing with different aspect of allergy management differed between countries. The main reason for specialist referral was a perceived need for tertiary assessment (54.3%), and the main barrier for referral was the consideration that the patient's condition could be appropriately diagnosed and treated in a primary care facility. Up to 44.7% and 55.3% of participants reported that they preferred e-Learning over traditional learning. Conclusions: This study identified the specific areas of skills training and educational needs of GPs in managing allergic conditions in primary care, and provided insights into possible strategies for more feasible and cost-effective approaches

Improved trapping and handling of an arboreal, montane mammal: Red Panda Ailurus fulgens

It is sometimes essential to have an animal in the hand to study some of their ecological and biological characteristics. However, capturing a solitary, cryptic, elusive arboreal species such as the red panda in the wild is challenging. We developed and successfully tested a protocol for tracking, trapping, immobilization, and handling of red pandas in the wild in eastern Nepal. We established a red panda sighting rate of 0.89 panda/day with a capture success rate of 0.6. We trapped and collared one animal in 3.7 days. On average, we took nearly 136 (range 50–317) min to capture an animal after spotting it. Further processing was completed in 38.5 (21–70) min. Before capture, we found it difficult to recognize the sex of the red panda and to differentiate sub-adults above six months from adults. However, body weight, body length, tail length, shoulder height, and chest girth can be used for diagnosis, as these attributes are smaller in sub-adults. Our method is a welfare-friendly way of trapping and handling wild red pandas. We report new morphometric data that could serve as a guide for field identification

Canine Distemper Virus in Tigers (Panthera tigris) and Leopards (P. pardus) in Nepal

From wild dogs (Lycaon pictus) in the Serengeti to tigers (Panthera tigris altaica) in the Russian Far East, canine distemper virus (CDV) has been repeatedly identified as a threat to wild carnivores. Between 2020 and 2022, six Indian leopards (P. pardus fusca) presented to Nepali authorities with fatal neurological disease, consistent with CDV. Here, we report the findings of a serosurvey of wild felids from Nepal. A total of 48 serum samples were tested, comprising 28 Bengal tigers (P. t. tigris) and 20 Indian leopards. Neutralizing antibodies were identified in three tigers and six leopards, equating to seroprevalences of 11% (CI: 2.8–29.3%, n = 28) and 30% (CI: 12.8–54.3%, n = 20), respectively. More than one-third of seropositive animals were symptomatic, and three died within a week of being sampled. The predation of domestic dogs (Canis lupus familiaris) has been posited as a potential route of infection. A comparison of existing diet studies revealed that while leopards in Nepal frequently predate on dogs, tigers do not, potentially supporting this hypothesis. However, further work, including molecular analyses, would be needed to confirm this