RESUMEN
In chemical industries, multiphase flows in a bubble column reactor are frequently observed. The nonlinearity associated with bubble hydrodynamics, such as bubble-bubble and bubble-liquid interactions, gives rise to complex spatiotemporal patterns with increased gas or liquid velocities, which are extremely difficult to model and predict. In the current study, we propose a new, computationally efficient recurrence-based approach involving the angular separation between suitably defined state vectors and implement it on the experimental multiphase flow variables. The experimental dataset that consists of image frames obtained using a high-speed imaging system is generated by varying air and water flow rates in a bubble column reactor setup. The recurrence plots using the new approach are compared with those derived from conventional recurrence, considering standard benchmark problems. Further, using the recurrence plots and recurrence quantification from the new recurrence methodology, we discover a transition from a high recurrence state to a complex regime with very low recurrence for an increase in airflow rate. Determinism exhibits a rise for the decrease in airflow rate. A sharp decline in determinism and laminarity, signifying the quick shift to complex dynamics, is more prominent for spatial recurrence than temporal recurrence, indicating that the rise in airflow rate significantly impacts the spatial location of bubbles. We identify three regimes that appeared as distinct clusters in the determinism-laminarity plane. The bubbly regime, characterized by high values of determinism and laminarity, is separated by an intermediate regime from the slug flow regime, which has low determinism and laminarity.
RESUMEN
Polarization of opinions has been empirically noted in many online social network platforms. Traditional models of opinion dynamics, based on statistical physics principles, do not account for the emergence of polarization and echo chambers in online network platforms. A recently introduced opinion dynamics model that incorporates the homophily factor-the tendency of agents to connect with those holding similar opinions as their own-captures polarization and echo chamber effects. In this work, we provide a nonintrusive framework for mildly nudging agents in an online community to form random connections. This is shown to lead to significant depolarization of opinions and decrease the echo chamber effects. Though a mild nudge effectively avoids polarization, overdoing this leads to another undesirable effect, namely, radicalization. Further, we obtain the optimal nudge probability to avoid the extremes of polarization and radicalization outcomes.
RESUMEN
As we are writing this paper, the number of daily affected COVID patients is around 0.38 million and with active cases over 3 million in India. This large number of active cases is putting the medical facilities under severe strain. Many researchers have proposed many ways of forecasting the COVID-19 patients but they mainly worked on the cumulative cases and moreover, all those methods required considerable skill and computational cost. In this work, a simple spreadsheet-based forecasting model has been developed which will help to predict the number of active cases in the immediate future i.e., the next few days. This information can be useful for emergency management. The difficulty which is generally faced in predicting the active cases is that the dynamics of active cases has a complex dependence on a number of Non-Pharmaceutical Interventions (NPI) and social factors and can undergo sharp changes. Quadratic, cubic and quartic polynomial functions have been applied to capture these peaks and observed that the quadratic function helps in better prediction of the peak. The accuracy of the prediction methods is measured as well as it is tried to observe how the methods predict data for the next 1 day, 3 days and 6 days. A prediction method analogous to weather forecasting method is recommended in this work where the prediction for each day gets updated depending on the most recent data available. This method has also been found to perform well even in the period there were sharp changes in the trend due to imposition of strict NPI measures.
RESUMEN
Respiratory droplets-which may contain disease spreading virus-exhaled during speaking, coughing, or sneezing are one of the significant causes for the spread of the ongoing COVID-19 pandemic. The droplet dispersion depends on the surrounding air velocity, ambient temperature, and relative humidity. In a confined space like an elevator, the risk of transmission becomes higher when there is an infected person inside the elevator with other individuals. In this work, a numerical investigation is carried out in a three-dimensional domain resembling an elevator using OpenFoam. Three different modes of air ventilation, viz., quiescent, axial exhaust draft, and exhaust fan, have been considered to investigate the effect of ventilation on droplet transmission for two different climatic conditions (30 °C , 50% relative humidity and 10 °C , 90% relative humidity). The risk assessment is quantified using a risk factor based on the time-averaged droplet count present near the passenger's hand to head region (risky height zone). The risk factor drops from 40% in a quiescent scenario to 0% in an exhaust fan ventilation condition in a hot dry environment. In general, cold humid conditions are safer than hot dry conditions as the droplets settle down quickly below the risky height zone owing to their larger masses maintained by negligible evaporation. However, an exhaust fan renders the domain in a hot dry ambience completely safe (risk factor, 0%) in 5.5 s whereas it takes 7.48 s for a cold humid ambience.
RESUMEN
In this work, we showcase a mechanism of rapid and focused solvent depletion using vapor-mediated interaction that can nonintrusively cleave a sessile water droplet reminiscent of Moses parting the Red Sea. The Marangoni effect is induced by the differential adsorption of vapor from a nearby pendant droplet of ethanol, leading to an exponential increase in surface velocity inside the water droplet. The Marangoni convection leads to the drainage of liquid from the central section of the water droplet and consequently splits it. By encoding the position of the ethanol (vertical as well as horizontal) droplet, an array of liquid motion is observed (split, shift, and slosh) in the water droplet. This method is further extended to nanocolloidal systems, where the liquid motion can be exploited to generate a wide gamut of deposit patterns ranging from uniform precipitate to sporadic islands without resorting to the more traditional evaporation-driven capillary flows ("coffee stains") or custom engineering of the shape of the nanoparticles. We further provide a detailed exposition of the physical mechanisms responsible for the splitting of the liquid drop and consequent particle deposition. The concept can be extended to liquid actuation in open channel microfluidic chips and surface patterning as in medical diagnostics, optoelectronics, and thermal management.
RESUMEN
A simple condensation of chitosan (from shrimp shells) and 4-hydroxybenzaldehyde was performed to yield bio-lubricant additive comprised of azomethine functional groups to be used with paraffin lube oil in industries. The synthesized Schiff base derivative of chitosan (SBC) additive was characterized using a CHN analyzer and FT-IR spectroscopy, and the thermal stability was explored using thermogravimetry. The rheological properties of SBC additives in paraffin oil were studied and are discussed herein. The tribological properties of SBC were tested in paraffin as the base oil employing a four-ball tester with different experimental conditions (viz. the concentration of the additive, applied load, speed and time duration), following ASTM D4172A standards. The optimum concentration of the additive in the base oil was found to be 150 ppm, exhibiting minimum coefficient of friction, but with higher concentrations of additive in base oils, the coefficient of friction increased. UV-Vis spectroscopy studies were also performed to confirm the formation of SBC and dispersion stability. The determined tribological parameters, such as the coefficient of friction, mean wear scar diameters and mean wear scar volumes, were found to significantly reduce the coefficient of friction of paraffin oil upon the addition of SBC. The state of steel balls upon exposure to various experimental conditions was analyzed and explained based on outcomes from FESEM, EDX, ferrography and AFM spectroscopy. The insights into interactions of the synthesized SBC with the metal surface were explored using ab initio density functional theory, Fukui indices, molecular dynamics simulation and radial distribution function.