A novel design for solar collector used for water heating application having nanofluid as working medium: CFD modeling and simulation.

A solar collector is a simple and cheap device that converts solar radiation into valuable heat energy. The thermal performance of the solar collectors can be enhanced significantly with the suspension of nanoparticles in the base fluid. A novel design for a solar-assisted water heater (SWH) is proposed in the current study, and the effect of nanofluid has been investigated on the thermal efficiency of the SWH. The use of nanofluid is one of the prominent methods in comparison to other techniques for improving the performance of solar collectors. Therefore, the base working fluid, i.e., water is mixed with the alumina nanoparticles of average particle size of 30 nm, and they are assumed to be spherical. The flow and thermal characteristics of nanofluid through the solar water heater are simulated numerically with the help of the Eulerian-Eulerian two-phase model using the finite volume method (FVM). The commercial package ANSYS Fluent, is used for modeling the problem under transient conditions with a pressure-based solver. In comparison to a conventional flat plate collector, the proposed solar water heater consists of a corrugated absorber-plate and the effect of the radius of curvature has been investigated on the heat transfer and collector efficiency. With the proposed design, the heat transfer area available with the riser tubes increases remarkably and it leads to a 43% and 14% increase in heat transfer augmentation and collector efficiency, in comparison to the conventional solar water heater.

Modeling and simulation of high energy density lithium-ion battery for multiple fault detection.

Lithium-ion battery, a high energy density storage device has extensive applications in electrical and electronic gadgets, computers, hybrid electric vehicles, and electric vehicles. This paper presents multiple fault detection of lithium-ion battery using two non-linear Kalman filters. A discrete non-linear mathematical model of lithium ion battery has been developed and Unscented Kalman filter (UKF) is employed to estimate the model parameter. Occurrences of multiple faults such as over-charge, over-discharge and short circuit faults between inter cell power batteries, affects the parameter variation of system model. Parallel combinations of some UKF (bank of filters) compare the model parameter variation between the normal and faulty situation and generates residual signal indicating different fault. Simulation results of multiple numbers of statistical tests have been performed for residual based fault diagnosis and threshold calculation. The performance of UKF is then compared with Extended Kalman filter (EKF) with same battery model and fault scenario. The simulation result proves that UKF model responses better and quicker than that of EKF for fault diagnosis.

Merits and Limitations of Mathematical Modeling and Computational Simulations in Mitigation of COVID-19 Pandemic: A Comprehensive Review.

Mathematical models have assisted in describing the transmission and propagation dynamics of various viral diseases like MERS, measles, SARS, and Influenza; while the advanced computational technique is utilized in the epidemiology of viral diseases to examine and estimate the influences of interventions and vaccinations. In March 2020, the World Health Organization (WHO) has declared the COVID-19 as a global pandemic and the rate of morbidity and mortality triggers unprecedented public health crises throughout the world. The mathematical models can assist in improving the interventions, key transmission parameters, public health agencies, and countermeasures to mitigate this pandemic. Besides, the mathematical models were also used to examine the characteristics of epidemiological and the understanding of the complex transmission mechanism. Our literature study found that there were still some challenges in mathematical modeling for the case of ecology, genetics, microbiology, and pathology pose; also, some aspects like political and societal issues and cultural and ethical standards are hard to be characterized. Here, the recent mathematical models about COVID-19 and their prominent features, applications, limitations, and future perspective are discussed and reviewed. This review can assist in further improvement of mathematical models that will consider the current challenges of viral diseases.

A novel CFD analysis to minimize the spread of COVID-19 virus in hospital isolation room.

The COVID-19 is a severe respiratory disease caused by a devastating coronavirus family (2019-nCoV) has become a pandemic across the globe. It is an infectious virus and transmits by inhalation or contact with droplet nuclei produced during sneezing, coughing, and speaking by infected people. Airborne transmission of COVID-19 is also possible in a confined place in the immediate environment of the infected person. Present study investigates the effectiveness of conditioned air released from air-conditioning machines to mix with aerosol sanitizer to reach every point of the space of the isolation room so as to kill the COVID-19 virus which will help to protect the lives of doctors, nurses and health care workers. In order to numerically model the laminar-transitional flows, transition SST k-ε model, which involves four transport equations are employed in the current study. It is found from the analysis that high turbulent fields generated inside the isolation room may be an effective way of distributing sanitizer in entire volume of isolation room to kill the COVID-19 virus.