How to model PM2.5 emissions?4 answersModeling PM2.5 emissions can be done using various approaches. One approach is to use machine learning algorithms such as Artificial Neural Networks (ANN). Another approach is to use a hybrid algorithm that combines autoregressive integrated moving average (ARIMA) and adaptive-neuro fuzzy inference system (ANFIS). Land use regression (LUR) models can also be used to study the influence of factors such as land use on PM2.5 pollution. Additionally, a machine learning algorithm based on multiple-input multiple-output linear regression models can be used to describe PM2.5 concentrations over time. A fully adaptive noise ensemble empirical modal decomposition (CEEMDAN) algorithm combined with deep learning hybrid models can also be used for PM2.5 concentration prediction. These different modeling approaches provide insights into PM2.5 emissions and can help in developing strategies for air quality management and environmental protection.
What is plasma thruster plumes?4 answersPlasma thruster plumes are the expanding clouds of plasma generated by various types of propulsion systems. These plumes play a crucial role in determining the performance and efficiency of the thrusters. Laser ablation plasma thrusters use a grid-based direct kinetic solver to simulate the expansion dynamics of the plasma plume, taking into account interparticle collisions and the high degree of thermodynamic nonequilibrium. Magnetic nozzle radiofrequency (rf) plasma thrusters transport and expand the plasma along a magnetic field, with the rf power coupling, plasma transport, loss to the wall, and acceleration process affecting the thrust and efficiency. Electric solid propellant microthrusters, ignited by an electric current, create plasma plumes with peak ion current density, electron temperature, and electron density, which are measured using various probes and analysis techniques. A kinetic model is used to study the electron behavior in a steady-state plasma plume, allowing for the investigation of electron collisionless cooling mechanisms.
What are the research gaps around nitrous oxides in rocket plumes?5 answersThe research gaps around nitrous oxides in rocket plumes include the need for more information on the contribution of NO(x) emissions from ground-based engine testing and actual rocket launches to the atmosphere. Additionally, there is a need for validation data to accurately assess the effects of rocket plumes on the atmosphere, which may require flight and ground campaigns as well as laboratory experiments. Furthermore, there is a lack of understanding and quantification of UV emissions from rocket plumes, with previous studies focusing more on IR emissions. The emission characteristics of rocket-exhaust plumes are strongly dependent on the aerothermochemistry of the plume, which varies depending on the rocket-engine parameters and specific propellant system employed. Overall, there is a need for further research to fill these gaps in knowledge and improve our understanding of the effects of nitrous oxides in rocket plumes.
How to find the Damköhler number of a rocket plume?5 answersThe Damköhler number of a rocket plume can be found by considering various factors such as heat release, diffusion, and combustion instability. The Damköhler number characterizes the interaction between vortices and heat release in a combustor. It is a critical parameter that affects the spatial patterns of fluctuating heat release and the behavior of the flame. In the context of vortex-driven combustion instability, a high Damköhler number corresponds to the leading edge of vortices coinciding with the high point in the local heat release cycle. However, at lower Damköhler numbers, a shift in the heat release pattern is observed, with the high point in local heat release occurring either in the vortex core or at the trailing edge of the vortex. Therefore, when designing an active control strategy for a rocket plume based on secondary fuel injection, the Damköhler number must be taken into consideration.
How can we model air quality in street canyons?5 answersAir quality in street canyons can be modeled using various approaches. One approach is to conduct field tests, wind tunnel experiments, and numerical simulations to study the dispersion characteristics of pollutants in street canyons and identify improvement measures. Another approach is to use numerical simulations to model air pollution dispersion inside street canyons and investigate the effectiveness of interventions such as deflector systems at rooftop level. Additionally, green infrastructure (GI) options such as trees, hedges, green walls, green screens, and green roofs can be evaluated for their suitability in improving air quality in street canyons. Large-eddy simulations coupled with reduced chemical schemes can also be used to investigate the processing, dispersion, and transport of reactive pollutants in street canyons. It is important to consider the geometry of the street canyon and surrounding buildings, as well as meteorological conditions and vegetation characteristics, when modeling air quality in street canyons.
How we can modelling the atmospheric boundary layer?5 answersModelling the atmospheric boundary layer involves parameterizing the structure of the boundary layer and accurately representing the variation of wind speed with height in the surface layer. Computational Fluid Dynamics (CFD) models are used to model airflow in a neutrally thermal stratified region, taking into account atmospheric stability. Input options over the boundary layer are defined for simulation in ANSYS, specifically for external aerodynamics of buildings. Machine learning techniques, such as neural networks, have been used to predict vertical turbulent fluxes in the boundary layer, providing accurate flux predictions across different turbulent regimes. A meteorological detection system of the atmospheric boundary layer has been developed, which collects data from multiple sensors and allows for local storage and wireless data transmission.