The objective of this study is to explore the limits of a one-dimensional model to predict the movement and mixing of the air and exhaust gases recirculation (EGR) flows in compact intake manifolds of recent automotive engines. In particular, the high pressure EGR loop configuration is evaluated in this study from the perspective of the EGR dispersion among cylinders. The experimental work includes the use of a fast CO₂ tracking system that provides crank-angle resolved results in six locations of the intake manifold together with the acquisition of the time-averaged CO₂ concentration in all the intake pipes (eight locations) to evaluate the EGR dispersion empirically. A specific system was developed to inject the EGR in three locations of the intake manifold in a flexible way to modify the dispersion. Up to 29 engine running conditions defined by engine speed, engine torque and EGR rate, spanning the entire engine map, including full load operation, were evaluated. A one-dimensional engine model was built to detect the limits in reproducing the EGR transport in the intake manifold and quantify the accuracy when predicting the dispersion among cylinders. The study concludes that the predicted EGR rate in the cylinders may differ up to 75% from the experimental measurement at low engine averaged EGR rate. The model prediction improves to differences lower than 40% in EGR rate per cylinder if the engine operating points with an EGR rate lower than 10% are excluded. In this situation, 80% of the predicted in-cylinder EGR rates have differences lower than 25% when compared to experiments.

Microscopic Particulate Matter (PM) below 10 µm can enter the respiratory system and affect human health in the short and long term. Railway enclosures are sites with high concentrations of fine PM and technical solutions like mechanical filtration exist to increase the air quality. However, several crucial factors must be evaluated and optimized like energy consumption, maintenance cost/interval, design and control. A fast and adaptable evaluation of decontamination solutions is required to find the optimal solution. To answer this, a 1D multizone model based on station discretization aligned with the track direction is proposed to precisely place decontamination systems along the station. In each zone, a set of ordinary differential equations is used to forecast the daily progression of PM concentrations, based on physical parameters (air and train velocities, and train traffic) used to describe the different physical phenomena (resuspension, deposition, ventilation and generation). Three-dimensional CFD (Computational Fluid Dynamics) simulations are used to characterize the efficiency and range of decontamination products and reproduce their effect in the 1D model. This approach allows for flexible optimization of local and global decontamination efficiencies with multiple parameter changes. PM₁₀ and PM_2.5 (below 10 and 2.5 µm) are studied here as they are often monitored.