EXPERIMENTAL STUDY OF THE DIRECT METHANE INJECTION AND COMBUSTION IN SI ENGINE

Abstrac

Numerical Simulations of DDT Limits in Hydrogen-Air Mixtures in Obstacle Laden Channel

The main aim of this study was to perform numerical simulations of deflagration to detonation transition process (DDT) in hydrogen–air mixtures and assess the capabilities of freeware open-source ddtFoam code to simulate and capture DDT limits. The numerical geometry was based on the real 0.08 × 0.11 × 4 m (H × W × L), rectangular cross-section detonation channel previously used to experimentally investigate DDT limits in obstacle-filled channel. The constant blockage ratio (BR) equal to 0.5 was kept for three obstacle spacing configurations: S = H, 2H, 3H. The results showed that hydrogen concentration limits for successful DDT from simulations are close to the experimental values, however, the simulated DDT limits range is wider than the experimental one and depends on the obstacles spacing. The numerical results were analyzed by means of propagation velocities, overpressures, and run-up distances. The best match between numerical and experimental DDT limits was observed for obstacles spacing L = 3H and the lowest match for spacing L = H. The comparison between experimental and numerical results points at the possible application of ddtFoam in geometry with a relatively low level of congestion. This work results proved that simulations in such geometry provide numerical flame acceleration velocity profiles, run-up distance, and recorded overpressures very close to experimentally measured

Laser diagnostics for urea-water solution spray characterization

In this study, we summarize the laser techniques used for urea-water solution (UWS) spray characterization at the Institute of Heat Engineering (ITC), Faculty of Power and Aeronautical Engineering at Warsaw University of Technology. In presented studies several techniques for both, global and local spray characterization were used. Shadowgraphy-based long distance microscopy was used to visualize individual droplets and primary breakup. High speed imaging of Mie scattering (scattering on the gas-liquid interface) signal was used for global spray characterization. Combination of LIF (Laser Induced Fluorescence) and Mie scattering allowed to determine qualitative droplet size distribution across the whole spray cloud. The structured illumination technique used to modulate laser light sheet allowed to minimize the effects of multiple scattering in detection of Mie signal, what indicated huge potential of this technique in characterization of UWS sprays. The results presented here prove the importance of laser diagnostics in SCR systems development

Badanie granic wybuchowości par cieczy palnych w różnych temperaturach początkowych

Artykuł zawiera wyniki badań doświadczalnych granic wybuchowości par metanolu, etanolu oraz 1-butanolu w temperaturach początkowych 40, 60, 80, 100 oraz 120 °C Badania przeprowadzono według metody B opisanej w standardzie PN-EN 1839. Dodatkowo, w treści artykułu przedstawiono przegląd stanu dotychczasowej wiedzy w zakresie metod określania granic wybuchowości na potrzeby bezpieczeństwa w transporcie i w magazynowaniu ciekłych substancji palnych

Predictive modelling of turbofan engine components condition using machine and deep learning methods

The article proposes an approach based on deep and machine learning models to predict a component failure as an enhancement of condition based maintenance scheme of a turbofan engine and reviews currently used prognostics approaches in the aviation industry. Component degradation scale representing its life consumption is proposed and such collected condition data are combined with engines sensors and environmental data. With use of data manipulation techniques, a framework for models training is created and models' hyperparameters obtained through Bayesian optimization. Models predict the continuous variable representing condition based on the input. Best performed model is identified by detemining its score on the holdout set. Deep learning models achieved 0.71 MSE score (ensemble meta-model of neural networks) and outperformed significantly machine learning models with their best score at 1.75. The deep learning models shown their feasibility to predict the component condition within less than 1 unit of the error in the rank scale

Numerical Simulation of Two-Stage Variable Geometry Turbine

The modern internal combustion engine (ICE) has to meet several requirements. It has to be reliable with the reduced emission of pollutant gasses and low maintenance requirements. What is more, it has to be efficient both at low-load and high-load operating conditions. For this purpose, a variable turbine geometry (VTG) turbocharger is used to provide proper engine acceleration of exhaust gases at low-load operating conditions. Such a solution is also efficient at high-load engine operating conditions. In this paper, the result of an unsteady, three-dimensional (3D) simulation of the variable two-stage turbine system is discussed. Three different VTG positions were considered for those simulations, along with three different turbine speeds. The turbine inlet was modeled as six equally placed exhaust pipes for each cylinder to eliminate the interference of pressure waves. The flow field at the outlet of the 1st stage nozzle vane and 2nd stage rotor was investigated. The simulations showed that the variable technologies significantly improve the efficiency of the two-stage turbine system. The highest overall efficiency of the two-stage system was achieved at 60,000 rpm and 11° VTG position