Fluid dynamics of frozen precipitation at the air–water interface

Precipitation in the forms of snow, hail, and rain plays a critical role in the exchange of mass, momentum and heat at the surfaces of lakes and seas. However, the microphysics of these interactions are not well understood. Motivated by recent observations, we study the physics of the impact of a single frozen canonical particle, such as snow and hail, onto the surface of a liquid bath using a numerical model. The descent, melting, bubble formation and thermal transport characteristics of this system are examined. Three distinct response regimes, namely particle impact, ice melting and vortex ring descent, have been identified and characterized. The melting rate and air content of the snow particle are found to be leading factors affecting the formation of a coherent vortex ring, the vertical descent of melted liquid and the vortex-induced transportation of the released gas bubble to lower depths. It is found that the water temperature can substantially alter the rate of phase change and subsequent flow and thermal transport, while the particle temperature has minimal effect on the process. Finally, the effects of the Reynolds, Weber and Stefan numbers are examined and it is shown that the Reynolds number modifies the strength of the vortex ring and induces the most significant effect on the flow dynamics of the snow particle. Also, the change of Weber number primarily alters the initial phases of snow–bath interaction while modifying the Stefan number of the snow particle essentially determines the system response in its later stages.

A Granular Thermodynamic Model to Describe the Temperature/Mechanical Characteristics of Sandy Soil

Based on the granular-solid-hydrodynamic theory, the constitutive model considering the thermo-hydro-mechanical (THM) coupled action is established, and the dilatancy property of sandy soil under coupled high mechanical pressure and temperature is simulated. The relationship between the energy dissipation and the macroscopic stress-strain changes at the grain level of saturated sandy soil is connected by defining the transfer coefficient and the energy function, without considering the concepts of yield surface and hardening parameters in classical plastic mechanics. Additionally, the changes in temperature, relative density and confining pressure during the shearing process cause particle rolling, slipping and friction. The energy dissipation in this process is described by defining the concept of particle entropy and particle temperature. In the calculation, the isotropic compression test, drained and undrained shear test of sandy soil under high stress are simulated respectively. The validity of the model is proved by comparing with the test results. Meanwhile, the stress-strain relationship and pore pressure variation law of sandy soil under different temperatures are predicted. The results show that the effect of temperature on shear strength is limited, and the pore pressure will gradually increase and become stable with the increase of temperature. Thus, this work establishes the soil THM coupled model from the perspective of micro energy dissipation, which can provide new theoretical support for the prediction of natural disasters such as landslides and debris flow.

Вплив діаметру частинок порошку нікелю на їх швидкість і температуру при холодному газодинамічному напилюванні

To deposit coatings in cold gas-dynamic spraying (CS), a high-speed gas flow is used to accelerate and heat particles. Therefore, first of all, it is necessary to consider the general laws of the gas flow and the movement of particles in the flow, as well as its interaction with the substrate. Due to the CS process depends primarily on the particle velocity, it is important to understand the effect of the process parameters (pressure and temperature at the nozzle inlet), the characteristics of the powder particles (material density, shape, and size), and the geometry of the nozzle. The gas velocity limits the particle velocity that can be achieved with the CS process. Utilization of high gas pressure, long nozzles, and small particles lead to the fact that the particles move at a velocity close to the velocity of the gas, which can be increased by using gases with low molecular weight, as well as heating it. As a result of the analysis of theoretical and experimental methods for studying the cold spraying process, it was found that for coating formation velocity of powder particles needs to obtain a certain value (critical velocity), which depends on particle temperature at the impact, and density of the particle material. Numerical simulation of gas dynamics of a two-phase flow in CS nozzle and at the outlet from it for the range of air temperatures from 573 K to 873 K and constant pressure of 1,0 MPa has been carried out. The influence of the diameter of nickel powder particles on their temperature and velocity at impact was investigated. Numerical simulations were performed for a range of particle diameters from 5 to 30 μm. In the future, the results obtained can be used to find the optimal size of the powder particles under certain spraying conditions, to calculate the critical particle velocity, and also to develop the window of deposition. This will make it possible to select the optimal parameters of the gas flow at the nozzle inlet (pressure and temperature), which are guaranteed to ensure the adhesion of particles to the substrate and the formation of coatings. Also, the results obtained can be used to predict the properties of coatings, as well as to achieve maximum deposition efficiency of the CS process.

Experimental and Numerical Analysis on Two-Phase Induced Low-Speed Pre-Ignition

The root cause of the initial low-speed pre-ignition (LSPI) is not yet clarified. The literature data suggest that a two-phase phenomenon is most likely triggering the unpredictable premature ignitions in highly boosted spark-ignition engines. However, there are different hypotheses regarding the actual initiator, whether it is a detached liquid oil-fuel droplet or a solid-like particle from deposits. Therefore, the present work investigates the possibility of oil droplet-induced pre-ignitions using a modern downsized engine with minimally invasive endoscopic optical accessibility incorporating in-cylinder lubrication oil detection via light-induced fluorescence. This setup enables the differentiation between liquid and solid particles. Furthermore, the potential of hot solid particles to initiate an ignition under engine-relevant conditions is analyzed numerically. To do so, the particle is generalized as a hot surface transferring heat to the reactive ambient gas phase. The gas-phase reactivity is represented as a TRF/air mixture based on RON/MON specifications of the investigated fuel. The chemical processes are predicted using a semi-detailed reaction mechanism, including 137 species and 633 reactions in a 2D CFD simulation framework. In the optical experiments, no evidence of a liquid oil droplet-induced pre-ignition could be found. Nevertheless, all observed pre-ignitions had a history of flying light-emitting objects. There are strong hints towards solid-like deposit LSPI initiation. The application of the numerical methodology to mean in-cylinder conditions of an LSPI prone engine operation point reveals that particles below 1000 K are not able to initiate a pre-ignition. A sensitivity analysis of the thermodynamic boundary conditions showed that the particle temperature is the most decisive parameter on the calculated ignition delay time.

A Non-Intrusive Particle Temperature Measurement Methodology Using Thermogram and Visible-Light Image Sets

The measurement of particle plume and curtain temperatures in particle-laden gravity-driven flows presents a unique challenge to thermometry due to the flow’s transient and stochastic nature. Earlier attempts to assess the bulk particle temperature of a plume using intrusive and non-intrusive methods have produced very limited success. Here we describe a non-intrusive method using a high-speed IR camera (ImageI8300 from Infratec) and a visible-light camera (Nikon D3500) to produce indirect particle temperature measurements. The IR camera produces thermogram sets mapping the apparent particle temperature, while the visible-light image sets allow for the calculation of the plume opacity as a function of flow discharge position. An in-house post-processing algorithm based on Planck’s radiation theory was developed to compute the true particle temperature which is a function of the apparent temperature (thermograms) and the plume opacity obtained from the visible-light images. To validate these results, a series of lab-scale tests generating particle curtains of known dimensions at various temperatures were performed. The lab-scale tests were conducted using a small particle receiver which is equipped with thermocouples to measure the temperature directly. Using the recorded thermocouple data, a particle temperature function can be derived empirically, based on the lumped capacitance model for a free-falling sphere. The empirical particle temperature function is then compared with the temperature data measured using the methodology outlined in this work yielding agreement of the bulk particle temperature of the plume. The methods described here will be developed further to estimate the heat losses from the falling particle receiver at Sandia National Labs.

Ensemble Methods for APS In-Flight Particle Temperature and Velocity Prediction Considering Torch Electrodes Ageing

In an atmospheric plasma spray (APS) process; in-flight powder particle characteristics; such as the particle velocity and temperature; have significant influence on the coating formation. The nonlinear relationship between the input process parameters and in-flight particle characteristics is thus of paramount importance for coating properties design and quality control. It is also known that the ageing of torch electrodes affects this relationship. In recent years; machine learning algorithms have proven to be able to take into account such complex nonlinear interactions. This work illustrates the application of ensemble methods based on decision tree algorithms to evaluate and to predict in-flight particle temperature and velocity during an APS process considering torch electrodes ageing. Experiments were performed to record simultaneously the input process parameters; the in-flight powder particle characteristics and the electrodes usage time. Various spray durations were considered to emulate industrial coating spray production settings. Random forest and gradient boosting algorithms were used to rank and select the features for the APS process data recorded as the electrodes aged and the corresponding predictive models were compared. The time series aspect of the data will be examined.

Study of the In-Flight Characteristics of Particles for Different Configurations of Cascade Plasma Torches

Cascaded plasma torches are becoming increasingly common, but the influence of geometry, notably that of the anode, is relatively unexplored. This work investigates the relationship between anode-cathode distance and plasma voltage fluctuations. The study was conducted using cascaded torches that can be configured with different numbers of neutrodes and commercially available Al2O3 powders. The powders were sprayed at different gas flow rates and current intensities while monitoring voltage fluctuations as well as in-flight particle temperature and velocity. The resulting alumina coatings were characterized based on microstructure, phase composition, porosity, and hardness. A frequency analysis of the arc voltage fluctuations revealed well-defined peaks at 60, 120, and 180 kHz that vary in intensity based on the number of neutrodes. The more neutrodes, the sharper and higher the peak. In contrast, the power spectra of the arc voltage generated by a conventional plasma torch contains no such peaks, indicating a random displacement of the arc root leading to less stability of the arc.

Numerical Simulation of Solid Ti6AI4V Particles Impinging on a Stainless-Steel Substrate at High Speed: Influence of the Particle Temperature

Additive manufacturing processes have been used to produce or repair components in different industry sectors like aerospace, automotive, and biomedical. In these processes, a part can be built by either melted particles as in selective laser melting (SLM) or solid-state particles as in the cold spray process. The cold spray has gained significant attention due to its potential for high deposition rate and nearly zero oxidation. However, the main concern associated with using the cold spray is the level of porosity in as-fabricated samples, altering their mechanical properties. These pores are primarily found in the regions where adiabatic shear instability does not occur. It is worth noting that the deformation of the impacted solid particle plays a vital role in reaching the shear instability. Therefore, for investigating the adiabatic shear instability region, an elastic-plastic simulation approach has been used. For this purpose, it is assumed that an elevated temperature solid Ti6Al4V particle impacts on a stainless-steel substrate surface at high velocity. The results show that increasing particle temperature will significantly enhance particle deformation because of thermal softening. Additionally, they illustrate that a material jet responsible for producing a bonding between particle and substrate by ejecting the broken oxide layer will be formed when the particle has a temperature above 1073 K and substrate remains at room temperature. In the end, it should be noted that increasing particle temperature up to 723 K will not have a significant effect on substrate deformation and final substrate temperature.

Particulate Matter Reduction in Residual Biomass Combustion

Counteracting emissions of particulate matter (PM) is an increasingly important goal in sustainable biomass combustion. This work includes a novel approach to investigate the PM emissions, originating from residual biomass combustion, at different combustion conditions in a lab-scale grate-fired furnace and includes in situ PM measurements by using on-line sensors. The interior furnace design allows installation of baffles to suppress the emissions by controlling the residence time. Moreover, the two-thermocouple method is used to measure the true gas temperature, and an on-line spatially resolved PM measurement method is developed to study the evolution of the PM concentration throughout the furnace for different experimental conditions thereby allowing accurate in-situ measurement of the PM reactivity. Experimental results and computational fluid dynamics (CFD) analyses are utilized in the current work to develop a kinetic model for reduction of particulate matter emissions in biomass combustion. The discrete particle model (DPM) is utilized in CFD analysis to improve the understanding of the particle temperature and residence time distribution which are difficult to quantify experimentally. By combining the experimental measurements of real soot formed during biomass combustion and information from the CFD analyses, a predictive kinetic model for PM10 reduction in biomass combustion is successfully developed.