ice particles

The Ice abrasive water jet technology uses cryogenically cooled ice particles instead of the mineral abrasive used in the Abrasive water jet technology. The aim is to avoid contamination of workpieces with mineral abrasives and to reduce the environmental impact of this technology. The ice particles are sucked into a high-speed water jet with speeds of up to 600 m•s -1 using the Venturi effect. Direct observation of the process is very difficult due to the extreme operating conditions. We have clearly shown that at least some of the ice particles, which have cryogenic temperatures when entering the high-speed water jet, neither completely melt nor are completely crushed in contact with the jet. Further on, the erosion capability of ice particles was evaluated by blasting the aluminium and glass surfaces at two impinging angles and compared to garnet mineral abrasive, showing that ice particles have the potential to generate similar damage in the workpiece material as garnet. These findings pave the way for exploring the potential of abrasive waterjet technology in a wide range of new applications, such as food processing, medical implant and turbine blade manufacturing, and post-processing of parts manufactured with additive manufacturing technologies.

Ice fog, diamond dust, and light snow usually form over extremely cold weather conditions, and they affect both visibility and Earth's radiative energy budget. Prediction of these hydrometeors using models is difficult because of limited knowledge of the microphysical properties at the small size ranges due to measurement issues. These phenomena need to be better represented in forecast and climate models; therefore, in addition to remote sensing accurate measurements using ground-based instrumentation are required. An imaging instrument, aimed at measuring ice fog and light snow particles, has been built and is presented here. The ice crystal imaging (ICI) probe samples ice particles into a vertical, tapered inlet with an inlet flow rate of 11 L min -1 . A laser beam across the vertical air flow containing the ice crystals allows for their detection by a photodetector collecting the scattered light. Detected particles are then imaged with high optical resolution. An illuminating LED flash and image capturing are triggered by the photodetector. In this work, ICI measurements collected during the fog remote sensing and modeling (FRAM) project, which took place during Winter of 2010-2011 in Yellowknife, NWT, Canada, are summarized and challenges related to measuring small ice particles are described. The majority of ice particles during the 2-month-long campaign had sizes between 300 and 800 lm. During ice fog events the size distribution measured had a lower mode diameter of 300 lm compared to the overall campaign average with mode at 500 lm.

Understanding the formation and evolution of ice in clouds requires detailed information on the size, shape, mass, and optical properties of individual cloud hydrometeors and their bulk properties over a broad range of atmospheric conditions. Since the 1960s, instrumentation and research aircraft have evolved, providing increasingly more accurate and larger quantities of data about cloud particle properties. In this chapter, the current status of electrical powered, in situ measurement systems are reviewed with respect to their strengths and weaknesses and their limitations and uncertainties are documented. There remain many outstanding challenges. These are summarized and accompanied by recommendations for moving forward through new developments that fill the remaining information gaps. Closing these gaps will remove the obstacles that continue to hinder our understanding of cloud processes in general and the evolution of ice in particular.

According to the classical Archimedes' principle ice floats in water and has a fraction of its volume above the water surface. However, for very small ice particles, other competing forces such as van der Waals forces due to fluctuating charge distributions and ionic forces due to salt ions and charge on the ice surface also contribute to the force balance. The latter crucially depend on both the pH of the water and the salt concentration. The role of these forces in governing the initial stages of ice condensation has never been considered. Here we show that small ice particles can only form below an exclusion zone, from 2 nm (in high salt concentrations) up to 1 µm (in pure water at pH 7) thick, under the water surface. This distance is defined by an equilibrium of upwards buoyancy forces and repulsive van der Waals forces. Ionic forces due to salt and ice surface charge push this zone further down. Only after growing to a radius larger than 10 µm will the ice particles eventually float towards the water surface in agreement with the simple intuition based on Archimedes' principle. Our result is the first prediction of observable repulsive van der Waals forces between ice particles and the water surface outside a laboratory setting. We posit that it has consequences on the biology of ice water as we predict an exclusion zone free of ice particles near the water surface which is sufficient to support the presence of bacteria.

A new parameterization of sticking efficiency for aggregation of ice crystals onto snow and graupel is presented. This parameter plays a crucial role for the formation of ice precipitation and for electrification processes. The parameterization is intended to be used in atmospheric models simulating the aggregation of ice particles in glaciated clouds. It should improve the ability to forecast snow. Based on experimental results and general considerations of collision processes, dependencies of the sticking efficiency on temperature, surface area, and collision kinetic energy of impacting particles are derived. The parameters have been estimated from some laboratory observations by simulating the experiments and minimizing the squares of the errors of the prediction of observed quantities. The predictions from the new scheme are compared with other available laboratory and field observations. The comparisons show that the parameterization is able to reproduce the thermal behavior of sticking efficiency, observed in published laboratory studies, with a peak around 2158C corresponding to dendritic vapor growth of ice. Finally, a new theory of sticking efficiency is proposed. It explains the empirically derived parameterization in terms of a probability distribution of the work that would be required to separate two contacting particles colliding in all possible ways among many otherwise identical collisions of the same pair with a given initial collision kinetic energy. For each collision, if this work done would exceed the initial collision kinetic energy, then there is no separation after impact. The probability of that occurring equals the sticking efficiency.

For decades, enhancement of ice concentrations above those of active ice nucleus aerosols was observed in deep clouds with tops too warm for homogeneous freezing, indicating fragmentation of ice (multiplication). Several possible mechanisms of fragmentation have been suggested from laboratory studies, and one of these involves fragmentation in ice–ice collisions. In this two-part paper, the role of breakup in ice–ice collisions in a convective storm consisting of many cloud types is assessed with a modeling approach. The colliding ice particles can belong to any microphysical species, such as crystals, snow, graupel, hail, or freezing drops. In the present study (Part I), a full physical formulation of initiation of cloud ice by mechanical breakup in collisions involving snow, graupel, and/or hail is developed based on an energy conservation principle. Theoretically uncertain parameters are estimated by simulating laboratory and field experiments already published in the literature....

A new parameterization of sticking efficiency for aggregation of ice crystals onto snow and graupel is presented. This parameter plays a crucial role for the formation of ice precipitation and for electrification processes. The parameterization is intended to be used in atmospheric models simulating the aggregation of ice particles in glaciated clouds. It should improve the ability to forecast snow. Based on experimental results and general considerations of collision processes, dependencies of the sticking efficiency on temperature, surface area, and collision kinetic energy of impacting particles are derived. The parameters have been estimated from some laboratory observations by simulating the experiments and minimizing the squares of the errors of the prediction of observed quantities. The predictions from the new scheme are compared with other available laboratory and field observations. The comparisons show that the parameterization is able to reproduce the thermal behavior of...

Small nonspherical particles settling in a quiescent fluid tend to orient so that their broad side faces down because this is a stable fixed point of their angular dynamics at small particle Reynolds number. Turbulence randomizes the orientations to some extent, and this affects the reflection patterns of polarized light from turbulent clouds containing ice crystals. An overdamped theory predicts that turbulence-induced fluctuations of the orientation are very small when the settling number Sv (a dimensionless measure of the settling speed) is large. At small Sv, by contrast, the overdamped theory predicts that turbulence randomizes the orientations. This overdamped theory neglects the effect of particle inertia. Therefore, we consider here how particle inertia affects the orientation of small crystals settling in turbulent air. We find that it can significantly increase the orientation variance, even when the Stokes number St (a dimensionless measure of particle inertia) is quite small. We identify different asymptotic parameter regimes where the tilt-angle variance is proportional to different inverse powers of Sv. We estimate parameter values for ice crystals in turbulent clouds and show that they cover several of the identified regimes. The theory predicts how the degree of alignment depends on particle size, shape, and turbulence intensity, and that the strong horizontal alignment of small crystals is only possible when the turbulent energy dissipation is weak, on the order of 1 cm 2 s 23 or less.

Ice fog, diamond dust, and light snow usually form over extremely cold weather conditions, and they affect both visibility and Earth's radiative energy budget. Prediction of these hydrometeors using models is difficult because of limited knowledge of the microphysical properties at the small size ranges due to measurement issues. These phenomena need to be better represented in forecast and climate models; therefore, in addition to remote sensing accurate measurements using ground-based instrumentation are required. An imaging instrument, aimed at measuring ice fog and light snow particles, has been built and is presented here. The ice crystal imaging (ICI) probe samples ice particles into a vertical, tapered inlet with an inlet flow rate of 11 L min-1. A laser beam across the vertical air flow containing the ice crystals allows for their detection by a photodetector collecting the scattered light. Detected particles are then imaged with high optical resolution. An illuminating LED flash and image capturing are triggered by the photodetector. In this work, ICI measurements collected during the fog remote sensing and modeling (FRAM) project, which took place during Winter of 2010-2011 in Yellowknife, NWT, Canada, are summarized and challenges related to measuring small ice particles are described. The majority of ice particles during the 2-month-long campaign had sizes between 300 and 800 lm. During ice fog events the size distribution measured had a lower mode diameter of 300 lm compared to the overall campaign average with mode at 500 lm.

Understanding the formation and evolution of ice in clouds requires detailed information on the size, shape, mass, and optical properties of individual cloud hydrometeors and their bulk properties over a broad range of atmospheric conditions. Since the 1960s, instrumentation and research aircraft have evolved, providing increasingly more accurate and larger quantities of data about cloud particle properties. In this chapter, the current status of electrical powered, in situ measurement systems are reviewed with respect to their strengths and weaknesses and their limitations and uncertainties are documented. There remain many outstanding challenges. These are summarized and accompanied by recommendations for moving forward through new developments that fill the remaining information gaps. Closing these gaps will remove the obstacles that continue to hinder our understanding of cloud processes in general and the evolution of ice in particular.

Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.

A simple scheme that is based on the shape and intensity of the radar bright band is used to infer the density of hydrometeors just above the freezing level in Sahelian mesoscale convective systems (MCS). Four MCS jointly observed by a ground-based X-band radar and by an instrumented aircraft as part of the Megha-Tropiques algorithm-validation campaign during August 2010 in Niamey, Niger, are analyzed. The instrumented aircraft (with a 94-GHz radar and various optical probes on board) provided mass–diameter laws for the particles sampled during the flights. The mass–diameter laws derived from the ground-radar vertical profile of reflectivity (VPR) for each flight are compared with those derived from the airborne measurements. The density laws derived by both methods are consistent and encourage further use of the simple VPR scheme to quantify hydrometeor density laws and their variability for various analyses (microphysical processes and icy-hydrometeor scattering and radiative prop...