Dry deposition and desorption of toxic gases to and from snow surfaces

A model describing toxic gas deposition to and desorption from a snow surface is presented. The model is based on the assumption that the deposition is caused by an adsorption of the toxic gas to small amounts of liquid water, which exist in the snow at temperatures equal to or below 0°C. It includes molecular diffusion in the snow, partition between gas and solution by use of Henry's law, drainage flow in melting snow and decomposition of agent. The interface to the atmosphere is defined by the flux to and from the surface with help of the aerodynamic resistance and the resistance in the viscous sub-layer. Deposition velocities to snow for some air pollutants are reviewed. The model is compared with sarin experiments in a test chamber, which verifies two main features of the model—primarily decreasing deposition with time and decreasing deposition with decreasing temperature. The model shows that the accumulation of sarin in the top layer of snow could be high enough to give lethal or severe injuries to people if the snow was used as drinking water. However, there is a tendency of the model to give too low deposition (too high surface resistance). Possible reasons for this observation are discussed.     

A new method of measuring the snow-surface temperature

Because a snow cover is so tenuous, measuring its surface temperature is not easy. The surface is illdefined and easily disturbed; invasive transducers commonly used for other surfaces are, thus, generally inappropriate for snow. We therefore describe a hygrometric method of measuring the snow-surface temperature. The advantages are that the method is non-invasive, that its accuracy depends only weakly on the surface structure, and that it is reliable even in bright sunlight. The key assumption is that the air at a snow surface is in saturation with the snow; the dew-point temperature of air right at the snow surface is thus the surface temperature. Consequently, under a fairly wide range of conditions we can, in effect, measure the surface temperature by measuring the dew-point temperature 10 cm above the surface. We develop a theoretical justification for the hygrometric measurement, discuss the meteorological parameters that affect the accuracy of the method, and compare hygrometer data with more traditional measurements.     

In situ measurements of the resistivity of Antarctic sea ice

The resistivity of first yea sea ice was measured in situ at two locations in McMurdo Sound, Antarctica using the Wenner array technique at audio frequencies. In addition, salinity and temperature profiles were measured. The results are adequately described by a three-layer model made up of a thin conducting surface layer, an insulating layer and finally sea water. The average resistivity of sea ice was found to lie in the range 50–200 Ω depending on salinity, structure and temperature. The resistivity and thicknesses of the surface layer could not be determined uniquely by the model but a maximum value for the resistivity as low as 4 Ω m was obtained. The resistivity of the surface layer was found to be influenced by the removal of the snow cover. The depth predicted by the Wenner sounding was found to be roughly 50% of the actual depth, a result that is consistent with a conductivity in the vertical direction and parallel to the brine channels of four times the conductivity in the horizontal direction within the bulk layer.     

Textile protection of snow and ice: Measured and simulated effects on the energy and mass balance

Measurements and simulations of the energy fluxes and mass changes of an artificially covered snow and ice surface (geotextile material) and an unaltered control plot in an Austrian glacier ski resort are presented and compared. A modified version of the snow cover model SNOWPACK is used to successfully reproduce the artificially compacted and the additionally covered snow cover in a physically based way. Supplementary measurements of crucial material properties of the 4.5 mm thin geotextile serve as model input as well. Results indicate that the shortwave reflectivity of the covers is responsible for 46% of the performance. Thermal insulation of the material (14%) and a negative latent heat flux due to evaporation of precipitation from the cover surface (10%) have almost the same contribution. A layer of air between the cover and the snow and ice surface (thickness 7.5 cm to 12 cm) adds the rest, which is at the upper limit of observations and may therefore also compensate for model errors. This generally explains the high performance of the method in glacier ski resorts and, most importantly, an altitude dependent application limit of the method: the method becomes less effective at lower altitudes, where sensible heat fluxes become more important compared to shortwave radiation.     

A multiple snow layer model including a parameterization of vertical water channel process in snowpack

Tohkamachi Experimental Station in Niigata prefecture, Japan, which is located along the Sea of Japan, usually has heavy snowfall in the winter. At this site, melting snow and rain are frequently observed in the middle of winter, because it has a higher temperature than other cold regions. As a consequence, water frequently infiltrates through the snowpack, creating vertical water channels. In this study, a new parameterization of the water channel process was implemented in a multiple snow layer model, which already had the infiltration process represented using the Darcy's law.The conceptual procedure used to model the water channel was based on the impermeable processes through which water infiltrates into dry snow and a new snowpack. The model does not consider the impermeable processes associated with a capillary barrier at the boundary between the fine textured upper layer and the coarse textured lower layer or at the boundary between the snow upper layer and the ice lower layer. The new parameterization controlled the vertical water flux at the wetting front layer just above the dry snow layer by a limiter which was expressed as the threshold value of the liquid water content. The water which should go through the water channel was removed at the uniformly infiltrated part of the snowpack.We found that the new water channel process implemented in this study worked well when it was applied to a rainfall event in the middle of winter, based on the vertical structure in the snowpack with a comparison between the pit observations and the simulated results. This comparison showed that the simulation with the water channel was more accurate than that with uniform infiltration. The seasonal mean of the agreement scores with the parameterization of the channel flow (0.91) became larger than the score under the uniform flow condition (0.79).     

A macroscale model for low density snow subjected to rapid loading

A Capped Drucker–Prager (CDP) model was used to simulate the deformation-load response of a low density (150–250 kg/m³) snow being loaded at high strain rates (i.e., strain rates associated with vehicle passage) in the temperature range of −1 to −10 °C. The range in the appropriate model parameters was determined from experimental data. The model parameters were refined by running finite-element models of a radially confined uniaxial compression test and a plate sinkage test and comparing these results with laboratory and field experiments of the same. This effort resulted in the development of two sets of model parameters for low density snow, one set that is applicable for weak or “soft” snow and a second set that is representative of stronger or “hard” (aged or sintered) snow. Together, these models provide a prediction of the upper and lower bound of the macroscale snow response in this density range. Furthermore, the modeled snow compaction density agrees well with measured data. These models were used to simulate a tire rolling through new fallen snow and showed good agreement with the available field data over the same depth and density range.     

Comparison of micro-structural snowpack parameters derived from penetration resistance measurements with fracture character observations from compression tests

Compression tests are snow stability tests that are widely used by avalanche professionals and snow researchers to identify potential weak snowpack layers. Describing fracture character in addition to the number of taps required to initiate a fracture improves the interpretation of compression test results, since certain types of fractures, i.e. sudden fractures, are more often associated with skier-triggered avalanches. Digital snowpack penetrometers provide high resolution penetration resistance data of the snow cover with depth. The SnowMicroPen (SMP) was used to measure high resolution penetration resistance profiles in the snowpack next to compression tests. A reliable method to automatically detect the snow surface in the SMP signals was introduced. Furthermore, a method based on the autocorrelation of the penetration resistance signal was developed to identify the failure layers, identified using compression tests, in the penetration resistance profiles. Using field data from 190 penetration resistance measurements, each collected between two compression tests, micro-structural parameters associated with different types of fractures were identified. More than 550 fractures were classified as either Progressive Compression (1.3%), Resistant Planar (12.1%), Sudden Planar (50.4%), Sudden Collapse (26.8%) or non-planar Break (9.4%). Measurement and analysis were focussed on micro-structural properties of the failure layer, the layer adjacent to the failure layer and the slab above the failure layer. Sudden collapse fractures were found to have typical micro-structural snowpack parameters that are generally associated with unstable snow conditions, such as large differences in penetration resistance between the failure layer and the adjacent layer.     

Comparison of micro-structural snowpack parameters derived from penetration resistance measurements with fracture character observations from compression tests

Compression tests are snow stability tests that are widely used by avalanche professionals and snow researchers to identify potential weak snowpack layers. Describing fracture character in addition to the number of taps required to initiate a fracture improves the interpretation of compression test results, since certain types of fractures, i.e. sudden fractures, are more often associated with skier-triggered avalanches. Digital snowpack penetrometers provide high resolution penetration resistance data of the snow cover with depth. The SnowMicroPen (SMP) was used to measure high resolution penetration resistance profiles in the snowpack next to compression tests. A reliable method to automatically detect the snow surface in the SMP signals was introduced. Furthermore, a method based on the autocorrelation of the penetration resistance signal was developed to identify the failure layers, identified using compression tests, in the penetration resistance profiles. Using field data from 190 penetration resistance measurements, each collected between two compression tests, micro-structural parameters associated with different types of fractures were identified. More than 550 fractures were classified as either Progressive Compression (1.3%), Resistant Planar (12.1%), Sudden Planar (50.4%), Sudden Collapse (26.8%) or non-planar Break (9.4%). Measurement and analysis were focussed on micro-structural properties of the failure layer, the layer adjacent to the failure layer and the slab above the failure layer. Sudden collapse fractures were found to have typical micro-structural snowpack parameters that are generally associated with unstable snow conditions, such as large differences in penetration resistance between the failure layer and the adjacent layer.     

Modeling the effect of high temperature on the bond of FRP reinforcing bars to concrete

The effect of high temperature on the bond between fiber reinforced polymers (FRP) reinforcing bars (rebars) and concrete was studied. The bond strength exhibited a severe reduction of 80–90% at relatively low temperature (up to 200°C), accompanied by changes in the pullout load-slip behavior. A semi-empirical model was developed in order to describe the extent of reduction in the bond strength as the temperature rises. The model is based on the following parameters: glass transition temperature of the polymer layer at the surface of the rod; polymer's degree of crosslinking; the residual bond strength at high temperature after the polymer of the external layer of the rebar ceased to contribute to the bond. The parameters of the rods that were tested for pullout at various temperatures were introduced into the model. The output curves of bond–temperature relationships showed good agreement with the test results.     

3D numerical model of snow deformation without failure and its application to cold room mechanical tests

A three-dimensional model developed for the slow deformation, without macroscopic failure, of a stratified snow cover has been used to simulate laboratory mechanical tests performed on sieved snow. The model is based on a non-linear visco-elastic constitutive law for snow whose parameters depend on the snow temperature and density. Snow densification is derived from the bulk viscous strain. The model has been implemented in the Flac3D finite-difference code. The experimental device is a convergent channel in which snow is forced at a constant velocity in the range 1–100 μm s^− 1. Although snow is compressed under plane strain conditions, the channel geometry allows obtaining a multi-axial stress-state. Since the testing conditions involve ranges of variation of both the snow density and the strain-rate wider than those encountered for a natural snowpack, the constitutive relations of the model had to be modified. In this paper we present the constitutive model for snow, some details about its implementation into the Flac3D code, and its application to the numerical simulation of the mechanical tests. The comparison of the model and experimental results shows a relatively good agreement, although snow microstructure is accounted for only through its density. However, the treatment of the non-linearity of the viscosity must be improved. This 3D numerical model can be regarded as an interesting tool for assessing a constitutive law for snow on the basis of cold-room experiments, as well as for studying natural snow covers.     

3D numerical model of snow deformation without failure and its application to cold room mechanical tests

A three-dimensional model developed for the slow deformation, without macroscopic failure, of a stratified snow cover has been used to simulate laboratory mechanical tests performed on sieved snow. The model is based on a non-linear visco-elastic constitutive law for snow whose parameters depend on the snow temperature and density. Snow densification is derived from the bulk viscous strain. The model has been implemented in the Flac3D finite-difference code. The experimental device is a convergent channel in which snow is forced at a constant velocity in the range 1–100 μm s^− 1. Although snow is compressed under plane strain conditions, the channel geometry allows obtaining a multi-axial stress-state. Since the testing conditions involve ranges of variation of both the snow density and the strain-rate wider than those encountered for a natural snowpack, the constitutive relations of the model had to be modified. In this paper we present the constitutive model for snow, some details about its implementation into the Flac3D code, and its application to the numerical simulation of the mechanical tests. The comparison of the model and experimental results shows a relatively good agreement, although snow microstructure is accounted for only through its density. However, the treatment of the non-linearity of the viscosity must be improved. This 3D numerical model can be regarded as an interesting tool for assessing a constitutive law for snow on the basis of cold-room experiments, as well as for studying natural snow covers.     

Numerical modeling of liquid water movement through layered snow based on new measurements of the water retention curve

Liquid water movement in snow is an important aspect of wet snow metamorphism and is vital for forecasting wet snow avalanches. However, despite its importance, liquid water movement is over-simplified in the current version of the numerical model SNOWPACK, yielding an inadequate simulation of the water content profile. In general, estimations of liquid water flux in porous materials are based on hydraulic conductivity and suction. This paper presents a water transport model based on the van Genuchten formulation, with parameters obtained from gravity drainage column experiments. Simulations that try to describe the capillary barrier between layers of different grain sizes lead to long computation times because of the small time increments required. In this study, a new algorithm was developed and incorporated in the water transport model in order to simulate the capillary barrier using relatively long time increments (60 s). The model was then used to simulate water movement between snow layers of different grain size. The results confirm that a water-saturated layer forms at the boundary between fine and underlying very coarse snow, which is consistent with observations.The new water transport model was incorporated in SNOWPACK, which then produced an unstable water-saturated layer at the boundary between different grain sizes. Simulation results from the SNOWPACK model were compared with measurements. The main achievement in this study is that the natural capillary barrier was documented and then reproduced using the modified SNOWPACK model. Nevertheless, much work has still to be done to get fully satisfactory results for the reproducibility of grain size and liquid water content.     

Observations and simulations of snow surface temperature on cross-country ski racing courses

Fast skis are essential for an Olympic cross-country skiing athlete. Accurate and timely estimates of the snow surface conditions on a race course are needed to prepare race skis. For training purposes prior to the 2010 Winter Olympics, snow surface and snowpack observations were collected on the cross-country racing track at the Whistler Olympic Park, British Columbia during February 2008 and 2009. During periods with clear skies, snow surface temperatures varied by more than 10 °C around the course while temperatures in the stadium area increased by more than 16 °C from morning to early afternoon. Simulations using the SNOWPACK model of snow surface temperature were within 1 °C of those measured during a four day observation period in the stadium area. Idealized simulations were completed varying cloud cover, slope and aspect. These simulations provided realistic appearing changes in snow surface temperature as a function of time of day.     

Double Glow Plasma Surface Alloying Process Modeling Using Artificial Neural Networks

A model is developed for predicting the correlation between processing parameters and the technical target of double glow by applying artificial neural network (ANN). The input parameters of the neural network (NN) are source voltage, workpiece voltage, working pressure and distance between source electrode and workpiece. The output of the NN model is three important technical targets, namely the gross element content, the thickness of surface alloying layer and the absorpticm rate (the ratio of the mass loss of source materials to the increasing mass of workpiece) in the processing of double glow plasma surface alloying. The processing parameters and technical target are then used as a training set for an artificial neural network. The model is based on multiplayer feedforward neural network. A very good performance of the neural network is achieved and the calculated results are in good agreement with the experimental ones.     

Measurements of localized dynamic loading in a mountain snow cover

In the majority of fatal avalanches, skiers and snowmobilers apply load to the snow cover which triggers the initial failure in a weak layer. Understanding how the stress due to the dynamic surface load transmits through the snow cover can help people avoid situations where they can trigger avalanches. Capacitive sensors were used to measure this stress within the mountain snow cover. The three main variables affecting stress transmission through the snow cover investigated in this paper are the type of loading, depth and snow cover stratigraphy. At specific depths, snowmobiles added more stress than skiers did, thus increasing the probability of initiating a fracture in a weak layer and releasing a slab avalanche. The increased penetration depth of snowmobiles into the snow cover compared to skiers was the primary reason for this increase in stress. A decrease in stress was observed with increasing depth. A decrease in stress was observed with increased snow cover hardness. Supportive surface layers created a ‘bridging effect’ that spread stress out laterally and decreased the depth to which it penetrated.     

Theoretical and experimental studies on isothermal adsorption and desorption characteristics of a desiccant-coated heat exchanger

Dynamic characteristics of desiccant–coated heat exchangers (DCHEs) were experimentally measured by wind tunnel. The surface of the DCHE was coated with polymer sorbent desiccant. The isothermal adsorption and desorption experiments were conducted under the condition where the temperatures of the air and brine passing through the DCHE were identical.The experimental results were compared to that obtained from theoretical calculations. A diffusion model predicting the distribution of moisture concentration and temperature in the desiccant layer was introduced. The equivalent diffusion coefficient of the water inside the desiccant layer was determined from the experimental results.The adsorption and desorption speeds were at the maximum values at the beginning of the sorption processes, and then they gradually decreased. The equivalent diffusion coefficient was dependent on the temperature. Assuming the temperature dependence of the diffusion coefficient, the calculated sorption performance correlated well with that obtained from the experimental results.     

Squeeze flow characterisation of thermoplastic polymer

New manufacturing concepts developed by the CRC-ACS involve co-curing a thermoplastic polymer layer onto the surface of a composite component. The layer can be reshaped to alter the dimensions of the laminate locally. A major physical phenomenon involved in these uses is squeeze flow of the thermoplastic polymer.

In the present work, the squeeze flow of a selected thermoplastic at high temperature and under given pressure was studied. A power-law model for viscosity variation with shear rate was assumed to describe the non-Newtonian behaviour of the thermoplastic at high temperatures. Based on the viscosity model, a fluid mechanics model was derived for the squeeze flow between approaching parallel plates of infinite length. The model relates the plate approaching speed to the applied pressure, thermoplastic geometry (both thickness and width) and power-law viscosity model parameters.

An experimental method and data analysis procedure were developed to determine the parameters of the power-law model that describes the viscosity of the thermoplastic material. Tests were conducted under isothermal conditions by squeezing composite laminates with integrated thermoplastic films. The transient thickness of the thermoplastic film was continuously measured and used to calculate the power-law model parameters for each test. A temperature range of 180–200 °C was investigated to establish the dependence of the power-law model parameters upon temperature.

Using the squeeze flow model, and experimentally determined power-law viscosity model parameters, the effect of various process conditions on the thermoplastic thickness was investigated. Predictions were found to be valid for situations where the shear rate range matched that achieved during the power-law viscosity model parameters tests.     

A semi-theoretical model for predicting refrigerant/lubricant mixture pool boiling heat transfer

This paper outlines the framework of a semi-theoretical model for predicting the pool boiling heat transfer of refrigerant/lubricant mixtures on a roughened, horizontal, flat pool-boiling surface. The predictive model is based on the mechanisms involved in the formation of the lubricant excess layer that exists on the heat transfer surface. The lubricant accumulates on the surface in excess of the bulk concentration via preferential evaporation of the refrigerant from the bulk refrigerant/lubricant mixture. As a result, excess lubricant resides in a thin layer on the surface and influences the boiling performance, giving either an enhancement or degradation in heat transfer. A dimensionless excess layer parameter and a thermal boundary layer constant were derived and fitted to data in an attempt to generalize the model to other refrigerant/lubricant mixtures. The model inputs include transport and thermodynamic refrigerant properties and the lubricant composition, viscosity, and critical solution temperature with the refrigerant. The model predicts the boiling heat transfer coefficient of three different mixtures of R123 and lubricant to within ±10%. Comparisons of heat transfer predictions to measurements for 13 different refrigerant/lubricant mixtures were made, including two different refrigerants and three different lubricants.     

Predicting the fracture character of weak layers from snowpack penetrometer signals

Digital penetrometers provide reliable assessments of snow penetration resistance with depth. However, extracting useful information from the signals relating to snow stability has proved to be challenging. In this study, penetrometer profiles were collected in close proximity to compression tests. A scheme for predicting the fracture character of weak layers in the compression tests from the penetrometer signals is presented. When a two-group classification between sudden (Q1) (an indicator of instability) and other fracture character groups was performed, potential failure layers were correctly classified 80% of the time. The variables offering the best discrimination between sudden and other categories were weak layer thickness, average force gradient above the weak layer, and both the average and the maximum force gradient below the weak layer. The effect of introducing randomly selected layers into the prediction scheme was also investigated. When such layers were introduced, the classification rate dropped to 67%, indicating that more effective fracture character prediction occurred when weak layers were manually pre-identified. This suggests that this scheme should be used in conjunction with a weak layer detection model rather than as a stand alone analytical technique for the purpose of critical weak layer identification. The classification rate dropped further to 55% when a more detailed, four-group classification scheme was used.     

Predicting the fracture character of weak layers from snowpack penetrometer signals

Digital penetrometers provide reliable assessments of snow penetration resistance with depth. However, extracting useful information from the signals relating to snow stability has proved to be challenging. In this study, penetrometer profiles were collected in close proximity to compression tests. A scheme for predicting the fracture character of weak layers in the compression tests from the penetrometer signals is presented. When a two-group classification between sudden (Q1) (an indicator of instability) and other fracture character groups was performed, potential failure layers were correctly classified 80% of the time. The variables offering the best discrimination between sudden and other categories were weak layer thickness, average force gradient above the weak layer, and both the average and the maximum force gradient below the weak layer. The effect of introducing randomly selected layers into the prediction scheme was also investigated. When such layers were introduced, the classification rate dropped to 67%, indicating that more effective fracture character prediction occurred when weak layers were manually pre-identified. This suggests that this scheme should be used in conjunction with a weak layer detection model rather than as a stand alone analytical technique for the purpose of critical weak layer identification. The classification rate dropped further to 55% when a more detailed, four-group classification scheme was used.