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Open access

Yuzheng Lu, Yang Wang and Weidong Gao

Abstract

In this study, the wicking properties of ring and compact-siro ring spun staple yarns were compared. The twist level, which is related to the structure of the staple yarns, was found to significantly influence the wicking property of the two kinds of yarn. Polyester staple fibers with 1.33 dtex × 38 mm were selected as the staple fiber material, and the effect of the twist level on the wicking property was investigated using the capillary rise method. The results show that with a decreasing twist coefficient, the wicking height increases with a decrease in yarn compactness. The compact-siro spun yarn showed better wicking properties owing to it special ply yarn structure. Furthermore, the tension property of the yarns decreased significantly with a decrease in the twist coefficient. Compact-siro spinning was carried out to obtain staple yarns with lower twist coefficients, and the yarns showed great improvement in terms of yarn strength, fiber straightness, and wicking properties. Thus, compact-siro spinning is an efficient method to improve the wicking properties of staple yarns.

Open access

Xuan Luo, Gaoming Jiang and Honglian Cong

Abstract

This paper focuses on the better performance between the garment simulation result and the simulation speed. For simplicity and clarity, a notation “PART” is defined to indicate the areas between the garment and the human body satisfying some constraints. The discrete mechanical model can be achieved by the two-stage process. In the first stage, the garment can be divided into several PARTs constrained by the distance. In the second stage, the mechanical model of each PART is formulated with a mathematical expression. Thus, the mechanical model of the garment can be obtained. Through changing the constrained distance, the simulation result and the simulation speed can be observed. From the variable distance, a desired value can be chosen for an optimal value. The results of simulations and experiments demonstrate that the better performance can be achieved at a higher speed by saving runtime with the acceptable simulation results and the efficiency of the proposed scheme can be verified as well.

Open access

Massimiliano Zappa, Ladislav Holko, Martin Šanda, Tomáš Vitvar and Juraj Parajka

Open access

Anton Yu. Komarov, Yury G. Seliverstov, Pavel B. Grebennikov and Sergey A. Sokratov

Abstract

The aim of the investigation was assessment of spatial variability of the characteristics of snowpack, including the snow water equivalent (SWE) as the main hydrological characteristic of a seasonal snow cover. The study was performed in Khibiny Mountains (Russia), where snow density and snow cover stratigraphy were documented with the help of the SnowMicropen measurements, allowing to determine the exact position of the snow layers’ boundaries with accuracy of 0.1 cm. The study site was located at the geomorphologically and topographically uniform area with uniform vegetation cover. The measurement was conducted at maximum seasonal SWE on 27 March 2016. Twenty vertical profiles were measured along the 10 m long transect. Vertical resolution depended on the thickness of individual layers and was not less than 10 cm. The spatial variation of the measured snowpack characteristics was substantial even within such a homogeneous landscape. Bulk snow density variability was similar to the variability in snow height. The total variation of the snowpack SWE values along the transect was about 20%, which is more than the variability in snow height or snow density, and should be taken into account in analysis of the results of normally performed in operational hydrology snow course SWE estimations by snow tubes.

Open access

Kerstin Hürkamp, Nadine Zentner, Anne Reckerth, Stefan Weishaupt, Karl-Friedrich Wetzel, Jochen Tschiersch and Christine Stumpp

Abstract

High amounts of precipitation are temporarily stored in high-alpine snow covers and play an important role for the hydrological balance. Stable isotopes of hydrogen (δ2H) and oxygen (δ18O) in water samples have been proven to be useful for tracing transport processes in snow and meltwater since their isotopic ratio alters due to fractionation. In 18 snow profiles of two snowfall seasons, the temporal and spatial variation of isotopic composition was analysed on Mt. Zugspitze. The δ18O and δ2H ranged between -26.7‰ to -9.3‰ and -193.4‰ to -62.5‰ in 2014/2015 and between -26.5‰ to -10.5‰ and -205.0‰ to -68.0‰ in 2015/2016, respectively. Depth-integrated samples of entire 10 cm layers and point measurements in the same layers showed comparable isotopic compositions. Isotopic composition of the snowpack at the same sampling time in spatially distributed snow profiles was isotopically more similar than that analysed at the same place at different times. Melting and refreezing were clearly identified as processes causing isotope fractionation in surficial, initial base or refrozen snow layers. For the future, a higher sampling frequency with detailed isotopic composition measurements during melt periods are recommended to improve the understanding of mass transport associated with snowmelt.

Open access

Martin Šanda, Tomáš Vitvar and Jakub Jankovec

Abstract

Nine years of seasonal δ18O values in precipitation, soilwater and groundwater were evaluated in the Uhlířská catchment between 2008 and 2016 and recharge winter/summer ratios were calculated using δ18O values. The longterm average 18O content in groundwater is lower than the mean weighted 18O content in precipitation. This is explained by more than 50% of winter- and snowmelt- induced groundwater recharge that occurs in all years except of 2010 and 2013. The recharge of the peat organic soil water is balanced between summer and winter, whereas the mineral hillslope soil is dominantly recharged by summer precipitation. The 67% portion of baseflow, dominantly generated in the winter season, is composed of groundwater and peat organic soil water, according to the hydrochemical distribution of runoff components. Isotopic mass balance of individual winters shows that precipitation in warmer winters is entirely transformed into outflow until the end of the winter season, generating no significant water storage for potential drought periods

Open access

Philippe Riboust, Guillaume Thirel, Nicolas Le Moine and Pierre Ribstein

Abstract

Conceptual degree-day snow models are often calibrated using runoff observations. This makes the snow models dependent on the rainfall-runoff model they are coupled with. Numerous studies have shown that using Snow Cover Area (SCA) remote sensing observation from MODIS satellites helps to better constrain parameters. The objective of this study was to calibrate the CemaNeige degree-day snow model with SCA and runoff observations. In order to calibrate the snow model with SCA observations, the original CemaNeige SCA formulation was revisited to take into account the hysteresis that exists between SCA and the snow water equivalent (SWE) during the accumulation and melt phases. Several parametrizations of the hysteresis between SWE and SCA were taken from land surface model literature. We showed that they improve the performances of SCA simulation without degrading the river runoff simulation. With this improvement, a new calibration method of the snow model was developed using jointly SCA and runoff observations. Further analysis showed that the CemaNeige calibrated parameter sets are more robust for simulating independent periods than parameter sets obtained from discharge calibration only. Calibrating the snow model using only SCA data gave mixed results, with similar performances as using median parameters from all watersheds calibration.

Open access

Jiajia Peng, Gaoming Jiang and Honglian Cong

Abstract

To realize 3D garment simulation online and show the wearing effect of different body types, a method for rapid parametric human modeling is proposed in this article. The parameterization consists of two phases. In the first phase, the characteristic parameters of the sample model are extracted according to the different types of feature information. In the second phase, the deformation is realized by combining the axial deformation method and the radial weight. Thus, according to contrasts between the input measurement and the sample sizes, parametric human modeling is realized by deformation of the sample model. In the deformation stage, the axis curve is simplified to the straight-line segment in the axis deformation method, reducing the calculation. Comparative analysis and the results of experiments demonstrate that the better performance can be achieved at a higher speed, and this method realizes real-time parametric human modeling.

Open access

A. Arda Şorman, Gökçen Uysal and Aynur Şensoy

Abstract

Predicting snow cover dynamics and relevant streamflow due to snowmelt is a challenging issue in mountainous basins. Spatio-temporal variations of snow extent can be analyzed using probabilistic snow cover maps derived from satellite images within a relatively long period. In this study, Probabilistic Snow Depletion Curves (P-SDCs) and Probabilistic Snow Lines (P-SLs) are acquired from Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-filtered daily snow cover images. Analyses of P-SDCs show a strong correlation with average daily runoff (R2 = 0.90) and temperature (R2 = 0.96). On the other hand, the challenge lies in developing noteworthy methods to use P-SDCs in streamflow estimations. Therefore, the main objective is to explore the feasibility of producing probabilistic runoff forecasts with P-SDC forcing in a snow dominated basin. Upper Euphrates Basin in Turkey has large snow extent and high snowmelt contribution during spring and summer periods. The melting characteristics are defined by P-SDCs using MODIS imagery for 2001-2012. The value of snow probability maps on ensemble runoff predictions is shown with Snowmelt Runoff Model (SRM) during 2013-2015 where the estimated runoff values indicate good consistency (NSE: 0.47-0.93) with forecasts based on the derived P-SDCs. Therefore, the probabilistic approach distinguishes the snow cover characteristics for a region and promotes a useful methodology on the application of probabilistic runoff predictions especially for snow dominated areas.