蓄冷板释冷过程的数值模拟和实验研究

对蓄冷板内共晶液的热力学特性进行了分析,并且建立了蓄冷板释冷的数学模型。通过数值模拟的方法,模拟了NaCl蓄冷板在初始温度为-30℃,环境温度为-10℃、0℃和10℃三种不同温度条件下的释冷过程,并且通过相关的实验研究,对模拟结果的准确性进行了验证。通过研究得到了蓄冷板在不同条件下的释冷过程及特点。研究结果表明:在NaCl蓄冷板的释冷过程中,当其所处的环境温度高于-21.2℃,即其共晶温度时,外界环境温度会对冷板内共晶冰开始发生相变的时刻产生较大影响;外界环境温度越高,蓄冷板内共晶冰开始融化到完全融化所需要的时间越短。计算结果与实验结果吻合良好,两者之间的平均偏差小于0.5℃,说明数学模型及计算方法的可靠性。     

水下爆破破冰爆炸冲击波传播规律数值分析

利用动力分析软件ANSYS/LS-DYNA模拟研究水下爆破破冰过程中爆炸冲击波压力的作用特征和传播规律,对比分析在冰体覆盖的相对封闭条件和常规水下爆炸时水中压力变化的差异性。研究表明:爆炸冲击波产生的水压力以炸药为中心向四周传播,对冰面破碎起主要作用,被扰动冰体主要发生振动折裂。炸药周围近区压力初始峰值大体上相同,爆源远区相差较大,冰盖的存在减弱了爆破能量的耗散。对于相同集中药包,入水深度直接影响爆破破冰效果。和常规水下爆炸相比,在冰体覆盖的相对封闭条件下水中峰值压力较小,衰减速度较慢。     

Empirical approach to develop a multilayer icebonded abrasive polishing tool for ultrafine finishing of Ti-6Al-4V alloy

This paper covers the development of a multilayer icebonded abrasive polishing (IBAP) tool for multistage polishing of Ti-6Al-4V alloy specimens based on a systematic study that determined the number of layers, thickness of each layer, and the type, size and concentration of abrasives in each layer. Based on this study, a three-layered IBAP tool with the bottom layer consisting of soft aluminum oxide abrasives of 3?µm size with 5% concentration, the middle layer with moderately hard silicon carbide abrasives of 8?µm size with 10% concentration and the top layer with hard boron carbide abrasives of 15?µm size with 30% concentration was formulated for ultrafine finishing of Ti-6Al-4V alloy specimen in a single setup. The performance of the three-layered IBAP tool assessed in terms of finish and morphology over the work surface showed 81% improvement in surface finish, showing its effectiveness over a single-layered IBAP tool. Polishing studies have clearly demonstrated the generation of ultrafine surfaces, yielding a finish of 37?nm while the morphological studies on the polished surface have shown a nearly scratch-free surface on the Ti-6Al-4V alloy.     

Validation of the Climate-SAF surface broadband albedo product: Comparisons with in situ observations over Greenland and the ice-covered Arctic Ocean

This paper describes a validation study performed by comparing the Climate-SAF Surface Albedo Product (SAL) to ground truth observations over Greenland and the ice-covered Arctic Ocean. We compare Advanced Very High Resolution Radiometer (AVHRR)-based albedo retrievals to data from the Greenland Climate Network (GCN) weather stations and the floating ice station Tara for polar summer 2007. The AVHRR dataset consists of 2755 overpasses. The overpasses are matched to in situ observations spatially and temporally. The SAL algorithm presented here derives the surface broadband albedo from AVHRR channels 1 and 2 using an atmospheric correction, temporal sampling of an empirical Bidirectional Reflectance Distribution Function (BRDF), and a narrow-to-broadband conversion algorithm. The satellite product contains algorithms for snow, sea ice, vegetation, bare soil, and water albedo. At the Summit and DYE-2 stations on the Greenland ice sheet, instantaneous SAL RMSE is 0.073. The heterogeneous surface conditions at satellite pixel scale over the stations near the Greenland west coast increase RMSE to > 0.12. Over Tara, the instantaneous SAL RMSE is 0.069. The BRDF sampling approach reduces RMSE over the ice sheet to 0.053, and to 0.045 over Tara. Taking into account various sources of uncertainty for both satellite retrievals and in situ observations, we conclude that SAL agrees with in situ observations within their limits of accuracy and spatial representativeness.     

Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake ice, and NDVI in southwest Alaska

Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake ice, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) calibrated radiance, snow cover extent, and vegetation index products for interpreting interannual variation in the duration and extent of snowpack, lake ice, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions.Throughout the observation period (2001-2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake ice season lagged the snow season by 2 to 3 months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and ice metrics, with start-of-season dates comparatively consistent across years. The start of growing season and snow melt were related to one another as they are both temperature dependent. Higher than average temperatures during the El Niño winter of 2002-2003 were expressed in anomalous ice and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal trends of each of these seasonal metrics and to map areas of change for the study area.     

六角网格系统下的多边形填充算法

针对六角网格系统下图形、图像处理及显示时像素之间相邻的唯一性,挺出六角网格系统下的多边形填充算法,其中包括边界填充算法和扫描线填充算法,采用图示与伪代码的方法描述箅法。与矩形网格上的图像处理算法相比,六角网格系统上的图像处理算法具有更好的唯一性和简便性。     

Evaluation of the HUT modified snow emission model over lake ice using airborne passive microwave measurements

The algorithms designed to estimate snow water equivalent (SWE) using passive microwave measurements falter in lake-rich high-latitude environments due to the emission properties of ice covered lakes on low frequency measurements. Microwave emission models have been used to simulate brightness temperatures (Tbs) for snowpack characteristics in terrestrial environments but cannot be applied to snow on lakes because of the differing subsurface emissivities and scattering matrices present in ice. This paper examines the performance of a modified version of the Helsinki University of Technology (HUT) snow emission model that incorporates microwave emission from lake ice and sub-ice water. Inputs to the HUT model include measurements collected over brackish and freshwater lakes north of Inuvik, Northwest Territories, Canada in April 2008, consisting of snowpack (depth, density, and snow water equivalent) and lake ice (thickness and ice type). Coincident airborne radiometer measurements at a resolution of 80 × 100 m were used as ground-truth to evaluate the simulations.The results indicate that subsurface media are simulated best when utilizing a modeled effective grain size and a 1 mm RMS surface roughness at the ice/water interface compared to using measured grain size and a flat Fresnel reflective surface as input. Simulations at 37 GHz (vertical polarization) produce the best results compared to airborne Tbs, with a Root Mean Square Error (RMSE) of 6.2 K and 7.9 K, as well as Mean Bias Errors (MBEs) of −8.4 K and −8.8 K for brackish and freshwater sites respectively. Freshwater simulations at 6.9 and 19 GHz H exhibited low RMSE (10.53 and 6.15 K respectively) and MBE (−5.37 and 8.36 K respectively) but did not accurately simulate Tb variability (R = −0.15 and 0.01 respectively). Over brackish water, 6.9 GHz simulations had poor agreement with airborne Tbs, while 19 GHz V exhibited a low RMSE (6.15 K), MBE (−4.52 K) and improved relative agreement to airborne measurements (R = 0.47). Salinity considerations reduced 6.9 GHz errors substantially, with a drop in RMSE from 51.48 K and 57.18 K for H and V polarizations respectively, to 26.2 K and 31.6 K, although Tb variability was not well simulated. With best results at 37 GHz, HUT simulations exhibit the potential to track Tb evolution, and therefore SWE through the winter season.     

Semi-automated feature-tracking of East Antarctic sea ice from Envisat ASAR imagery

While feature tracking of sea ice using cross-correlation methods on pairs of satellite Synthetic Aperture Radar (SAR) images has been extensively carried out in the Arctic, this is not the case in the Antarctic. This is due to the dynamic nature of Antarctic pack ice, its microwave signature, the tendency for SAR swath paths to be poorly aligned with the often narrow sea ice zone around the continent and inadequate satellite sampling. A semi-automated system, known as IPADS (IMCORR [IMageCORRelation] Processing, Analysis and Display System), has been developed to map fast ice and pack ice in Antarctica using multiple pairs of SAR images. The software processing pipeline uses overlapping image pairs which are geocoded and roughly registered using only data contained in the image headers. Next, fast ice maps are rapidly generated using zero motion features located within ocean regions. This also provides precise image registration. Finally, the same image pairs are re-examined for pack ice motion in a slower off-line batch process. The pack and fast ice are identified using a cluster-based search method which compares both location and motion information. Each image pair generates a NetCDF file which adds to a growing database of Antarctic sea ice motion and ice roughness. Five image-pair examples are presented to illustrate the methods used as well as their strengths and limitations. Substantial pack ice motion can often be detected in the marginal ice zone on SAR images only a few days apart.     

Correcting for the influence of frozen lakes in satellite microwave radiometer observations through application of a microwave emission model

The spatial resolution of passive microwave observations from space is of the order of tens of kilometers with currently available instruments, such as the Special Sensor Microwave/Imager (SSM/I) and Advanced Microwave Scanning Radiometer (AMSR-E). The large field of view of these instruments dictates that the observed brightness temperature can originate from heterogeneous land cover, with different vegetation and surface properties.In this study, we assess the influence of freshwater lakes on the observed brightness temperature of AMSR-E in winter conditions. The study focuses on the geographic region of Finland, where lakes account for 10% of the total terrestrial area. We present a method to mitigate for the influence of lakes through forward modeling of snow covered lakes, as a part of a microwave emission simulation scheme of space-borne observations. We apply a forward model to predict brightness temperatures of snow covered sceneries over several winter seasons, using available data on snow cover, vegetation and lake ice cover to set the forward model input parameters. Comparison of model estimates with space-borne observations shows that the modeling accuracy improves in the majority of examined cases when lakes are accounted for, with respect to the case where lakes are not included in the simulation. Moreover, we present a method for applying the correction to the retrieval of Snow Water Equivalent (SWE) in lake-rich areas, using a numerical inversion method of the forward model. In a comparison to available independent validation data on SWE, also the retrieval accuracy is seen to improve when applying the influence of snow covered lakes in the emission model.