纤维细度和细度分布测定的数字分布图处理

对于毛生产者、商人及加工者来说,纤维细度是取重要的物理特性,它也是最终产品的耐穿性、舒适性和质量的重要指标。除了纤维平均细度之外,在毛质量的测定中,细度分布值是最重要的。测定纤维细度主要通过仪器使用气流万法。可是这种方法只能测定纤维平均细度,包括样品中杂质造成的疵点。费时间的微投影法广泛用于测定纤维细度分布。操作者不适当的统计会影响到测定结果的可靠性。这个资料不能满足当前更精确的纤维细度分析和在纺丝性能及质量方面的效果的要求。 Siegfried

Model heat source using actual distribution of laser power density for simulation of laser processing

The model of heat source(MHS) which reflects the thermal interaction between materials and laser during processing determines the accuracy of simulation results. To acquire desirable simulations results, although various modifications of heat sources in the aspect of absorption process of laser by materials have been purposed, the distribution of laser power density(DLPD) in MHS is still modeled theoretically. However, in the actual situations of laser processing, the DLPD is definitely different from the ideal models. So, it is indispensable to build MHS using actual DLPD to improve the accuracy of simulation results. Besides, an automatic modeling method will be benefit to simplify the tedious pre-processing of simulations. This paper presents a modeling method and corresponding algorithm to model heat source using measured DLPD. This algorithm automatically processes original data to get modeling parameters and provides a step MHS combining with absorption models. Simulations and experiments of heat transfer in steel plates irradiated by laser prove the mothed and the step MHS. Moreover, the investigations of laser induced thermal-crack propagation in glass highlight the signification of modeling heat source based on actual DLPD and demonstrate the enormous application of this method in the simulation of laser processing.

Development of a mass model in estimating weight-wise particle size distribution using digital image processing

Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.

Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data

At 5:39 am on June 24, 2017, a landslide occurred in the village of Xinmo in Maoxian County, Aba Tibet and Qiang Autonomous Prefecture(Sichuan Province, Southwest China). On June 25, aerial images were acquired from an unmanned aerial vehicle(UAV), and a digital elevation model(DEM) was processed. Landslide geometrical features were then analyzed. These are the front and rear edge elevation, accumulation area and horizontal sliding distance. Then, the volume and the spatial distribution of the thickness of the deposit were calculated from the difference between the DEM available before the landslide, and the UAV-derived DEM collected after the landslide. Also, the disaster was assessed using high-resolution satellite images acquired before the landslide. These include Quick Bird, Pleiades-1 and GF-2 images with spatial resolutions of 0.65 m, 0.70 m, and 0.80 m, respectively, and the aerial images acquired from the UAV after the landslide with a spatial resolution of 0.1 m. According to the analysis, the area of the landslide was 1.62 km2, and the volume of the landslide was 7.70 ± 1.46 million m3. The average thickness of the landslide accumulation was approximately 8 m. The landslide destroyed a total of 103 buildings. The area of destroyed farmlands was 2.53 ha, and the orchard area was reduced by 28.67 ha. A 2-km section of Songpinggou River was blocked and a 2.1-km section of township road No. 104 was buried. Constrained by the terrain conditions, densely populated and more economically developed areas in the upper reaches of the Minjiang River basin are mainly located in the bottom of the valleys. This is a dangerous area regarding landslide, debris flow and flash flood events Therefore, in mountainous, high-risk disaster areas, it is important to carefully select residential sites to avoid a large number of casualties.

Experimental study of the optical fiber characteristics by digital hologram

The characteristics of optical fiber are quite important for improving the performance of optical fiber communication and sensor systems.Based on the Mach-Zehnder interferometer,a new measuring method is proposed and the digital holograms between the single mode fibers(SMFs) and specialty double-cladding(DC) fibers are analyzed.The experimental results show that the fringe density can be changed under the conditions of coaxial and off-axial interferences.Therefore it can be used to analyze the optical fiber characteristics including refractive index distribution,fiber modes,phase difference,etc.

Contributions of non-tectonic micro-fractures to hydraulic fracturing—A numerical investigation based on FSD model

Shale gas has been discovered in the Upper Triassic Yanchang Formation, Ordos Basin, China. Due to the weak tectonic activities in which the shale plays, core observations indicate abundant random non-tectonic micro- fractures in the producing shales. The non-tectonic micro-fractures are different from tectonic fractures and are characterized by being irregular, curved, discontinuous, and randomly distributed. The role of micro-fractures in hydraulic fracturing for shale gas development is currently poorly understood yet potentially critical. Two-dimensional computational modeling studies have been used in an initial attempt toward understanding how naturally random fractured reservoirs respond during hydraulic fracturing. The aim of the paper is to investigate the effect of random non-tectonic fractures on hydraulic fracturing. The numerical models with random non-tectonic micro-fractures are built by extracting the fractures of rock blocks after repeated heating and cooling, using a digital image process. Simulations were conducted as a function of:(1) the in-situ stress ratio;(2) internal friction angle of random fractures;(3) cohesion of random fractures;(4) operational variables such as injection rate; and(5) variable injection rate technology. A sensitivity study reveals a number of interesting observations resulting from these parameters on the shear stimulation in a natural fracture system. Three types of fracturing networks were observed from the studied simulations, and the results also show that variable injection rate technology is most promising for producing complex fracturing networks. This work strongly links the production technology and geomechanical evaluation. It can aid in the understanding and optimization of hydraulic fracturing simulations in naturally random fractured reservoirs.