scholarly journals The movement and forces of spinning solution in the nozzle during high-speed centrifugal spinning

2019 ◽  
Vol 14 ◽  
pp. 155892501982820 ◽  
Author(s):  
Yaoshuai Duan ◽  
Zhiming Zhang ◽  
Binbin Lu ◽  
Boya Chen ◽  
Zilong Lai
Keyword(s):  
Rotational Speed ◽  
High Speed ◽  
Large Scale ◽  
Production Efficiency ◽  
Critical Value ◽  
Parametric Model ◽  
Rotating Speed ◽  
Centrifugal Spinning ◽  
Novel Method

High-speed centrifugal spinning is a novel method to fabricate nanofiber. It has the potential to fabricate nanofiber on a large scale because its production efficiency is much greater than traditional methods. Nozzle is an important part of high-speed centrifugal spinning equipment because its length, shape, and diameter all will affect the morphology and quality of nanofiber. It is useful to study the movement and forces of spinning solution in the nozzle. In this article, the principle and equipment structure of high-speed centrifugal spinning are briefly introduced at first. Then the movement and forces of spinning solution are analyzed by establishing parametric model at nozzle. It can be found that the spinning solution is ejected from nozzle when the rotating speed reaches a critical value. The critical rotating speed is inversely proportional to the radius of nozzle and directly proportional to the viscosity of spinning solution. There are several nozzle structures proposed and compared for nozzle optimization. Finally, the effects of nozzle parameters, concentration of spinning solution, and rotational speed on the morphology of nanofiber are verified by high-speed centrifugal spinning experiments. It lays the foundation for optimizing spinning equipment.

scholarly journals Using Sentinel-2 Images to Estimate Topography, Tidal-Stage Lags and Exposure Periods over Large Intertidal Areas

2021 ◽  
Vol 13 (2) ◽  
pp. 320
Author(s):  
José P. Granadeiro ◽  
João Belo ◽  
Mohamed Henriques ◽  
João Catalão ◽  
Teresa Catry
Keyword(s):  
Large Scale ◽  
Exposure Period ◽  
Intertidal Area ◽  
Digital Elevation ◽  
Geographical Bias ◽  
Novel Method ◽  
Tidal Stage ◽  
Sentinel 2

Intertidal areas provide key ecosystem services but are declining worldwide. Digital elevation models (DEMs) are important tools to monitor the evolution of such areas. In this study, we aim at (i) estimating the intertidal topography based on an established pixel-wise algorithm, from Sentinel-2 MultiSpectral Instrument scenes, (ii) implementing a set of procedures to improve the quality of such estimation, and (iii) estimating the exposure period of the intertidal area of the Bijagós Archipelago, Guinea-Bissau. We first propose a four-parameter logistic regression to estimate intertidal topography. Afterwards, we develop a novel method to estimate tide-stage lags in the area covered by a Sentinel-2 scene to correct for geographical bias in topographic estimation resulting from differences in water height within each image. Our method searches for the minimum differences in height estimates obtained from rising and ebbing tides separately, enabling the estimation of cotidal lines. Tidal-stage differences estimated closely matched those published by official authorities. We re-estimated pixel heights from which we produced a model of intertidal exposure period. We obtained a high correlation between predicted and in-situ measurements of exposure period. We highlight the importance of remote sensing to deliver large-scale intertidal DEM and tide-stage data, with relevance for coastal safety, ecology and biodiversity conservation.

Quality of Service on Link Aggregation Network Virtualization for Docker Containers

2019 ◽  
Vol 886 ◽  
pp. 227-232
Author(s):  
Yanapat Chuchuen ◽  
Kritwara Rattanaopas ◽  
Sarapee Chunkaew
Keyword(s):  
Traffic Control ◽  
Load Balance ◽  
High Speed ◽  
Large Scale ◽  
Network Virtualization ◽  
Network Bandwidth ◽  
Working Together ◽  
Multiple Network ◽  
Implementation Tool

Docker engine is an extremely powerful tool for PaaS platform of cloud computing. It gives benefits for large-scale of internet services. Web service is basic service for everyone who requires to access internet that web infrastructure must has scalability with load-balance web server called reverse proxy. The key answers for a large-scale web must have multiple web servers working together with high speed bandwidth. Moreover, multiple clusters can find in the same data center there are required to assign priority and quality of each cluster service. We investigate load-balance assign link aggregation with network QoS by using pipework script and traffic control tool in frontend reverse proxy server on each cluster. Our research evaluates scenario of network QoS ratios which include 50/50, 60/40, 70/30 and 80/20. We compare network bandwidth between both web reverse proxy clusters. The results present our designed and implementation tool not only can control network QoS on each web reverse proxy cluster in all load-balance link aggregation modes which include round-robin, XOR and ALB but also those of clusters can access multiple network interface. In experiment, average network bandwidths in all QoS cases are around 200 MB per second for link aggregation of 2 gigabit interface.

Affect of Application of Hairiness Reduction Equipment on Winding Quality

2011 ◽  
Vol 331 ◽  
pp. 437-443
Author(s):  
Jian Ping Lin ◽  
Hong Jun Cui
Keyword(s):  
High Speed ◽  
Production Efficiency ◽  
Standard Test ◽  
Appearance Quality ◽  
Yarn Quality ◽  
Test Conditions ◽  
Yarn Hairiness ◽  
The Given

In order to reduce yarn hairiness of spooling procedure and improve the quality of knotless yarn, contrast experiments, under the given standard test conditions, is performed among several cheese with or without airflow hairiness reduction equipment (HRE); analyzing and discussing the application effect and affect of HRE on yarn quality indexs. It is found from the investigation that the application of airflow HRE can effectively reduce yarn hairiness and also reduce yarn’s CV value of tenacity and improve its minimum tenacity, which can decrease ends’ breakage and machine suspension during high speed warping and high speed weaving production and improve weaving efficiency and appearance quality of fabric. Through analytic comparison, the application of airflow HRE will slightly increase yarn neps, but it’s still an effective method for reducing yarn hairiness and improve fabric appearance quality and weaving production efficiency.

scholarly journals The Production of Rencong Souvenir Based on Reused Brass Metal Waste

2019 ◽  
Vol 1 (2) ◽  
pp. 119-124
Author(s):  
Ahmad Farhan
Keyword(s):  
Metal Forming ◽  
Large Scale ◽  
Production Efficiency ◽  
Raw Materials ◽  
Economic Sectors ◽  
Field Training ◽  
Metal Waste ◽  
The Cost

The Traditional metal forming in fabricating rencong as souvenir requires high demands of energy, time, and accuracy skills from the blacksmith, but the quality that has been obtained is quite low, which includes colors diversity, and non-uniformity of brightness. The raw materials of brass metal are importantly needed for manufacturers, so that the cost of productions is relatively expensive. This study aims to improve the technology for fabricating rencong souvenir, which is expected to increase the production efficiency as well as conserving and improving the cultural and economic sectors. The simple casting techniques were conducted to be taught to the craftsmen from designing, mold and field training. This technology was able to be adopted very well by the craftsmen, while the rencong blades were produced in large scale by utilizing the brass metal waste. The diversity of sizes and shapes were obtained in small size and shapes blades, and the uniformity of color brightness was produced, so that the quality of souvenirs increases. Thus, the application of this technology can increase the income of craftsmen and the quality of souvenirs.

Thickness and Fiber Content Optimization in VARTM Method for High Speed Craft

2013 ◽  
Vol 789 ◽  
pp. 412-416 ◽  
Author(s):  
Sunaryo ◽  
Gerry Liston Putra ◽  
Sri Maharani Lestari
Keyword(s):  
High Speed ◽  
Production Efficiency ◽  
High Strength ◽  
Fiber Content ◽  
Optimum Number ◽  
Material Efficiency ◽  
Hull Structure ◽  
The Matrix ◽  
Improve Production Efficiency

To improve production efficiency and quality of fiber-glass boatyards many research have been done both through technological as well as management aspects. One of these developments is Vacuum Assisted Resin Transfer Molding (VARTM) which is claimed to have high strength and material efficiency. This method has not much been applied in Indonesian boatyards, most of them are still using conventional hand lay-up. The research is aimed to investigate the strength of the composite and the optimum amount of materials to obtain the required strength for its application on boat buildings. Experimental approach was conducted in the research using 800 biaxial and 900 unidirectional E-glass for reinforcement, and vinylester (RIPOXY R-802-EX-1) resin for the matrix. The ultimate tensile strength and Youngs modulus of the composites are obtained through tensile and flexural test based on ASTM D 3039 and ASTM D 790 standards. The data obtained are used to determine the optimum number of layers and fiber content on certain locations of the boat hull structure in order to comply with the requirements of classification rules.

scholarly journals A Novel Method of Constrained Feature Selection by the Measurement of Pairwise Constraints Uncertainty

2020 ◽  
Author(s):  
Kamal Berahmand ◽  
Mehrdad Rostami ◽  
Saman Forouzandeh
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Rapid Growth ◽  
Classification Accuracy ◽  
High Speed ◽  
Large Scale ◽  
Learning Algorithm ◽  
Target Class ◽  
Partially Labeled Data ◽  
Novel Method

Abstract In the past decades, the rapid growth of computer and database technologies has led to the rapid growth of large-scale datasets. On the other hand, data mining applications with high dimensional datasets that require high speed and accuracy are rapidly increasing. Semi-supervised learning is a class of machine learning in which unlabeled data and labeled data are used simultaneously to improve feature selection. The goal of feature selection over partially labeled data (semi-supervised feature selection) is to choose a subset of available features with the lowest redundancy with each other and the highest relevancy to the target class, which is the same objective as the feature selection over entirely labeled data. This method actually used the classification to reduce ambiguity in the range of values. First, the similarity values of each pair are collected, and then these values are divided into intervals, and the average of each interval is determined. In the next step, for each interval, the number of pairs in this range is counted. Finally, by using the strength and similarity matrices, a new constraint feature selection ranking is proposed. The performance of the presented method was compared to the performance of the state-of-the-art, and well-known semi-supervised feature selection approaches on eight datasets. The results indicate that the proposed approach improves previous related approaches with respect to the accuracy of the constrained score. In particular, the numerical results showed that the presented approach improved the classification accuracy by about 3% and reduced the number of selected features by 1%. Consequently, it can be said that the proposed method has reduced the computational complexity of the machine learning algorithm despite increasing the classification accuracy.

scholarly journals A review on nanofiber fabrication with the effect of high-speed centrifugal force field

2019 ◽  
Vol 14 ◽  
pp. 155892501986751 ◽  
Author(s):  
Zhi-Ming Zhang ◽  
Yao-Shuai Duan ◽  
Qiao Xu ◽  
Biao Zhang
Keyword(s):  
Surface Tension ◽  
Force Field ◽  
Centrifugal Force ◽  
Formation Process ◽  
Rotational Speed ◽  
High Speed ◽  
Solution Concentration ◽  
Solution Viscosity ◽  
Centrifugal Spinning ◽  
Solution Parameters

Among the traditional methods for nanofiber fabrication, their inherent defects limit their application in industry. This work presents a simple and novel spinning technology to fabricate nanofiber, which uses a high-speed rotary spinneret called high-speed centrifugal spinning. Unlike electrospinning, the electric field is not required, and it could fabricate nanofiber in bulk from melt or solution materials. This work introduces the mechanism principle and development of high-speed centrifugal spinning. Besides, the high-speed centrifugal spinning is compared with the traditional spinning methods. The jet movement and nanofiber formation process under the action of centrifugal force are explained in detail. The effects of equipment parameters and spinning solution parameters on final nanofiber morphology are presented. These parameters are controllable, they include rotational speed of spinneret, length and diameter of nozzle, spinning solution concentration, spinning solution viscosity and surface tension, and collection distance.

Performance of High-Speed Precision Air-Bearing Spindle with Active Aerodynamic Bearing

2015 ◽  
Vol 9 (3) ◽  
pp. 297-302 ◽  
Author(s):  
Hiroshi Mizumoto ◽  
◽  
Yoichi Tazoe ◽  
Tomohiro Hirose ◽  
Katsuhiko Atoji ◽  
...  
Keyword(s):  
Rotational Speed ◽  
High Speed ◽  
Wedge Angle ◽  
Small Diameter ◽  
Air Bearing ◽  
Double Row ◽  
Single Row ◽  
Thrust Bearings ◽  
Spindle Vibration

A high-speed precision air-bearing tool spindle with active aerodynamic bearing is proposed for improving the quality of machining using small-diameter cutting and grinding tools. The spindle is basically supported by aerostatic radial and thrust bearings. According to the spindle vibration detected by capacitance sensors, the wedge angle of the active aerodynamic bearing was controlled using piezoelectric actuators, thereby suppressing the spindle vibration. In the present paper, the performances of a prototype air-bearing spindle with single-row active aerodynamic bearing and an improved air-bearing spindle with double-row bearings are reported. Through experiments, it was demonstrated that the maximum rotational speed controlled by the active aerodynamic bearing is 800 Hz (48,000 min-1), and that the amplitude of spindle vibration can be suppressed to <50 nm at the rotational speed of 500 Hz (30,000 min-1).

Balancing of Tool/Toolholder Assembly for High-Speed Machining

2004 ◽  
Vol 471-472 ◽  
pp. 542-546
Author(s):  
Song Zhang ◽  
Xing Ai ◽  
Wei Xiao Tang ◽  
J.G. Liu
Keyword(s):  
Centrifugal Force ◽  
Rotational Speed ◽  
High Speed ◽  
Manufacturing Industry ◽  
High Speed Machining ◽  
High Rotational Speed ◽  
Good Balance ◽  
Machining Quality ◽  
System Maintenance

High-speed machining has become mainstream in machining manufacturing industry. In industries such as moldmaking and aerospace, it has become the norm rather the exception. The centrifugal force increases as the square of the speed. At rotational spindle speeds of 6,000 r/min and higher however, centrifugal force from unbalance becomes a damaging factor and it reduces the life of the spindle and the tool, as well as diminishes the quality of the finished product. Under high rotational speed, good balance becomes issue. High-speed machining experimental results shown that a well-balanced tool/toolholder assembly could obviously improve machining quality, extend tool life and shorten downtime for spindle system maintenance etc.

scholarly journals A novel method of constrained feature selection by the measurement of pairwise constraints uncertainty

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Mehrdad Rostami ◽  
Kamal Berahmand ◽  
Saman Forouzandeh
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Rapid Growth ◽  
Classification Accuracy ◽  
High Speed ◽  
Large Scale ◽  
Learning Algorithm ◽  
Target Class ◽  
Partially Labeled Data ◽  
Novel Method

Abstract In the past decades, the rapid growth of computer and database technologies has led to the rapid growth of large-scale datasets. On the other hand, data mining applications with high dimensional datasets that require high speed and accuracy are rapidly increasing. Semi-supervised learning is a class of machine learning in which unlabeled data and labeled data are used simultaneously to improve feature selection. The goal of feature selection over partially labeled data (semi-supervised feature selection) is to choose a subset of available features with the lowest redundancy with each other and the highest relevancy to the target class, which is the same objective as the feature selection over entirely labeled data. This method actually used the classification to reduce ambiguity in the range of values. First, the similarity values of each pair are collected, and then these values are divided into intervals, and the average of each interval is determined. In the next step, for each interval, the number of pairs in this range is counted. Finally, by using the strength and similarity matrices, a new constraint feature selection ranking is proposed. The performance of the presented method was compared to the performance of the state-of-the-art, and well-known semi-supervised feature selection approaches on eight datasets. The results indicate that the proposed approach improves previous related approaches with respect to the accuracy of the constrained score. In particular, the numerical results showed that the presented approach improved the classification accuracy by about 3% and reduced the number of selected features by 1%. Consequently, it can be said that the proposed method has reduced the computational complexity of the machine learning algorithm despite increasing the classification accuracy.

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