scholarly journals Sintering and Smelting Property Investigations of Ludwigite

Processes ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 159
Author(s):  
Gongjin Cheng ◽  
Xuezhi Liu ◽  
He Yang ◽  
Xiangxin Xue ◽  
Lanjie Li
Keyword(s):  
Carbon Content ◽  
Influencing Factors ◽  
Gas Permeability ◽  
Maximum Pressure ◽  
Analysis Method ◽  
Range Analysis ◽  
Scoring Method ◽  
Orthogonal Experiments ◽  
Sintering Characteristics ◽  
Start Temperature

In this paper, orthogonal experiments are designed to study the sintering and smelting characteristics of the ludwigite ore. The predominant influencing factors of the optimal ratio, basicity and carbon content on different single sintering indexes, including the vertical sintering speed, yield rate, drum strength and low-temperature reduction pulverization index, are firstly explored by the range analysis method, and the main influencing factors on comprehensive indexes are obtained by a weighted scoring method based on different single index investigation. Considering the sintering characteristics, the primary and secondary influencing factors are: ordinary ore ratio, carbon content and basicity, and the optimal ore blending scheme is: basicity 1.7, ordinary ore blending ratio 60% and carbon content 5%. In terms of the smelting characteristics, the research obtains the order of the influencing factors on the softening start temperature, softening end temperature, softening zone, smelting start temperature, dripping temperature, smelting-dripping zone, maximum pressure difference and gas permeability index of the ludwigite sinters by simply considering various single smelting indexes. On this basis, considering the comprehensive softening-melting-dripping characteristics, the primary and secondary influencing factors are: carbon content, ordinary ore ratio and basicity, and the optimal ore blending scheme is: basicity 1.9, ordinary ore blending ratio 60% and a carbon content of 5.5%. Comprehensively, considering the sintering and smelting property of the ludwigite ore, the primary and secondary influencing factors are: carbon content, ordinary ore ratio and basicity, and the optimal ore blending scheme is: basicity 1.9, ordinary ore blending ratio 60% and a carbon content of 5.5%.

Experiments and Optimization of Mix Proportions for Cement Paste Backfill Materials with Extra-Fine Unclassified Tailings

2017 ◽  
Vol 744 ◽  
pp. 146-151
Author(s):  
Ming Qing Huang ◽  
Xiao Hui Liu ◽  
Hai Yong Cheng
Keyword(s):  
Cement Paste ◽  
Mass Concentration ◽  
Influential Factors ◽  
Range Analysis ◽  
Bleeding Rate ◽  
Orthogonal Experiments ◽  
Optimal Mix ◽  
Backfill Materials ◽  
Unclassified Tailings ◽  
Paste Backfill

To produce effective cement paste backfill materials at iron mines technologically and economically, orthogonal experiments of mix proportions with extra-fine unclassified tailings were carried out. The results of the range analysis showed that the sensitivity of influential factors to the slurry slump is sequentially mass concentration, tailing/rock ratio, and cement/(tailing+rock) ratio. The sensitivity to bleeding rate, concretion time and 28-day uniaxial compressive strength is sequentially mass concentration, cement/(tailing+rock) ratio and tailing/rock ratio. Relationships of paste properties and influential factors can be demonstrated with regression analysis. Additionally, the optimal mix proportion for cement paste backfill was obtained with 78% mass concentration, 7:3 tailing/rock ratio and 1:25 cement/(tailing+rock) ratio. The slump, bleeding rate, concretion time and R28 of the optimal mixture are 25.2 cm, 8.77%, 20.9 h and 1.29 MPa, respectively. The experimental results show a feasible way to produce the industry standard backfilling materials.

Effects of Wet Activation Process Parameters on Surface Hydrophilicity in Silicon Direct Wafer Bonding

2012 ◽  
Vol 235 ◽  
pp. 250-253
Author(s):  
Lei Nie ◽  
Jun Xing Yu ◽  
Kun Zhang
Keyword(s):  
Wafer Bonding ◽  
Orthogonal Experiment ◽  
Volume Ratio ◽  
Holding Time ◽  
Activation Process ◽  
Analysis Method ◽  
Range Analysis ◽  
Surface Hydrophilicity ◽  
Direct Wafer Bonding ◽  
Value Range

Wet activation is a very important step in silicon direct wafer bonding process and a optimized activation process is desirable to improve the surface hydrophilicity. Therefore the pivotal parameters of activation process were investigated which were volume ratio, holding time and treat temperature. A orthogonal experiment array was designed to reveal the effects of these parameters and the experiment results were analyzed by range analysis method. The analysis results indicted among those three parameters, everyone had intimidate relationship with surface hydrophilicity, which was indexed by contact angle. And higher concentration, longer holding time and higher treating temperature in possible value range were more desirable. Based on these conclusions, optimized activation process was desigened using which void-free bonding was realized.

scholarly journals Relationship and Mechanism Analysis of Soft-Melt Dropping Properties and Primary-Slag Formation Behaviors of the Mixed Burden in Increasing Lump Ore Ratio

Metals ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1254 ◽  
Author(s):  
Yun-Fei Li ◽  
Zhi-Jun He ◽  
Wen-Long Zhan ◽  
Wei-Guo Kong ◽  
Peng Han ◽  
...  
Keyword(s):  
Pressure Difference ◽  
Cohesive Zone ◽  
Gas Permeability ◽  
Effective Means ◽  
Maximum Pressure ◽  
Slag Formation ◽  
Mechanism Analysis ◽  
Temperature Zone ◽  
Slag Properties ◽  
The Relationship

At present, cost reduction and environmental protection are the mainstream of blast furnace (BF) development and the high lump ore ratio is an effective means. Therefore, it is significant to explore the relationship and mechanism of burden soft-melt dropping and its primary-slag formation behaviors under increasing lump ore ratio. In this paper, the melt–drop test is carried out on the single ore and mixed burden, and obtained primary-slag properties are subjected to analysis. The experimental results show that the primary-slag of lump ore contains a large amount of FeO and SiO2, so it simply produces many low melting point compounds, which cause terrible soft-melt dropping properties and primary-slag formation behaviors. Notably, mixing with sinter and pellet can effectively improve both the properties. With the increase in lump ore ratio, the CaO in the primary-slag decreases, FeO and SiO2 increase, resulting in the melting temperature of the primary-slag sequentially decreasing and the cohesive zone moves to the low temperature zone. In addition, the maximum pressure difference increases, and the gas permeability deteriorates. Increasing the sinter ratio can overcome the defect of high lump ore ratio that can effectively improve the poor softening performance, melting performance and the position and thickness of the cohesive zone. However, because of the pulverization performance, the maximum pressure difference and gas permeability of the burden become worse.

scholarly journals Experimental Development of Coal-Like Material with Solid-Gas Coupling for Quantitative Simulation Tests of Coal and Gas Outburst Occurred in Soft Coal Seams

Processes ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 155 ◽  
Author(s):  
Xingkai Wang ◽  
Wenbing Xie ◽  
Zhili Su ◽  
Qingteng Tang
Keyword(s):  
Compressive Strength ◽  
Elastic Modulus ◽  
Influencing Factors ◽  
Co2 Sequestration ◽  
Range Analysis ◽  
Coal Seams ◽  
Gas Outburst ◽  
Soft Coal ◽  
Coal Powder ◽  
Adsorption Desorption

Solid-gas coupling coal-like materials are essential for simulating coal and gas outbursts and the long-term safety study of CO2 sequestration in coal. However, reported materials still differ substantially from natural coal in mechanical, deformation and gaseous properties; the latter two aspects are common not considered. There is a lack of a definite and quantitative preparation method of coal-like materials with high similarity for future reference. Here, 25 groups of raw material ratios were designed in the orthogonal experiment using uniaxial compression, shearing and adsorption/desorption tests. Experiment results indicated that the coal-like materials were highly similar to soft coals in properties mentioned above. And range analysis revealed the key influencing factors of each mechanical index. The gypsum/petrolatum ratio controls the density, compressive strength, elastic modulus, cohesion and deformation characteristic. The coarse/fine coal powder (1–2 and 0–0.5 mm) controls the internal friction angle and is the secondary controlling factor for compressive strength and elastic modulus. The effect of coal particle size on the sample strength was studied using scanning electron microscope (SEM). When the gypsum/petrolatum ratio increased, the deformation characteristics changed from ductile to brittle. The different failure modes in the samples were revealed. The coal powder content is a key in the gas adsorption/desorption properties and an empirical formula for estimating the adsorption capacity was established. Based on the range analysis of experimental results, a multiple linear regression model of the mechanical parameters and their key influencing factors was obtained. Finally, a composition closely resembling the natural coal was determined, which differs by only 0.47–7.41% in all parameters except porosity (11.76%). Possible improvements and extension to similar materials are discussed. The findings of this study can help for better understanding of coal and gas outburst mechanism and stability of CO2 sequestration in soft coal seams.

A novel approach of fault-influencing factors analysis for high-voltage switchgears quality supervision based on industrial big data

2019 ◽  
Vol 233 (14) ◽  
pp. 2531-2546 ◽  
Author(s):  
Xianguang Kong ◽  
Jiantao Chang ◽  
Pei Wang ◽  
Siyi Gong ◽  
Yabin Shi ◽  
...  
Keyword(s):  
Big Data ◽  
Qualitative Analysis ◽  
Influencing Factors ◽  
High Voltage ◽  
Occurrence Probability ◽  
Analysis Method ◽  
Factors Analysis ◽  
Industrial Big Data ◽  
Discrete Interval ◽  
Interval Value

Fault-influencing factors analysis is an important part of the quality supervision process. There are double functions for high-voltage switchgears that switch off and protect electric circuits in power transmission lines. Such devices have serious impact on power grid–operating efficiency, factory operation, and resident life, which will cause economic losses. As it was difficult for traditional methods to analyze fault-influencing factors accurately and comprehensively, a novel method based on industrial big data was proposed to analyze high-voltage switchgears fault-influencing factors in the process of quality supervision in this article, which integrated the qualitative and quantitative analyses method. In this model, the Classification Based on Multiple Class-Association Rules based on Gaussian Mixture Model as the qualitative analysis method was adapted to analyze the whole life cycle of fault-influencing factors of high-voltage switchgears comprehensively, and supplied fault-influencing factors with discrete interval value ranges. The logistic regression method based on qualitative analysis was constructed to calculate fault occurrence probability quantitatively, including the single-fault occurrence probability and the multiple-faults joint occurrence probability. In addition, the single-fault occurrence probability was used to modify the discrete interval value ranges calculated by the qualitative analysis method, which could make the ranges more accurately. Consequently, the proposed method could provide important reference for high-voltage switchgears operation maintenance, and it would be possible to design accurate maintenance plans before equipment failure. The final instance demonstrates the effectiveness of the proposed methodology.

Experimental Study of Elastic Modulus of Crumb Rubber Plastic Concrete

2010 ◽  
Vol 150-151 ◽  
pp. 1176-1183 ◽  
Author(s):  
Mei Zhou ◽  
Xiao Ming Yang ◽  
Kun Song
Keyword(s):  
Elastic Modulus ◽  
Influencing Factors ◽  
Crumb Rubber ◽  
Prediction Equation ◽  
Specimen Size ◽  
Analysis Method ◽  
Plastic Concrete ◽  
Binder Ratio ◽  
Crumb Rubber Concrete ◽  
Rubber Concrete

this paper got the compressive stress-strain fitting curve of crumb rubber plastic concrete, analyzed the influencing factors of elastic modulus of crumb rubber plastic concrete and found the influence law of specimen size and measuring distance to measured value of elastic modulus, through our experiments. The results of our experiments show that the method and operation of experiment strongly influence the measured value of elastic modulus of crumb rubber plastic concrete, but we can use the measures of step loading, screening and fitting curve to get the relatively exact measured value of elastic modulus of plastic concrete. And then, this paper analyzed a 16 sets of uniform experiment results with regression analysis method. As a result, we found the main influencing factors of elastic modulus of crumb rubber concrete are cement mixing amount, crumb rubber mixing amount and product of water-binder ratio and water reducer mixing amount, which the importance of them decreases progressively. Finally, this paper established the prediction equation of elastic modulus of crumb rubber concrete and found the connection of elastic modulus of crumb rubber concrete with specimen size and measuring distance.

Comparison and Analysis of Prediction Methods for Water Consumption per Ten Thousand Yuan Industrial Added Value

2014 ◽  
Vol 1073-1076 ◽  
pp. 2653-2658
Author(s):  
Zhi Jun Yan ◽  
Ming Yue Zhang ◽  
Chun Xiao Xu ◽  
Hai Tao Zhao ◽  
Yue Ping Tang ◽  
...  
Keyword(s):  
Water Management ◽  
Influencing Factors ◽  
Water Consumption ◽  
Management System ◽  
Added Value ◽  
Specific Situation ◽  
Water Efficiency ◽  
Analysis Method ◽  
Water Management System ◽  
Factors Analysis

Water consumption per ten thousand yuan industrial added value (WCPIAV) is the assessment indicator to implement the most stringent water management system to control water efficiency. This paper proposes trend analysis method, elasticity coefficient analysis method and influencing factors analysis method to predict WCPIAV in Jiangsu province, the experimental areas where implement the most stringent water management system. The results show that different methods predict well in different cities, influencing factors analysis method works better than the other two methods. An appropriate method should be selected depending on the specific situation.

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