Startseite Naturwissenschaften Furnace heat prediction and control model and its application to large blast furnace
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Furnace heat prediction and control model and its application to large blast furnace

  • Zhuang-nian Li , Man-sheng Chu EMAIL logo , Zheng-gen Liu , Gen-ji Ruan und Bao-feng Li
Veröffentlicht/Copyright: 29. November 2019

Abstract

Blast furnace heat is the key to the blast furnace’s high efficiency and stable operation, and it is difficult to maintain a suitable temperature for large blast furnace operations. When designing the furnace heat prediction and control model, parameters with good reliability and measurability should be chosen to avoid using less accurate parameters and to ensure the accuracy and practicability of the model. This paper presents an effective model for large blast furnace temperature prediction and control. Using thermal equilibrium and the carbon-oxygen balance of the blast furnace’s high-temperature zone, the slag-iron heat index was calculated. Using the relation between the molten iron temperature and slag-iron heat index, the furnace heat parameter can be calculated while production conditions are changed,which can guide furnace heat control.

1 Introduction

Maintaining reasonable heat is the key to the blast furnace’s high efficiency and stable operation. It is difficult to maintain suitable temperature for a large blast furnace, and temperatures that are too high or too low will not only cause blast furnace condition fluctuation, but also the production and technical indicators of the blast furnace and molten iron quality will be adversely affected. Because to the blast furnace production process is a complex reaction process involving high temperatures, external the factors that influence furnace temperature, and long time lag for large blast furnace heat change, furnace temperature control is difficult [1, 2, 3, 4].

With the improvement in equipment and technology in the large blast furnace, the accuracy of certain blast furnace process parameters has clearly improved. For example, the air leaking rate of most small blast furnaces before was more than 8%, but in the modern large blast furnace, it is usually less than 2%. Meanwhile, the required accuracy for furnace temperature control is also improved. When designing the furnace heat prediction and control model, good parameters should be chosen for reliability and to avoid using less accurate parameters to ensure the accuracy and practicality of the model. In order to satisfy the temperature requirements, the operators of blast furnaces should predict the furnace temperature correctly according to the operation parameters and accurate adjustment measures. This paper presents an effective method for large blast furnace temperature prediction and control, which can guide furnace heat adjustment.

There are many factors that influence blast furnace heat. The main factors are blast parameters (including blast volume, rich oxygen flow, PCI rate, blast humidity, and blast temperature), coke load, gas utilization, operation yield, quality of raw materials and fuel (including: coke, coal, sintering, and pellet), heat load, and furnace dust. The furnace heat parameters should be calculated when the above mentioned conditions are changed.

The calculation model presented in this paper are as follows. Firstly, recent data on blast furnace operation were collected, as the benchmark data for blast furnace operation. Secondly, the blast furnace benchmark data were used in the blast furnace high temperature thermal equilibrium and carbon-oxygen balance equations, the theoretical PCI rate was calculated, the theoretical direct reduction of carbon consumption under the benchmark conditions and slag-iron heat index was calculated. Thirdly, the blast furnace target parameters was used in the thermal equilibrium and carbon-oxygen balance equations for the blast furnace high-temperature zone, target slag-iron heat index was calculated, the relation between the temperature and slag-iron heat index was established, and the molten iron temperature and [Si] were calculated; Finally, corresponding to the target molten iron temperature, the slag-iron heat index was used in the blast furnace high temperature thermal equilibrium and carbon-oxygen balance equations, and the PCI rate and the quantity of coal needed were calculated, such that heat control could be achieved.

2 Calculation of the theoretical PCI rate

First, the benchmark parameters should be statistics that can represent the recent operating status of the blast furnace (the "0" on the right is marked as the benchmark parameter), and the statistical parameters are shown in Table 1.

Table 1

Benchmark parameters of blast furnace.

ItemSymbolUnitsBenchmark parameter
Blast volumeVbNm3/min6096.00
Rich oxygen flowVo2Nm3/h15929.00
Atmospheric humidityHATSg/m33.00
Humidification quantityHADDt/h0.10
Blast temperatureBTC1267.00
Gas utilization ratioηCO-49.51%
Molten iron temperaturePTC1515.00
Coke rateKkg/tFe326.56
PCI rate(dry)Mkg/tFe190.60
Yield of ironPt/d9458.72
Heat loadQload10MJ/h8453.00
Carbon in cokeω(Ccoke)%87.29
Ash in cokeω(Acoke)%11.67
Carbon in coalω(Ccoal)%69.97
Ash in coalω(Acoal)%10.86
Consumption of sintering per ton ironMsintkg/tFe1213.30
Consumption of pellets per ton ironMpellkg/tFe391.11
[Si][Si]%0.42
[Fe][Fe]%94.72
[C][C]%4.70
[Mn][Mn]%0.04
[P][P]%0.07
[Ti][Ti]%0.03
Slag rateMslagkg/tFe305.00
Moisture in coalω(H2Ocoal)%1.32
O in coalω(Ocoal)%8.21
Fe2O3 in Sinteringω(Fe2O3sint)%72.44
FeO in Sinteringω(FeOsint)%9.59
Fe2O3 in pelletsω(Fe2O3pell)%90.88
FeO in pelletsω(FeOpell)%0.66
FeO in Slag(FeO)%0.04
S in Slag(S)%1.02
Furnace dust production per ton ironMdustkg/tFe17.00
Fe2O3 in dustω(Fe2O3dust)%48.12
FeO in dustω(FeOdust)%6.82
C in dustω(Cdust)%20.25
O in cokeω(Ocoal)%0.70
Blast volume by PCVcoalNm3/min2873.00
Nitrogen volume by PCVcoal_N2Nm3/h4000.00
Hydrogen utilizationηH2-40.00%

Atmospheric humidity (%):

(1)f0=22.4×HATS01000×18

Amount of O2 per minute (Nm3/min):

(2)O2_b0=[0.21×(1f0)+0.5×f0]×Vb0+Vcoal060+λo2×Vo2060+1000×22.4×HADD02×18×60

where, λO2 is the quality percentage of O2 in rich oxygen, which is 99.7%.

Oxygen consumption in combustion per ton iron (Nm3/tFe):

(3)OCBT0=1440×O2_b0P0

Carbon consumption in combustion per ton iron (kg/tFe):

(4)CCBT0=OCBT0×2422.4

Under normal circumstances, the ratio of unburned coal powder to furnace dust is lower, and the influence on calculation of the thermal equilibrium and carbon-oxygen balance is not larger, but as the PCI rate increases, unburned coal powder into the furnace dust markedly increases, M0 should be the quantity of coal that actually reacts in the furnace, which is the total quantity of coal minus the quantity of coal increased in the furnace dust. Assuming that the coal is burned completely in the tuyere zone, then carbon consumption of coke in combustion per ton iron (kg/tFe)

(5)CCBT_coke0=CCBT0M0×ω0Ccoal/100

Amount of coke gasification per ton iron (kg/tFe):

(6)CGAS_coke0=K0×ω0(Ccoke)/100CCBR0Cdust0

Carbon consumption by direct reduction per ton iron (kg/tFe):

(7)CdFe0=CGAS_coke0CCBT_coke0Cda0

where Cda0represents carbon consumption of elements reduced other than iron (kg/tFe) and CCBR0is the amount of carburizing in pig iron (kg/tFe). Cdu0is the carbon content in dust per ton iron (kg/tFe).

The amount of oxygen entering into the blast furnace gas from raw materials and fuel (kg/tFe) is

(8)OM0=msint0×[ω0(Fe2O3sint)/100×48/160+ω0(FeOsint)/100×16/72]+mpell0×[ω0(Fe2O3pell)/100×48/160+ω0(FeOpell)/100×16/72]mdust0×[ω0(Fe2O3dust)/100×48/160+ω0(FeOdust)/100×16/72]mslag0×ω0(FeO)/100×16/72+M0×[ω0(H2Ocoal)/100/(1ω0(H2Ocoal)/100)/18×16+ω0(Ocoal)/100]+K0×ω0(Ocoke/100)+10×([Si]0×32/28+[Mn]0×16/55+[P]0×80/62)+mslag0×(S)0/100×16/32

Amount of moles H containing in per kg coal (kmol/kg):

(9)n0(Hcoal)=[ω0(Hcoal)/100/2+ω0(H2Ocoal)/100/(1ω0(H2Ocoal)/100)/18]

Use the above calculation results in the carbon-oxygen balance equation [5]:

(10)ηCO0=OM0/16CdFe0/12M0×ω0(Ccoal)/100+CGAS_coke0/12ηH2×vH2O_b0×CCBT0/22.4+M0×n0(Hcaol)M0×ω0(Ccoal)/100+CGAS_coke0/12

The denominator is the total volume of carbon gas in moles, the numerator is the total volume of CO2 gas in moles, and the amount is equal to the total amount of CO2 generated from reaction of CO and O. CO comes from the tuyere combustion and O from raw materials and fuel, minus the mole amount of CO that derived from the direct reduction process of C and FeO, and minus the molar volume of H2O that is derived from the direct reduction of H and O. ηH2 indicates the utilization ratio of hydrogen in the high temperature zone, which is generally 30%-50%.

Transform equation (9) to be

(11)M0=12×OM0/16+CCBT0+Cda0(ηCO0+1)×ω0(Ccoal)/100+12×n0(Hcoal)(ηCO0+1)×CGAS_coke012×ηH2×vH20_b0×CCBT0/22.4(ηCO0+1)×ω0(Ccoal)/100+12×n0(Hcoal)

Use M0 in equations (5) and (7), CCBT_coke0and CdFe0can be calculated.

Comparing the theoretical PCI rate calculated from the above equation with the actual coal, if the deviation is not large, it can be directly used in the next calculation. However, the calculated data need to be checked for mistakes or parameter distortion. Based on this premise, the deviation between theoretical and actual quantity of coal needed (or PCI rate) is adjusted to ensure the accuracy of the calculated results.

3 Calculation of slag-iron heat index [6, 7, 8, 9, 10]

Total volume of hot air coming into the blast furnace per minute (Nm3/min):

(12)VHA0=Vb0+Vo20/60+Vcoal0/60+Vcoal_N20/60+HADD0×1000×22.4/18/60

The ratio of H2O in hot air:

(13)φ0(H2O)=(HADD0×1000000/60+(Vb0+Vcoal0/60)×HATS0)×22.4/18/1000/Vb0

The ratio of O2 in hot air after the decomposition of H2O:

(14)φ10(O2)=[(0.21+0.29×HATS0×22.4/18/1000)×(Vb0+Vcoal0/60)+Vo20/60×λo2+HADD0×1000×22.4/18/2/60]/Vb0

The ratio of O2 in hot air before the decomposition of H2O:

(15)φ20(O2)=φ10(O2)φ0(H2O)/2

The ratio of N2 in hot air:

(16)φ0(N2)=1φ20(O2)φ0(H2O)

The volume of hot air needed to burn per kilogram carbon (Nm3/kg):

(17)vHA0=22.4/24/φ10(O2)

The volume of H2O in hot air to burn per kilogram carbon (Nm3/kg):

(18)vH2O_HA0=vHA0×φ0(H2O)

The volume of O2 in hot air to burn per kilogram carbon (Nm3/kg):

(19)vO2_HA0=vHA0×φ20(O2)

The volume of N2 in hot air to burn per kilogram carbon (Nm3/kg):

(20)vN2_HA0=vHA0×φ0(N2)

The volume of CO generated by burning per kilogram carbon (Nm3/kg):

(21)vCO_GAS0=22.4/2

The volume of N2 generated by burning per kilogram carbon (Nm3/kg):

(22)vN2_GAS0=vN2_HB0

The volume of H2 generated by burning per kilogram carbon (Nm3/kg):

(23)vH2_GAS0=22.4/24/ϕ10(O2)×ϕ0(H2O)×(1ηH2)

The volume of H2O generated by burning per kilogram carbon (Nm3/kg):

(24)vH2O_GAS0=22.4/24/ϕ10(O2)×ϕ0(H2O)×ηH2

Thermal revenue by burning per kilogram carbon in high-temperature zone (kJ/kg (C)):

(25)qC_CBT0=9800+(qCO_HA0×vCO_HA0+qN2_HA0×vN2_HA0+qH2O_HA0×vH2O_HA0)10785×vH2O_HA0qH_RDC×ηH2×vH2O_HB0(qCO_GAS0×vCO_GAS0)+qN2_GAS0×vN2_GAS0+qH2O_GAS0×vH2O_GAS0+qH2O_GAS0×vH2O_GAS0)

where, qx_HB0indicate the heat enthalpy of x gas at s specific under blast temperature, and qx_GAS0represents the heat enthalpy of x gas at the limit temperature (950C). The heat enthalpy calculation uses the method mentioned in the literature [6]. qH_RDC is the thermal consumption of hydrogen reduced per kmol.

While burning coke, thermal revenue burning per kilogram carbon (kJ/kg (C)) is

(26)qC_CBT_coke0=qC_CBT0C¯coke×ω0Acokeω0Ccoke×(tslagtlimit)

While burning coal, thermal revenue burning per kilogram coal (kJ/kg (C)) is

(27)qcoal0=qC_CBT0×ω0(Ccoal)/100qH_RDC×ηH2×n0(Hcoal)qDEC

Thermal consumption of carbon per kilogram directly reduced (kJ/kg (C)) is

(28)qdFe0=qdFe_RDC0+C¯coke×ω0Acokeω0Ccoke×(tslagtlimit)

Heat loss per ton iron (kJ/tFe):

(29)Qloss0=λloss×Qload×10000×24/P0

Using the above calculation results in the thermal equilibrium and carbon-oxygen balance equations to calculate the blast furnace high-temperature zone, the target slag-iron heat index (kJ/tFe) is

(30)Qheat0=qC_CBT0×CCBT_coke0+qcoal0×M0qdFe0×CdFe0Qloss0

The slag-iron heat index indicates the heat of iron and slag per ton of iron, which represent the heat level of the blast furnace. The higher the slag-iron heat index is, the higher the furnace heat is.

4 Furnace heat prediction and control

Using the target parameters (or actual running parameters) in the thermal equilibrium and carbon-oxygen balance equations,

(31)λheat×Qheat0=qC_CBT×CCBT_coke+qcoal×MqdFe×CdFeQloss
(32)ηCO=OM/16CdFe/12M×ω(Ccoal)/100+CGAS_coke/12ηH2×vH2O_b×CCBT/22.4+M×n(Hcoal)M×ω(Ccaol)/100+CGAS_coke/12

where,

(33)CGAS_coke=K×ω(Ccoke)/100CCBRCdust
(34)CCBT_coke=CGAS_cokeCdFeCda
(35)CCBT=CCBTcoke+M×ω(Ccoal)/100
(36)CCBT=CGAS_cokeCdFeCda+M×ω(Ccoal)/100

The calculation method of OM, Cda, CCBR, Cdust, n(Hcoal), qC_CBT, qcoal, qdFe is the same as OM0,Cda0,CCBR0,Cdust0,n0(Hcoal),qC_CBT0,qcoal0,qdFe0.

Qheat = λ heat ×Q0heatheat is heat coefficient, and when λ heat = 1, furnace heat can be considered equivalent to the benchmark furnace heat.

The formula of molten iron temperature prediction:

(37)Tiron=[1+α×λheat1]×Tiron0

where, α is the correlation coefficient between molten iron temperature and slag-iron heat index.

Using the above calculation results in equations (31) and (32), only M and CdFe are the two unknowns in the equation [5].

(38)qcoal×M+(qdFeqC_CBT)×CdFe=λheat×Qheat0qC_CBT×(CGAS_cokeCda)+Qloss
(39)[ηCO×ω(Ccoal)/10012+ηH2×(vH2O_HB×ω(Ccoal)/10022.4+n(Hcoal)]×M+(112+ηH2×vH2O_HB22.4)×CdFe=OM16ηH2×vH2O_HB×(CGAS_cokeCda)22.4ηCO×CGAS_coke12

M and CdFe can be obtained from equations (38) and (39), and the result can be use in equations (34) and (35) to calculate CCBT_coke and CCBT.

The estimated daily output of molten iron (t/d):

(40)P=1440×O2_HBCCBT×22.4/24

The quantity of coal needed (t/h):

(41)mcoal=P×[M+(MaM0)]/1ω(H2Ocoal)/100/1000/24

5 Application of blast furnace heat control

Using the benchmark parameters of Table 1 in the above calculation equation, the calculation results are shown in Table 2.

Table 2

Heat calculation results of blast furnace.

ItemSymbolUnitsResults
Atmospheric humidityf-0.37%
Ratio of O2 in hot airO2_HBNm3/min1562.59
Oxygen consumption in combustion per ton ironOCBTNm3/tFe237.89
Carbon consumption in combustion per ton ironCCBTkg/tFe254.88
Amount of coke gasification per ton ironCGAS_cokekg/tFe234.60
Amount of oxygen entering blast furnace gasOMkg/tFe421.52
from raw materials and fuel
Amount of moles H in per kilogram coalN(Hcoal)kmol/kg0.018
PCI rateMkg/tFe184.72
Oxygen consumption in combustion per ton ironCCBT_cokekg/tFe123.35
Carbon consumption by direct reduction per ton ironCdFekg/tFe105.65
Total volume of hot air coming into the blast furnace per minuteVHBNm3/min6748.11
Ratio of H2O in hot airφ(H2O)-0.39%
Ratio of O2 in hot air after the decomposition of H2Oφ1(O2)-24.12%
Ratio of O2 in hot air after the decomposition of H2Oφ2(O2)-23.93%
Ratio of N2 in hot airφ(N2)-75.69%
Volume of hot air needed to burn per kilogram carbonNHBNm3/kg3.87
Volume of H2O in hot air to burn per kilogram carbonνH2O_HBNm3/kg0.015
Volume of O2 in hot air to burn per kilogram carbonνO2_HBNm3/kg0.93
Volume of N2 in hot air to burn per kilogram carbonνN2_HBNm3/kg2.93
Volume of CO generated by burning per kilogram carbonνCO_GASNm3/kg1.87
Volume of N2 generated by burning per kilogram carbonνN2_GASNm3/kg2.93
Volume of H2 generated by burning per kilogram carbonνH2_GASNm3/kg0.009
Volume of H2O generated by burning per kilogram carbonνH2O_GASNm3/kg0.006
Thermal revenue by burning per kilogram carbon in high-temperature zoneqC_CBTkJ/kg(C)10308.33
Thermal revenue by burning per kilogram carbon while burning cokeqC_CBT_cokekJ/kg(C)10223.32
Thermal revenue by burning per kilogram coal while burning coalqcoalkJ/kg6561.37
Thermal consumption of per kilogram carbon directly reducedqdFekJ/kg(C)12746.92
Heat loss per ton ironQlosskJ/tFe214481.47
Slag-iron heat indexQheatkJ/tFe720564

According to the calculations in the above section, while the operation parameters of the blast furnace are changed to maintain constant furnace heat, the quantity of the coal needed or other control parameters can be calculated.

In actual production, to stabilize the furnace conditions and heat, the operating parameters are often kept constant, but ηCO changes frequently. Through the above section, the estimated fuel rate and quantity of coal needed can be calculated for different ηCO, and the calculation results as shown in Figure 1.

Figure 1 Estimated fuel rate and quantity of coal needed on different ηCO
Figure 1

Estimated fuel rate and quantity of coal needed on different ηCO

When the heat of blast furnace needs to be adjusted, assuming that only the quantity of coal is adjusted, other operating parameters remain the same, and at the same time direct reduction of heat consumption is constant. Therefore, simultaneous equations (37), (38) and (39), with such parameters as estimated fuel rate, quantity of coal needed, estimated yield and ηCO can be obtained for different temperatures, and the calculation results are shown in Figure 2 and Figure 3.

Table 3

Amount of coal needed when the operating parameters of the blast furnace are changed.

ItemUnitsOperating parameters changedAmount of coal needed (t/h)
Blast volumeNm3/min+100+1.03
Rich oxygen flowNm3/h+1000+0.82
Atmospheric humidityg/m3+10+0.50
Humidification quantityt/h+1+0.35
Coke ratekg/tFe+10−4.27
Figure 2 Estimated fuel rate and quantity of coal needed at different temperature.
Figure 2

Estimated fuel rate and quantity of coal needed at different temperature.

Figure 3 Estimated yield and ηCO at different temperature.
Figure 3

Estimated yield and ηCO at different temperature.

The furnace heat prediction model can be used to calculate the temperature of molten iron while the operation parameters of blast volume, ηCO, and operation yield change simultaneously. The slag-iron heat index, which is 693976 kJ/tFe, can be calculated for the following conditions: blast volume is 6196 Nm3/min, rich oxygen flow is 16929 Nm3/min, atmospheric humidity is 13.00 g/m3, humidification quantity is 1.10 t/h, ηCO is 50.51%, coke rate is 336.56 kg/tFe, operation yield is 9558.72 t/d, and estimated molten iron temperature is 1507C.

By adopting the furnace heat prediction and control model, the qualified rate of hot metal temperature in a TISCO large blast furnace (T = 1495~1515C) increased from 60.5% to 76.7%, and the qualified rate of [Si] in hot metal (the ratio of [Si] in hot metal < 0.55%) increased from 62.9% to 68.7%, which were good results.

6 Summary

When designing the furnace heat prediction and control model, parameters with good reliability to should be chosen, to avoid using less accurate parameters and to ensure the accuracy and practicality of the model. This paper presents an effective method for blast furnace temperature prediction and control.

  1. The primary factors that influence blast furnace heat include blast parameters, coke load, gas utilization ratio, operation yield, quality of raw materials and fuel, heat load, and furnace dust. Using the furnace heat control model proposed in this paper, furnace heat parameters can be calculated when the above mentioned conditions are changed.

  2. By using the thermal equilibrium and carbon-oxygen balance equation for the blast furnace high-temperature zone, the slag-iron heat index which represent the heat level of the blast furnace can be calculated.

  3. Using the relation between the molten iron temperature and slag-iron heat index, the furnace heat parameters can be calculated when production conditions are changed, which can guide furnace heat control.

References

[1] M.S. Chu, Modelling on Blast Furnace Process and Innovative Technologies, Northeast University Press, Shenyang, 2006.Suche in Google Scholar

[2] J.C. Song, Blast Furnace Iron of Theory and Operation, Metallurgical Industry Press, Beijing, 2005 (in Chinese).Suche in Google Scholar

[3] X.G. Bi, Mathematical Model and Computer Control of Blast Furnace Process, Metallurgical Industry Press, Beijing, 1996 (in Chinese).Suche in Google Scholar

[4] X.G. Liu, F. Liu, Blast Furnace Ironmaking Process Optimization and Intelligent Control System, Metallurgical Industry Press, Beijing, 2003 (in Chinese).Suche in Google Scholar

[5] S.R. Na, Analysis of Ironmaking Calculation, Metallurgical Industry Press, Beijing, 2010, 297-321 (in Chinese).Suche in Google Scholar

[6] S.R. Na, Ironmaking Calculation, Metallurgical Industry Press, Beijing, 2005, 258-275 (in Chinese).Suche in Google Scholar

[7] L. Wei, S.S. Yang, F. Zhang, Q. Bai, Mathematical Model for Predicting Silicon content and Hot Metal Temperature of Blast Furnace Molten Iron by Means of Furnace Heat Index, Metallurgical Research Center, Beijing, 2005.Suche in Google Scholar

[8] C.X. Cao, G.Y. Zhang, Prediction System of Silicon Content in Blast Furnace Molten Iron Based on Furnace Heat Index and BP Network, Chongqing University, Chongqing, 2008.Suche in Google Scholar

[9] Y.Q. Huang, Prediction System of Blast Furnace Thermal State Based on Furnace Heat Index and RBF, Chongqing University, Chongqing, 2007.Suche in Google Scholar

[10] S. P. Mehrotta, C. Nand, ISIJ Int. 33(1993) 839-844.10.2355/isijinternational.33.839Suche in Google Scholar

Received: 2018-07-31
Accepted: 2019-08-06
Published Online: 2019-11-29
Published in Print: 2019-02-25

© 2019 Zhuang-nian Li et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 Public License.

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  43. The Microstructure and Property of the Heat Affected zone in C-Mn Steel Treated by Rare Earth
  44. Microwave-Assisted Molten-Salt Facile Synthesis of Chromium Carbide (Cr3C2) Coatings on the Diamond Particles
  45. Effects of B on the Hot Ductility of Fe-36Ni Invar Alloy
  46. Impurity Distribution after Solidification of Hypereutectic Al-Si Melts and Eutectic Al-Si Melt
  47. Induced Electro-Deposition of High Melting-Point Phases on MgO–C Refractory in CaO–Al2O3–SiO2 – (MgO) Slag at 1773 K
  48. Microstructure and Mechanical Properties of 14Cr-ODS Steels with Zr Addition
  49. A Review of Boron-Rich Silicon Borides Basedon Thermodynamic Stability and Transport Properties of High-Temperature Thermoelectric Materials
  50. Siliceous Manganese Ore from Eastern India:A Potential Resource for Ferrosilicon-Manganese Production
  51. A Strain-Compensated Constitutive Model for Describing the Hot Compressive Deformation Behaviors of an Aged Inconel 718 Superalloy
  52. Surface Alloys of 0.45 C Carbon Steel Produced by High Current Pulsed Electron Beam
  53. Deformation Behavior and Processing Map during Isothermal Hot Compression of 49MnVS3 Non-Quenched and Tempered Steel
  54. A Constitutive Equation for Predicting Elevated Temperature Flow Behavior of BFe10-1-2 Cupronickel Alloy through Double Multiple Nonlinear Regression
  55. Oxidation Behavior of Ferritic Steel T22 Exposed to Supercritical Water
  56. A Multi Scale Strategy for Simulation of Microstructural Evolutions in Friction Stir Welding of Duplex Titanium Alloy
  57. Partition Behavior of Alloying Elements in Nickel-Based Alloys and Their Activity Interaction Parameters and Infinite Dilution Activity Coefficients
  58. Influence of Heating on Tensile Physical-Mechanical Properties of Granite
  59. Comparison of Al-Zn-Mg Alloy P-MIG Welded Joints Filled with Different Wires
  60. Microstructure and Mechanical Properties of Thick Plate Friction Stir Welds for 6082-T6 Aluminum Alloy
  61. Research Article
  62. Kinetics of oxide scale growth on a (Ti, Mo)5Si3 based oxidation resistant Mo-Ti-Si alloy at 900-1300C
  63. Calorimetric study on Bi-Cu-Sn alloys
  64. Mineralogical Phase of Slag and Its Effect on Dephosphorization during Converter Steelmaking Using Slag-Remaining Technology
  65. Controllability of joint integrity and mechanical properties of friction stir welded 6061-T6 aluminum and AZ31B magnesium alloys based on stationary shoulder
  66. Cellular Automaton Modeling of Phase Transformation of U-Nb Alloys during Solidification and Consequent Cooling Process
  67. The effect of MgTiO3Adding on Inclusion Characteristics
  68. Cutting performance of a functionally graded cemented carbide tool prepared by microwave heating and nitriding sintering
  69. Creep behaviour and life assessment of a cast nickel – base superalloy MAR – M247
  70. Failure mechanism and acoustic emission signal characteristics of coatings under the condition of impact indentation
  71. Reducing Surface Cracks and Improving Cleanliness of H-Beam Blanks in Continuous Casting — Improving continuous casting of H-beam blanks
  72. Rhodium influence on the microstructure and oxidation behaviour of aluminide coatings deposited on pure nickel and nickel based superalloy
  73. The effect of Nb content on precipitates, microstructure and texture of grain oriented silicon steel
  74. Effect of Arc Power on the Wear and High-temperature Oxidation Resistances of Plasma-Sprayed Fe-based Amorphous Coatings
  75. Short Communication
  76. Novel Combined Feeding Approach to Produce Quality Al6061 Composites for Heat Sinks
  77. Research Article
  78. Micromorphology change and microstructure of Cu-P based amorphous filler during heating process
  79. Controlling residual stress and distortion of friction stir welding joint by external stationary shoulder
  80. Research on the ingot shrinkage in the electroslag remelting withdrawal process for 9Cr3Mo roller
  81. Production of Mo2NiB2 Based Hard Alloys by Self-Propagating High-Temperature Synthesis
  82. The Morphology Analysis of Plasma-Sprayed Cast Iron Splats at Different Substrate Temperatures via Fractal Dimension and Circularity Methods
  83. A Comparative Study on Johnson–Cook, Modified Johnson–Cook, Modified Zerilli–Armstrong and Arrhenius-Type Constitutive Models to Predict Hot Deformation Behavior of TA2
  84. Dynamic absorption efficiency of paracetamol powder in microwave drying
  85. Preparation and Properties of Blast Furnace Slag Glass Ceramics Containing Cr2O3
  86. Influence of unburned pulverized coal on gasification reaction of coke in blast furnace
  87. Effect of PWHT Conditions on Toughness and Creep Rupture Strength in Modified 9Cr-1Mo Steel Welds
  88. Role of B2O3 on structure and shear-thinning property in CaO–SiO2–Na2O-based mold fluxes
  89. Effect of Acid Slag Treatment on the Inclusions in GCr15 Bearing Steel
  90. Recovery of Iron and Zinc from Blast Furnace Dust Using Iron-Bath Reduction
  91. Phase Analysis and Microstructural Investigations of Ce2Zr2O7 for High-Temperature Coatings on Ni-Base Superalloy Substrates
  92. Combustion Characteristics and Kinetics Study of Pulverized Coal and Semi-Coke
  93. Mechanical and Electrochemical Characterization of Supersolidus Sintered Austenitic Stainless Steel (316 L)
  94. Synthesis and characterization of Cu doped chromium oxide (Cr2O3) thin films
  95. Ladle Nozzle Clogging during casting of Silicon-Steel
  96. Thermodynamics and Industrial Trial on Increasing the Carbon Content at the BOF Endpoint to Produce Ultra-Low Carbon IF Steel by BOF-RH-CSP Process
  97. Research Article
  98. Effect of Boundary Conditions on Residual Stresses and Distortion in 316 Stainless Steel Butt Welded Plate
  99. Numerical Analysis on Effect of Additional Gas Injection on Characteristics around Raceway in Melter Gasifier
  100. Variation on thermal damage rate of granite specimen with thermal cycle treatment
  101. Effects of Fluoride and Sulphate Mineralizers on the Properties of Reconstructed Steel Slag
  102. Effect of Basicity on Precipitation of Spinel Crystals in a CaO-SiO2-MgO-Cr2O3-FeO System
  103. Review Article
  104. Exploitation of Mold Flux for the Ti-bearing Welding Wire Steel ER80-G
  105. Research Article
  106. Furnace heat prediction and control model and its application to large blast furnace
  107. Effects of Different Solid Solution Temperatures on Microstructure and Mechanical Properties of the AA7075 Alloy After T6 Heat Treatment
  108. Study of the Viscosity of a La2O3-SiO2-FeO Slag System
  109. Tensile Deformation and Work Hardening Behaviour of AISI 431 Martensitic Stainless Steel at Elevated Temperatures
  110. The Effectiveness of Reinforcement and Processing on Mechanical Properties, Wear Behavior and Damping Response of Aluminum Matrix Composites
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