Home Effect of applying a full oxygen blast furnace on carbon emissions based on a carbon metabolism calculation model
Article Open Access

Effect of applying a full oxygen blast furnace on carbon emissions based on a carbon metabolism calculation model

  • Hui Li , Yuhua Xia , Qingyong Meng EMAIL logo , Hao Bai and Yunjin Xia EMAIL logo
Published/Copyright: May 15, 2024
Download Article (PDF)
Become an author with De Gruyter Brill
Submit Manuscript Author Information
High Temperature Materials and Processes
From the journal High Temperature Materials and Processes Volume 43 Issue 1

Abstract

In this study, the effects of applying a full oxygen blast furnace (FOBF) on carbon emissions were investigated by determining the ultimate minimum carbon consumption and a carbon metabolism calculation model. The results demonstrate that the minimum coke ratio of the top gas circulation-FOBF (TGR-FOBF) is significantly reduced (from 270 to 207 kg·thm−1) compared to that of the traditional ironmaking blast furnace (TBF). Owing to the complete recycling of the furnace top gas of the TGR-FOBF, the degree of direct reduction of TGR-FOBF significantly decreased to 0.14. The replacement of the TGR-FOBF with the three TBFs significantly reduced the CO2 emissions, which were the highest at 1.761 t-CO2/t-CS. Most of the CO2 emissions were generated by the direct combustion emissions (CDE) and direct process emissions (PDE), with a small amount generated by the electricity indirect emissions (EIE). The CO2 emissions generated by CDE, PDE, and EIE were 0.872 t-CO2/t-CS, 0.840 t-CO2/t-CS, and 0.049 t-CO2/t-CS, respectively. As the amount of TGR-FOBF replaced with the three TBFs increased, the CO2 emissions generated by the CDE and PDE significantly decreased. When all three TBFs were replaced with TGR–FOBF, the CO2 emissions generated by the CDE and PDE decreased to extremely low levels of 0.267 t-CO2/t-CS and 0.065 t-CO2/t-CS, respectively.

Keywords: full oxygen blast furnace; carbon emissions; carbon metabolism; model

1 Introduction

Approximately 91% of crude steel in China is produced using the traditional ironmaking blast furnace (TBF) – basic oxygen furnace process [1]. Direct emissions from the TBF process accounted for approximately 60% of the total plant carbon emissions; therefore, carbon reduction in the TBF process was the most important factor for reducing carbon emissions. Researchers have proposed many processes and technologies to replace the TBF process [2], such as reduction melting [3,4], direct reduction [5], iron ore electrolysis [6,7], hydrogen metallurgy [8,9], and top-gas recycling oxygen blast furnaces (TGR-OBF) [10]. Wenzel et al. [10] suggested that the TGR-OBF process is a low-carbon alternative to the TBF process that can change the traditional steelmaking process and has high application prospects. Many studies have been conducted regarding carbon emissions of the top gas circulation-full oxygen blast furnace (TGR-FOBF) process. Helle et al. [11,12] demonstrated that reducing both the production costs and emissions was conflicting for a steel plant with a TGR-FOBF process; thus, they formulated the task as a multi-objective optimization problem. Mitra et al. [13] encountered the multi-objective problem using genetic algorithms with a predator–prey strategy for constructing the Pareto frontier of non-dominating solutions. Four alternative methods for treating the top gas recycling problem were explored, for which cold-blowing oxygen and hot cycling gas were determined as the best methods. Arasto et al. [14] investigated the application of an OBF with and without carbon capture and storage (CCS) in an integrated steel mill and found that CO2 emissions can be significantly reduced by the application of an oxygen blast furnace and CCS. Tsupar et al. [15] evaluated the economic advantages of TBF steel plants, TBF steel plants with CCS, FOBF steel plants, and FOBF steel plants with CCS under different carbon taxes and electricity prices. Ghanbari et al. [16,17,18] studied the economic and environmental impacts of an integrated steelmaking plant using surrogate, empirical, and shortcut models based on the mass and energy balance equations for unit operations.

Production costs and emissions were considered equally important in the aforementioned studies, in which minimizing the production costs was more emphasized. Under the limitations of economic cost factors, such as an increase in the circulating gas volume, carbon capture (CC) costs increase [19]. Consequently, the carbon reduction potential of the TGR-FOBF process has not been fully demonstrated. Considering the current global advocacy for reducing CO2 emissions, steel mills are focusing more on carbon emissions than cost reduction. Researchers have also studied the impact of applying TGR-FOBFs for the carbon reduction efficiency and potential. Sahu et al. [20] studied the effects of the furnace charge and fuel properties on carbon consumption and CO2 emissions in the TGR-FOBF process by using a two‐zone furnace model, which demonstrated that the total carbon requirement ranges were estimated to decrease from 420–440 to 323–342 kg·thm−1 under optimal conditions. Jin et al. [21] established a TGR-OBF model comprising an oxygen blast furnace, top gas removal process, and preheating units. Based on an analysis of the material and energy flows, they concluded that the TGR-OBF significantly decreased the generation and consumption of metallurgical gas. In these studies, different modeling methods were used, including multidimensional models, discretized discrete element methods, and continuous fluid dynamics models. Owing to the different assumptions in each model, the carbon reduction potential of the TGR-FOBF process differed. However, these complex models do not intuitively reflect the mechanism, source, or essence of carbon reduction in the TGR-FOBF process [22].

A classic energy consumption analysis of TBF has been applied widely based on iron ore reduction and heat demand of TBF [23]. The theoretical minimum carbon consumption (TMCC) of TBF can be calculated by this method. However, this method cannot be directly used to obtain TMCC of FOBF. This is because recycling of the top gas would change carbon source and iron ore reduction environment of the blast furnace, and thus, the thermodynamic of iron ore indirect reduction must be considered to obtain carbon saving by the additional CO of the recycle gas. In this work, a novel and reasonable method for the calculation of FOBF carbon consumption which can reflect carbon reduction potential was proposed, and then the effect of FOBF application on energy mix and carbon reduction was comprehensively analyzed using carbon emission calculation model.

2 Ultimate carbon consumption model for FOBF

2.1 Thermodynamics of iron ore reduction

Because the majority of the iron ore reduction reactions in the TGR-FOBF are indirect, only the carbon consumption of the indirect reduction reaction is considered. The reduction sequence of iron ore is Fe2O3 → Fe3O4 → FeO → Fe. When the degree of direct reduction is less than 0.5, the overall amount of required CO for the iron ore reduction process in the TGR-FOBF can be obtained from equation (1):

(1) FeO ( s ) + n 1 CO ( g ) = Fe ( s ) + ( n 1 − 1 ) CO ( g ) + C O 2 ( g ) ,

where n 1 is the excess coefficient related to the temperature. Equation (1) demonstrates that the reduction reaction of iron ore requires additional CO; however, CO can only be generated from carbon in the TGR-FOBF, which indicates that when a greater amount of CO is required, a higher carbon consumption is required.

When there is no gas recycling system in the BF, the carbon consumption required for the indirect reduction of iron ore can be expressed as follows:

(2) w ( C ) 1 = 12 56 n 1 w [ Fe ] ( 1 − r d − r H 2 ) ,

where w [Fe] is the mass fraction of Fe in molten steel (%), r d is the degree of direct reduction, w(C)1 is the carbon consumption of the iron ore by indirect reduction (kg CO2·thm−1), r H2 is the degree of H2 reduction (%). According to the production data provided by the steel plant and the TBF production practice, because H2 in BF is only approximately 1% of the input C, the effect of H2 on the reduction of iron ore is relatively small. To simplify the calculation, the utilization rate of H2 is assumed to be 40%.

2.2 Theoretical ultimate carbon consumption and degree of direct reduction

Not all the CO can react with the iron ore in the TGR-FOBF process, and excess CO is discharged with the top gas of the furnace. The gas-recycling system can reinject this excess CO from the top gas into the furnace hearth for participation in the iron ore reduction reaction. Because the nitrogen from other materials in the TGR-FOBF process is little, the effect of nitrogen is ignored during the calculation. In an ideal situation, if this excess CO is not lost during the cycle and the thermal operation system remains unchanged, the heat distribution within the TGR-FOBF is considered constant, and the values of n 1 in equations (1) and (2) do not change. At this point, the iron-ore reduction reaction does not require additional CO. Therefore, the CO consumed by the indirect reduction reaction of iron ore in the TGR-FOBF process can be expressed as follows:

(3) w ( C ) 2 = 12 56 w [ Fe ] ( 1 − r d − r H 2 ) + 12 56 w [ Fe ] ( 1.5 − 1 ) = 12 56 w [ Fe ] ( 1.5 − r d − r H 2 ) .

Ignoring the effect of the water–gas reaction on the generation of CO, the CO entering the furnace top gas without reacting with the iron ore can be expressed as follows:

(4) V CO, Top gas = 22.4 12 [ w ( C ) 1 − w ( C ) 2 ] .

The carbon consumption caused by the heat demand in the TGR-FOBF process, w(C)Heat, can be expressed as follows:

(5) [ w ( C ) Heat − w ( C ) 2 ] q CO + w ( C ) 2 q C O 2 + Q Recycle gas = Q Output ,

where w(C)2 is the carbon consumption of the iron ore by indirect reduction in the TGR-FOBF process. q CO and q CO2 are the heats generated by the oxidation of carbon to CO and CO2, respectively, and q CO and q CO2 are 9,798 and 33,388 kJ·kg−1-C, respectively. Q Recycle gas is the heat generated by preheating the recycled gas (kJ). Q Output is the heat required to smelt 1 ton of molten iron (kJ), which can be calculated from the heat balance of the entire furnace.

By combining equations (3)–(5), the relationship between the carbon consumption w(C) and degree of direct reduction r d can be obtained, as shown in Figure 1, which demonstrates that as the degree of direct reduction increases, the carbon consumption for the indirect and direct reduction of iron ore decreases gradually, but the carbon consumption caused by the heat demand linearly increases. The lines of the carbon consumption for the indirect reduction and carbon consumption caused by the heat demand intersect at point A in Figure 1, which is theoretically the lowest point of the indirect reduction of carbon consumption for the TGR-FOBF process.

Figure 1 Relationship between the carbon consumption and degree of direct reduction.
Figure 1

Relationship between the carbon consumption and degree of direct reduction.

During the model-establishment process, the value of w(C)1 was determined using the value of the excess coefficient (n 1) in equation (1). However, obtaining the value of the excess coefficient is difficult because it is related to the temperature distribution during the TGR-FOBF process. In the TBF process, to ensure that the w(C)1 line was similar to a real situation, the degree of direct reduction of the real TBF and CO utilization rate of the furnace top gas were used to determine the w(C)1 line. Because the production operating conditions of the TGR-FOBF process simulated in this study were similar to those of the TBF process, the degree of direct reduction and CO utilization rate in the TBF process were used to calculate w(C)1 and n 1. The values of r d and η CO provided by the steel mill, as well as w(C)1 and n 1 calculated by equations (6) and (7), are listed in Table 1.

(6) η CO = φ CO 2 φ CO 2 + φ CO = w ( C ) 2 w ( C ) 1 ,

(7) n 1 = 12 56 w [ Fe ] ( 1.5 − r d − r H 2 ) 12 56 w [ Fe ] ( 1 − r d − r H 2 ) ⋅ η CO ,

where η CO is the CO utilization rate, and φ CO and φ CO2 are the ratios of CO and CO2 in the furnace top gas, respectively.

Table 1

Values of r d, η CO, w(C)1, and n 1

r d η CO n 1 w ( C ) 1
0.40 0.50 3.86 736.15 ‒ 780.55 r d

2.3 Calculation of the compositions of the top gas, recycle gas, and pure oxygen injection rate

The composition of the top gas in the TGR-FOBF process was calculated as follows:

(8) V C O 2 , Top gas = 22.4 12 w ( C ) 2 ,

(9) V H 2 , Top ga s = ( 1 − η H 2 ) Σ H 2 ,

(10) V H 2 O,Top ga s = 18 22.4 η H 2 Σ H 2 + 22.4 18 P ⋅ [ w ( H 2 O ) P, Free water + ( 1 − ψ H 2 O ) ⋅ w ( H 2 O ) P, Combined water ] ,

where V CO2, Top gas, V H2, Top gas, and V H2O, Top gas are the volumes of CO2, H2, and H2O in the top gas, respectively. P is the mixed ore (kg), w(H2O)P, Free water is the mass fraction of the free water contained in the mixed ore (%), ψ H 2 O is the decomposition rate of the crystalline water in the high-temperature zone of the raw material, which is 30% in this study, and w(H2O)P, Combined water is the mass fraction of bound water in the mixed ore (%). Significantly small amounts of N2 introduced by the mixed ore, coke, and pulverized coal injection (PCI) were ignored in this study.

Pressure swing adsorption technology was used in the CC process in this study. The adsorption material used in this process exhibited a unique recovery rate for each gas type in the top furnace. The recycle gas, V Recycle gas, is that which is re-injected into the blast furnace after passing through the CC process. The gas recovered by the CC process was CO2-enriched gas ( V C O 2 enriched gas ). The composition of the recycled gas was calculated CC as follows:

(11) V C O 2 , C O 2 enriched gas = V C O 2 , Top gas ⋅ X C O 2 ,

(12) V CO, C O 2 enriched gas = V CO, Top gas ⋅ X CO ,

(13) V H 2 , C O 2  enriched gas = V H 2 , Top ga s ⋅ X H 2 ,

(14) V N 2 , C O 2  enriched gas = V N 2 , Top gas ⋅ X N 2 ,

(15) V C O 2 enriched gas = ∑ i = 4 ( V Ga s i , C O 2 enriched gas ) ,

(16) V C O 2 , Recycle gas = V C O 2 , Top gas ⋅ ( 1 − X C O 2 ) ,

(17) V CO, Recycle gas = V CO,Top gas ⋅ ( 1 − X CO ) ,

(18) V H 2 , Recycle gas = V H 2 , Top gas ⋅ ( 1 − X H 2 ) ,

(19) V N 2 , Recycle gas = V N 2 ,Top gas ⋅ ( 1 − X N 2 ) ,

(20) V Recycle gas = ∑ i = 4 ( V Ga s i ,Recycle ga s ) .

where V C O 2 , C O 2   e n r i c h e d g a s , V C O , C O 2   e n r i c h e d g a s , V H 2 C O 2   e n r i c h e d g a s and V N 2 C O 2   e n r i c h e d g a s are the volumes of CO2, CO, H2, and N2 in the CO2-enriched gas, respectively. V CO2, Recycle gas, V CO, Recycle gas, V H 2 Recycle gas , and V N 2 Recycle gas are the volumes of CO2, CO, H2, and N2 in the recycled gas, respectively. X C O 2 , X CO, X H 2 , and X N 2 are the recovery rates of CO2, CO, H2, and N2 in the CC process, respectively.

The ultimate minimum carbon consumption (w(C)Total) and coke ratio (K) of the TGR-FOBF process at a coal ratio (M) of 170 kg·thm−1 can be expressed as follows:

(21) w ( C ) Total = w ( C ) ' + w ( C ) e + w ( C ) H 2 O + 22.4 12 ( V CO, C O 2  enriched gas − V C O 2 , Recycle ga s ) ,

(22) K = [ ( C ) − M ⋅ T ( C ) M ] T ( C ) K ,

where T(C)M is the mass fraction of C in PCI (%), T(C)K is the mass fraction of C in coke (%), w(C)′ is the carbon consumption of the indirect reduction (kg), w(C)e is the amount of carburization removed by the molten iron (kg), and w ( C ) H 2 O is the carbon consumption during the water–gas reaction of the ore in high-temperature regions (kg).

The required pure oxygen blowing volume for the TGR-FOBF process is expressed as follows:

(23) V Blast = 22.4 24 w ( C ) − w ( C ) d − 12 22.4 V C O 2 , Recycle gas ω O 2 ,

where ω O 2 is the concentration of O2 in the blast (%).

2.4 Carbon emission calculation model based on the carbon metabolism

Based on the input and output of the carbon metabolism process, a direct and indirect CO2 emission calculation model for steel enterprises was established to analyze the carbon metabolism in various processes within the steel plant. Steel plant emissions can be divided into direct and indirect CO2 emissions from purchased electricity and coke. Direct emissions include direct process emissions (PDE) and direct combustion emissions (CDE). In the TBF process, the PDE is composed of emitted CO, CO2, and CO2 in the traditional blast furnace gas (TBFG), and the CDE is the combustion of CO2 in the hot blast furnace waste. In contrast, in the TGR-FOBF process, because all of the top gas enters the gas recycling system, there is no PDE considered. The CO2 contained in the exhaust gas generated by the combustion of the gas preheating system or natural gas was considered as the CDE. The carbon emission analysis of other processes was included in the study by Tian et al. [24]. The PDE of various processes in a comprehensive steel plant can be calculated as follows:

(24) PDE k = ∑ i = 1 m RM i · EF RM i − ∑ j = 1 n PM j · EF PM j − GG k · CMEF g ,

where PDE k is the direct emission of k, RM i is the quantity of raw material i, PM j is the quantity of product j, EF PM j is the carbon emission factor of product j, GG k is the by-product gas of process k, and CMEF g is the carbon emission factor of the by-product gas, which can be obtained by the following:

(25) CMEF g = 44 22.4 ∑ i = 1 n w i ,

where w i is the volume fraction under standard conditions of the carbon combustion components in the by-product gas (g).

The CDE of various processes is expressed as follows:

(26) CDE k = ∑ i = 1 3 GC g · CMEF g + ∑ j = 1 n FC j · EF FC j ,

where CDE k is the direct combustion emission of k, GC g is the consumption of the by-product gas, FC j is the consumption of other fuels such as natural gas, coal, and coke, and EF FC j is the carbon emission factor of other fuels.

3 Results and discussion

3.1 Carbon reduction of the FOBF

The theoretical minimum of the indirect reduction carbon consumption point of the TGR-FOBF process was determined by combining equations (1)–(4). Subsequently, according to equations (5)–(23), as well as the raw materials and fuel conditions of the TGR-FOBF process, the corresponding production and operation data were calculated for the TGR-FOBF process. A comparison between the calculation results and TBF in the steel plant is presented in Table 2.

Table 2

Comparison of the operational parameters or indicators between TBF and TGR-FOBF

TBF TGR-FOBF
Fuel K (kg·thm−1) 325.0 207.0
M (kg·thm−1) 170.0 170.0
Top gas V Top gas (m3·thm−1) 1522.12 1228.22
φ CO 2 , Top gas ( Vol% ) 22.80 55.00
φ CO , Top gas ( Vol% ) 22.83 42.36
φ H 2 , Top ga s % (Vol%) 2.67 2.62
φ N 2 , Top ga s ( Vol% ) 48.92 —
φ H 2 O , Top gas ( Vol% ) 2.78 1.97
V Recycle gas (m3·thm−1) — 701.39
V CO 2  enriched ga s (m3·thm−1) — 502.62
Output gas (m3) 1,479 —
Operation parameter η CO (%) 50.09 42.36
r d 0.40 0.14
V Blast (m3·thm−1) 1005.2 222.6
ω O 2 (%) 25 99.2
t Blast (°C) 1,200 25
t Recycle gas (°C) — 1,200

According to the calculation results shown in Table 2, considering fuel, when the coal ratio was maintained at 170 kg·thm−1, the minimum coke ratio of TGR-FOBF significantly reduced (to 207 kg·thm−1) compared to that of TBF. Considering the furnace top gas, that of TBF will be completely exported to TBFG after dust removal and participate in the production of steel plants. The use of nearly pure oxygen blowing in the TGR-FOBF significantly reduces the total volume of the furnace top gas. Moreover, compared to TBF, the content of N2 in the furnace top gas of TBFG is extremely low, and it is mainly composed of CO and CO2. Consequently, the furnace top gas is fully circulated to utilize CO without producing metallurgical gas for export. Considering the operational parameters, the degree of direct reduction of the TBF was 0.4; however, that of the TGR-FOBF significantly decreased to 0.14 owing to recycling of the gas. The injection of pure oxygen at room temperature and recycled gas preheated to 1,200°C were used in TGR-FOBF. In contrast, the temperature of the injection gas was 1,200°C and no recycle gas was used in TBF. Therefore, owing to the significant changes in the coke ratio and operating parameters, the auxiliary equipment and direct CO2 emissions of TGR-FOBF will also undergo significant changes, mostly the introduction of CC units and a significant increase in the pure oxygen demand [25].

Figure 2 presents a comparison of the power and energy consumption of the auxiliary equipment in the TBF and TGR-FOBF. As shown in Figure 2, when the power consumption of the pure oxygen production of the air separation plant in the steel plant is maintained at 0.87 kW·h·m−3, the air separation unit in the auxiliary equipment of TGR-FOBF will consume the most electricity, reaching 193.63 kW·h·thm−1. In addition, the CC unit requires a large amount of electricity (119.7 kW·h·thm−1). Owing to the decrease in the amount of furnace top gas in the TGR-FOBF, the TRT power generation will also decrease. Therefore, without considering the entry of TBFG into self-generating power plants, the total power consumption of the TGR-FOBF process increases by 311%.

Figure 2 Comparison of the power and energy consumption of the auxiliary equipment between TBF and TGR-FOBF.
Figure 2

Comparison of the power and energy consumption of the auxiliary equipment between TBF and TGR-FOBF.

3.2 Analysis of replacing TBF with TGR-FOBF in steel plants

To systematically analyze the impact of applying the TGR-FOBF on the energy structure and emissions of steel plants, all three TBFs were replaced with TGR-FOBF in a steel plant. The scenarios for replacing TGR-FOBF with the three TBFs are listed in Table 3.

Table 3

Scenarios of the replacing all TBFs with TGR-FOBF

TBF TGR-FOBF
Basic scenario 3 0
Scenario 1 2 1
Scenario 2 1 2
Scenario 3 0 3

Figure 3 presents the calculation results of the comprehensive CO2 emissions (including CDE, PDE, and electricity indirect emission (EIE)) from the steel plants in each scenario. In the basic scenario, the steel plant generated the highest CO2 emissions of 1.761 t-CO2/t-CS. Most of the CO2 emissions were generated by the CDE and PDE, with a small amount generated by the EIE. The CO2 emissions generated by CDE, PDE, and EIE were 0.872 t-CO2/t-CS, 0.840 t-CO2/t-CS, and 0.049 t-CO2/t-CS, respectively. In scenario 1, the CO2 emissions generated by the PDE and CDE significantly decreased, but the CO2 emissions generated by the EIE correspondingly increased after a TBF was replaced with TGR-FOBF. The comprehensive CO2 emissions for Scenario 1 was 1.455 t-CO2/t-CS, which decreased by 17.4% compared to the basic scenario. For Scenario 2, the CO2 emissions further decreased to 1.148 t-CO2/t-CS, which decreased by 34.8% compared to the basic scenario. For scenario 3, when all three TBFs were replaced with TGR-FOBF, and natural gas with a high calorific value and low carbon content was purchased as supplementary fuel, the CO2 emissions generated by the CDE and PDE decreased to extremely low levels of 0.267 t-CO2/t-CS and 0.065 t-CO2/t-CS, respectively; however, the corresponding CO2 emissions generated by the EIE was the highest at 0.399 t-CO2/t-CS. The comprehensive CO2 emissions for Scenario 3 was 0.729 t-CO2/t-CS, which decreased by 58.6% compared to the basic scenario.

Figure 3 Comparison of the comprehensive CO2 emissions under different scenarios.
Figure 3

Comparison of the comprehensive CO2 emissions under different scenarios.

Figure 4 presents the total energy consumption and energy structure under different scenarios. For the basic scenario, the main energy source entering the steel plant was washed coal, accounting for 77.4%, which was mainly used to produce coke. As the TBF was gradually replaced with TGR-FOBF, the consumption of coke and the energy proportion of washed coal significantly decreased. In contrast, the proportions of energy consumed by the purchased electricity and natural gas correspondingly increased. For example, in Scenario 3, the energy proportion of washed coal decreased to 56.4%. The proportion of energy purchased from external sources significantly increased to 10.6%. Owing to the insufficient metallurgical gas produced by the steel plant department, the proportion of purchased natural gas increased to 9.6%. Therefore, the application of TGR-FOBF can significantly alter the energy structure of steel plants, which will change from primarily relying on coal as fuel to partially relying on purchased electricity and new fuels to supplement the internal heat demand.

Figure 4 (a) Total energy consumption and (b) energy structure under different scenarios.
Figure 4

(a) Total energy consumption and (b) energy structure under different scenarios.

Figure 5 presents the production sources and consumption of metallurgical gas or electricity within steel mills under different scenarios. For a basic scenario, the metallurgical gas generated by the TBF, coke oven, and converter can fully meet the production/consumption requirements of the steel plant, with an additional 10.25 GJ of metallurgical gas entering the self-generating process. When the power generation efficiency of the self-generating process in the steel plant is fixed at 36%, 955.2 kW·h of self-generated electricity is generated, and the final purchased electricity required by the steel plant is 257.4 kW·h. For Scenario 1, 5.29 GJ of metallurgical gas remains to enter the self-generating process, producing 455.8 kW·h of spontaneous electricity. The final amount of purchased electricity required by the steel plant was 1,047 kW·h. However, starting from Scenario 2, no metallurgical gas will enter the self-generating process, and the steel plant will need to purchase 0.38 GJ of natural gas to meet the production needs inside the plant. Electricity purchased from the steel plant will increase to 1,790.3 kW·h. For Scenario 3, the natural gas purchased from the steel plant increases to 5.33 GJ, and the electricity purchased from the steel plant increases to 2077.8 kW·h.

Figure 5 (a) Metallurgical gas balance and (b) power balance under different scenarios.
Figure 5

(a) Metallurgical gas balance and (b) power balance under different scenarios.

4 Conclusions

The effects of using a FOBF on carbon emissions from steel production were studied using a carbon metabolism calculation model. The results are summarized as follows:

  1. The minimum coke ratio of the TGR-FOBF was significantly reduced compared to that of the TBF, which reduced to 207 kg·thm−1 with coal ratio maintained at 170 kg·thm−1. The degree of direct reduction of TGR-FOBF significantly decreased to 0.14.

  2. Compared to the TBF, the air separation unit in the auxiliary equipment of the TGR-FOBF and CC unit required large amounts of electricity consumption. Without considering the entry of TBFG into self-generating power plants, the total power consumption of the TGR-FOBF process increases by 311%.

  3. The replacement of the three TBFs with TGR-FOBF significantly reduced the CO2 emissions. Most of the CO2 emissions were generated by the CDE and PDE, with a small amount generated by the EIE. The CO2 emissions generated by CDE, PDE, and EIE were 0.872 t-CO2/t-CS, 0.840 t-CO2/t-CS, and 0.049 t-CO2/t-CS, respectively. As the amount of TGR-FOBF replacing the three TBFs increased, the CO2 emissions generated by the CDE and PDE significantly decreased.

Acknowledgements

The authors would like to express their gratitude to the National Natural Science Fund (Grant Nos 52074001 and 52074003), and the Natural Science Foundation of Educational Department of Anhui Province (Grant No. 2022AH010024) for sponsoring this study. We would like to thank Editage (www.editage.cn) for English language editing.

  1. Funding information: Financial support for this study was supplied from the National Natural Science Fund of China (Grant Nos. 52074001 and 52074003), and the Natural Science Foundation of Educational Department of Anhui Province (Grant Nos. 2022AH010024 and DTR2023015) for sponsoring this study.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Conflict of interest: The authors state no conflict of interest.

References

[1] Zhang, Q., L. Shen, and L. Xu. Carbon peak and low-carbon transition path of China’s iron and steel industry. Iron and Steel, Vol. 56, 2021, pp. 152–163.Search in Google Scholar

[2] Hashimoto, Y., Y. Okamoto, T. Kaise, Y. Sawa, and M. Kano. Practical operation guidance on thermal control of blast furnace. ISIJ International, Vol. 59, 2019, pp. 573–1581.10.2355/isijinternational.ISIJINT-2019-119Search in Google Scholar

[3] Yu, H., J. Zhang, X. Pan, and B. Wei. S. B. Mineral transition of iron-aluminum symbiotic ore during melting reduction process. The Chinses Journal of Nonferrous Metals, Vol. 31, 2021, pp. 433–442.Search in Google Scholar

[4] Wang, M., R. Ren, H. Dong, G. Zhang, and S. Liu. Latest technology of melting reduction ironmaking process and discussion of process route choice. Iron and Steel, Vol. 55, 2020, pp. 145–150.Search in Google Scholar

[5] Nicola, Z., D. Paul, L. Leonie, and M. Giampaolo. SEWGS integration in a direct reduction steelmaking process for CO2 mitigation. International Journal of Greenhouse Gas Control, Vol. 130, 2023, id. 103991.10.1016/j.ijggc.2023.103991Search in Google Scholar

[6] Allanore, A., H. Lavelaine, G. Valentin, J. Birat, and F. Lapicque. Iron metal production by bulk electrolysis of iron ore particles in aqueous media. Journal of the Electrochemical Society, Vol. 155, 2009, pp. E125–E129.10.1149/1.2952547Search in Google Scholar

[7] Wang, J., H. Meng, L. Zhang, K. Jin, and H. Zhou. Application of a clean fuel produced by electrolysis in iron ore sintering process: Brown gas injection to assist sintering. Fuel Processing Technology, Vol. 251, 2023, id. 107932.10.1016/j.fuproc.2023.107932Search in Google Scholar

[8] Li, Z., Z. Qi, L. Zhang, M. Guo, D. Liang, and Q. Dong. Numerical simulation of H2-intensive shaft furnace direct reduction process. Journal of Cleaner Production, Vol. 409, 2023, id. 137059.10.1016/j.jclepro.2023.137059Search in Google Scholar

[9] Group, C. Relaunching a process that uses 100% H2 for the direct reduction of iron ore. Chemical Engineering, Vol. 129, 2022, id. 5.Search in Google Scholar

[10] Wenzel, W., H. Gudenau, T. Fukushima. Blast furnace operating methods. US3884677A, May, 1975.Search in Google Scholar

[11] Helle, H., M. Helle, F. Pettersson, and H. Saxen. Multi–objective optimization of ironmaking in the blast furnace with top gas recycling. ISIJ International, Vol. 50, 2010, pp. 1380–1387.10.2355/isijinternational.50.1380Search in Google Scholar

[12] Helle, H., M. Helle, H. Saxen, and F. Pettersson. Optimization of top gas recycling conditions under high oxygen enrichment in the blast furnace. ISIJ International, Vol. 50, 2010, pp. 931–938.10.2355/isijinternational.50.931Search in Google Scholar

[13] Mitra, T., M. Helle, F. Pettersson, H. Saxen, and N. Chakraborti. Multiobjective optimization of top gas recycling conditions in the blast furnace by genetic algorithms. Materials and manufacturing processes, Vol. 26, 2011, pp. 475–480.10.1080/10426914.2010.515644Search in Google Scholar

[14] Arasto, A., E. Tsupar, J. Kärki, J. Lilja, and M. Sihvonen. Oxygen blast furnace with CO2 capture and storage at an integrated steel mill—Part I: Technical concept analysis. International Journal of Greenhouse Gas Control, Vol. 30, 2014, pp. 140–147.10.1016/j.ijggc.2014.09.004Search in Google Scholar

[15] Tsupar, E., J. Kärki, A. Arasto, J. Lilja, K. Kinnunen, and M. Sihvonen. Oxygen blast furnace with CO2 capture and storage at an integrated steel mill—Part II: Economic feasibility in comparison with conventional blast furnace highlighting sensitivities. International Journal of Greenhouse Gas Control, Vol. 32, 2015, pp. 189–196.10.1016/j.ijggc.2014.11.007Search in Google Scholar

[16] Ghanbari, H., M. Helle, F. Pettersson, and H. Saxen. Optimization study of steelmaking under novel blast furnace operation combined with methanol production. Industrial & Engineering Chemistry Research, Vol. 50, 2011, pp. 12103–12112.10.1021/ie201198jSearch in Google Scholar

[17] Ghanbari, H., F. Pettersson, and H. Saxen. Optimal operation strategy and gas utilization in a future integrated steel plant. Chemical Engineering Research and Design, Vol. 102, 2015, pp. 322–336.10.1016/j.cherd.2015.06.038Search in Google Scholar

[18] Ghanbari, H., F. Pettersson, and H. Saxen. Sustainable development of primary steelmaking under novel blast furnace operation and injection of different reducing agents. Chemical Engineering Science, Vol. 129, 2015, pp. 208–222.10.1016/j.ces.2015.01.069Search in Google Scholar

[19] Helle, H., M. Helle, and H. Saxén. Nonlinear optimization of steel production using traditional and novel blast furnace operation strategies. Chemical Engineering Science, Vol. 66, 2011, pp. 6470–6481.10.1016/j.ces.2011.09.006Search in Google Scholar

[20] Sahu, R., S. Roy, and P. Sen. Applicability of top gas recycle blast furnace with downstream integration and sequestration in an integrated steel plant. Steel Research International, Vol. 86, 2015, pp. 502–516.10.1002/srin.201400196Search in Google Scholar

[21] Jin, P., Z. Jiang, C. Bao, S. Hao, and X. Zhang. The energy consumption and carbon emission of the integrated steel mill with oxygen blast furnace. Resources Conservation and Recycling, Vol. 117, 2017, pp. 58–65.10.1016/j.resconrec.2015.07.008Search in Google Scholar

[22] Zhang, J., S. Wu, and X. Wang. Iron and Steel Metallurgy (Ironmaking Part), Metallurgical Industry Press, Beijing, 2019.Search in Google Scholar

[23] Zhang, Z., J. Meng, L. Guo, and Z. Guo. Numerical study of the reduction process in an oxygen blast furnace. Metallurgical and materials transactions B, Vol. 47B, 2016, pp. 467–484.10.1007/s11663-015-0483-ySearch in Google Scholar

[24] Tian, W., H. An, X. Li, H. Li, K. Quan, X. Lu et al. CO2 accounting model and carbon reduction analysis of iron and steel plants based on intra– and inter–process carbon metabolism. Journal of Cleaner Production, Vol. 360, 2022, id. 132190.10.1016/j.jclepro.2022.132190Search in Google Scholar

[25] Quader, M., S. Ahmed, S. Dawal, and Y. Nukman. Present needs, recent progress and future trends of energy–efficient ultra–low carbon dioxide (CO) steelmaking (ULCOS) program. Renewable and Sustainable Energy Reviews, Vol. 55, 2016, pp. 537–549.10.1016/j.rser.2015.10.101Search in Google Scholar
Received: 2023-12-23
Revised: 2024-04-06
Accepted: 2024-04-22
Published Online: 2024-05-15

© 2024 the author(s), published by De Gruyter

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

Articles in the same Issue

  1. Research Articles
  2. De-chlorination of poly(vinyl) chloride using Fe2O3 and the improvement of chlorine fixing ratio in FeCl2 by SiO2 addition
  3. Reductive behavior of nickel and iron metallization in magnesian siliceous nickel laterite ores under the action of sulfur-bearing natural gas
  4. Study on properties of CaF2–CaO–Al2O3–MgO–B2O3 electroslag remelting slag for rack plate steel
  5. The origin of {113}<361> grains and their impact on secondary recrystallization in producing ultra-thin grain-oriented electrical steel
  6. Channel parameter optimization of one-strand slab induction heating tundish with double channels
  7. Effect of rare-earth Ce on the texture of non-oriented silicon steels
  8. Performance optimization of PERC solar cells based on laser ablation forming local contact on the rear
  9. Effect of ladle-lining materials on inclusion evolution in Al-killed steel during LF refining
  10. Analysis of metallurgical defects in enamel steel castings
  11. Effect of cooling rate and Nb synergistic strengthening on microstructure and mechanical properties of high-strength rebar
  12. Effect of grain size on fatigue strength of 304 stainless steel
  13. Analysis and control of surface cracks in a B-bearing continuous casting blooms
  14. Application of laser surface detection technology in blast furnace gas flow control and optimization
  15. Preparation of MoO3 powder by hydrothermal method
  16. The comparative study of Ti-bearing oxides introduced by different methods
  17. Application of MgO/ZrO2 coating on 309 stainless steel to increase resistance to corrosion at high temperatures and oxidation by an electrochemical method
  18. Effect of applying a full oxygen blast furnace on carbon emissions based on a carbon metabolism calculation model
  19. Characterization of low-damage cutting of alfalfa stalks by self-sharpening cutters made of gradient materials
  20. Thermo-mechanical effects and microstructural evolution-coupled numerical simulation on the hot forming processes of superalloy turbine disk
  21. Endpoint prediction of BOF steelmaking based on state-of-the-art machine learning and deep learning algorithms
  22. Effect of calcium treatment on inclusions in 38CrMoAl high aluminum steel
  23. Effect of isothermal transformation temperature on the microstructure, precipitation behavior, and mechanical properties of anti-seismic rebar
  24. Evolution of residual stress and microstructure of 2205 duplex stainless steel welded joints during different post-weld heat treatment
  25. Effect of heating process on the corrosion resistance of zinc iron alloy coatings
  26. BOF steelmaking endpoint carbon content and temperature soft sensor model based on supervised weighted local structure preserving projection
  27. Innovative approaches to enhancing crack repair: Performance optimization of biopolymer-infused CXT
  28. Structural and electrochromic property control of WO3 films through fine-tuning of film-forming parameters
  29. Influence of non-linear thermal radiation on the dynamics of homogeneous and heterogeneous chemical reactions between the cone and the disk
  30. Thermodynamic modeling of stacking fault energy in Fe–Mn–C austenitic steels
  31. Research on the influence of cemented carbide micro-textured structure on tribological properties
  32. Performance evaluation of fly ash-lime-gypsum-quarry dust (FALGQ) bricks for sustainable construction
  33. First-principles study on the interfacial interactions between h-BN and Si3N4
  34. Analysis of carbon emission reduction capacity of hydrogen-rich oxygen blast furnace based on renewable energy hydrogen production
  35. Just-in-time updated DBN BOF steel-making soft sensor model based on dense connectivity of key features
  36. Effect of tempering temperature on the microstructure and mechanical properties of Q125 shale gas casing steel
  37. Review Articles
  38. A review of emerging trends in Laves phase research: Bibliometric analysis and visualization
  39. Effect of bottom stirring on bath mixing and transfer behavior during scrap melting in BOF steelmaking: A review
  40. High-temperature antioxidant silicate coating of low-density Nb–Ti–Al alloy: A review
  41. Communications
  42. Experimental investigation on the deterioration of the physical and mechanical properties of autoclaved aerated concrete at elevated temperatures
  43. Damage evaluation of the austenitic heat-resistance steel subjected to creep by using Kikuchi pattern parameters
  44. Topical Issue on Focus of Hot Deformation of Metaland High Entropy Alloys - Part II
  45. Synthesis of aluminium (Al) and alumina (Al2O3)-based graded material by gravity casting
  46. Experimental investigation into machining performance of magnesium alloy AZ91D under dry, minimum quantity lubrication, and nano minimum quantity lubrication environments
  47. Numerical simulation of temperature distribution and residual stress in TIG welding of stainless-steel single-pass flange butt joint using finite element analysis
  48. Special Issue on A Deep Dive into Machining and Welding Advancements - Part I
  49. Electro-thermal performance evaluation of a prismatic battery pack for an electric vehicle
  50. Experimental analysis and optimization of machining parameters for Nitinol alloy: A Taguchi and multi-attribute decision-making approach
  51. Experimental and numerical analysis of temperature distributions in SA 387 pressure vessel steel during submerged arc welding
  52. Optimization of process parameters in plasma arc cutting of commercial-grade aluminium plate
  53. Multi-response optimization of friction stir welding using fuzzy-grey system
  54. Mechanical and micro-structural studies of pulsed and constant current TIG weldments of super duplex stainless steels and Austenitic stainless steels
  55. Stretch-forming characteristics of austenitic material stainless steel 304 at hot working temperatures
  56. Work hardening and X-ray diffraction studies on ASS 304 at high temperatures
  57. Study of phase equilibrium of refractory high-entropy alloys using the atomic size difference concept for turbine blade applications
  58. A novel intelligent tool wear monitoring system in ball end milling of Ti6Al4V alloy using artificial neural network
  59. A hybrid approach for the machinability analysis of Incoloy 825 using the entropy-MOORA method
  60. Special Issue on Recent Developments in 3D Printed Carbon Materials - Part II
  61. Innovations for sustainable chemical manufacturing and waste minimization through green production practices
  62. Topical Issue on Conference on Materials, Manufacturing Processes and Devices - Part I
  63. Characterization of Co–Ni–TiO2 coatings prepared by combined sol-enhanced and pulse current electrodeposition methods
  64. Hot deformation behaviors and microstructure characteristics of Cr–Mo–Ni–V steel with a banded structure
  65. Effects of normalizing and tempering temperature on the bainite microstructure and properties of low alloy fire-resistant steel bars
  66. Dynamic evolution of residual stress upon manufacturing Al-based diesel engine diaphragm
  67. Study on impact resistance of steel fiber reinforced concrete after exposure to fire
  68. Bonding behaviour between steel fibre and concrete matrix after experiencing elevated temperature at various loading rates
  69. Diffusion law of sulfate ions in coral aggregate seawater concrete in the marine environment
  70. Microstructure evolution and grain refinement mechanism of 316LN steel
  71. Investigation of the interface and physical properties of a Kovar alloy/Cu composite wire processed by multi-pass drawing
  72. The investigation of peritectic solidification of high nitrogen stainless steels by in-situ observation
  73. Microstructure and mechanical properties of submerged arc welded medium-thickness Q690qE high-strength steel plate joints
  74. Experimental study on the effect of the riveting process on the bending resistance of beams composed of galvanized Q235 steel
  75. Density functional theory study of Mg–Ho intermetallic phases
  76. Investigation of electrical properties and PTCR effect in double-donor doping BaTiO3 lead-free ceramics
  77. Special Issue on Thermal Management and Heat Transfer
  78. On the thermal performance of a three-dimensional cross-ternary hybrid nanofluid over a wedge using a Bayesian regularization neural network approach
  79. Time dependent model to analyze the magnetic refrigeration performance of gadolinium near the room temperature
  80. Heat transfer characteristics in a non-Newtonian (Williamson) hybrid nanofluid with Hall and convective boundary effects
  81. Computational role of homogeneous–heterogeneous chemical reactions and a mixed convective ternary hybrid nanofluid in a vertical porous microchannel
  82. Thermal conductivity evaluation of magnetized non-Newtonian nanofluid and dusty particles with thermal radiation
https://doi.org/10.1515/htmp-2024-0012
Keywords for this article
full oxygen blast furnace; carbon emissions; carbon metabolism; model
Creative Commons
BY 4.0

Articles in the same Issue

  1. Research Articles
  2. De-chlorination of poly(vinyl) chloride using Fe2O3 and the improvement of chlorine fixing ratio in FeCl2 by SiO2 addition
  3. Reductive behavior of nickel and iron metallization in magnesian siliceous nickel laterite ores under the action of sulfur-bearing natural gas
  4. Study on properties of CaF2–CaO–Al2O3–MgO–B2O3 electroslag remelting slag for rack plate steel
  5. The origin of {113}<361> grains and their impact on secondary recrystallization in producing ultra-thin grain-oriented electrical steel
  6. Channel parameter optimization of one-strand slab induction heating tundish with double channels
  7. Effect of rare-earth Ce on the texture of non-oriented silicon steels
  8. Performance optimization of PERC solar cells based on laser ablation forming local contact on the rear
  9. Effect of ladle-lining materials on inclusion evolution in Al-killed steel during LF refining
  10. Analysis of metallurgical defects in enamel steel castings
  11. Effect of cooling rate and Nb synergistic strengthening on microstructure and mechanical properties of high-strength rebar
  12. Effect of grain size on fatigue strength of 304 stainless steel
  13. Analysis and control of surface cracks in a B-bearing continuous casting blooms
  14. Application of laser surface detection technology in blast furnace gas flow control and optimization
  15. Preparation of MoO3 powder by hydrothermal method
  16. The comparative study of Ti-bearing oxides introduced by different methods
  17. Application of MgO/ZrO2 coating on 309 stainless steel to increase resistance to corrosion at high temperatures and oxidation by an electrochemical method
  18. Effect of applying a full oxygen blast furnace on carbon emissions based on a carbon metabolism calculation model
  19. Characterization of low-damage cutting of alfalfa stalks by self-sharpening cutters made of gradient materials
  20. Thermo-mechanical effects and microstructural evolution-coupled numerical simulation on the hot forming processes of superalloy turbine disk
  21. Endpoint prediction of BOF steelmaking based on state-of-the-art machine learning and deep learning algorithms
  22. Effect of calcium treatment on inclusions in 38CrMoAl high aluminum steel
  23. Effect of isothermal transformation temperature on the microstructure, precipitation behavior, and mechanical properties of anti-seismic rebar
  24. Evolution of residual stress and microstructure of 2205 duplex stainless steel welded joints during different post-weld heat treatment
  25. Effect of heating process on the corrosion resistance of zinc iron alloy coatings
  26. BOF steelmaking endpoint carbon content and temperature soft sensor model based on supervised weighted local structure preserving projection
  27. Innovative approaches to enhancing crack repair: Performance optimization of biopolymer-infused CXT
  28. Structural and electrochromic property control of WO3 films through fine-tuning of film-forming parameters
  29. Influence of non-linear thermal radiation on the dynamics of homogeneous and heterogeneous chemical reactions between the cone and the disk
  30. Thermodynamic modeling of stacking fault energy in Fe–Mn–C austenitic steels
  31. Research on the influence of cemented carbide micro-textured structure on tribological properties
  32. Performance evaluation of fly ash-lime-gypsum-quarry dust (FALGQ) bricks for sustainable construction
  33. First-principles study on the interfacial interactions between h-BN and Si3N4
  34. Analysis of carbon emission reduction capacity of hydrogen-rich oxygen blast furnace based on renewable energy hydrogen production
  35. Just-in-time updated DBN BOF steel-making soft sensor model based on dense connectivity of key features
  36. Effect of tempering temperature on the microstructure and mechanical properties of Q125 shale gas casing steel
  37. Review Articles
  38. A review of emerging trends in Laves phase research: Bibliometric analysis and visualization
  39. Effect of bottom stirring on bath mixing and transfer behavior during scrap melting in BOF steelmaking: A review
  40. High-temperature antioxidant silicate coating of low-density Nb–Ti–Al alloy: A review
  41. Communications
  42. Experimental investigation on the deterioration of the physical and mechanical properties of autoclaved aerated concrete at elevated temperatures
  43. Damage evaluation of the austenitic heat-resistance steel subjected to creep by using Kikuchi pattern parameters
  44. Topical Issue on Focus of Hot Deformation of Metaland High Entropy Alloys - Part II
  45. Synthesis of aluminium (Al) and alumina (Al2O3)-based graded material by gravity casting
  46. Experimental investigation into machining performance of magnesium alloy AZ91D under dry, minimum quantity lubrication, and nano minimum quantity lubrication environments
  47. Numerical simulation of temperature distribution and residual stress in TIG welding of stainless-steel single-pass flange butt joint using finite element analysis
  48. Special Issue on A Deep Dive into Machining and Welding Advancements - Part I
  49. Electro-thermal performance evaluation of a prismatic battery pack for an electric vehicle
  50. Experimental analysis and optimization of machining parameters for Nitinol alloy: A Taguchi and multi-attribute decision-making approach
  51. Experimental and numerical analysis of temperature distributions in SA 387 pressure vessel steel during submerged arc welding
  52. Optimization of process parameters in plasma arc cutting of commercial-grade aluminium plate
  53. Multi-response optimization of friction stir welding using fuzzy-grey system
  54. Mechanical and micro-structural studies of pulsed and constant current TIG weldments of super duplex stainless steels and Austenitic stainless steels
  55. Stretch-forming characteristics of austenitic material stainless steel 304 at hot working temperatures
  56. Work hardening and X-ray diffraction studies on ASS 304 at high temperatures
  57. Study of phase equilibrium of refractory high-entropy alloys using the atomic size difference concept for turbine blade applications
  58. A novel intelligent tool wear monitoring system in ball end milling of Ti6Al4V alloy using artificial neural network
  59. A hybrid approach for the machinability analysis of Incoloy 825 using the entropy-MOORA method
  60. Special Issue on Recent Developments in 3D Printed Carbon Materials - Part II
  61. Innovations for sustainable chemical manufacturing and waste minimization through green production practices
  62. Topical Issue on Conference on Materials, Manufacturing Processes and Devices - Part I
  63. Characterization of Co–Ni–TiO2 coatings prepared by combined sol-enhanced and pulse current electrodeposition methods
  64. Hot deformation behaviors and microstructure characteristics of Cr–Mo–Ni–V steel with a banded structure
  65. Effects of normalizing and tempering temperature on the bainite microstructure and properties of low alloy fire-resistant steel bars
  66. Dynamic evolution of residual stress upon manufacturing Al-based diesel engine diaphragm
  67. Study on impact resistance of steel fiber reinforced concrete after exposure to fire
  68. Bonding behaviour between steel fibre and concrete matrix after experiencing elevated temperature at various loading rates
  69. Diffusion law of sulfate ions in coral aggregate seawater concrete in the marine environment
  70. Microstructure evolution and grain refinement mechanism of 316LN steel
  71. Investigation of the interface and physical properties of a Kovar alloy/Cu composite wire processed by multi-pass drawing
  72. The investigation of peritectic solidification of high nitrogen stainless steels by in-situ observation
  73. Microstructure and mechanical properties of submerged arc welded medium-thickness Q690qE high-strength steel plate joints
  74. Experimental study on the effect of the riveting process on the bending resistance of beams composed of galvanized Q235 steel
  75. Density functional theory study of Mg–Ho intermetallic phases
  76. Investigation of electrical properties and PTCR effect in double-donor doping BaTiO3 lead-free ceramics
  77. Special Issue on Thermal Management and Heat Transfer
  78. On the thermal performance of a three-dimensional cross-ternary hybrid nanofluid over a wedge using a Bayesian regularization neural network approach
  79. Time dependent model to analyze the magnetic refrigeration performance of gadolinium near the room temperature
  80. Heat transfer characteristics in a non-Newtonian (Williamson) hybrid nanofluid with Hall and convective boundary effects
  81. Computational role of homogeneous–heterogeneous chemical reactions and a mixed convective ternary hybrid nanofluid in a vertical porous microchannel
  82. Thermal conductivity evaluation of magnetized non-Newtonian nanofluid and dusty particles with thermal radiation
Sign up now to receive a 20% welcome discount
Institutional Access
How does access work?
Have an idea on how to improve our website?
Please write us.
© 2025 De Gruyter Brill
Downloaded on 16.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/htmp-2024-0012/html
Scroll to top button