CIESC Journal ›› 2024, Vol. 75 ›› Issue (12): 4617-4628.DOI: 10.11949/0438-1157.20240553
• Process system engineering • Previous Articles Next Articles
Xinshan KONG1(
), Xin GAO1, Lixia KANG1,2, Yongzhong LIU1,2(
)
Received:2024-05-23
Revised:2024-07-13
Online:2025-01-03
Published:2024-12-25
Contact:
Yongzhong LIU
通讯作者:
刘永忠
作者简介:孔昕山(1998—),男,博士研究生,xskong@stu.xjtu.edu.cn
基金资助:CLC Number:
Xinshan KONG, Xin GAO, Lixia KANG, Yongzhong LIU. Analysis and regulation on operating window of renewable methanol production system[J]. CIESC Journal, 2024, 75(12): 4617-4628.
孔昕山, 高鑫, 康丽霞, 刘永忠. 可再生甲醇生产系统操作窗口特性分析与调控[J]. 化工学报, 2024, 75(12): 4617-4628.
Add to citation manager EndNote|Ris|BibTeX
| 设备单元 | 约束条件 |
|---|---|
| 反应器 | 反应选择性、反应转化率、反应温度范围、压降 |
| 精馏塔 | 降液管液泛、雾沫夹带液泛、液相负荷上下限、漏液 |
| 换热器 | 换热面积余量、管程和壳程流速、管程和壳程压降、进出口ρv2 |
Table 1 Constraints of different equipment units
| 设备单元 | 约束条件 |
|---|---|
| 反应器 | 反应选择性、反应转化率、反应温度范围、压降 |
| 精馏塔 | 降液管液泛、雾沫夹带液泛、液相负荷上下限、漏液 |
| 换热器 | 换热面积余量、管程和壳程流速、管程和壳程压降、进出口ρv2 |
| 工艺参数 | 数值 |
|---|---|
| 进料CO2/H2摩尔比 | 1/3 |
| 进料H2流量 | 0.22 t/h |
| 甲醇产量和产品规格 | 7600 t/a, 98.5%(质量分数) |
| 循环摩尔比 | 4.8 |
| 单程转化率 | 29.01% |
| 选择性 | 99% |
| 吹扫排空气体 | 1% |
Table 2 Process parameter of methanol production system
| 工艺参数 | 数值 |
|---|---|
| 进料CO2/H2摩尔比 | 1/3 |
| 进料H2流量 | 0.22 t/h |
| 甲醇产量和产品规格 | 7600 t/a, 98.5%(质量分数) |
| 循环摩尔比 | 4.8 |
| 单程转化率 | 29.01% |
| 选择性 | 99% |
| 吹扫排空气体 | 1% |
| 约束条件 | 操作下限 | 操作上限 |
|---|---|---|
| 转化率 | 28.5% | — |
| 选择性 | 98.5% | — |
| 压降/bar | 0.1 | 0.4 |
Table 3 Constraints for adiabatic fixed-bed reactor
| 约束条件 | 操作下限 | 操作上限 |
|---|---|---|
| 转化率 | 28.5% | — |
| 选择性 | 98.5% | — |
| 压降/bar | 0.1 | 0.4 |
| 长度/m | 直径/m | 长径比 | 催化剂/kg | 操作窗口 |
|---|---|---|---|---|
| 6.0 | 0.75 | 8 | 4705 | 68%~140% |
| 5.6 | 0.70 | 8 | 3825 | 61%~113% |
| 6.4 | 0.80 | 8 | 5710 | 74%~152% |
| 4.9 | 0.85 | 6 | 4935 | 98%~148% |
| 4.8 | 0.80 | 6 | 4282 | 87%~127% |
| 5.2 | 0.90 | 6 | 5871 | — |
| 7.0 | 0.70 | 10 | 4781 | 55%~112% |
| 6.5 | 0.65 | 10 | 3828 | 50%~100% |
| 7.5 | 0.75 | 10 | 5881 | 60%~124% |
Table 4 Reactor equipment database
| 长度/m | 直径/m | 长径比 | 催化剂/kg | 操作窗口 |
|---|---|---|---|---|
| 6.0 | 0.75 | 8 | 4705 | 68%~140% |
| 5.6 | 0.70 | 8 | 3825 | 61%~113% |
| 6.4 | 0.80 | 8 | 5710 | 74%~152% |
| 4.9 | 0.85 | 6 | 4935 | 98%~148% |
| 4.8 | 0.80 | 6 | 4282 | 87%~127% |
| 5.2 | 0.90 | 6 | 5871 | — |
| 7.0 | 0.70 | 10 | 4781 | 55%~112% |
| 6.5 | 0.65 | 10 | 3828 | 50%~100% |
| 7.5 | 0.75 | 10 | 5881 | 60%~124% |
| 工艺参数 | 换热器1 | 冷却器 |
|---|---|---|
| 管程/壳程 | 1/1 | 1/1 |
| 壳径内/外 | 290/320 mm | 360/400 mm |
| 管长 | 3200 mm | 3000 mm |
| 折流板间距 | 120 mm | 120 mm |
| 管径内/外 | 10/14 mm | 15/19 mm |
| 管心距 | 18 mm | 25 mm |
| 折流板圆缺率 | 25% | 25% |
| 管根数 | 181 | 144 |
| 换热面积 | 24.5 m2 | 24.9 m2 |
Table 5 Heat exchangers design parameter results
| 工艺参数 | 换热器1 | 冷却器 |
|---|---|---|
| 管程/壳程 | 1/1 | 1/1 |
| 壳径内/外 | 290/320 mm | 360/400 mm |
| 管长 | 3200 mm | 3000 mm |
| 折流板间距 | 120 mm | 120 mm |
| 管径内/外 | 10/14 mm | 15/19 mm |
| 管心距 | 18 mm | 25 mm |
| 折流板圆缺率 | 25% | 25% |
| 管根数 | 181 | 144 |
| 换热面积 | 24.5 m2 | 24.9 m2 |
| 约束条件 | 操作下限 | 操作上限 |
|---|---|---|
| 管程流速/(m/s) | 0.6(液相);5(气相) | 3(液相);30(气相) |
| 壳程流速/(m/s) | 0.3(液相);2(气相) | 1.5(液相);15(气相) |
| 进出口ρv2/(kg/(m·s2)) | — | 5950 |
| 换热面积余量 | 0 | — |
Table 6 Constraints for heat exchanger
| 约束条件 | 操作下限 | 操作上限 |
|---|---|---|
| 管程流速/(m/s) | 0.6(液相);5(气相) | 3(液相);30(气相) |
| 壳程流速/(m/s) | 0.3(液相);2(气相) | 1.5(液相);15(气相) |
| 进出口ρv2/(kg/(m·s2)) | — | 5950 |
| 换热面积余量 | 0 | — |
| 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 |
|---|---|---|---|---|
| 320 | 3200 | 10 | 24.5 | 72%~135% |
| 300 | 3100 | 10 | 19.9 | 59%~105% |
| 340 | 3400 | 10 | 29.5 | 81%~173% |
| 350 | 2600 | 8 | 24.1 | 88%~106% |
| 320 | 2600 | 8 | 19.7 | — |
| 370 | 2900 | 8 | 29.9 | 96%~150% |
| 310 | 3800 | 12 | 24.9 | 61%~154% |
| 290 | 3500 | 12 | 19.9 | 53%~116% |
| 320 | 3900 | 12 | 29.3 | 70%~190% |
Table 7 Heat exchanger HE1 equipment database
| 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 |
|---|---|---|---|---|
| 320 | 3200 | 10 | 24.5 | 72%~135% |
| 300 | 3100 | 10 | 19.9 | 59%~105% |
| 340 | 3400 | 10 | 29.5 | 81%~173% |
| 350 | 2600 | 8 | 24.1 | 88%~106% |
| 320 | 2600 | 8 | 19.7 | — |
| 370 | 2900 | 8 | 29.9 | 96%~150% |
| 310 | 3800 | 12 | 24.9 | 61%~154% |
| 290 | 3500 | 12 | 19.9 | 53%~116% |
| 320 | 3900 | 12 | 29.3 | 70%~190% |
| 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 |
|---|---|---|---|---|
| 400 | 3000 | 7.5 | 24.9 | 58%~150% |
| 380 | 2800 | 7.5 | 19.9 | 97%~153% |
| 420 | 3100 | 7.5 | 29.0 | 62%~162% |
| 370 | 3700 | 10 | 24.2 | 55%~122% |
| 350 | 3400 | 10 | 19.5 | 47%~107% |
| 390 | 3800 | 10 | 30.2 | 57%~149% |
| 450 | 2300 | 5 | 25.5 | 76%~134% |
| 430 | 2100 | 5 | 21.1 | 67%~106% |
| 470 | 2400 | 5 | 30.8 | 75%~162% |
Table 8 Cooler C1 equipment database
| 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 |
|---|---|---|---|---|
| 400 | 3000 | 7.5 | 24.9 | 58%~150% |
| 380 | 2800 | 7.5 | 19.9 | 97%~153% |
| 420 | 3100 | 7.5 | 29.0 | 62%~162% |
| 370 | 3700 | 10 | 24.2 | 55%~122% |
| 350 | 3400 | 10 | 19.5 | 47%~107% |
| 390 | 3800 | 10 | 30.2 | 57%~149% |
| 450 | 2300 | 5 | 25.5 | 76%~134% |
| 430 | 2100 | 5 | 21.1 | 67%~106% |
| 470 | 2400 | 5 | 30.8 | 75%~162% |
| 工艺参数 | 数值 |
|---|---|
| 塔板类型 | NUTTER-BDP浮阀板 |
| 塔径 | 0.8 m |
| 板间距 | 0.6 m |
| 塔板数 | 24 |
| 堰长 | 0.64 m |
| 堰高 | 50 mm |
Table 9 Distillation column design parameter results
| 工艺参数 | 数值 |
|---|---|
| 塔板类型 | NUTTER-BDP浮阀板 |
| 塔径 | 0.8 m |
| 板间距 | 0.6 m |
| 塔板数 | 24 |
| 堰长 | 0.64 m |
| 堰高 | 50 mm |
| 约束条件 | 操作下限 | 操作上限 |
|---|---|---|
| 液泛率 | — | 85% |
| 降液管停留时间/s | 4 | — |
| 液相负荷/(m3/( m·h)) | 3.07 | — |
Table 10 Constraints for distillation column
| 约束条件 | 操作下限 | 操作上限 |
|---|---|---|
| 液泛率 | — | 85% |
| 降液管停留时间/s | 4 | — |
| 液相负荷/(m3/( m·h)) | 3.07 | — |
| 塔板数 | 进料板 | 塔径/m | 操作窗口 |
|---|---|---|---|
| 24 | 12 | 0.8 | 61%~125% |
| 27 | 14 | 0.8 | 73%~150% |
| 30 | 15 | 0.8 | 84%~162% |
| 24 | 12 | 0.9 | 69%~158% |
| 27 | 14 | 0.9 | 82%~189% |
| 30 | 15 | 0.9 | 94%~202% |
| 24 | 12 | 1.0 | 78%~194% |
| 27 | 14 | 1.0 | 92%~234% |
| 30 | 15 | 1.0 | — |
Table 11 Distillation column equipment database
| 塔板数 | 进料板 | 塔径/m | 操作窗口 |
|---|---|---|---|
| 24 | 12 | 0.8 | 61%~125% |
| 27 | 14 | 0.8 | 73%~150% |
| 30 | 15 | 0.8 | 84%~162% |
| 24 | 12 | 0.9 | 69%~158% |
| 27 | 14 | 0.9 | 82%~189% |
| 30 | 15 | 0.9 | 94%~202% |
| 24 | 12 | 1.0 | 78%~194% |
| 27 | 14 | 1.0 | 92%~234% |
| 30 | 15 | 1.0 | — |
| 设计情景 | 设计参数 | |||||
|---|---|---|---|---|---|---|
| 名义设计 | 反应器 | 长度/m | 直径/m | 长径比 | 催化剂/kg | 操作窗口 |
| 6.0 | 0.75 | 8 | 4705 | 68%~140% | ||
| 换热器HE1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 320 | 3200 | 10 | 24.5 | 72%~135% | ||
| 冷却器C1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 400 | 3000 | 7.5 | 24.9 | 58%~150% | ||
| 精馏塔 | 塔板数 | 进料板 | 塔径/m | 操作窗口 | ||
| 24 | 12 | 0.8 | 61%~125% | |||
| 最低操作下限 | 反应器 | 长度/m | 直径/m | 长径比 | 催化剂/kg | 操作窗口 |
| 7.5 | 0.75 | 10 | 5881 | 60%~124% | ||
| 换热器HE1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 310 | 3800 | 12 | 24.9 | 61%~154% | ||
| 冷却器C1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 400 | 3000 | 7.5 | 24.9 | 58%~150% | ||
| 精馏塔 | 塔板数 | 进料板 | 塔径/m | 操作窗口 | ||
| 24 | 12 | 0.8 | 61%~125% | |||
最高操作上限/ 最大操作窗口 | 反应器 | 长度/m | 直径/m | 长径比 | 催化剂/kg | 操作窗口 |
| 6.4 | 0.80 | 8 | 5710 | 74%~152% | ||
| 换热器HE1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 320 | 3900 | 12 | 29.3 | 70%~190% | ||
| 冷却器C1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 420 | 3100 | 7.5 | 29.0 | 62%~162% | ||
| 精馏塔 | 塔板数 | 进料板 | 塔径/m | 操作窗口 | ||
| 24 | 12 | 0.9 | 69%~158% | |||
Table 12 Parameters of equipment in various scenarios
| 设计情景 | 设计参数 | |||||
|---|---|---|---|---|---|---|
| 名义设计 | 反应器 | 长度/m | 直径/m | 长径比 | 催化剂/kg | 操作窗口 |
| 6.0 | 0.75 | 8 | 4705 | 68%~140% | ||
| 换热器HE1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 320 | 3200 | 10 | 24.5 | 72%~135% | ||
| 冷却器C1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 400 | 3000 | 7.5 | 24.9 | 58%~150% | ||
| 精馏塔 | 塔板数 | 进料板 | 塔径/m | 操作窗口 | ||
| 24 | 12 | 0.8 | 61%~125% | |||
| 最低操作下限 | 反应器 | 长度/m | 直径/m | 长径比 | 催化剂/kg | 操作窗口 |
| 7.5 | 0.75 | 10 | 5881 | 60%~124% | ||
| 换热器HE1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 310 | 3800 | 12 | 24.9 | 61%~154% | ||
| 冷却器C1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 400 | 3000 | 7.5 | 24.9 | 58%~150% | ||
| 精馏塔 | 塔板数 | 进料板 | 塔径/m | 操作窗口 | ||
| 24 | 12 | 0.8 | 61%~125% | |||
最高操作上限/ 最大操作窗口 | 反应器 | 长度/m | 直径/m | 长径比 | 催化剂/kg | 操作窗口 |
| 6.4 | 0.80 | 8 | 5710 | 74%~152% | ||
| 换热器HE1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 320 | 3900 | 12 | 29.3 | 70%~190% | ||
| 冷却器C1 | 壳径/mm | 管长/mm | 长径比 | 换热面积/m2 | 操作窗口 | |
| 420 | 3100 | 7.5 | 29.0 | 62%~162% | ||
| 精馏塔 | 塔板数 | 进料板 | 塔径/m | 操作窗口 | ||
| 24 | 12 | 0.9 | 69%~158% | |||
| 1 | Wang B, Wang Q, Wei Y M, et al. Role of renewable energy in China's energy security and climate change mitigation: an index decomposition analysis[J]. Renewable and Sustainable Energy Reviews, 2018, 90: 187-194. |
| 2 | Zhu Q Y, Chen X F, Song M L, et al. Impacts of renewable electricity standard and Renewable Energy Certificates on renewable energy investments and carbon emissions[J]. Journal of Environmental Management, 2022, 306: 114495. |
| 3 | González-Garay A, Frei M S, Al-Qahtani A, et al. Plant-to-planet analysis of CO2-based methanol processes[J]. Energy & Environmental Science, 2019, 12(12): 3425-3436. |
| 4 | Tabibian S S, Sharifzadeh M. Statistical and analytical investigation of methanol applications, production technologies, value-chain and economy with a special focus on renewable methanol[J]. Renewable and Sustainable Energy Reviews, 2023, 179: 113281. |
| 5 | Sun M Y, Zhao B H, Chen F P, et al. Thermally-assisted photocatalytic CO2 reduction to fuels[J]. Chemical Engineering Journal, 2021, 408: 127280. |
| 6 | 李鑫, 曾少娟, 彭奎霖, 等. CO2电催化还原制合成气研究进展及趋势[J]. 化工学报, 2023, 74(1): 313-329. |
| Li X, Zeng S J, Peng K L, et al. Research progress and tendency of CO2 electrocatalytic reduction to syngas[J]. CIESC Journal, 2023, 74(1): 313-329. | |
| 7 | Navarro-Jaén S, Virginie M, Bonin J, et al. Highlights and challenges in the selective reduction of carbon dioxide to methanol[J]. Nature Reviews Chemistry, 2021, 5(8): 564-579. |
| 8 | Wei H R, Su C Q, Dai J, et al. Towards a sustainable, and economic production future: proposing a new process for methanol production based on renewable hydrogen[J]. Journal of Cleaner Production, 2023, 389: 135976. |
| 9 | Bos M J, Kersten S R A, Brilman D W F. Wind power to methanol: Renewable methanol production using electricity, electrolysis of water and CO2 air capture[J]. Applied Energy, 2020, 264: 114672. |
| 10 | 孟文亮, 李贵贤, 周怀荣, 等. 绿氢重构的粉煤气化煤制甲醇近零碳排放工艺研究[J]. 化工学报, 2022, 73(4): 1714-1723. |
| Meng W L, Li G X, Zhou H R, et al. A novel coal to methanol process with near zero CO2 emission by pulverized coal gasification integrated green hydrogen[J]. CIESC Journal, 2022, 73(4): 1714-1723. | |
| 11 | Gu Y, Wang D F, Chen Q Q, et al. Techno-economic analysis of green methanol plant with optimal design of renewable hydrogen production: a case study in China[J]. International Journal of Hydrogen Energy, 2022, 47(8): 5085-5100. |
| 12 | Svitnič T, Sundmacher K. Renewable methanol production: optimization-based design, scheduling and waste-heat utilization with the FluxMax approach[J]. Applied Energy, 2022, 326: 120017. |
| 13 | Han Y L, Shi K N, Qian Y, et al. Design and operational optimization of a methanol-integrated wind-solar power generation system[J]. Journal of Environmental Chemical Engineering, 2023, 11(3): 109992. |
| 14 | Fu K H, Li M Z, Li P, et al. Designing CO2 reduction microreactor systems under fluctuating renewable H2 supply by multi-objective stochastic optimization[J]. Applied Energy, 2024, 357: 122482. |
| 15 | Kojima H, Nagasawa K, Todoroki N, et al. Influence of renewable energy power fluctuations on water electrolysis for green hydrogen production[J]. International Journal of Hydrogen Energy, 2023, 48(12): 4572-4593. |
| 16 | 孔昕山, 黄仁星, 康丽霞, 等. 甲醇模块化生产中分时储热系统的优化设计[J]. 化工学报, 2022, 73(2): 770-781. |
| Kong X S, Huang R X, Kang L X, et al. Optimal design of time-sharing heat storage system for modular production of methanol[J]. CIESC Journal, 2022, 73(2): 770-781. | |
| 17 | Herdem M S, Mazzeo D, Matera N, et al. Simulation and modeling of a combined biomass gasification-solar photovoltaic hydrogen production system for methanol synthesis via carbon dioxide hydrogenation[J]. Energy Conversion and Management, 2020, 219: 113045. |
| 18 | Decker M, Schorn F, Samsun R C, et al. Off-grid power-to-fuel systems for a market launch scenario - A techno-economic assessment[J]. Applied Energy, 2019, 250: 1099-1109. |
| 19 | Chen C, Yang A D. Power-to-methanol: the role of process flexibility in the integration of variable renewable energy into chemical production[J]. Energy Conversion and Management, 2021, 228: 113673. |
| 20 | Tso W W, Demirhan C D, Heuberger C F, et al. A hierarchical clustering decomposition algorithm for optimizing renewable power systems with storage[J]. Applied Energy, 2020, 270: 115190. |
| 21 | Ahmed U. Techno-economic analysis of dual methanol and hydrogen production using energy mix systems with CO2 capture[J]. Energy Conversion and Management, 2021, 228: 113663. |
| 22 | Wang J, Kang L X, Liu Y Z. Optimal design of a cooperated energy storage system to balance intermittent renewable energy and fluctuating demands of hydrogen and oxygen in refineries[J]. Computers & Chemical Engineering, 2021, 155: 107543. |
| 23 | Shirazi A, Rahbari A, Asselineau C A, et al. A solar fuel plant via supercritical water gasification integrated with Fischer–Tropsch synthesis: system-level dynamic simulation and optimisation[J]. Energy Conversion and Management, 2019, 192: 71-87. |
| 24 | Smith C, Torrente-Murciano L. The importance of dynamic operation and renewable energy source on the economic feasibility of green ammonia[J]. Joule, 2024, 8(1): 157-174. |
| 25 | Seifert T, Lesniak A K, Sievers S, et al. Capacity flexibility of chemical plants[J]. Chemical Engineering & Technology, 2014, 37(2): 332-342. |
| 26 | Sudhoff D, Leimbrink M, Schleinitz M, et al. Modelling, design and flexibility analysis of rotating packed beds for distillation[J]. Chemical Engineering Research and Design, 2015, 94: 72-89. |
| 27 | Radatz H, Elischewski J M, Heitmann M, et al. Design of equipment modules for flexibility[J]. Chemical Engineering Science, 2017, 168: 271-288. |
| 28 | Bruns B, Di Pretoro A, Grünewald M, et al. Flexibility analysis for demand-side management in large-scale chemical processes: an ethylene oxide production case study[J]. Chemical Engineering Science, 2021, 243: 116779. |
| 29 | Huang R X, Kang L X, Liu Y Z. Renewable synthetic methanol system design based on modular production lines[J]. Renewable and Sustainable Energy Reviews, 2022, 161: 112379. |
| 30 | Van-Dal É S, Bouallou C. Design and simulation of a methanol production plant from CO2 hydrogenation[J]. Journal of Cleaner Production, 2013, 57: 38-45. |
| 31 | 中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. 热交换器: [S]. 北京: 中国标准出版社, 2015. |
| General Administration of Quality Supervision Inspection and Quarantine of the People's Republic of China, Standardization Administration of the People's Republic of China. Heat exchangers: [S]. Beijing: Standards Press of China, 2015. | |
| 32 | 孙兰义. 换热器工艺设计[M]. 北京: 中国石化出版社, 2015: 77-171. |
| Sun L Y. Thermal Design of Heat Exchangers[M]. Beijing: China Petrochemical Press, 2015: 77-171. | |
| 33 | Standards of the Tubular Exchanger Manufacturers Association, Tubular Exchanger Manufacturers Association. TEMA, 10th ed [S]. USA: Tubular Exchanger Manufacturers Association, 2019. |
| [1] | Liming PU, Gui WANG, Chunlai ZHENG, Ke WANG, Tenglong XIANG, Zhihong WANG. Optimization and analysis of natural gas liquefaction process in mixed fluid cascade [J]. CIESC Journal, 2024, 75(S1): 267-275. |
| [2] | Jian HU, Jinghua JIANG, Shengjun FAN, Jianhao LIU, Haijiang ZOU, Wanlong CAI, Fenghao WANG. Research on heat extraction performance of deep U-type borehole heat exchanger [J]. CIESC Journal, 2024, 75(S1): 76-84. |
| [3] | Junfeng WANG, Junjie ZHANG, Wei ZHANG, Jiale WANG, Shuyan SHUANG, Yadong ZHANG. Liquid-phase discharge plasma decomposition of methanol for hydrogen production: optimization of electrode configuration [J]. CIESC Journal, 2024, 75(9): 3277-3286. |
| [4] | Ziyang LI, Nan ZHENG, Jiabin FANG, Jinjia WEI. Performance analysis and multi-objective optimization of recompression S-CO2 Brayton cycle [J]. CIESC Journal, 2024, 75(6): 2143-2156. |
| [5] | Rufeng XU, Yucheng CHEN, Dan GAO, Jingyu JIAO, Dong GAO, Haibin WANG, Shanjing YAO, Dongqiang LIN. Model-assisted process optimization of ion-exchange chromatography for monoclonal antibody charge variant separation [J]. CIESC Journal, 2024, 75(5): 1903-1911. |
| [6] | Yujiao ZENG, Xin XIAO, Gang YANG, Yibo ZHANG, Guangming ZHENG, Fang LI, Fengling WANG. Surrogate modeling and optimization of wet phosphoric acid production process based on mechanism and data hybrid driven [J]. CIESC Journal, 2024, 75(3): 936-944. |
| [7] | Lingxian ZHANG, Bin LIU, Lin DENG, Yuhang REN. PEMFC fault diagnosis based on improved TSO optimized Xception [J]. CIESC Journal, 2024, 75(3): 945-955. |
| [8] | Changhui LIU, Tong XIAO, Qingyi LIU, Long GENG, Jiateng ZHAO. Investigation of the thermal storage mechanism of porous TiO2 enhanced phase change materials [J]. CIESC Journal, 2024, 75(2): 706-714. |
| [9] | Yuhua YIN, Can FANG, Qingfeng YI, Guang LI. Impact of different carbon conductive agents on performance of iron-air battery [J]. CIESC Journal, 2024, 75(2): 685-694. |
| [10] | Ming LI, Luchang HAN, Hean LUO. Research on rapid reactor for propylene high-temperature chlorination based on NSGA-Ⅲ multi-objective optimization [J]. CIESC Journal, 2024, 75(12): 4547-4554. |
| [11] | Leilei GUO, Zhen WU, Fusheng YANG, Zaoxiao ZHANG. Experimental research on flow-through type metal hydride reactor running in by-product mixture for hydrogen purification [J]. CIESC Journal, 2024, 75(12): 4576-4586. |
| [12] | Yong ZHANG, Jingbo ZHAO, Limin QUAN. A prediction method for effluent ammonia nitrogen concentration based on convolutional layer and attention mechanism long short-term memory network [J]. CIESC Journal, 2024, 75(12): 4679-4688. |
| [13] | Jian CAO, Hongliang QIAN, Xin FENG, Xiaohua LU. Three questions on carbon neutrality from the perspective of thermodynamics [J]. CIESC Journal, 2024, 75(11): 4378-4384. |
| [14] | Wenjing LU, Xianfeng LI. Research process of porous composite ion conducting membranes for flow batteries [J]. CIESC Journal, 2024, 75(11): 3870-3882. |
| [15] | Gen LIU, Zhongshun SUN, Bo ZHANG, Rongjiang ZHANG, Zhiqiang WU, Bolun YANG. Establishment of machine learning-driven biomass pyrolysis model and optimization of volatiles chemical looping reforming hydrogen production process [J]. CIESC Journal, 2024, 75(11): 4333-4347. |
| Viewed | ||||||
|
Full text |
|
|||||
|
Abstract |
|
|||||