Optimization of steam-to-water ratio in sodium aluminate solution evaporation process based on dynamic evolution analysis of operation boundaries

REN Chao; HAN Jie; LIU Yishun; YANG Chunhua

doi:10.11949/0438-1157.20260808

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Optimization of steam-to-water ratio in sodium aluminate solution evaporation process based on dynamic evolution analysis of operation boundaries

更新时间：2026-08-07

- Optimization of steam-to-water ratio in sodium aluminate solution evaporation process based on dynamic evolution analysis of operation boundaries
- CIESC Journal (2026)
- 作者机构：
  
  中南大学自动化学院，湖南长沙 410083
- 作者简介：
- 基金信息：
- DOI：10.11949/0438-1157.20260808
  CLC： TP273
- Received：12 June 2026，
  
  Revised：2026-08-06，
  
  Accepted：07 August 2026，
- 稿件说明：
移动端阅览
REN Chao, HAN Jie, LIU Yishun, et al. Optimization of steam-to-water ratio in sodium aluminate solution evaporation process based on dynamic evolution analysis of operation boundaries[J/OL]. CIESC Journal, 2026.
DOI：

REN Chao, HAN Jie, LIU Yishun, et al. Optimization of steam-to-water ratio in sodium aluminate solution evaporation process based on dynamic evolution analysis of operation boundaries[J/OL]. CIESC Journal, 2026. DOI： 10.11949/0438-1157.20260808.

摘要

蒸发过程是氧化铝生产流程中的核心高能耗单元，降低其新蒸汽消耗是实现节能降耗的关键。因此，本文提出了一种基于趋势一致性ConvNeXt的蒸发系统建模与先验动态边界约束的汽水比优化方法。在建模阶段，通过对新蒸汽流量、进料量等操纵变量施加趋势一致性约束，构建了符合物理演化规律的数据驱动模型；在优化阶段，基于所建的模型分析了传热效率的下降对系统操作特性的影响，并揭示了操纵变量可行域边界的动态演变规律。同时，提出了自适应边界调整策略，在满足出料浓度约束的前提下实现了汽水比的优化。基于西南某氧化铝厂真实生产数据的验证表明，所提建模方法在确保预测精度的同时实现了物理趋势一致性；所提汽水比优化方法使平均蒸汽消耗降低8.17%，汽水比降低5.04%，为氧化铝蒸发过程的智能节能运行提供了新的解决方案。

Abstract

Evaporation is a core energy-intensive operation in the alumina production process

and reducing fresh steam consumption is essential for energy conservation. This paper proposes a steam-to-water ratio optimization method that integrates trend-consistency ConvNeXt-based system modeling with a priori dynamic boundary constraints. In the modeling stage

trend consistency constraints are imposed on manipulated variables such as fresh steam flow and feed rate

thereby constructing a data-driven model that conforms to physical evolution dynamics. In the optimization stage

the influence of heat transfer efficiency degradation on the operational characteristics of the evaporation system is analyzed based on the developed model

revealing the dynamic evolution of manipulated variable boundaries; an adaptive boundary adjustment strategy is then proposed to optimize the steam-to-water ratio while satisfying outlet concentration constraints. Validation based on real production data from an alumina plant in Southwest China demonstrates that the proposed modeling method ensures prediction accuracy while maintaining trend consistency with physical evolution; the proposed optimization method reduces average steam consumption by 8.17% and the steam-to-water ratio by 5.04%

providing a new solution for intelligent energy-efficient operation of the alumina evaporation process.

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