Model for prediction of methanol formation in kraft pulping process using fast-growing eucalyptus wood

ZHANG Chunyun; CHAI Xinsheng

doi:10.11949/j.issn.0438-1157.20141646

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Model for prediction of methanol formation in kraft pulping process using fast-growing eucalyptus wood

更新时间：2025-12-10

- Model for prediction of methanol formation in kraft pulping process using fast-growing eucalyptus wood
- CIESC Journal Issue 3, Pages: 987-991(2015)
- 作者机构：
  
  华南理工大学制浆造纸工程国家重点实验室,广东,广州,510641
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20141646
  CLC： S743.1
- Online First：05 March 2015，
  
  Published：05 March 2015
- 稿件说明：
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ZHANG Chunyun, CHAI Xinsheng. Model for prediction of methanol formation in kraft pulping process using fast-growing eucalyptus wood[J]. CIESC Journal, 2015, (3): 987-991.
DOI：

ZHANG Chunyun, CHAI Xinsheng. Model for prediction of methanol formation in kraft pulping process using fast-growing eucalyptus wood[J]. CIESC Journal, 2015, (3): 987-991. DOI： 10.11949/j.issn.0438-1157.20141646.

摘要

以速生桉木硫酸盐法制浆为研究对象

考察了制浆过程中有效碱浓度、H因子(时间和温度)对甲醇生成量以及残余有效碱浓度变化的影响

研究发现制浆过程残余有效碱浓度与蒸煮H因子的负指数呈线性关系

结合这一关系从动力学角度建立了引入碱浓动态变化的制浆过程中预测甲醇生成量的数学模型。结果表明该模型能很好地预测速生桉木硫酸盐法蒸煮过程中各工艺条件下的甲醇生成量(R2 0.990)。模型的预测效果表明

温度对甲醇生成量影响显著

而初始有效碱浓度对甲醇生成量影响较小。实际生产中

可根据该模型对各工艺条件对甲醇生成量影响程度的预测效果适当改变工艺条件

以控制制浆过程中单位木素脱除量的甲醇生成量。

Abstract

The effects of the initial concentration of effective alkali

H factor (ie

coupled time and temperature) on methanol formation in the eucalyptus pulping and residual alkali concentration in the pulping effluents were investigated. It was found that there existed a linear relationship between the effective alkali concentration and negative exponent of H factor for pulping process. From this observation

a mathematical model that takes account for the time-dependent concentration of effective alkali was established from the kinetic analysis for wood demethoxylation during pulping process. The results showed that the proposed model could predict methanol formation in kraft pulping at various process conditions with a good accuracy (R2 = 0.990). It was found from the results predicted by this model that the methanol formation was much more sensitive to pulping temperature than to initial concentration of effective alkali. The prediction of this model for formation amount of methanol at various process conditions could be a good guidance for control and reduction of methanol formation per unit mass removal of lignin in pulping process.

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