GOALI/IUCP: Prediction of Wood Pulp K-Number with Neural Networks
GOALI/IUCP:用神经网络预测木浆 K 值
基本信息
- 批准号:9522981
- 负责人:
- 金额:$ 7.95万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:1996
- 资助国家:美国
- 起止时间:1996-04-01 至 1999-03-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
9522981 Musavi Lignin holds wood fibers together, and must be removed to produce high strength pulp for kraft paper. The Kappa- or K-number indicates the degree of lignin removal by a pulping process, and is probably the key variable for measuring quality in this process. A difficulty is that it is an off-line measurement. More importantly, there is usually a four hour process delay between when raw materials enter a pulping digester and when the K-number is measured. This makes modeling and control difficult. This Grant Opportunity for Academic Liaison with Industry project uses neural network models to predict K-number as a function of a number of more readily available process parameters. This is a first step in improving the control and responsiveness of this process to changes in chip feed stock. The research team from the University of Maine and S.D. Warren Company will develop characterization and prediction models using data from an operating plant, and compare their long term predicative capability when integrated into digester operations. Throughout, seminar and workshops are part of the technology transfer and model improvement. The impact of this research will be more uniform quality of pulp, even with variable feed stock, and more uniform quality in subsequent bleaching and papermaking processes.
小行星9522981 木质素将木材纤维结合在一起,必须去除木质素以生产用于牛皮纸的高强度纸浆。 卡伯值或K值表示制浆过程中木质素的去除程度,并且可能是该过程中测量质量的关键变量。 困难在于它是离线测量。 更重要的是,从原料进入制浆蒸煮器到测量K值之间通常有四个小时的工艺延迟。 这使得建模和控制变得困难。 这个学术联络与工业项目的赠款机会使用神经网络模型来预测K数作为一个更容易获得的过程参数的函数。 这是改善该过程对木片进料变化的控制和响应的第一步。 来自缅因州大学和南达科他州的研究小组。Warren公司将使用来自运营工厂的数据开发表征和预测模型,并在集成到蒸煮器操作中时比较其长期预测能力。 在整个过程中,研讨会和讲习班是技术转让和模型改进的一部分。 这项研究的影响将是更均匀的纸浆质量,甚至与可变的原料,并在随后的漂白和造纸过程中更均匀的质量。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Mohamad Musavi其他文献
Classification of chromosomes using a probabilistic neural network.
使用概率神经网络对染色体进行分类。
- DOI:
10.1002/cyto.990160104 - 发表时间:
1994 - 期刊:
- 影响因子:0
- 作者:
W.P. Sweeney;Mohamad Musavi;John N. Guidi - 通讯作者:
John N. Guidi
Mohamad Musavi的其他文献
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{{ truncateString('Mohamad Musavi', 18)}}的其他基金
NSF INCLUDES Collaborative: Creating a Diverse STEM Pathway with Community Water Research
NSF 包括合作:通过社区水研究创建多样化的 STEM 途径
- 批准号:
1649346 - 财政年份:2017
- 资助金额:
$ 7.95万 - 项目类别:
Standard Grant
Engineering Innovative Solutions to Storm Water Problems through Diverse Community Participation
通过多元化的社区参与设计雨水问题的创新解决方案
- 批准号:
1348266 - 财政年份:2013
- 资助金额:
$ 7.95万 - 项目类别:
Standard Grant
Biodiversity and Ecosystem Informatics - BDEI - Planning Workshop on Biodiversity and Ecosystem Informatics for the Indian River Lagoon, Florida
生物多样性和生态系统信息学 - BDEI - 佛罗里达州印第安河泻湖生物多样性和生态系统信息学规划研讨会
- 批准号:
0131889 - 财政年份:2001
- 资助金额:
$ 7.95万 - 项目类别:
Standard Grant
An Intelligent System for Automated DNA Base Calling
自动化 DNA 碱基识别的智能系统
- 批准号:
9902565 - 财政年份:1999
- 资助金额:
$ 7.95万 - 项目类别:
Fellowship Award
Classification of Mouse Chromosomes Using Artificial Neural Networks
使用人工神经网络对小鼠染色体进行分类
- 批准号:
9417279 - 财政年份:1995
- 资助金额:
$ 7.95万 - 项目类别:
Continuing Grant
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