• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

优化生物废水处理应用的运行

Optimising operation of a biological wastewater treatment application.

作者信息

Murphy R B, Young B R, Kecman V

机构信息

Department of Mechanical Engineering, The University of Auckland, New Zealand.

出版信息

ISA Trans. 2009 Jan;48(1):93-7. doi: 10.1016/j.isatra.2008.07.006. Epub 2008 Aug 30.

DOI:10.1016/j.isatra.2008.07.006
PMID:18762295
Abstract

The objective of this work was to optimize (minimize) the compressed air required to control the rate of ammonia removal in a commercially operated wastewater bioreactor, while still maintaining operation within environmental consent limits. In order to do this, a nonlinear dynamic model based on the International Association on Water Quality (IAWQ) activated sludge model No. 3 was developed, expressing the nitrification kinetics and hydraulic dynamics of the system. From this model a steady state representation of the plant was derived, and simulated for various load characteristics experienced at the facility, and as a result an optimal load profile was developed for the compressed air distribution to the four aerobic zones. The optimal load profile will ensure that the amount of compressed air required to control the rate of ammonia removal is optimized.

摘要

这项工作的目标是优化(最小化)控制商业运行的废水生物反应器中氨去除率所需的压缩空气量,同时仍在环境许可范围内维持运行。为了实现这一目标,基于国际水质协会(IAWQ)活性污泥模型第3号开发了一个非线性动态模型,该模型表达了系统的硝化动力学和水力动力学。从该模型中得出了该工厂的稳态表示,并针对该设施所经历的各种负荷特性进行了模拟,结果为向四个好氧区分配压缩空气制定了最佳负荷曲线。最佳负荷曲线将确保控制氨去除率所需的压缩空气量得到优化。

相似文献

1
Optimising operation of a biological wastewater treatment application.优化生物废水处理应用的运行
ISA Trans. 2009 Jan;48(1):93-7. doi: 10.1016/j.isatra.2008.07.006. Epub 2008 Aug 30.
2
2,4-Dichlorophenol (DCP) containing wastewater treatment using a hybrid-loop bioreactor.使用混合环流生物反应器处理含2,4-二氯苯酚(DCP)的废水。
Bioresour Technol. 2009 Feb;100(3):1459-62. doi: 10.1016/j.biortech.2008.07.054. Epub 2008 Sep 7.
3
Simultaneous estimation of sludge biological activity and influent nitrogen load using ORP and DO dynamics.利用氧化还原电位(ORP)和溶解氧(DO)动态变化同时估算污泥生物活性和进水氮负荷
Bioprocess Biosyst Eng. 2005 Aug;27(5):329-37. doi: 10.1007/s00449-005-0411-7. Epub 2005 Jun 29.
4
Performance and model of a novel membrane bioreactor to treat the low-strengthen complex wastewater.新型膜生物反应器处理低浓度复杂废水的性能与模型。
Bioresour Technol. 2012 Jun;114:33-45. doi: 10.1016/j.biortech.2012.02.026. Epub 2012 Feb 20.
5
Bacterial community dynamics in a functionally stable pilot-scale wastewater treatment plant.功能稳定的中试规模污水处理厂中细菌群落动态。
Bioresour Technol. 2011 Feb;102(3):2352-7. doi: 10.1016/j.biortech.2010.10.095. Epub 2010 Oct 23.
6
Performance of a commercial inoculum for the aerobic biodegradation of a high fat content dairy wastewater.一种用于高脂肪含量乳制品废水好氧生物降解的商业接种物的性能
Bioresour Technol. 2007 Mar;98(5):1045-51. doi: 10.1016/j.biortech.2006.04.030. Epub 2006 Jun 21.
7
Effect of sludge-fly ash ceramic particles (SFCP) on synthetic wastewater treatment in an A/O combined biological aerated filter.污泥-粉煤灰陶瓷颗粒(SFCP)对A/O组合生物曝气滤池中合成废水处理的影响。
Bioresour Technol. 2009 Feb;100(3):1149-55. doi: 10.1016/j.biortech.2008.08.035. Epub 2008 Sep 30.
8
Modeling of submerged membrane bioreactor treating cheese whey wastewater by artificial neural network.基于人工神经网络的浸没式膜生物反应器处理奶酪乳清废水的建模
J Biotechnol. 2006 May 17;123(2):204-9. doi: 10.1016/j.jbiotec.2005.11.002. Epub 2005 Dec 6.
9
Modeling of the Contact-Adsorption-Regeneration (CAR) activated sludge process.接触-吸附-再生(CAR)活性污泥工艺的建模。
Bioresour Technol. 2011 Feb;102(3):2199-205. doi: 10.1016/j.biortech.2010.10.003. Epub 2010 Oct 8.
10
Parallel hybrid modeling methods for a full-scale cokes wastewater treatment plant.用于全尺寸焦化废水处理厂的并行混合建模方法
J Biotechnol. 2005 Feb 9;115(3):317-28. doi: 10.1016/j.jbiotec.2004.09.001.