...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Building and Environment >Prompt Tracking Of Indoor Airborne Contaminant Source Location With Probability-based Inverse Multi-zone Modeling
【24h】

Prompt Tracking Of Indoor Airborne Contaminant Source Location With Probability-based Inverse Multi-zone Modeling

机译：基于概率的逆多区域建模对室内空气污染物源位置的快速跟踪

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Indoor air quality (IAQ) has a significant influence on occupants' comfort, health, productivity, and safety. Existing studies show that the primary causes of many IAQ problems are various airborne contaminants that either are generated indoors or penetrate into indoor environments with passive or active airflows. Accurate and prompt identification of contaminant sources can help determinate appropriate IAQ control solutions, such as, eliminating contaminant sources, isolating and cleaning contaminated spaces. This study develops a fast and effective inverse modeling method for identifying indoor contaminant source characteristics. The paper describes the principles of the probability-based adjoint inverse modeling method and formulates a multi-zone model based inverse prediction algorithm that can rapidly track contaminant source location with known source release time in a building with many compartments. The paper details the inverse modeling procedure with modification of an existing multi-zone airflow and contaminant transport simulation program. The application of the method has been demonstrated with two case studies: contaminant releases in a multi-compartment residential house and in a complex institutional building. The numerical experiments tested the source identification capability of the program for various contaminant sensing scenarios. The investigation verifies the effectiveness and accuracy of the developed method for indoor contaminant source tracking, which will be further explored to identify more complicated indoor contamination episodes.
机译：室内空气质量（IAQ）对乘员的舒适度，健康，生产力和安全性有重要影响。现有研究表明，许多室内空气质量问题的主要原因是各种空气传播的污染物，这些污染物要么在室内产生，要么通过被动或主动气流渗入室内环境。准确迅速地识别出污染源可以帮助确定适当的IAQ控制解决方案，例如消除污染源，隔离和清洁受污染的空间。这项研究开发了一种快速有效的逆建模方法，用于识别室内污染物源的特征。本文介绍了基于概率的伴随逆建模方法的原理，并制定了一种基于多区域模型的逆预测算法，该算法可以在具有多个隔室的建筑物中以已知的源释放时间快速跟踪污染物源的位置。本文详细介绍了逆建模过程，并修改了现有的多区域气流和污染物迁移模拟程序。已通过两个案例研究证明了该方法的应用：污染物在多隔室住宅和复杂机构建筑物中的释放。数值实验测试了该程序在各种污染物感测情况下的源识别能力。该调查验证了开发的室内污染物源跟踪方法的有效性和准确性，将进一步探索该方法以识别更复杂的室内污染物事件。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号