Identification of contaminant sources in enclosed spaces by a single sensor

To protect occupants from infectious diseases or possible chemical/biological agents released by a terrorist in an enclosed space, such as an airliner cabin, it is critical to identify gaseous contaminant source locations and strengths. This paper identified the source locations and strengths by solving inverse contaminant transport with the quasi-reversibility (QR) and pseudo-reversibility (PR) methods. The QR method replaces the second-order diffusion term in the contaminant transport equation with a fourth-order stabilization term. By using the airflow pattern calculated by computational fluid dynamics (CFD) and the time when the peak contaminant concentration was measured by a sensor in downstream, the QR method solves the backward probability density function (PDF) of contaminant source location. The PR method reverses the airflow calculated by CFD and solves the PDF in the same manner as the QR method. The position with the highest PDF is the location of the contaminant source. The source strength can be further determined by scaling the nominal contaminant concentration computed by CFD with the concentration measured by the sensor. By using a two-dimensional and a three-dimensional aircraft cabin as examples of enclosed spaces, the two methods can identify contaminant source locations and strengths in the cabins if the sensors are placed in the downstream location of the sources. The QR method performed slightly better than the PR method but with a longer computing time. PRACTICAL IMPLICATIONS: The paper presents a method that can be used to find a gaseous contaminant source location and determine its strength in enclosed spaces with the data of contaminant concentration measured by one sensor. The method can be a very useful tool to find where, what, and how the contamination has happened. The method is also useful for optimally placing sensors in enclosed spaces. The results can be applied to develop appropriate measures to protect occupants in enclosed environments from infectious diseases or chemical/biological warfare agents released by a terrorist.     

Location identification for indoor instantaneous point contaminant source by probability-based inverse Computational Fluid Dynamics modeling

Indoor pollutions jeopardize human health and welfare and may even cause serious morbidity and mortality under extreme conditions. To effectively control and improve indoor environment quality requires immediate interpretation of pollutant sensor readings and accurate identification of indoor pollution history and source characteristics (e.g. source location and release time). This procedure is complicated by non-uniform and dynamic contaminant indoor dispersion behaviors as well as diverse sensor network distributions. This paper introduces a probability concept based inverse modeling method that is able to identify the source location for an instantaneous point source placed in an enclosed environment with known source release time. The study presents the mathematical models that address three different sensing scenarios: sensors without concentration readings, sensors with spatial concentration readings, and sensors with temporal concentration readings. The paper demonstrates the inverse modeling method and algorithm with two case studies: air pollution in an office space and in an aircraft cabin. The predictions were successfully verified against the forward simulation settings, indicating good capability of the method in finding indoor pollutant sources. The research lays a solid ground for further study of the method for more complicated indoor contamination problems. PRACTICAL IMPLICATIONS: The method developed can help track indoor contaminant source location with limited sensor outputs. This will ensure an effective and prompt execution of building control strategies and thus achieve a healthy and safe indoor environment. The method can also assist the design of optimal sensor networks.     

Prompt tracking of indoor airborne contaminant source location with probability-based inverse multi-zone modeling

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.     

Principles and applications of probability-based inverse modeling method for finding indoor airborne contaminant sources

Building indoor air quality (IAQ) has received growing attentions lately because of the extended time people spend indoors and the increasing reports of health problems related to poor indoor environments. Recent alarms to potential terrorist attacks with airborne chemical and biological agents (CBA) have further highlighted the research needs on building vulnerability and protection. To maintain a healthful and safe indoor environment, it is crucial to identify contaminant source locations, strengths, and release histories. Accurate and prompt identification of contaminant sources can ensure that the contaminant sources can be quickly removed and contaminated spaces can be effectively isolated and cleaned. This paper introduces a probability concept based prediction method—the adjoint probability method-that can track potential indoor airborne contaminant sources with limited sensor outputs. The paper describes the principles of the method and presents the general modeling algorithm and procedure that can be implemented with current computational fluid dynamics (CFD) or multi-zone airflow models. The study demonstrates the application of the method for identifying airborne pollutant source locations in two realistic indoor environments with few sensor measurement outputs. The numerical simulations verify the feasibility and accuracy of the method for indoor pollutant tracking applications, which forms a good foundation for developing an intelligent and integrated indoor environment management system that can promptly respond to indoor pollution episodes with effective detection, analysis, and control.     

CFD boundary conditions for contaminant dispersion,heat transfer and airflow simulations around human occupants in indoor environments

Indoor computational fluid dynamics (CFD) simulations can predict contaminant dispersion around human occupants and provide valuable information in resolving indoor air quality or homeland security problems. The accuracy of CFD simulations strongly depends on the appropriate setting of boundary conditions and numerical simulation parameters. The present study explores influence of the following three key boundary condition settings on the simulation accuracy: (1) contaminant source area size, (2) convective/radiative heat fluxes, and (3) shape/size of human simulators. For each of the boundary conditions, numerical simulations were validated with experimental data obtained in two different environmental chambers. In CFD simulations, a small release area of a contaminant point source causes locally high concentration gradients that require a very fine local grid system. This fine grid system can slow down the simulations substantially. The convergence speed of calculation is greatly increased by the source area enlargement. This method will not influence the simulation accuracy of passive point source within well-predicted airflow field. However, for active point source located within complicated airflow filed, such an enlargement should be carried out cautiously because simulation inaccuracy might be introduced. For setting thermal boundary conditions, convection to radiation heat flux ratio is critical for accurate CFD computations of temperature profiles around human simulators. The recommended convection to radiation (C:R) ratio is 30:70 for human simulators. Finally, simplified human simulators can provide accurate temperature profiles within the whole domain of interest. However, velocity and contaminant concentration simulations require further work in establishing the influence of simplifications on the simulation accuracy in the vicinity of the human simulator.     

Development of a system for predicting snow distribution in built-up environments: Combining a mesoscale meteorological model and a CFD model

A system has been developed for predicting snow distribution in built-up environments. This system combines a mesoscale meteorological model that predicts precipitation, including snowfall in an area, and a Computational Fluid Dynamics (CFD) model that predicts snow phenomena on building scale. The system focuses on snow distribution around buildings, which often leads to snow disaster and snow-related difficulties in urban areas. It can be used for predicting snow distribution due to snowfall and snowdrift in a development area and is expected to be a useful design tool for city and architectural planning in snowy regions. This paper outlines the system and examines its performance by comparing its results with measured data. The snowdrift patterns, i.e. erosion around the upwind corners and deposition in front of and behind a building, obtained by the present model show good correspondence with those obtained from field observation. However, the model under-predicted the decrease of snow depth near the building. Further investigations required to comprehensively evaluate the prediction accuracy of the system are discussed.     

A CFD study of convection in a double glazed window with an enclosed pleated blind

A numerical study has been conducted of steady free convection in a double glazed window with a between-panes pleated cloth blind. The model geometry is based on a commercial product that is available on the consumer market in North America. The study considers the effects of Rayleigh number, enclosure aspect ratio, and blind geometry on the convective heat transfer. A simplified model of the coupled convective and radiative heat transfer is also presented. Sample results show that the average Nusselt number data from the CFD study can be combined with a one-dimensional model to closely predict the glazing-to-glazing U-value.     

CFD simulation of VOCs concentrations in a resident building with new carpet under different ventilation strategies

This paper investigates the effect of ventilation strategies on the concentrations of volatile organic compounds (VOCs) emitted from a new carpet in an apartment with the VOCs emission characteristics taken from chamber test data. The commercial software FLUENT 6 has been employed to solve the continuity, momentum, turbulence and concentration equations under five different ventilation strategies. Numerical results show that ventilation strategies have a small effect on VOCs emission from carpet. Continuous ventilation keeps a low level of VOCs concentration in the air. Flushing ventilation has a significant effect on the VOCs concentration in the air. During a period without ventilation, VOCs concentration in the air usually increases to a high level. Thus, the ventilation should be carried out before the arrival of residents to ensure a low level of VOCs concentration. At the startup of ventilation run, the sudden flow strongly promotes the mixing of VOCs, which may lead to local high concentration.     

Comparison of sensor systems designed using multizone,zonal, and CFD data for protection of indoor environments

Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is mostly by intuition and experience rather than by systematic design. To develop a sensor system design methodology, the proper selection of an indoor airflow model is needed. Various indoor airflow models exist in the literature, from complex computational fluid dynamics (CFD) to simpler approaches such as multizone and zonal models. Airflow models provide the contaminant concentration data, to which an optimization method can be applied to design sensor systems. The authors utilized a subzonal modeling approach when using a multizone model and were the first to utilize a zonal model for systematic sensor system design. The objective of the study was to examine whether or not data from a simpler airflow model could be used to design sensor systems capable of performing just as well as those designed using data from more complex CFD models. Three test environments, a small office, a large hall, and an office suite were examined. Results showed that when a unique sensor system design was not needed, sensor systems designed using data from simpler airflow models could perform just as well as those designed using CFD data. Further, only for the small office did the common engineering sensor system design practice of placing a sensor at the exhaust result in sensor system performance that was equivalent to one designed using CFD data.     

非饱和土中水分迁移及污染物扩散的离心模拟

近十年来 ,土工离心机被作为模拟污染物扩散的一个重要手段。但是 ,目前能否采用离心机进行非饱和土中的水分迁移研究尚有争议 ;另外在无机可溶性污染物方面的研究也仅限于对惰性的、土壤吸附能力很低的无机物 (如钠离子 )在土体中的扩散机理研究。本文选用能够与土颗粒发生较强作用的重金属镉 ,利用土工离心机进行了非饱和土中一维模型的模拟研究 ,分析了非饱和土中含水率的变化和污染物的迁移机理 ,检验采用离心模拟方法研究污染物扩散机理的可行性 ,验证与污染物扩散机理相关的模型相似律。     

Analysis of mass transfer characteristics in a tubular membrane using CFD modeling

In contrast to the large amount of research into aerobic membrane bioreactors, little work has been reported on anaerobic membrane bioreactors (AMBRs). As to the application of membrane bioreactors, membrane fouling is a key issue. Membrane fouling generally occurs more seriously in AMBRs than in aerobic membrane bioreactors. However, membrane fouling could be managed through the application of suitable shear stress that can be introduced by the application of a two-phase flow. When the two-phase flow is applied in AMBRs, little is known about the mass transfer characteristics, which is of particular importance, in tubular membranes of AMBRs. In our present work, we have employed fluid dynamic modeling to analyze the mass transfer characteristics in the tubular membrane of a side stream AMBR in which, gas-lift two-phase flow was applied. The modeling indicated that the mass transfer capacity at the membrane surface at the noses of gas bubbles was higher than the mass transfer capacity at the tails of the bubbles, which is in contrast to the results when water instead of sludge is applied. At the given mass transfer rate, the filterability of the sludge was found to have a strong influence on the transmembrane pressure at a steady flux. In addition, the model also showed that the shear stress in the internal space of the tubular membrane was mainly around 20 Pa but could be as high as about 40 Pa due to gas bubble movements. Nonetheless, at these shear stresses a stable particle size distribution was found for sludge particles.     

Verification of the accuracy of CFD simulations in small-scale tunnel and atrium fire configurations

In preparation for the use of computational fluid dynamics (CFD) simulation results as ‘numerical experiments’ in fire research, the agreement with experimental data for two different small-scale set-ups is discussed. The first configuration concerns the position of smoke-free height in case of fire with vertical ventilation in an atrium. The second set-up deals with the critical velocity for smoke backlayering in case of fire in a horizontally ventilated tunnel. An N-percent rule is introduced for the determination of the presence of smoke in the simulation results, based on the local temperature rise. The CFD package FDS is used for the numerical simulations. The paper does not scrutinize the detailed accuracy of the results, as this is hardly possible with any state-of-the-art experimental data at hand. Rather, the global accuracy is discussed with current numerical implementation and models in FDS, considering continuous evolution over different version releases with time. The agreement between the experiments and numerical simulations is very promising. Even when quantitative agreement with experimental data is not perfect, the trends are very well reproduced in the simulations. While much additional work is required, both in CFD as in ‘real’ experiments, the results are encouraging for the potential of state-of-the-art CFD to be used as numerical experiments.     

CFD技术在大空间烟气运动模拟中的应用

介绍了CFD技术在消防性能化设计中的应用，以及两个得到广泛应用的CFD软件FLUENT与FDS。给出了一个体育场馆的应用案例，比较了FLUENT软件与FDS软件的优缺点及适用性，体现了CFD技术的应用为工程所带来的效果。     

温州某工业建筑室外风环境的CFD模拟分析

建筑室内风环境受室外风环境影响很大,尤其是自然通风、建筑防风效果受室外风环境决定性影响。通过采用Fluent对温州某工业建筑的室外风环境进行了模拟计算,对比分析了2个规划方案在冬夏2种工况下的速度场与压力场。在模拟结果分析基础上,提出了建议规划方案。     

CFD assessment of intake fraction in the indoor environment

In this paper we use a validated CFD model to calculate the inhalation exposure, expressed as an intake fraction (iF), of a seated person in an office with different contaminant sources, a floor diffuser, and a ceiling vent. These sources include the floor, the walls, a desk, and the human body. First, experimental data is used to determine the correct turbulent Schmidt number for the computational model to predict the transport of the species in an indoor environment. It was found at a turbulent Schmidt number of ∼0.9 produced the best fit when compared to experimental data. Then, the iF was calculated for two representations of the computer simulated person (CSP): a CSP with detailed surface geometry, and a simplified CSP with multi-block geometry. It was found that the simplified multi-block geometry is not adequate for predicting iF because it radically changes the flowfield of the thermal plume in the breathing zone (BZ). Next, the effect of personal ventilation systems on iF was investigated. The results show that such systems can reduce the iF by an order of magnitude compared with conventional mixing and displacement ventilation systems. Finally, a comparison of iF results were made for a surface body temperature of 32 °C and 28 °C. It was found that a 4 °C change in body surface temperature influenced the iF by less than 10%.     

Enhanced vulnerability assessment in karst areas by combining mapping with modeling approaches

The objective of this work is to facilitate a sustainable regional planning of water resources in karst areas by providing a conceptual framework for an integrative vulnerability assessment. A combined mapping and modeling approach is proposed, taking into account both spatial and temporal aspects of karst groundwater vulnerability. The conceptual framework comprises the delineation of recharge areas, vulnerability mapping, numerical flow and transport modeling and the integration of information into a combined vulnerability map and time series. The approach is illustrated at a field site in northwest Switzerland (Gempen plateau). The results show that the combination of vulnerability mapping and numerical modeling allows the vulnerability distribution, both in the recharge and discharge areas, to be identified, and at the same time, the time dependence of karst groundwater vulnerability to be assessed. The combined vulnerability map and time series provide a quantitative basis for drinking water management and for regional planning.     

沿海城市住宅小区风环境研究

随着城市的飞速发展,住宅小区风环境问题日益突出。沿海地区受海陆风影响明显,全年风速一般较大,其住宅小区的风环境研究需特别考虑。本文通过IECM CFD10.0建立数值风洞,采用SSTK-ω湍流物理模型求解住宅小区内风速的方法来研究某沿海城市住宅小区的群体建筑风环境。研究表明,数值方法能准确模拟小区风流场,建筑布局和来流方向对小区风环境影响明显,可结合城市风玫瑰图合理规划建筑布局。采用数值方法,可以对己建小区提出措施改进不良风环境,还可以指导、优化未建小区的规划与设计,以营造健康舒适的居住区微气候环境。     

基于CFD技术的室外风热环境分析在某大型商业建筑中的应用

商业建筑的室外风、热环境不仅影响室外广场等人行区域的舒适与安全,更是室内空间进行物理环境设计时的外部条件。该文采用CFD数值模拟方法,对重庆市某大型商业综合体的室外风热环境进行了详细的分析与评价,并提出优化设计建议。该文的研究将为改善该项目的建筑风热环境品质提出有效的技术措施,并为类似工程问题提供参考。     

广东地区某建筑夏季室内热环境的CFD仿真评价

在暖通空调领域,计算流体动力学CFD（Computational Fluid Dynamics）方法常被用来求解气流及温度分布。本文利用CFD仿真软件对广东地区某一使用风机盘管的夏季空调建筑室内温度场、速度场进行模拟仿真,得出了夏季空调情况下该建筑的室内温度场和气流组织分布,结果分析表明,其室内平均温度及送风温差满足《公共建筑节能设计标准》广东省实施细则DBJ15—51—2007中的相关要求。     

CFD modeling of pollution dispersion in a street canyon: Comparison between LES and RANS

CFD modeling using RANS and LES of pollutant dispersion in a three-dimensional street canyon is investigated by comparison with measurements. The purpose of this study is to confirm the accuracy of LES in modeling plume dispersion in a simple street canyon model and to clarify the mechanism of the discrepancy in relation to RANS computation. Simple LES modeling is shown by comparison with wind tunnel experiments to give better results than conventional RANS computation (RNG) modeling of the distribution of mean concentration. The horizontal diffusion of concentration is well reproduced by LES, mainly due to the reproduction of unsteady concentration fluctuations in the street canyon.