南昌红谷隧道通风及洞口污染物排放分析

通过对隧道需风量计算、通风网络模拟及现场风速测试,得到了隧道各匝道在不同车速条件下的通风量,分析了多匝道风量分配特性;采用隧道出口污染物扩散TOP模式,预测隧道出口不同风量条件下的污染物扩散情况,并实测了隧道出口污染物浓度,分析了洞口排风对敏感建筑附近环境的影响.研究表明,城市隧道通风计算中污染物CO基准排放量取值偏高...     

风火山隧道空气与围岩对流换热和围岩热传导耦合问题的三维非线性分析

根据流体力学、冻土学和传热学的基本理论,建立了寒区隧道空气与围岩对流换热和围岩热传导耦合问题的三维计算模型,用Galerkin法进行了有限元分析,进一步编制了有限元计算程序。运用该计算程序对青藏铁路风火山隧道空气与围岩对流换热和围岩热传导耦合问题进行了三维非线性分析。结果表明:运用该计算模型和有限元计算程序,在不知道寒区隧道内气温的情况下,能够正确预测围岩的冻融状态,从而节约现场观测隧道内气温的费用。     

燃气圆管道在空气中泄漏源地面逸出区域反算方法应用研究

本文为解决燃气管道泄漏定位问题,采用基于贝叶斯推理的马尔科夫链蒙特卡罗抽样方法,对天然气泄漏的信息参数进行反演,结合各区域可能发生泄漏的先验概率、高精准检测得到的位置和甲烷浓度信息,以及天然气泄漏扩散模型计算的浓度序列,综合计算检测区域范围内地面各位置的概率分布情况,反算泄漏源地面逸出区域,确定疑似地面逸出位置和强度。     

隧道洞口施工对边坡稳定性影响的预测分析

结合隧道洞口边坡的位移监测数据,采用有限元弹塑性位移反分析方法,对隧道洞口土层参数进行了反演;并采用洞口土层的反演结果,对隧道后续施工扰动对围岩变形的影响进行了预测分析,预测结果与后期现场监测数据基本吻合。隧道洞口施工对边坡的影响非常大,采用有限元反演、预测的数值计算方法,能够有效地对施工造成的变形破坏进行预测预报。     

考虑对流-弥散效应的污染物溶质运移模型及解析解

基于饱和多孔介质反应溶质运移的对流-弥散方程,同时考虑了污染物中放射性核素进入地下水系统时的衰变。根据下边界质量浓度为零,得出该模型的解析解,编译了相应的计算程序进行求解。通过算例分析,得出了在污染物扩散问题上应考虑渗透速度的合理性和重要性。有效地将原先运用情况单一的对流-弥散方程拓展到了复杂的、敏感性强的有机污染物扩散条件下,为水文地质和环境工程中与污染物扩散相关的流体流动问题的求解提供了新的解答。     

优化反演理论在隧道围岩参数反演中的应用

优化反演法是结合优化技术来进行参数反演的一种方法,这种方法使反演的效率得到了很大的提高.它是建立寻找与之相应的位移计算值与实测值相比误差最小的围岩参数,并将所得的参数作为反演计算结果的方法.作者利用APDL编制用户程序调用现有的有限元优化模块实现对隧道围岩参数的优化反演,利用现有的工具,建立参数化模型来进行优化分析,提高了参数反演的效率,使整个优化过程的实现更加灵活简便.     

城市长大隧道集中排放的环境影响分析

随着城市交通量不断地增长,为了缓解日益突出的交通问题,许多城市大量兴建隧道,而隧道废气集中排放又对隧道周边环境空气质量产生显著影响,长大隧道的排放影响更为明显.根据高斯模型和TOP模型理论,以某长大隧道为例,对城市长大隧道竖井排放和洞口扩散的环境影响做出分析.结果表明针对相同条件,CO的环境污染贡献率要比NO2的环境污染贡献率明显偏小;同时竖井高度并不能唯一决定污染物地面浓度大小,必须保证合理的排风量;此外,洞口废气扩散的环境影响要比竖井排放更为严重,并且洞口扩散作用受风向的影响也很大.     

城市隧道峒口二氧化氮扩散的环境影响分析

本文对上海某隧道CO和NO2排放量和需风量进行了计算,并采用三维数值模拟的方法对隧道峒口集中排放废气的扩散进行了分析。计算结果表明隧道内稀释NO2的风量要大于CO,且峒口排放的废气中NO2对周围环境的影响要大于CO。因此在隧道通风设计中应重视NO2的影响。环境风对峒口污染物扩散影响很大,横向风会导致隧道背风侧很大范围区域内污染物浓度超标。     

公路隧道火灾事故污染数值模拟与分析

建立了用于描述隧道内火灾事故污染物的一维扩散模型。并用此模型对公路隧道火灾事故在短时间污染物的流态进行了数值模拟和分析。通过模拟分析结果和实验统计结果的对比，表明了模型的可行性。最后，给出了污染物浓度计算公式，以供参考。     

基于优化算法的岩体初始应力场随机识别方法

根据隧道开挖后其周围地应力变化的观测数据，建立了基于优化算法的岩体初始应力场识别方法。将地应力场参数识别反问题转化为优化问题，然后采用BFGS方法求解。最优估计的岩体初始应力场是通过比较观测到的应力变化与预计值的差异而得到的，数值算例中考虑了观测误差对参数识别结果的影响。采用所建立的反演方法，地应力场的主应力的大小和方向可以被准确识别出来。数值计算结果表明，所建立的地应力场反演方法是十分有效的，并且具有良好的抗观测噪音的能力。     

Identification of contaminant sources in enclosed environments by inverse CFD modeling

In case contaminants are found in enclosed environments such as aircraft cabins or buildings, it is useful to find the contaminant sources. One method to locate contaminant sources is by inverse computational fluid dynamics (CFD) modeling. As the inverse CFD modeling is ill posed, this paper has proposed to solve a quasi-reversibility (QR) equation for contaminant transport. The equation improves the numerical stability by replacing the second-order diffusion term with a fourth-order stabilization term in the governing equation of contaminant transport. In addition, a numerical scheme for solving the QR equation in unstructured meshes has been developed. This paper demonstrates how to use the inverse CFD model with the QR equation and numerical scheme to identify gaseous contaminant sources in a two-dimensional aircraft cabin and in a three-dimensional office. The inverse CFD model could identify the contaminant source locations but not very accurate contaminant source strength because of the dispersive property of the QR equation. The results also show that this method works better for convection dominant flows than the flows that convection is not so important. PRACTICAL IMPLICATIONS: This paper presents a methodology that can be used to find contaminant source locations and strengths in enclosed environments with the data of airflow and contaminants measured by sensors. The method can be a very useful tool to find where, what, and how contamination has happened. The results can be used to develop appropriate measures to protect occupants in the enclosed environments from infectious diseases or terrorist releases of chemical/biological warfare agents as well as to decontaminate the environments.     

基于箱式模型的地下车库通风量确定方法

根据全面通风的质量平衡定律，基于室内空气污染物质量平衡方程的箱式模型，采用视车道为线源的污染物点源计算方法计算出地下车库内汽车尾气CO的排放量，由此推导出地下车库通风量的动态计算公式。结合某一具体工程进行计算和分析表明：该方法较以往各国常用的体积换气次数法和单位地面面积法更能真实反映地下车库通风量的动态变化，切合实际。说明本文提出的基于箱式模型的地下车库通风量确定方法及其结构是正确的，为在实际条件下方便而正确地得到用于通风节能控制目的的地下车库通风量确定找到了一种新的方法。本文的实验测量和理论分析方法都比较简单，可以直接推广于工程实际中。     

耦合墙体扩散的室内双扩散混合对流输运过程

研究了建筑墙体传热传质与气流流动综合作用下室内双扩散混合对流过程,介绍了整体求解流体固体区域动量守恒方程、能量守恒方程、污染物组分守恒方程及热函数和质函数方程的数值方法,分析了送风强度、热源强度、污染源强度及墙体热质扩散性能对室内混合对流过程的影响,采用流线、热线与质线反映了热和污染物在墙体和建筑室内的输运过程。     

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.     

A study on VOC source and sink behavior in porous building materials - analytical model development and assessment

Building materials can strongly affect indoor air quality. Porous building materials are not only sources of indoor air pollutants such as volatile organic compounds (VOC) but they are also strong sinks of these pollutants. The knowledge of VOC transfer mechanisms in these materials is an important step for controlling the indoor VOC concentration levels, and for determining the optimum ventilation requirements for acceptable IAQ. This study provides a theoretical investigation of primary and secondary VOC source and sink behavior of porous building materials. A new analytical model was developed based on the fundamental theories of mass transfer mechanisms in porous materials. The proposed model considers both primary and secondary source/sink behavior for the first time. The former refers to the transfer of gas-phase and/or physically adsorbed VOC, while the latter refers to the generation or elimination of VOC within the solid because of chemical reactions like oxidation, hydrolysis, chemical adsorption, etc. The proposed model was assessed with experimental data, namely emission tests of carpets and sorption tests of wood chipboard. It was demonstrated that, unlike the existing analytical models, the proposed analytical model could simultaneously account for the effect of air velocity on both VOC source as well as sink behavior. Case studies were then carried out for secondary VOC source behavior. Due to the lack of experimental studies on mechanisms of secondary behavior, hypothetical generation functions were implemented. It was demonstrated that the proposed analytical model is suitable for describing various mechanisms involved in the secondary behavior due to the little limitations imposed on the generation/elimination term. When VOC generation takes place at the material-air interface, the simulation shows that although the primary emission is not affected by air velocity, the secondary emission, however, is clearly affected. This behavior agrees with the available experimental findings on secondary emissions. PRACTICAL IMPLICATION: The analytical model presented in this paper can predict both primary and secondary VOC source (emission) or sink (sorption) behavior of porous building materials. Since the model considers diffusion and adsorption/desorption within the material, and convection over the material surface, the simulation using the model can readily provide the effects of material properties and airflow properties on the primary and/or the secondary behavior, hence, it can provide a better understanding on the mechanisms. This will enable us to keep the indoor VOC concentration within a desirable level.     

交通隧道CO动态浓度控制指标研究

合理的交通隧道通风控制浓度目标限值,不仅能够为司乘人员提供健康良好的行车环境,而且能够节约大量的电能。本文从纵向通风方式的污染物浓度分布趋势入手,分析了车辆通过隧道时人体受到污染物的暴露当量的表达式。进而研究了CO与人体的相互作用机理,应用初始条件得到了CFK方程的解析解及数值解。将3%作为人体血液中COHb浓度的最大允许值,并且综合考虑污染物浓度c和通过时间t两个指标,提出了一种基于动态浓度控制方式的污染物负载指标表达式。通过实例计算对所提出的控制指标进行验证,结果显示,本文提出的方法能够适应交通流不断变化的特点,对通风控制更具有合理性和可靠性。     

垃圾渗滤液在土体中扩散规律的模拟计算

建立了垃圾渗滤液在土体中的扩散方程，提出了渗滤液中的污染物在土体中扩散系数的实验测量方法和垃圾填埋场中污染物强度的数值计算方法。运用有限元方法对垃圾渗滤液在土体中的扩散进行了静态和动态分析，结果表明在取得足够的资料后，可以对垃圾填埋场中的渗滤液对周围土体的污染情况进行预测。     

An open-terrain line source model coupled with street-canyon effects to forecast carbon monoxide at traffic roundabout

A double-lane four-arm roundabout, where traffic movement is continuous in opposite directions and at different speeds, produces a zone responsible for recirculation of emissions within a road section creating canyon-type effect. In this zone, an effect of thermally induced turbulence together with vehicle wake dominates over wind driven turbulence causing pollutant emission to flow within, resulting into more or less equal amount of pollutants upwind and downwind particularly during low winds. Beyond this region, however, the effect of winds becomes stronger, causing downwind movement of pollutants. Pollutant dispersion caused by such phenomenon cannot be described accurately by open-terrain line source model alone. This is demonstrated by estimating one-minute average carbon monoxide concentration by coupling an open-terrain line source model with a street canyon model which captures the combine effect to describe the dispersion at non-signalized roundabout. The results of the modeling matched well with the measurements compared with the line source model alone and the prediction error reduced by about 50%. The study further demonstrated this with traffic emissions calculated by field and semi-empirical methods.     

Inverse identification of the release location,temporal rates,and sensor alarming time of an airborne pollutant source

With an accidental release of an airborne pollutant, it is always critical to know where, when, and how the pollutant has been released. Then, emergency measures can be scientifically advised to prevent any possible harm. This investigation proposes an inverse model to identify the release location, the temporal rate profile, and the sensor alarming time from the start of a pollutant release. The first step is to implement the inverse operation to the cause–effect matrix to obtain the release rate profiles for discrete candidate scenarios with concentration information provided by one sensor. The second step is to interpret the occurrence probability of each solution in the first step with the Bayesian model by matching the concentration at the other sensor. The proposed model was applied to identify a single pollutant source in a two‐dimensional enclosure using measurement data and in a three‐dimensional aircraft cabin with simulated data. The results show that the model is able to correctly determine the pollutant source location, the temporal rate profile, and the sensor alarming time. The known conditions for input into the inverse model include a steady flow field and the valid temporal concentrations at two different locations.