Detailing the effects of geometry approximation and grid simplification on the capability of a CFD model to address the benchmark test case for flow around a computer simulated person

This paper details the use of a simplified CFD model to predict the flow patterns around a computer simulated person in a displacement ventilated room. The use of CFD is a valuable tool for indoor airflow analysis and the level of complexity of the model being investigated is often critical to the accuracy of predictions. The closer the computational geometry is to the real geometry of interest, the more accurate the corresponding results are expected to be. High complexity meshes enable elaborated geometries to be resolved. The drawback is, however, their increased computational cost. The Fire Dynamics Simulator (FDS) model (Version 5) enabled to investigate the effects of geometry and computational grid simplification on the accuracy of numerical predictions. The FDS model is based on a three-dimensional Cartesian coordinate system and all solid obstructions are forced to conform to the underlying numerical grid which is a potential limitation when dealing with complex geometries such as those of a human body. Nevertheless, the developed computational model was based exclusively on a three-dimensional rectangular geometry. At the same time, in order to limit the total number of grid cells, a relatively coarser grid than those used for similar simulations was adopted in the investigation. The developed model was then assessed in terms of its capability of reproducing benchmark temperature and air velocity distributions. The extent to which numerical results depend on different simulation settings was detailed and different boundary conditions are discussed in order to provide some guidance on the parameters that resulted to affect the accuracy of the predicted results. The comparison between numerical results and measurements showed that a simplified CFD model can be used to capture the airflow characteristics of the investigated scenario with predictions showing a favourable agreement with experimental data at least in the qualitative features of the flow (the detailed investigation of the local airflow field near the occupant can not be probably conducted apart from considering the real human geometry). Significant influence of simulator geometry and of boundary conditions was found.     

CFD modelling of an industrial air diffuser—predicting velocity and temperature in the near zone

This article describes experimental and modelling results from CFD simulation of an air diffuser for industrial spaces. The main objective of this paper is to validate a manufacturer model of the diffuser. In the air diffuser, the low velocity part is placed on top of a multi-cone diffuser in order to increase airflow rates and maximize the cooling capacity of a single diffuser unit. This kind of configuration should ensure appropriate performance of industrial air diffusers, which is discussed briefly at the end of the article. The paper illustrates the importance of a simulation model jointly with the manufacturer's product model and the grid layout near the ventilation device to achieve accurate results. Parameters for diffuser modelling were adapted from literature and manufacturer's product data. Correct specification of diffuser geometry and numerical boundary conditions for CFD simulations are critical for prediction. The standard k–ε model was chosen to model turbulence because it represents the best-known model utilized and validated for air diffuser performance. CFD simulations were compared systematically with data from laboratory measurements; air velocity was measured by ultrasonic sensors. Results show that CFD simulation with a standard k–ε model accurately predicts non-isothermal airflow around the diffuser. Additionally, smoke tests revealed that the flow around the diffuser is not completely symmetrical as predicted by CFD. The cause of the observed asymmetry was not identified. This was the main reason why some simulation results deviate from the measured values.     

Numerical investigation on thermal performance and correlations of double skin façade with buoyancy-driven airflow

This paper briefly reviews the primary parameters for a double skin façade (DSF) design. The research presents an integrated and iterative modeling process for analyzing the thermal performance of DSF cavities with buoyancy-driven airflow by using a building energy simulation program (BESP) along with a computational fluid dynamics (CFD) package. A typical DSF cavity model has been established and simulated. The model and the modeling process have been calibrated and validated against the experimental data. The validated model was used to develop correlations that can be implemented in a BESP, allowing users to take advantage of the accuracy gained from CFD simulations without the required computation time. Correlations were developed for airflow rate through cavity, average and peak cavity air temperature, cavity air pressure, and interior convection coefficient. The correlations are valuable for “back of the envelope” calculation and for examining accuracy of zonal-model-based energy and airflow simulation programs.     

Predicting airflow distribution and contaminant transport in aircraft cabins with a simplified gasper model

This study investigated the air distribution and contaminant transport in aircraft cabins with gaspers by using computational fluid dynamics (CFD). If the detailed gasper geometry were used in the CFD simulations, the grid number would be unacceptably high. To reduce the grid number, this investigation proposed a method for simplifying the gasper geometry. The method was then validated by two sets of experimental data obtained from a cabin mockup and a real aircraft cabin. It was found that for the cabin mockup, the CFD simulation with the simplified gasper model reduced the grid number from 1.58 to 0.3 million and the computing cost from 2 days to 1 hour without compromising the accuracy. In the five-row economy-class cabin of the MD-82 airplane, the CFD simulation with the simplified gasper model was acceptable in predicting the distribution of air velocity, air temperature, and contaminant concentration.     

On CFD simulation of wind-induced airflow in narrow ventilated facade cavities: Coupled and decoupled simulations and modelling limitations

Heat and mass transfer modelling in building facades with ventilated cavities requires information on the cavity air change rates, which can be a complex function of the building and cavity geometry and the meteorological conditions. This paper applies Reynolds-averaged Navier–Stokes (RANS) CFD to study wind-induced airflow in the narrow (23 mm) ventilated facade cavities of an isolated low-rise building. Both coupled and decoupled simulations are performed. In the coupled simulations, the atmospheric boundary layer wind-flow pattern around the building and the resulting airflow in the cavities are calculated simultaneously and within the same computational domain. In the decoupled simulations, two separate CFD simulations are conducted: a simulation of the outdoor wind flow around the building (with closed cavities) to determine the surface pressures at the position of the cavity inlet and outlet openings, and a simulation of the cavity airflow, driven by these surface pressures. CFD validation is performed for the external and internal (cavity) flows. It indicates an important modelling limitation: while both laminar and turbulent cavity airflow can be accurately reproduced with low-Reynolds number modelling, this method fails in the transitional regime. The valid CFD results (outside the transitional regime) are analysed in terms of cavity airflow patterns and cavity air change rates per hour (ACH) for different cavity positions, wind speeds and wind directions. The CFD results of cavity air speed and ACH compare favourably with values from previous experimental studies. The coupled and decoupled simulation results are compared to provide an indication of the local losses. It is concluded that future work should focus on adapting RANS CFD low-Reynolds number models to accurately model cavity flow in the transitional regime.     

Low-Reynolds number mixing ventilation flows: Impact of physical and numerical diffusion on flow and dispersion

Quality assurance in computational fluid dynamics (CFD) is essential for an accurate and reliable assessment of complex indoor airflow. Two important aspects are the limitation of numerical diffusion and the appropriate choice of inlet conditions to ensure the correct amount of physical diffusion. This paper presents an assessment of the impact of both numerical and physical diffusion on the predicted flow patterns and contaminant distribution in steady Reynolds-averaged Navier–Stokes (RANS) CFD simulations of mixing ventilation at a low slot Reynolds number (Re≈2,500). The simulations are performed on five different grids and with three different spatial discretization schemes; i.e. first-order upwind (FOU), second-order upwind (SOU) and QUICK. The impact of physical diffusion is assessed by varying the inlet turbulence intensity (TI) that is often less known in practice. The analysis shows that: (1) excessive numerical and physical diffusion leads to erroneous results in terms of delayed detachment of the wall jet and locally decreased velocity gradients; (2) excessive numerical diffusion by FOU schemes leads to deviations (up to 100%) in mean velocity and concentration, even on very high-resolution grids; (3) difference between SOU and FOU on the coarsest grid is larger than difference between SOU on coarsest grid and SOU on 22 times finer grid; (4) imposing TI values from 1% to 100% at the inlet results in very different flow patterns (enhanced or delayed detachment of wall jet) and different contaminant concentrations (deviations up to 40%); (5) impact of physical diffusion on contaminant transport can markedly differ from that of numerical diffusion.     

Sensitivity of the predicted convective heat transfer in a cooled room to the computational fluid dynamics simulation approach

Computational fluid dynamics (CFD) plays an increasingly important role in the design, analysis and optimization of engineering systems. However, CFD does not necessarily provide reliable results. The most crucial numerical solution error is caused by inadequate grid resolution, and the key modelling error sources in CFD in ventilated indoor environments are turbulence modelling and diffuser modelling. Many researchers already proposed guidelines, but they based their analyses on local variables. In response, underlying study intended to verify the impact of the CFD simulation approach on the convective heat flux, an integral quantity. The authors tested several grids, Reynolds averaged Navier–Stokes turbulence models and diffuser models for three convection regimes in a cooled room. The diffuser modelling had a much larger impact than the grid and the turbulence modelling, as long as the jet dominated the airflow. So, CFD users, who want to model forced/mixed convection airflow indoors, certainly need to pay attention to the diffuser modelling.     

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.     

The effect of source motion on contaminant distribution in the cleanrooms

In the recent decades, cleanrooms have found growing applications in broad range of industries such as pharmacy and microelectronics. Concerns about negative effects of the contaminant exposure on the human health and product quality motivate many researchers towards understanding of the airflow and contaminant distribution though these environments. With an improvement in computational capacity of the computers, computational fluid dynamics (CFD) technique has become a powerful tool to study the engineering problems including indoor air quality (IAQ). In this research, indoor airflow in a full-scale cleanroom is investigated numerically using Eulerian-Eulerian approach. To evaluate the ventilation system effectiveness, a new index, called final efficiency, is introduced which takes all aspects of the problem into account. The results show that the contaminant source motion and its path have a great influence on the contaminant dispersion through the room. Based on the results, the contaminant distribution indexes, e.g. final efficiency and spreading radius, are improved when the source motion path is in the dominant direction of the ventilation airflow. Consequently, the efficiency of an air distribution system which provides a directional airflow pattern shows the least source path dependency. This study and its results may be useful to gain better understanding of the source motion effects on the indoor air quality (IAQ) and to design more effective ventilation systems.     

The effect of ceiling configurations on indoor air motion and ventilation flow rates

The purpose of this paper is to evaluate the effects of a building parameter, namely ceiling configuration, on indoor natural ventilation. The computational fluid dynamics (CFD) code Phoenics was used with the RNG k–? turbulence model to study wind motion and ventilation flow rates inside the building. All the CFD boundary conditions were described. The simulation results were first validated by wind tunnel experiment results in detail, and then used to compare rooms with various ceiling configurations in different cases. The simulation results generated matched the experimental results confirming the accuracy of the RNG k–? turbulence model to successfully predict indoor wind motion for this study. Our main results reveal that ceiling configurations have certain effects on indoor airflow and ventilation flow rates although these effects are fairly minor.     

Coupled simulations for naturally ventilated rooms between building simulation (BS) and computational fluid dynamics (CFD) for better prediction of indoor thermal environment

The coupling strategies for natural ventilation between building simulation (BS) and computational fluid dynamics (CFD) are discussed and coupling methodology for natural ventilation is highlighted. Two single-zone cases have been used to validate coupled simulations with full CFD simulations. The main discrepancy factors have also been analyzed. The comparison results suggest that for coupled simulations taking pressure from BS as inlet boundary conditions can provide more accurate results for indoor CFD simulation than taking velocity from BS as boundary conditions. The validation results indicate that coupled simulations can improve indoor thermal environment prediction for natural ventilation taking wind as the major force. With the aids of developed coupling program, coupled simulations between BS and CFD can effectively improve the speed and accuracy in predicting indoor thermal environment for natural ventilation studies.     

Development of new and validation of existing convection correlations for rooms with displacement ventilation systems

Building airflow, thermal, and contaminant simulation programs need accurate models for the surface convective boundary conditions. This is, especially, the case for displacement ventilation (DV) systems, where convective buoyancy forces at room surfaces significantly affect the airflow pattern and temperature and contaminant distributions. Nevertheless, for DV, as a relatively new ventilation system, the convective correlations are adopted from more traditional mixing ventilation correlations, or non-existent. In this study, the existing recommended correlations are validated in a full-scale experimental facility representing an office space. In addition, new correlations are developed for floor surfaces because the current literature does not provide necessary correlations, even though, the floor surface is responsible for >50% of the total convective heat transfer at the envelope. The convective correlations are typically functions of a surface-air temperature difference, airflow parameters, and characteristic room dimensions. Validation results show that the floor convection correlations expressed as a function of volume flow rate are much stronger than the correlations expressed as a function of a temperature difference between the surface and local air. Consequently, the new convection correlation for floor surfaces is a function of the number of hourly room air changes (ACH). This correlation also takes into account buoyant effects from local floor heat patches. Experimental data show that the existing correlation can be successfully applied to vertical and ceiling surfaces in spaces with DV diffuser(s). Overall, the new and the existing convection correlations are tabulated for use in building simulation programs, such as annual energy analyses or computational fluid dynamics.     

Source term models for fine particle resuspension from indoor surfaces

Understanding the dispersion of contaminants inside buildings is important for improving indoor air quality (IAQ). Detailed information on the dispersion profile within a room is required to design active protection systems and to develop countermeasure strategies against potential threats from particulate based agents. A number of computational fluid dynamics (CFD) codes in the public and commercial domain can simulate contaminant dispersion inside a building. One of the critical boundary conditions required by these CFD codes is a resuspension source term model. This paper develops general source term models for particle resuspension from indoor surfaces based on dimensional analysis. First, the physical mechanisms responsible for fine particle resuspension from indoor surfaces are investigated and relevant parameters are identified. Then, three different models are developed using dimensional analysis and published resuspension data in the literature. Finally, the models are evaluated against independent experimental data that were not used to determine the model coefficients.     

On the effect of turbulent intensity towards the accuracy of the zero-equation turbulence model for indoor airflow application

The zero-equation turbulence model for indoor airflow applications proposed by Chen and Xu [4] has obtained immense popularity amongst the CFD practitioners in HVAC industry. A uniform turbulent intensity of 10% has been assumed in their model. In this paper, following the analogy of Chen and Xu [4] in deriving the coefficient of their zero-equation turbulence model (0.03874) which is indeed expressed as a function of turbulent intensity, the effect of turbulent intensity value assumed in the model towards the solution accuracy is investigated in this paper. Three indoor airflow cases, i.e. forced convection, natural convection and mixed convection problems are studied. It has been discovered that as the assumed uniform turbulent intensity T_i is reduced, the solution accuracy is significantly improved and the prediction comes closer to those of the two-equation standard k-? model, LES model as well as the experimental data.     

Influence of movements on contaminant transport in an operating room

The influence of persons' movements on contaminant transport during an orthopedic surgical operation is examined. Orthopedic surgical operations require an ultra clean environment usually provided by a LAF device (laminar airflow). During hip replacements bone cement is sometimes applied. Due to practical reasons cement mixing is performed outside the LAF area. During the cement transport from the mixing location to the surgeon there is a potential risk of bacterial transport to the clean zone. This phenomenon is examined by smoke visualization and computational fluid dynamics (CFD). The movements are modeled by CFD using distributed momentum sources as well as a turbulent kinetic energy source. A significant risk of contaminant transport from the less clean zone to the ultra clean zone is found. The results indicate that it is possible to simulate the influence of movements using a relatively simple CFD model that considers the significant influence of a transient phenomenon in an approximate way. PRACTICAL IMPLICATIONS: In real-life ventilated enclosures like operating rooms movements take place. Persons' movements may influence the local flow field as well as the contaminant field substantially. Most often movements are ignored in simulations due to the complexity of the phenomenon. This paper presents an indirect and simple method to consider the influence of movements that may enable modelers to include this important phenomenon in the engineering application of CFD. This may improve practical risk assessment--for instance risk assessment of unintended transport of bacteria during orthopedic surgical operations that may jeopardize the hygiene.     

Contaminant dispersion with personal displacement ventilation,Part I: Base case study

Personal displacement ventilation (PDV) is a new ventilation concept that combines the positive features of displacement ventilation with those of task conditioning or personalized ventilation. PDV is expected to create a micro-environment around an occupant to control the environment individually. In this study, a base PDV case with a contaminant source at different locations was modeled for contaminant dispersion in a full-scale chamber. Computational fluid dynamics (CFD) was used to simulate the indoor airflow and pollutant transport, and the simulation results were validated against the experimental data. The contaminant concentration field for three different contaminant source locations was analyzed. Based on our results, it seems that this kind of PDV system cannot create the expected “micro-environment” to avoid the disturbance of the outside airflow. Further studies on how to improve the PDV performance are given in the companion paper.     

Fast and informative flow simulations in a building by using fast fluid dynamics model on graphics processing unit

Fast indoor airflow simulations are necessary for building emergency management, preliminary design of sustainable buildings, and real-time indoor environment control. The simulation should also be informative since the airflow motion, temperature distribution, and contaminant concentration are important. Unfortunately, none of the current indoor airflow simulation techniques can satisfy both requirements at the same time. Our previous study proposed a Fast Fluid Dynamics (FFD) model for indoor flow simulation. The FFD is an intermediate method between the Computational Fluid Dynamics (CFD) and multizone/zonal models. It can efficiently solve Navier–Stokes equations and other transportation equations for energy and species at a speed of 50 times faster than the CFD. However, this speed is still not fast enough to do real-time simulation for a whole building. This paper reports our efforts on further accelerating FFD simulation by running it in parallel on a Graphics Processing Unit (GPU). This study validated the FFD on the GPU by simulating the flow in a lid-driven cavity, channel flow, forced convective flow, and natural convective flow. The results show that the FFD on the GPU can produce reasonable results for those indoor flows. In addition, the FFD on the GPU is 10–30 times faster than that on a Central Processing Unit (CPU). As a whole, the FFD on a GPU can be 500–1500 times faster than the CFD on a CPU. By applying the FFD to the GPU, it is possible to do real-time informative airflow simulation for a small building.     

Indoor mould growth prediction using coupled computational fluid dynamics and mould growth model

This study investigates, using in-situ and numerical simulation experiments, airflow and hygrothermal distribution in a mechanically ventilated academic research facility with known cases of microbial proliferations. Microclimate parameters were obtained from in-situ experiments and used as boundary conditions and validation of the numerical experiments with a commercial computational fluid dynamics (CFD) analysis tool using the standard k–ε model. Good agreements were obtained with less than 10% deviations between the measured and simulated results. Subsequent upon successful validation, the model was used to investigate hygrothermal and airflow profile within the shelves holding stored components in the facility. The predicted in-shelf hygrothermal profile was superimposed on mould growth limiting curve earlier documented in the literature. Results revealed the growth of xerophilic species in most parts of the shelves. The mould growth prediction was found in correlation with the microbial investigation in the case-studied room reported by the authors elsewhere. Satisfactory prediction of mould growth in the room successfully proved that the CFD simulation can be used to investigate the conditions that lead to microbial growth in the indoor environment.     

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.     

采用"二区+CFD"模型研究点源自然通风及其羽流

讨论了几个典型的羽流流量计算公式,结合一种二区自然通风模型,建立了热分层高度、通风量和中和界高度的计算式。基于单步静态耦合(或预定边界条件)的思想,采用“二区 CFD”模型的方法研究了自然通风及其羽流。二区模型提供CFD模拟边界条件,CFD模拟反向检验二区模型,同时检验各羽流公式的适用性。