Ventilation Analysis
Ventilation Analysis is at the core of what we do at our Singapore office at BroadTech Engineering.
Featured Ventilation Analysis Case Studies
Ventilation Simulation Analysis for Building Contamination Control in Public Spaces
Objective: Simulation objective was to identify the best circulation zones in a standard office space and hospital room for disinfection and controlling the contaminant concentration.
Methodology Approach: A scaled experimental setup was fabricated to demonstrate the feasibility of simulated results and 2D and 3D turbulent flow simulations were obtained with Fortran coding and using Ansys Fluent and Cham Phoenix software.
Outcome: The outcome is the design strategy for best recirculations zone and conclusions were based on the different inclination angles for incoming air for separate design models.
Simulation of SUV Ventilation System (Single Phase flow)
Objective: To identify the pressure drop regions inside the car dashboard
Methodology: StarCCM+ Computational Numerical Simulation Software
Outcome: The pressure drop regions were identified and was conveyed to the Client regarding the improvement that can be done.
Natural Ventilation CFD study using Wind-Catcher
Objective: To predict Thermal Comfort in a room on using wind-catcher (natural ventilation) with proper atmospheric boundary layer modeling
Methodology:
1. An existing wind-catcher in Singapore was chosen for the analysis from a Client project. (In this project, only 2D and uniform inflow was considered)
2. Modeling of ABL based on the ground roughness and reference velocity at reference height on the location of the house with windcatcher
3. CFD analysis using ANSYS FLUENT
Outcome & Conclusion
1. PMV computed falls within the requirement
2. Presented our work in World Energy Summit Conference held in Singapore.
3. Earlier researchers on natural ventilation concentrated only on IAQ, but in this research, we concentrated on thermal comfort with proper ABL modeling
Investigation of the influence of Partitions on Buoyancy Induced Convection
Objective: Numerically investigated the influence of partitions on buoyancy induced convection with thermal radiation in a cubical enclosure at large temperature difference.
Four distinct arrangements of partitions from the top-bottom and front-back walls were examined by adopting asymmetric (inline) and asymmetric (offset) configuration of partitions.
Such configurations are representative of the industrial furnace and high rise buildings, with the later necessitating understanding of the flow and heat transfer in events of fire and are essential for setting up of fire and smoke detector, a design of evacuation routes in buildings.
This study aims at achieving optimum thermal design (higher heat transfer rates with minimum entropy production) among all partition configurations.
Approach: An in-house three-dimensional FVM based numerical solver employs a non-Boussinesq, low-Mach number formulation on arbitrary polyhedral meshes for the numerical simulations of high-temperature difference natural convection coupled with surface and gas radiation.
Results: The simulation results reveal that heat transfer irreversibility is the dominant mechanism of entropy production. Furthermore, offset configuration of front-back partitions could be a preferred choice in the practical design of buildings where the impact of combined convective-radiative heat transfer is significant.
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Impact Study of Solar Radiation & HVAC to Optimize Furniture Placement
Study of the impact of solar radiation and HVAC on our office to find out the ideal placement of desks and furniture
The topmost recent CFD engineering project that we conducted in the area of Ventilation involved the study of the impact of solar radiation and HVAC on our office to find out the ideal placement of desks and furniture to ensure human comfort.
The simulation task involved the following tasks:
1) Area calculation of the room
2) Identification of the centralized AC vents location
3) Identification of window locations
4) Using the architectural plan to identify the material used for the construction of walls and windows
5) Development of the CFD model
6) Validation of the CFD model
7) Running of the simulation in ANSYS Fluent
8) Post-Processing using CFD post
9) The conclusion of the exercise to depict the most optimum desk positions
Methodology:
Initial Sizing
To ensure the accuracy of the simulation, real-world parameters were taken into consideration. The office room dimensions were initially obtained using the architectural plan ( 10 m (length)×4 m (width)×2.5 m (height). Once the dimensions were obtained, individual material properties were identified. The outer wall was 0.4 m thick and was made from red bricks. The inner walls were also made from a single layer of bricks having a thickness of 0.2 m. The door was made from solid wood whereas the windows were made of a single insulated glass having a thickness of 0.002 m.
The orientation of the room was as follows:
1) Room was on the first floor (of a three-floor building) with the door facing a corridor along the south direction.
2) 2 windows facing the north direction.
3) One outer wall facing the north direction
4) Three inner walls with two walls facing the east and west respectively and flanked by rooms on either side and one wall connected to the door facing the south direction and is a part of the internal corridor of the building
5) 4 vents on the ceiling (location identified using the plan)
Based on the orientation of the room it was assumed that the solar radiation would have an indirect impact on the room and needed to be quantified.
Geometry Generation:
The geometry of the room was then generated using SOLIDWORKS and was a full-scale model of the room with exact dimensions.
Mesh Generation:
The SOLIDWORKS geometry model was imported into the Workbench Meshing Tool in ANSYS. It was decided that owing to the size of the room as well a tetrahedral meshing method was adopted. For complex geometries, a tetrahedral mesh saves meshing time as compared to a hexahedral structured mesh with a very low trade-off in terms of accuracy. Three different meshes of 250k, 500k, and 1 million mesh elements were generated, and a grid independence study was conducted. The actual temperature at the center of the room was measured and used as a parameter to identify if each individual mesh was refined enough to accurately attain the temperature value from the simulation.
Based on the grid independence study, the mesh with 500k elements was chosen due to its relative accuracy and time-saving. The difference between the temperature values for the fine mesh (1 million elements) and the medium mesh was roughly 1.5% and was small enough to be ignored.
CFD model, setup, and validation:
The CFD model for the entire exercise was the k-ϵ turbulence model. The energy equation was activated in FLUENT to calculate heat transfer rates.
To ensure that the model could accurately represent the real-world phenomenon, the k-ϵ model was first validated and benchmarked to an existing case attained from literature. As the k-ϵ model with scalable wall function accurately depicted the real-world phenomenon, I had no hesitation in using it to do a study of the radiation and HVAC ventilation of the office.
The setup of the model for simulation involved setting up individual boundary conditions in FLUENT. The solar radiation was calculated using the radiation calculator in FLUENT. The radiation calculator accurately calculates the position of the sun based on the location (latitude and longitude) as well as the date.
Inlet conditions were given to the AC vents whereas all other surfaces were given wall boundary conditions. A mixed heat transfer condition was set up in FLUENT. Each individual surface was given a material property based on the actual material (Data of the material was obtained either through fluent or using a user-defined material property).
The thickness of each individual surface was also set up in FLUENT.
The simulation was run as a steady state simulation rather than a transient simulation owing to computational constraints. Ideally, the simulation would be time-dependent and would be run over a designated period (the time step would have to be calculated). The simulation was given a convergence criterion of 〖10〗^(-3) owing to computation constraints.
Post-Processing:
Once the simulation converged, Post processing was done in CFD post. Contour plots were plotted on different planes at selected sections in the office to study the impact of cool air from the AC vents as well as the impact of heat transfer from a 35° C ambient temperature from outside.
Contours were plotted for temperature distribution (based on changes in the Inlet temperature ranging from 15° C-20° C).
Contours were also plotted for the radiation. Velocity streamlines were plotted from the inlet to see the flow distribution from the inlet.
Conclusions:
The temperature distribution within the room provided the most optimum seating positions in the office. It was obvious that no desks would be placed below individual vents. The orientation of the desks was also obtained in a manner to keep them away from the outer walls and the windows and closer to the inner walls of the room. The use of CFD as a tool provided a preliminary analysis of the most optimum and comfortable locations within the room so as to ensure maximum comfort and productivity of office staff.
Limitations:
Every simulation has certain limitations. In this particular case, the limitations are as follows:
1) The use of steady-state simulation to attain a time-independent solution instead of a time-dependent one.
2) The presence of people in the office was not taken into account. Human presence would influence the temperature distribution as well.
3) The room was devoid of any office furniture which would impact the air distribution from the vents.
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