Autonomous HVAC CFD - An Art Driven By Science
Wednesday, December 22, 2021
Autonomous HVAC CFD - An Art Driven By Science
By
Manish Kamath
Blog Author - Manish Kamath
Written by Manish Kamath
Approximately
10 Minutes Reading
Approximately
10 Minutes Reading
Scenario Space
Scenario Space
The Autonomous HVAC CFD (AHC) is a fully autonomous cloud-based CFD simulation web app developed to evaluate the performance of your HVAC systems without having any prior knowledge of CFD. AHC provides users with an efficient way of creating a design layout and simulating the space for different air distribution systems. By automating the simulation, a non-CFD specialist will be able to overcome CFD challenges while also developing a better grasp of the app's derived data. After executing the simulation, the user can examine the results for the HVAC system, scenario, and space. The app interprets results into 5 categories, which enables the user to articulate the data as follows.
Thermal Comfort
According to the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE), thermal comfort is "that condition of mind which expresses satisfaction with the thermal environment and is assessed by subjective evaluation". You are most likely experiencing thermal comfort if you feel more comfortable in a room regardless of the temperature outside. This is a scenario that occurs when the body is in a relaxed state. Thermal comfort is a fundamental priority for engineers when building HVAC systems to satisfy their clients. It occurs when the heat produced by humans is allowed to dissipate, resulting in temperature equilibrium. Employee productivity is influenced by their thermal comfort. As a result, investing in high-quality HVAC could help you create the ideal working atmosphere for your personnel. The top-rated feature of AHC is that the app itself can analyze each manikin comfort. Individual manikin comfort is displayed on a scale ranging from - 3 to + 3: cold, comfortable, and hot. The manikin is enlivened by a function called "Animate," which allows for a comprehensive graphical picture of the occupant's thermal comfort.
Thermal Comfort
Thermal Comfort
Surface Plots
People's sense of well-being in a room, or their level of comfort, is governed by a range of specific external influencing factors. These measurement parameters can be determined and influenced appropriately by measuring comfort levels: Temperature, humidity, air movement, and thermal radiation are all aspects to consider. The success of the thermal comfort approach has been largely based on personal experience and the use of common methods. The most often studied thermal comfort metrics are the predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD).
PMV - Rather than responding to conditions in the surrounding environment, the heat felt by a person is induced by the temperature of the skin rather than the temperature of the air. The predicted mean vote (PMV) index is a thermal sensation index used in the thermal comfort standard.
PPD - The predicted percentage of dissatisfied (PPD) index estimates the number of occupants in space who would be dissatisfied with the thermal conditions. It is a quantitative prediction of the percentage of thermally dissatisfied people who are either too cool or too warm.
These are simply not predictable in advance. With AHC, this speculation has been removed from the equation, enabling anyone to explore any given space for compliance with thermal comfort easily.
Surface Plots
Surface Plots
Contour Plots
A contour plot is a two-dimensional representation in which all points with the same response are joined to form contour lines with constant responses. These are useful in order to indicate velocity and temperature distribution. It is a powerful tool for conveying information as well as for on-screen and presentational data analysis. Contour plots can be used to evaluate desired response values and operating scenarios. These are one of the major aspects of post-processing which displays a band of colors that can be classified according to Velocity, Temperature, Predicted Mean Vote (PMV), Effective Draft Temperature (EDT), % people dissatisfied, Draft Rating % (RH), Relative Humidity % and Mean Age of Air. AHC provides a feature of a cut plane which makes understanding contour plots easier as the user gets an option of viewing contour plots at various locations in space.
Contour Plots
Contour Plots
Comfort Clouds
This feature acts as a volume of space just like a cloud manifesting comfort for a designated space. The temperature, humidity, and air movement range that most people evaluate for mental and physical well-being are being showcased in this feature in the most understandable way possible for appropriate analysis of a given space. A series of scenarios consisting of PMV, PDD, Effective Draft Temperature is provided to view thermal comfort of discomfort regions in the space. Designers can analyze these clouds, find comfort regions and make the design better.
Comfort Clouds
Comfort Clouds
Flow Lines
Flowlines are the paths that individual fluid particles travel. These can be conceived of as "recording" the route of a fluid element in a flow over a specific period. Flowlines are used to envisage the air conditioning flow in space, visualize and understand the flow patterns in a given space. The user gets to view all as well as selected diffuser airflow, easing the analysis step. These lines can be distinguished according to velocity and pressure. Additional settings such as animating flowlines by varying the speed and changing bubble opacity offered by the app can also be useful to understand the scenario.
Flow Lines
Flow Lines
Results Summary
The process of evaluation becomes easier with the help of the result summary tab present in the result section, which provides a better understanding of the obtained results. The result summary is divided into 2 parts: design conditions and operating conditions. Design considerations consist of HVAC system configuration, supply airflow, supply temperature, and thermostat space. The operating conditions are Mode, Supply Airflow, Supply Temperature, and the achieved Space Temperature. Thus, it enables users to visualize quantitative data most simply.
Autonomous HVAC CFD has comprehended the exigency of thermal comfort and has been able to deliver the results most coherently. Experience thermal comfort scenarios for different spaces by opting for hands-on experience on the Autonomous HVAC CFD App and get a free trial period to explore your desired space.
Results Summary
Results Summary
Case studies
Nothing demonstrates the power of a product more than its real-world examples. View case studies of how AHC is used for estimating thermal comfort.
Simulation gallery
Get FREE early access
Wish to explore the Autonomous HVAC CFD application and optimize the design for thermal comfort ? Sign-up and get early access. Simulation credits worth $500 will be allocated for FREE. Explore the product and estimate thermal comfort for a space of 5000 square foot area for FREE.
Blog Author - Manish Kamath
Manish Kamath
Manish is a Technical Sales Engineer at Centre for Computational Technologies Private Limited (CCTech). At CCTech he is keenly interested in learning the upcoming new technologies in the field of Computational Fluid Dynamics and Machine Learning. His areas of interest are Comput-Aided-Engineering, and Fluid Mechanics. He holds a Bachelor's degree in Mechanical Engineering from Savitribai Phule Pune University. Studying Cosmology and reading books are some of his hobbies.
Blog Author - Manish Kamath
Manish Kamath
Manish is a Technical Sales Engineer at Centre for Computational Technologies Private Limited (CCTech). At CCTech he is keenly interested in learning the upcoming new technologies in the field of Computational Fluid Dynamics and Machine Learning. His areas of interest are Comput-Aided-Engineering, and Fluid Mechanics. He holds a Bachelor's degree in Mechanical Engineering from Savitribai Phule Pune University. Studying Cosmology and reading books are some of his hobbies.
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