scholarly journals The Examination of Air Blowing Method and Thermal Comfort of Variable Air Conditioning System using Coanda Effect

2019 ◽  
Vol 111 ◽  
pp. 01079
Author(s):  
Hikari Sakakibara ◽  
Takashi Akimoto ◽  
Hitomi Igarashi ◽  
Shunsuke Nakamura ◽  
Madoka Kimura
Keyword(s):  
Thermal Comfort ◽  
Air Conditioning ◽  
Air Flow ◽  
Building Design ◽  
Upper Body ◽  
Coanda Effect ◽  
Subjective Perception ◽  
Air Conditioning System ◽  
Air Blowing ◽  
Coandǎ Effect

The “Strategic Energy Plan” implemented by the Cabinet of Japan in 2014 strives for zero energy building design for typical new construction by 2030. The present study focuses on a ductless and variable air conditioning system, using the Coanda effect, with the aim of reducing fan power, and saving of resources by reducing the space between the ceiling. In this study, we examined the air blowing method and evaluated thermal comfort using computational fluid dynamics as well as subjective perception of coolness in a midsize office. A draft zone was reduced by extending the interval between conditioned air outlets. However, if the extension of throw length was excessive, hot space would be formed near the air outlets, and there would be a risk of impacting thermal comfort. Moreover, we confirmed that the thermal comfort was generally favourable. In particular, perceived thermal comfort was better at the position in the office where the air flow landed on the upper body of the subjects. On the other hand, it decreased when the influence of the air flow was small, and at the point where air flow landed on the lower body of the subjects.

Air Flow in Large Space Building with CFD Model and Local Test

2011 ◽  
Vol 213 ◽  
pp. 260-266
Author(s):  
Jun Wang ◽  
Hai Xia Wang
Keyword(s):  
Energy Efficiency ◽  
Thermal Comfort ◽  
Air Conditioning ◽  
Air Flow ◽  
Air Distribution ◽  
Cfd Model ◽  
Large Space ◽  
Air Conditioning System ◽  
Local Test ◽  
Comparison And Analysis

Simulation with CFD and local test are two main methods in study on air flow in large space building. This paper tests and simulates thermal comfort and air distribution of existing air- conditioning mode of some exhibition center. Through comparison and analysis on existing and simulated air-conditioning pattern, draw a conclusion that it’s feasible to simulate thermal comfort and air distribution of air-conditioning. And the research is important to guide energy efficiency and design optimization of air-conditioning system in large space building.

scholarly journals The Effects of an Air Conditioning System using the Coanda Effect on an Indoor Office Environment

2019 ◽  
Vol 111 ◽  
pp. 01088
Author(s):  
Hitomi Igarashi ◽  
Takashi Akimoto ◽  
Daisuke Hatori ◽  
Shun Kato ◽  
Hikari Sakakibara ◽  
...  
Keyword(s):  
Air Conditioning ◽  
Thermal Environment ◽  
Flow Characteristics ◽  
Heating System ◽  
Residential Area ◽  
Coanda Effect ◽  
Medium Size ◽  
Air Conditioning System ◽  
Net Zero Energy Building ◽  
Coandǎ Effect

In this study, we propose a ductless air conditioning system using the Coanda Effect for a medium size office building to achieve a net-zero energy building (ZEB). The indoor temperature environment and air flow characteristics during cooling and heating conditions created by this system were evaluated. In addition, to validate the computational fluid dynamics (CFD) analysis results when the heating system was activated, the results were compared with the measurement results. The investigation indicated that for cooling, a good thermal environment could be established in the residential area; however, local draught continued to be an issue. For heating, it was confirmed that heating of the residential area could be accomplished using floor suction. In addition, it was shown that the accuracy of the CFD analytical results can be improved by adjusting the input conditions to the actual conditions.

Effect of Air Conditioning Position on Thermal Comfort in the Floor Air Conditioning System

2014 ◽  
Vol 493 ◽  
pp. 74-79
Author(s):  
Y.A. Sabtalistia ◽  
S.N.N. Ekasiwi ◽  
B. Iskandriawan
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Energy Consumption ◽  
Thermal Comfort ◽  
Energy Efficient ◽  
Air Conditioning ◽  
Air Conditioning System ◽  
Air Supply ◽  
Air Conditioning Systems ◽  
Air Diffusion

Energy consumption for air conditioning systems (air conditioning system) increased along with the increasing need for fresh air and comfortable in the room especially apartments. FAC system (Floor Air Conditioning) is growing because it is more energy efficient than CAC (Ceiling Air Conditioning) system. However, the position of the AC supply is on the lower level at the FAC system causes draft discomfort becomes greater as air supply closer to the occupants so that thermal comfort can be reduced. Heat mixture of windows, exterior walls, kitchen, and occupants in the studio apartment affect thermal comfort in the room too.This study aims to determine the position of the AC supply which has the best thermal comfort of FAC system in the studio apartment. It can be done by analyzing ADPI (Air Diffusion Performance Index), the distribution of air temperature, wind speed, RH (Relative Humidity), and DR (Draft Risk) to change the position of the AC supply supported by CFD (Computational Fluid Dynamics) simulation.This result prove that AC position 2 (on wall near the kitchen) is more comfortable than AC position 1 (on the bathroom wall) because AC position 2 away from occupied areas, thereby reducing the occurrence of draught discomfort.

scholarly journals Thermal Comfort Study Based on PMV-PPD in the Building of a Screening Center for COVID-19

2021 ◽  
Author(s):  
Danial Mohammadi ◽  
Simin Nasrabadi
Keyword(s):  
Thermal Stress ◽  
Energy Consumption ◽  
Thermal Comfort ◽  
Air Conditioning ◽  
Thermal Condition ◽  
R Software ◽  
Air Conditioning System ◽  
Thermal Index ◽  
Predicted Mean Vote ◽  
Hot Climate

Background: One way to achieve a standard heating, ventilating, and air conditioning system with maximum satisfaction is to use a thermal index to identify and determine the thermal comfort of people. In this study we intend to evaluate thermal comfort based on PMV-PPD (Predicted Mean Vote/Predicted Percentage Dissatisfied) model in workers of screening center for COVID-19. Methods: The study period was from March 1 to October 31, 2020. In this study, we used the ISO 7730 model to determinate PMV-PPD index. PMV index was used to determine thermal comfort at different scales in Birjand city with arid and hot climate. All data were analyzed using R software (version 3.3.0) and IBM SPSS statistics softwares. Results: The maximum and minimum recorded physical PMV values in the study period were observed in June as (2.09 ± 0.03) and March as (-1.27 ± 0.14), respectively. The amplitude of the thermal sense in the study period was varied between slightly cool (-1.5) and warm (+2.5). The PPD in spring was 40% which indicated slightly warm to hot condition. Conclusions: The October was the only month during the study in which thermal stress was in comfort or neutral thermal condition.  Our results suggest that thermal comfort has dimensions and indices which are helpful in managing energy consumption.

scholarly journals Thermal comfort control via air conditioning system using fuzzy neural network feedback controller

2020 ◽  
Vol 19 (2) ◽  
pp. 586
Author(s):  
Somaye A. Mohamadi ◽  
Abdulraheem J. Ahmed
Keyword(s):  
Neural Network ◽  
Thermal Comfort ◽  
Environmental Conditions ◽  
Air Conditioning ◽  
Fuzzy Controller ◽  
Environmental Parameters ◽  
Thermal Conditions ◽  
Real Time Control ◽  
Air Conditioning System ◽  
Air Conditioning Systems

<span>Despite their complexity and uncertainty, air conditioning systems should provide the optimal thermal conditions in a building. These controller systems should be adaptable to changes in environmental parameters. In most air conditioning systems, today, there are On/Off controllers or PID in more advanced types, which, due to different environmental conditions, are not optimal and cannot provide the optimal environmental conditions. Controlling thermal comfort of an air conditioning system requires estimation of thermal comfort index. In this study, fuzzy controller was used to provide thermal comfort in an air conditioning system, and neural network was used to estimate thermal comfort in the feedback path of the controller. Fuzzy controller has a good response given the non-linear features of air conditioning systems. In addition, the neural network makes it possible to use thermal comfort feedback in a real-time control.</span>

A dynamic model for human thermal comfort for smart building applications

2019 ◽  
Vol 234 (4) ◽  
pp. 472-483
Author(s):  
Ghezlane Halhoul Merabet ◽  
Mohamed Essaaidi ◽  
Driss Benhaddou
Keyword(s):  
Thermal Comfort ◽  
Air Conditioning ◽  
Research Work ◽  
Comfort Level ◽  
Indoor Environments ◽  
Air Conditioning System ◽  
Human Thermal Comfort ◽  
Local Quality ◽  
Set Up ◽  
Air Conditioning Systems

Thermal comfort is closely related to the evaluation of heating, ventilation, and air conditioning systems. It can be seen as the result of the perception of the occupants of a given environment, and it is the product of the interaction of a number of personal and environmental factors. Otherwise, comfort issues still do not play an important role in the daily operation of commercial buildings. However, in the workplace, local quality effects, in addition to the health, the productivity that has a significant impact on the performance of the activities. In this regard, researchers have conducted, for decades, investigations related to thermal comfort and indoor environments, which includes developing models and indices through experimentations to establish standards to evaluate comfort and factors and set-up parameters for heating, ventilation, and air conditioning systems. However, to our best knowledge, most of the research work reported in the literature deals only with parameters that are not dynamically tracked. This work aims to propose a prototype for comfort measuring through a wireless sensor network and then presenting a model for thermal comfort prediction. The developed model can be used to set up a heating, ventilation, and air conditioning system to meet the expected comfort level. In particular, the obtained results show that there is a strong correlation between users’ comfort and variables such as age, gender, and body mass index as a function of height and weight.

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