scholarly journals Heating and Cooling Application in Energy Efficient Buildings using Trombe Wall: A Review

2021 ◽  
Vol 1130 (1) ◽  
pp. 012015
Author(s):  
S. Navakrishnan ◽  
B. Sivakumar ◽  
R. Senthil ◽  
Rajendran Senthil Kumar
Keyword(s):  
Energy Efficient ◽  
Heating And Cooling ◽  
Energy Efficient Buildings ◽  
Trombe Wall

New developments in illumination, heating and cooling technologies for energy-efficient buildings

Energy ◽  
2010 ◽  
Vol 35 (6) ◽  
pp. 2647-2653 ◽  
Author(s):  
H.J. Han ◽  
Y.I. Jeon ◽  
S.H. Lim ◽  
W.W. Kim ◽  
K. Chen
Keyword(s):  
Energy Efficient ◽  
New Developments ◽  
Heating And Cooling ◽  
Energy Efficient Buildings

scholarly journals Predicting Heating and Cooling Loads in Energy-Efficient Buildings Using Two Hybrid Intelligent Models

2019 ◽  
Vol 9 (17) ◽  
pp. 3543 ◽  
Author(s):  
Dieu Tien Bui ◽  
Hossein Moayedi ◽  
Dounis Anastasios ◽  
Loke Kok Foong
Keyword(s):  
Energy Efficient ◽  
Residential Buildings ◽  
Influential Factors ◽  
Ann Model ◽  
Wall Area ◽  
Heating And Cooling ◽  
Energy Efficient Buildings ◽  
Performance Error ◽  
Artificial Neural Network Ann ◽  
Intelligent Models

Today, energy conservation is more and more stressed as great amounts of energy are being consumed for varying applications. This study aimed to evaluate the application of two robust evolutionary algorithms, namely genetic algorithm (GA) and imperialist competition algorithm (ICA) for optimizing the weights and biases of the artificial neural network (ANN) in the estimation of heating load (HL) and cooling load (CL) of the energy-efficient residential buildings. To this end, a proper dataset was provided composed of relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, glazing area distribution, as the HL and CL influential factors. The optimal structure of each model was achieved through a trial and error process and to evaluate the accuracy of the designed networks, we used three well-known accuracy criterions. As the result of applying GA and ICA, the performance error of ANN decreased respectively by 17.92% and 23.22% for the HL, and 21.13% and 24.53% for CL in the training phase, and 20.84% and 23.74% for HL, and 27.57% and 29.10% for CL in the testing phase. The mentioned results demonstrate the superiority of the ICA-ANN model compared to GA-ANN and ANN.

scholarly journals The Effect of Density on the Delicate Balance between Structural Requirements and Environmental Issues for AAC Blocks: An Experimental Investigation

2021 ◽  
Vol 13 (23) ◽  
pp. 13186
Author(s):  
Daniele Ferretti ◽  
Elena Michelini
Keyword(s):  
Thermal Conductivity ◽  
Energy Efficient ◽  
Construction Materials ◽  
Mechanical Index ◽  
Material Density ◽  
Safety Issues ◽  
Heating And Cooling ◽  
Energy Efficient Buildings ◽  
Optimum Material ◽  
Energy Efficient Building

Among other construction materials, Autoclaved Aerated Concrete (AAC) offers several advantages to face the pressing need to build more sustainable and energy-efficient buildings. From the building side, the low thermal conductivity of AAC allows the realization of energy-efficient building envelopes, with interesting savings in terms of heating and cooling processes. The equilibrium between structural performances (related to safety issues) and energy efficiency requirements is, however, very delicate since it is strictly related to the search for an “optimum” material density. Within this context, this work discusses the results of wide experimental research, showing the dependency of the most important mechanical properties (compressive strength, elastic modulus, flexural strength and fracture energy) from density, as well as the corresponding variation in thermal conductivity. In order to identify the better compromise solution, a sort of eco-mechanical index is also defined. The big challenge for future researches will be the improvement of this eco-mechanical index by working on pore structure and pore distribution within the material without significantly reducing the density and/or by improving the strength of the skeleton material.

A STUDY ON THE APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES FOR PREDICTING THE HEATING AND COOLING LOADS OF BUILDINGS

2019 ◽  
Vol 14 (3) ◽  
pp. 115-128 ◽  
Author(s):  
Sushmita Das ◽  
Aleena Swetapadma ◽  
Chinmoy Panigrahi
Keyword(s):  
Artificial Intelligence ◽  
Energy Efficient ◽  
Energy Performance ◽  
Accurate Estimation ◽  
Cooling Load ◽  
Alternative Technologies ◽  
Heating And Cooling ◽  
Energy Efficient Buildings ◽  
Cooling Loads ◽  
Heating And Cooling Load

The prediction of the heating and cooling loads of a building is an essential aspect in studies involving the analysis of energy consumption in buildings. An accurate estimation of heating and cooling load leads to better management of energy related tasks and progressing towards an energy efficient building. With increasing global energy demands and buildings being major energy consuming entities, there is renewed interest in studying the energy performance of buildings. Alternative technologies like Artificial Intelligence (AI) techniques are being widely used in energy studies involving buildings. This paper presents a review of research in the area of forecasting the heating and cooling load of buildings using AI techniques. The results discussed in this paper demonstrate the use of AI techniques in the estimation of the thermal loads of buildings. An accurate prediction of the heating and cooling loads of buildings is necessary for forecasting the energy expenditure in buildings. It can also help in the design and construction of energy efficient buildings.

scholarly journals The Influence of Building’s Orientation on the Overall Thermal Performance

2018 ◽  
Vol 3 (1) ◽  
pp. 63 ◽  
Author(s):  
Aiman Albatayneh ◽  
Sulaiman Mohaidat ◽  
Atif Alkhazali ◽  
Zakariya Dalalah ◽  
Mathhar Bdour
Keyword(s):  
Thermal Comfort ◽  
Thermal Performance ◽  
Energy Efficient ◽  
Low Cost ◽  
Ghg Emissions ◽  
Heating And Cooling ◽  
Correct Orientation ◽  
Energy Efficient Buildings ◽  
Building Orientation ◽  
Save Energy

Containing and then reducing greenhouse gas (GHG) emissions require designing energy efficient buildings which save energy and emit less GHG. Orientation has an impact on the building’s overall thermal performance and designing heating and cooling to reach occupants’ thermal comfort. Correct orientation is a low cost option to improve occupant's thermal comfort and decrease cooling and heating energy. An appropriate building orientation will allow the desirable winter sun to enter the building and allow ventilation in the summer by facing the summer wind stream. In this paper, a building module in Jordan will be assessed using Design Builder Simulation packages to find the effect of the building orientation on the overall thermal performance. It was found that the larger windows should be in the southern walls in the northern hemisphere to provide the most heat to the building through the window which allows the sun in winter to enter the building and heat it up. This will reduce the amount required for heating by approximately 35% per annum.

THE ASSESSMENT OF NOISE GENERATED BY HEAT PUMPS INSTALLED OUTDOORS

Akustika ◽  
2020 ◽  
pp. 2-7
Author(s):  
Marián Flimel
Keyword(s):  
Present Article ◽  
Energy Efficient ◽  
Heat Pumps ◽  
Assessment Methods ◽  
Secondary Effect ◽  
Renewable Sources ◽  
Time Exposure ◽  
Energy Efficient Buildings ◽  
Important Position

Energy-efficient buildings utilise the potential of renewable sources, among which heat pumps hold an important position. As this technology has a secondary effect on the environment through its noise immission, locations of outdoor units in the exterior should be subjected to the assessment. The present article deals with the options of placing heat pumps in the exterior and the placement assessment methods. The noise burden identification through the assessment of the time exposure is presented in the example of an in situ measurement.

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