Applying recent efficient numerical methods for long-term simulations of heat transfer in walls to optimize thermal insulation

Omle, Issa; Kovács, Endre; Bolló, Betti

doi:10.1016/j.rineng.2023.101476

Cited by 9 publications

(2 citation statements)

References 19 publications

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“…where q * in = ε in σ in (u in ) 4 and q * out (t) = α sun G cout (t) + α Low ε out σ out [u out (t)] 4 [41]. The convection heat transfer coefficient for outside elements as a function of air velocity is estimated as follows [42]: G cout (t): The solar radiation is taken every 100 s in December and July [W/m 2 ].…”

Section: Mesh Construction Initial and Boundary Conditionsmentioning

confidence: 99%

Prediction and Optimization of Thermal Loads in Buildings with Different Shapes by Neural Networks and Recent Finite Difference Methods

Askar,

Kovács,

Bolló

2023

Buildings

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This study aimed to estimate the heating load (HL) and the cooling load (CL) of a residential building using neural networks and to simulate the thermal behavior of a four-layered wall with different orientations. The neural network models were developed and tested using Multi-Layer Perceptron (MLP) and Radial Basis (RB) networks with three algorithms, namely the Levenberg-Marquardt (LM), the Scaled Conjugate Gradient (SCG), and the Radial Basis Function (RB). To generate the data, 624 models were used, including six building shapes, four orientations, five glazing areas, and five ways of distributing glazing. The LM model showed the best accuracy compared to the experimental data. The L-shape facing south with windows on the east and south sides and a 20% window area was found to be the best shape for balancing the lighting and ventilation requirements with the heating and cooling loads near the mean value. The heating and cooling loads for this shape were 22.5 kWh and 24.5 kWh, respectively. The simulation part used the LH algorithm coded in MATLAB to analyze the temperature and heat transfer across the wall layers and the effect of solar radiation. The maximum and minimum percentage differences obtained by HAP are 10.7% and 2.7%, respectively. The results showed that the insulation layer and the wall orientation were important factors for optimizing the thermal comfort of a building. This study demonstrated the effectiveness of neural networks and simulation methods for building energy analysis.

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Section: Mesh Construction Initial and Boundary Conditionsmentioning

confidence: 99%

Prediction and Optimization of Thermal Loads in Buildings with Different Shapes by Neural Networks and Recent Finite Difference Methods

Askar,

Kovács,

Bolló

2023

Buildings

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“…Omleod calculated the winter transient heat transfer lost through building walls using the leapfrog-hopscotch and modified Dufort-Frankel techniques. The orientation of the outside walls and solar radiation were investigated [10]. However, the solar radiation angle was not taken into account.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of the Transient Thermal Load of a Sightseeing Airship Cockpit

Li,

Lin,

et al. 2024

Aerospace

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The calculation of a cockpit’s transient thermal load is important for determining the capacity of the cockpit environmental control system, ensuring the safety of electronic equipment and increasing the health and comfort of cockpit occupants. According to the structural parameters of the cockpit of a sightseeing airship, a physical model is established. The turbulence model and calculation method are selected and verified. The transient thermal load within full flight envelope, the cockpit thermal loads at different times of the day, and the cockpit thermal loads under different free-flow velocities are obtained based on the Computational Fluid Dynamics (CFD) method. The cockpit transient thermal loads during different seasons are also obtained. The results show that solar radiation has a great influence on the cockpit transient thermal load. As the flight altitude increases, the thermal load decreases from 8.8 kW (H = 0 m) to 4.7 kW (H = 3000 m). With the change in the solar radiation intensity and solar radiation angle, the thermal load increases considerably, from 2.2 kW (8:00 a.m.) to 5.4 kW (12:00 a.m.). The influence of the free-flow velocity is not very obvious at an altitude of 3000 m, as discussed in this study. The influence of seasons is significant. Finally, the influence of the solar absorptivity and infrared emissivity of the cockpit surface material are studied, and the temperature distribution on the cockpit’s surface is determined.

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The influence of the climate, the materials of the walls, and the gas effects of double and triple-glazed windows in terms of energy evaluation and economic expenses

Delarami,

Mohammadbeigi,

Gharib

2024

Results in Engineering

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Applying recent efficient numerical methods for long-term simulations of heat transfer in walls to optimize thermal insulation

Cited by 9 publications

References 19 publications

Prediction and Optimization of Thermal Loads in Buildings with Different Shapes by Neural Networks and Recent Finite Difference Methods

Prediction and Optimization of Thermal Loads in Buildings with Different Shapes by Neural Networks and Recent Finite Difference Methods

Numerical Simulation of the Transient Thermal Load of a Sightseeing Airship Cockpit

The influence of the climate, the materials of the walls, and the gas effects of double and triple-glazed windows in terms of energy evaluation and economic expenses

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