Calculation of radiation exchange using macro-class viewfactors

2017 ◽  
Author(s):  
T. Paul Etheredge ◽  
M. Blake Haynes ◽  
Matthey C. Rigney ◽  
Brad H. Seal ◽  
Jamie E. Burns
Keyword(s):  
Radiation Exchange

Must attic ventilation be preserved in energy retrofits?

2019 ◽  
Vol 37 (4) ◽  
pp. 461-472
Author(s):  
William Rose
Keyword(s):  
Vapor Pressure ◽  
Energy Efficient ◽  
Design Methodology ◽  
Air Leakage ◽  
Content Type ◽  
Buoyancy Flow ◽  
Spreadsheet Model ◽  
Radiation Exchange ◽  
Moisture Performance ◽  
Ashrae Standards

Purpose The addition of thermal insulation into attics along with air-tightening of the ceiling plane is a common first step in making homes more energy efficient. Attic ventilation was introduced decades ago on the assumption that air leakage across the ceiling was inevitable and not correctible – this was before the era of spray-applied foams. Often attic ventilation is provided at roof eaves, and ensuring good insulation in their location is critical to avoid cold corners in the rooms below. So may vents be blocked in the course of energy retrofits? The paper aims to discuss this issue. Design/methodology/approach This study consists of a simple spreadsheet model of attic performance. The model is built using material from ASHRAE Handbook Fundamentals and ASHRAE Standards. It includes: Glaser calculations for temperature, vapor pressure and vapor pressure excess; radiation exchange – solar and sky; buoyancy flow assumption for leakage from indoors; wind flow assumption for leakage from outdoors; and change in attic air RH as assumed indicator of change in sheathing moisture performance. Findings The model results show that lowered moisture contributions across air-tightened ceilings may compensate effectively for added insulation (which lowers the attic air temperature) and reduced moisture dilution from attic ventilation. Originality/value These results provide support for the policy of allowing attic ventilation reductions that are proportionate to ceiling air leakage reductions as part of weatherization efforts. Given the limitations of the model, continued field observations remain critical.

Computer Simulation of Heat Transfer in Alumina and Cement Rotary Kilns

2021 ◽  
pp. 1-57
Author(s):  
Atinder Pal Singh ◽  
P.S. Ghoshdastidar
Keyword(s):  
Heat Transfer ◽  
Computer Simulation ◽  
Rotary Kiln ◽  
Cement Kiln ◽  
Gas Temperature ◽  
Contact Heat ◽  
Dry Process ◽  
Radiation Exchange ◽  
Covered Wall ◽  
Rotary Kilns

Abstract The paper presents computer simulation of heat transfer in alumina and cement rotary kilns. The model incorporates radiation exchange among solids, wall and gas, convective heat transfer from the gas to the wall and the solids, contact heat transfer between the covered wall and the solids, and heat loss to the surroundings as well as chemical reactions. The mass and energy balances of gas and solids have been performed in each axial segment of the kilns. The energy equation for the wall is solved numerically by the finite-difference method. The dust entrainment in the gas is also accounted for. The solution marches from the solids inlet to the solids outlet. The kiln length predicted by the present model of the alumina kiln is 77.5 m as compared to 80 m of the actual kiln of Manitius et al. (1974, Manitius, A., Kurcyusz, E., and Kawecki, W., “Mathematical Model of an Aluminium Oxide Rotary Kiln,” Ind. Eng. Chem. Process Des. Dev., 13 (2), pp. 132-142). In the second part, heat transfer in a dry process cement rotary kiln is modelled. The melting of the solids and coating formation on the inner wall of the kiln are also taken into account. A detailed parametric study lent a good physical insight into axial solids and gas temperature distributions, and axial variation of chemical composition of the products in both the kilns. The effect of kiln rotational speed on the cement kiln wall temperature distribution is also reported.

scholarly journals Modeling Thermal Interactions between Buildings in an Urban Context

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2382
Author(s):  
Xuan Luo ◽  
Tianzhen Hong ◽  
Yu-Hang Tang
Keyword(s):  
Energy Demand ◽  
Energy Use ◽  
Longwave Radiation ◽  
Radiant Heat ◽  
Urban Context ◽  
Exterior Surface ◽  
Radiation Exchange ◽  
Urban Planning And Design ◽  
New Feature ◽  
The Impact

Thermal interactions through longwave radiation exchange between buildings, especially in a dense urban environment, can strongly influence a building’s energy use and environmental impact. However, these interactions are either neglected or oversimplified in urban building energy modeling. We developed a new feature in EnergyPlus to explicitly consider this term in the surface heat balance calculations and developed an algorithm to batch calculating the surrounding surfaces’ view factors using a ray-tracing technique. We conducted a case study with a district in the Chicago downtown area to evaluate the longwave radiant heat exchange effects between urban buildings. Results show that the impact of the longwave radiant effects on annual energy use ranges from 0.1% to 3.3% increase for cooling and 0.3% to 3.6% decrease for heating, varying among individual buildings. At the district level, the total energy demand increases by 1.39% for cooling and decreases 0.45% for heating. We also observe the longwave radiation can increase the exterior surface temperature by up to 10 °C for certain exterior surfaces. These findings justify a detailed and accurate way to consider the thermal interactions between buildings in an urban context to inform urban planning and design.

scholarly journals Using unsupervised learning to partition 3D city scenes for distributed building energy microsimulation

2020 ◽  
pp. 239980832091431
Author(s):  
Sameh Zakhary ◽  
Julian Rosser ◽  
Peer-Olaf Siebers ◽  
Yong Mao ◽  
Darren Robinson
Keyword(s):  
Community Detection ◽  
High Performance ◽  
Computational Cost ◽  
Building Energy ◽  
Data Locality ◽  
Urban Scenes ◽  
Detection Algorithms ◽  
Radiation Exchange ◽  
Energetic Interactions ◽  
High Performance Computing Cluster

Microsimulation is a class of Urban Building Energy Modeling techniques in which energetic interactions between buildings are explicitly resolved. Examples include SUNtool and CitySim+, both of which employ a sophisticated radiosity-based algorithm to solve for radiation exchange. The computational cost of this algorithm increases in proportion to the square of the number of surfaces of which an urban scene is comprised. To simulate large scenes, of the order of 10,000 to 1,000,000 surfaces, it is desirable to divide the scene to distribute the simulation task. However, this partitioning is not trivial as the energy-related interactions create uneven inter-dependencies between computing nodes. To this end, we describe in this paper two approaches ( K-means and Greedy Community Detection algorithms) for partitioning urban scenes, and subsequently performing building energy microsimulation using CitySim+ on a distributed memory High-Performance Computing Cluster. To compare the performance of these partitioning techniques, we propose two measures evaluating the extent to which the obtained clusters exploit data locality. We show that our approach using Greedy Community Detection performs well in terms of exploiting data locality and reducing inter-dependencies among sub-scenes, but at the expense of a higher data preparation cost and algorithm run-time.

scholarly journals Estimating thermal transmittance of the aluminium window profiles in practice

2020 ◽  
Vol 172 ◽  
pp. 24003
Author(s):  
Arkadiusz Witek ◽  
Barbara Pietruszka
Keyword(s):  
Heat Exchange ◽  
Accurate Method ◽  
Radiative Heat Exchange ◽  
Conductivity Method ◽  
Equivalent Thermal Conductivity ◽  
Thermal Transmittance ◽  
Radiation Exchange ◽  
First Case ◽  
Air Cavities ◽  
The Impact

Calculation of the heat flow through the air cavities in the EN ISO 10077-2:2017 standard for the determination of the thermal transmittance of window profiles uses models based on the equivalent thermal conductivity method. The method takes into account the radiative heat exchange in a simplified or accurate manner. In the first case, the heat exchange depends on the average temperature in cavity, in the second case - it is determined accurately by the ray tracing method. It is also of importance to differentiate emissivity of surfaces due to aging or painting what influences calculation time. In this work, the impact of the calculation method and the impact of simplifications in modelling of the untreated surfaces on the value of the thermal transmittance of aluminium profiles was analysed on the example of a real series of products. Comparing the simplified and accurate method of determining the radiation exchange in cavities, the differences in the thermal transmittances of window profiles were up to 22%. The differences between the most simplified and the most accurate modelling of the surfaces emissivity reached 23%.

Sign in / Sign up

Export Citation Format

Share Document