Quantum mechanics

Building code

Engineering

Reliability engineering

Roof

Computer graphics (images)

Telecommunications

Power (physics)

Envelope (radar)

Civil engineering

Computer science

Optimal design

Physics

Glazing

Genetic algorithm

Geography

Thermal

Building envelope

Electronic engineering

Environmental science

Reliability (semiconductor)

Sensitivity (control systems)

Meteorology

Radar

Shading

Machine learning

Journal of Building Engineering

Little attention has been given to the use of optimization approach in the envelope design of thermally-massive structures in extreme hot climates. In addition, limited studies are reported to compare the optimal envelope design with those stipulated in standards and codes, considering the 3Es: energy, economic and environment. This study employs a computational approach for optimizing envelope design for housing in hot climates using a genetic algorithm (GA) technique, and a life cycle cost (LCC) analysis coupled with the EnergyPlus simulation program. A sensitivity analysis was performed using a verified housing model to determine the upper and lower limits of the optimization search domain. Several envelope design strategies were evaluated including walls and roof insulation, thermal mass, air tightness, window's areas, types of glazing, and window's shading. The optimization was then conducted for the subsidized and unsubsidized energy cost scenarios under three representative hot climates of Oman. The results indicated that window's shading is thermally and economically attractive across all climates. Depending on the energy cost scenario, 2.5 cm–5 cm more of thermal insulation is cost-optimal for envelope systems in hot climates when compared to warm-humid climate. The optimized cases were then compared to design cases following four prevalent regional thermal regulations; the Saudi code, the Estidama requirements, the Kuwaiti code, and the Gulf Cooperation Council (GCC) thermal regulations. Similar to the cost-optimal design, the GCC design case is proven to be economically attractive across all climates. With the exception of the warm-humid climate, other code-compliant design cases are economically feasible, provide more energy savings and have less impact on the environment for the hot climates. The government may provide rebates or incentives by redirecting the subsidy fund to promote these requirements.

Optimization of envelope design for housing in hot climates using a genetic algorithm (GA) computational approach