Tony-Andreas Arntsen

Bio: Tony-Andreas Arntsen is an academic researcher. The author has contributed to research in topics: Thermal comfort & Daylight. The author has co-authored 1 publications.

Optimization of Window Design for Daylight and Thermal Comfort in Cold Climate Conditions

Abstract: Window design affects the overall performance of a building. It is important to include window design during the initial stages of a project since it influences the performance of daylight and thermal comfort as well as the energy demand for heating and cooling. The Norwegian building code facilitates two alternative methods for achieving a sufficient daylight, and only guidelines for adequate indoor thermal comfort. In this study, a typical Norwegian residential building was modeled to investigate whether the criteria and methods facilitate consistent and good performance through different scenario changes and furthermore, how the national regulations compare to European standards. A better insulated and more air-tight building has usually a lower annual heating demand, with only a marginal decrease in the daylight performance when the window design is unchanged. A more air-tight construction increases the risk of overheating, even in cold climates. This study confirms that a revision of the window design improves the overall performance of a building, which highlights the importance of proper window design. The pursuit of lower energy demand should not be at the expense of indoor thermal comfort considering the anticipated future weather conditions. This study indicates that criteria for thermal comfort and daylight, if clearly defined, can affect the energy demand for heating and cooling, as well as the indoor climate positively, and should be taken into account at the national level. A comparison between the national regulations and the European standards was made, and this study found that the results are not consistent.

Optimizing Window Configuration Counterbalancing Energy Saving and Indoor Visual Comfort for Sydney Dwellings

Abstract: Building penetrations are the most-potent elements providing daylight and moderating the lighting energy consumption and affecting indoor comfort and consequent energy usage. In a semi-tropical climate with a green environment such as Sydney, there is a radical demand to extend windows providing views. This research aims to optimize sunlight admission and maintain indoor comfort while minimizing energy consumption. The method for investigation is to simulate a multiobjective optimization using NSGA-II considering visual and thermal comfort along with energy usage and view of the outside. A combination of human and machine assessments responding to manual and microcontroller-operated indoor validating simulation improves the generalizability. The solutions were assessed for local codes compliance and double-checked against statistical sky conditions. Regarding north, a window-to-wall ratio of 10.7–20% delivers an optimum daylight metric, yielding a 12.16% decrease in energy use intensity. For an east-facing window, altering 26.4% of WWR decreases 2% in lighting energy and a provides a drastic change in visual comfort. Regarding west, changing WWR by about 51% brings about a 50% saving in lighting but no change in other energy loads. Regarding south, when window length is limited to 39% envelope width, it delivers the optimum energy consumption. This study covers visual and thermal comfort together with energy usage and view of the outside, which has not been investigated for southern hemisphere dwellings. A combined simulation and field measurement of human and machine assessment justifies the solutions.

A study on multicollinearity of design variables of office buildings’ standard floor regarding daylight and thermal performance

Abstract: Taking standard floor of high-rise office buildings as a research object in five cities of northern coastal region, Lianyungang, Qingdao, Yantai, Tianjin and Dalian included, model simulation and performance calculation are carried out with the help of Ladybug + Honeybee (L + H) platform. Principal component analysis (PCA) is used to solve the multicollinearity problem that 15 design variables including a building’s body (B, DR, FH, C and RE), window form (WWR, WH, SH, WHD and WVD) and envelope property (K, SHGC, VT, EW_R and F_R) were reduced to 12 and divided into four principal components (PCs), namely PC1 (buildings’ appearance), PC2 (window position), PC3 (window property) and PC4 (exterior-wall property), and then weights of PC1~PC4 were obtained by weight analysis to be 0.41, 0.268, 0.188 and 0.134 respectively, and the principal component linear evaluation function was proposed as Q = 0.41 PC1 + 0.268 PC2 + 0.188 PC3 + 0.134 PC4. On the other hand, with the help of genetic algorithm (GA), buildings’ energy consumption (BEC), thermal discomfort (PPD, Predicted Percentage Dissatisfied) and natural daylighting (sDA, Spatial Daylight Autonomy) were coupled to optimize standard floor shapes to find out excellent solutions. In summary, the paper proposes a performance optimization design process of high-rise office buildings’ standard floor.