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AbstractThe present study provides an analysis of existing literature encompassing the wind and thermal analysis of football stadia, and how both can be manipulated through the modification of roof geometry. It introduces the potential for cooling strategies to create an internal environment capable of hosting elite-level international football in a hot climate. The motivation for the study stems from an absence of existing literature focussing on thermal flow in hot conditions for stadia and the requirement to investigate the hosting capabilities of Qatar for the 2022 FIFA World Cup. Stadium design plays a crucial role in determining the success of the tournament not only through the month-long event, but also with the legacy it leaves afterwards. To carry out the analysis, Computational Fluid Dynamics (CFD) simulations were conducted in an effort to produce internal conditions that satisfy official FIFA guidelines on optimal playing conditions in terms of wind and temperature distribution. These are ran on a model validated against existing literature to ensure accuracy, but considering the potential for error between model generations. The conclusions drawn suggest that a downward-pitched, large-radius retractable roof subsidised by the introduction of a mechanical system to create a cooling strategy reduces the external temperature down to 23 °C, with wind velocities not exceeding 4 m/s. Reinforced by results, these desired playing conditions can be achieved by closing the roof to precondition the stadium before an event, with the roof then retracted to ensure compliance with FIFA guidelines. The results from the present study can be a component in achieving a sustained positive legacy for the upcoming FIFA World Cup.

Abstract:While attending seminary school in Pennsylvania, Martin Luther King Jr. cultivated “the arts of pulpit oratory,” the habit of visualizing philosophical problems and other objects of criticism by invoking many-sided jewels and multi-runged ladders. This article appropriates King’s jewels and ladders as tools for humanizing juridico-discursive practice toward migrants/emigrants/immigrants and refugees. By drawing attention to the process whereby persons are subordinated and become subpersons, we are able to see how the standpoint of racialized dehumanization is historically patterned and furthermore involves an overlap of legal, political, and artistic expressions. Consequently, jewels and ladders become theoretical as well as practical tools for visualizing the moral standing of migrant/refugee populations in modernity.

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Computational Fluid Dynamics tools and Response Surface Methodology optimization techniques were coupled for the evaluation of an optimum window opening design that improves the ventilation efficiency in a naturally-ventilated building. The multi-variable optimization problem was based on Design of Experiments analysis and the Central Composite Design method for the sampling process and estimation of quadratic models for the response variables. The Screening optimization method was used for the generation of the optimal design solution. The generated results indicated a good performance of the estimated response surface revealing the strength correlations between the parameters. Window width was found to have greater impact on the flow rate values with correlation coefficient of 73.62%, in comparison to the standard deviation 55.68%, where the window height prevails with correlation coefficient of 96.94% and 12.35% for the flow rate. The CFD results were validated against wind tunnel experiments and the optimization solution was verified with simulation runs, proving the accuracy of the methodology followed, which is applicable to numerous environmental design problems. [ABSTRACT FROM AUTHOR]

•A computer vision-based approach for the detection of window conditions is introduced.•The performance of the detection approach was evaluated by conducting field testing in a university lecture room.•Impact of different data curation, labelling and training methods on performance were evaluated•The impact on the ventilation heat loss and energy demand was evaluated using building simulation.•The training approach with the labels assigned to the opening gaps of windows achievedthe best performance.

•Machine and deep learning models for building energy efficiency, thermal comfort and air quality.•Applications of machine and deep learning models and trends in the built environment sector.•Challenges of adopting machine and deep learning in the built environment sector.•Limited studies applied machine and deep learning-based strategies in real buildings and conducted post-occupancy evaluation.•Limited machine and deep learning studies investigated energy use, thermal comfort, and indoor air quality simultaneously.