Mohammad Abdullah Alshenaifi

Sustainable campus design plays a vital role in shaping student well-being, academic performance, and institutional adaptability. This study investigates how sustainable design strategies influence student life at Hail University, Saudi Arabia, a campus located in an arid, culturally specific environment that presents unique spatial and climatic challenges. By integrating empirical observations, structured surveys (n = 1186), and semi-structured interviews, the research adopts a mixed-methods approach to examine three core dimensions: social life enhancement, environmental sustainability, and student-centric design. The methodology incorporates both descriptive and inferential analyses, including correlation, regression, and ANOVA, to evaluate the impact of design features on student satisfaction, engagement, and resource efficiency. Results show that a 10% increase in social infrastructure correlates with a 6.5% rise in student satisfaction. The study further identifies gaps in climate-responsive planning, green space utilization, and participatory design practices. It offers a replicable, context-sensitive framework for sustainable campus development that aligns with multiple UN Sustainable Development Goals (SDGs), contributing new insights to the global discourse on higher education environments in arid regions.

Heating, ventilation, and air conditioning (HVAC) system performance research has received much attention in recent years. Many researchers suggest a set of appropriate fuzzy inputs that can be used to design fuzzy rules-based smart thermostats or controllers that can respond to demand-controlled ventilation, which in turn optimizes HVAC energy usage and provides satisfactory indoor temperatures. Previous research has focused on limited input parameters, such as indoor occupancy status, ambient temperature, and humidity constraints, which cannot efficiently and precisely manage thermal comfort. Hence, this study proposes a novel fuzzy controller with additional input parameters to keep indoor thermal comfort consistent with the corresponding number of occupants. The process employs an automatic fuzzy rule generation method to simplify the task of generating rules in the fuzzy inference system (FIS) using Mamdani FIS. A design-builder is used for modeling the HVAC systems. Local weather data were used to conduct simulations via EnergyPlus. The thermal comfort analysis using the Fanger model for three different scenarios shows that the proposed FIS controller can successfully respond to the indoor comfort variation in all possible scenarios and ensure a satisfactory comfort level. The proposed method demonstrates up to 50% energy savings if occupants do not worry about comfort.

Building energy consumption in hot arid climates is dominated by air conditioning use. Therefore, using passive cooling methods could reduce this demand, improve resource efficiency, and decrease carbon emissions. In this study, an innovative configuration of a passive downdraught evaporative cooling (PDEC) tower is investigated numerically. The governing equations are solved using the finite element method (FEM), and the effects of inlet velocity (0.5 m·s⁻¹ ≤ u_in ≤ 3 m·s⁻¹) and temperature (35 °C ≤ T_in ≤ 45 °C) on the fluid structure, temperature field, and relative humidity are studied for three cases related to the position of the air outlet. The flow is considered as turbulent, and the building walls and the tower are assumed to be thermally well insulated. The PDEC tower is equipped with two vertical isotropic saturated porous layers. The results revealed that the inlet velocity and temperature play an essential role in the quality of the indoor temperature. In fact, the temperature can be reduced by about 7 degrees, and the relative humidity can be enhanced by 9% for lower inlet velocities.