Adverse weather delays forty-five percent of construction projects worldwide, costing project owners and contractors billions of dollars in additional expenses and lost revenue each year. Additionally, changes in climate are expected to increase the frequency and intensity of weather conditions that cause these construction delays. Researchers have investigated the effect of weather on several aspects of construction. Still, no previous study comprehensively (1) identifies and quantifies the risks weather imposes on construction projects, (2) categorizes modeling and simulation approaches developed, and (3) summarizes mitigation strategies and adaptation techniques to provide best management practices for the construction industry. This paper accomplishes these goals through a systematic state-of-the-art review of 3207 articles published between 1972 and October 2020. This review identified extreme temperatures, precipitation, and high winds as the most impactful weather conditions on construction. Despite the prevalence of climate-focused delay studies, existing research fails to account for future climate in the modeling and identification of delay mitigation strategies. Accordingly, planners and project managers can use this research to identify weather-vulnerable activities, account for changing climate in projects, and build administrative or organizational capacity to assist in mitigating weather delays in construction. The cumulative contribution of this review will enable sustainable construction scheduling that is robust to a changing climate.

Global urbanization, combined with evidence of increased prevalence of mental illness in urban environments, highlights a need to investigate potential connections between the built environment and mental health. Previous research has shown that the built environment may impact occupant mental health through its effects on connection to nature, personal control and indoor air quality. Contact with the natural environment has physiological and psychological benefits; consequently, reduced contact or exposure leads to negative mental health outcomes. The control an occupant has in the built environment can alter the mental health of individuals through direct pathways, such as prevention of exposures to environmental stressors and indirect pathways, such as social connections to others. Indoor air quality is connected to the mental health of built environment occupants, as particulate matter, malodorous irritants and toxins have all been shown to alter mental well-being. Opportunities for architects and engineers to optimize building designs that improve occupant mental health include planned urban greenspace, personalized temperature control and building ventilation. To understand optimization targets, interdisciplinary research utilizing controlled experiments are needed to confirm causality and improve our current understanding of mechanisms underlying the association between the built environment and mental health.

In November 2019, U.S. Marines, Air Force, and Army Corps of Engineers personnel demonstrated the viability and simplicity of three-dimensionally (3D)-printed construction in a controlled environment at the U.S. Army Engineer Research and Development Center—Construction Engineering Research Laboratory in Champaign, Illinois. The tri-service exercise spanned three days and culminated in the construction of three 1 m × 1 m × 1 m (3 ft × 3 ft × 3 ft) concrete dragon’s teeth (square pyramid military fortifications used to defend against tanks and armored vehicles) and several custom-designed objects. The structural components were printed using a custom-built, gantry-style printer called ACES Lite 2 and a commercially available, proprietary mortar mix. This paper examines the viability of using 3D-printed construction in remote, isolated, and expeditionary environments by considering the benefits and challenges associated with the printing materials, structural design, process efficiency, labor demands, logistical considerations, environmental impact, and project cost. Based on the results of this exercise, 3D-printed construction was found to be faster, safer, less labor-intensive, and more structurally efficient than conventional construction methods: the dragon’s teeth were printed in an average of 57 min each and required only two laborers. However, the use of commercially procured, pre-mixed materials introduced additional cost, logistical burden, and adverse environmental impact as compared to traditional, on-site concrete mixing and production. Finally, this paper suggests future applications and areas of further research for 3D-printed construction.

Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data—an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined dataset with an R² value of 0.94. As a comparative measure, other machine learning algorithms resulted in R² values of 0.50–0.94. Additionally, the data from each location was modeled separately with R² values ranging from 0.91 to 0.97, indicating a range of consistency across all sites. Using an input variable permutation approach with the random forest algorithm, we found that the three most important variables for power prediction were ambient temperature, humidity, and cloud ceiling. The analysis showed that machine learning potentially allowed for accurate power prediction while avoiding the challenges associated with modeled irradiation data.