Impact of Climate Change on Transportation Infrastructure over Unsaturated Expansive Clay
Dr. Shay Nachum
The Ministry of Innovation, Science & Technology
31.12.2025
Project Title: Impact of Climate Change on Transportation Infrastructure over Unsaturated Expansive Clay: Coupled Infiltration-Traffic Full-Scale Experiments and Feasibility of Adaptive
Big congrats to Dr. Shai Nahum on winning the MOST research grant! An incredible achievement for a brilliant researcher. Best of luck with the next steps of your project.
This research serves as a feasibility study to explore a new and practical method for stabilizing expansive clay subgrades.
It investigates the impacts of climate change–driven hydrological extremes on transportation infrastructure over unsaturated expansive clays, highly sensitive to wetting–drying cycles. Increasing heavy rains and prolonged droughts accelerate shrink–swell activity, loss of stiffness which induce cracking, settlement, and reduced service life.
The study will measure subgrade response to traffic and wetting in a full-scale field test over compacted clay, monitoring moisture, matric suction, and both normal and shear stresses and strains using advanced, validated instruments uniquely developed by the researchers. In parallel, laboratory experiments will evaluate electro-osmotic stabilization (EOS) on representative clay specimens, quantifying its potential to limit water ingress and preserve shear stiffness under wetting. Field-derived maps of stiffness versus moisture will inform adaptive EOS activation strategies once real-time monitoring thresholds are established. Together, these experiments provide a foundation for a practical, climate-resilient approach to subgrade stabilization, linking process understanding to innovative, scalable solutions for transportation infrastructure.
An analytical empirical model and root causes analysis for construction accidents and proposed methods for mitigating the severity and prevalence of injuries
Dr. Fadi Shahin
The Ministry of Innovation, Science & Technology
1.12.2025
Project Title: An analytical empirical model and root causes analysis for construction accidents and proposed methods for mitigating the severity and prevalence of injuries
Congratulations to Dr. Fadi Shahin on being awarded a research grant from the Ministry of Innovation, Science, and Technology (MOST).
This research develops an AI/ML-based predictive framework to identify the root causes of unsafe decisions made by construction workers and to prevent accidents before they occur.
It integrates accident databases, literature reviews, worker interviews, and surveys to classify construction accident patterns, examine the psychological and organizational mechanisms underlying workers’ decisions to err, and assess how human resources, sites, and management factors influence safety outcomes. Using machine learning techniques such as Artificial Neural Networks and Random Forest models, the study aims to build a predictive tool capable of identifying workers and conditions associated with elevated accident risk, enabling targeted interventions, improved risk awareness, and more effective safety management.
Ultimately, the research seeks to transform construction safety from a reactive process into a proactive, data-driven system that enhances decision-making and reduces workplace injuries and fatalities.