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Robust road transportation networks are essential to facilitate truck movements between regions. Disruptions along certain road links could degrade the network’s robustness and curtail regional commerce. A network is considered robust if the network-wide travel cost does not change significantly before and after disruptions. The network robustness index (NRI) is a well-known measure for examining the effect of reduced capacity on one or more links. It has been mainly applied to urban networks and passenger trips. In this paper, the NRI is applied to assess the robustness of the Ontario-wide truck network. Truck flows between the 49 census divisions within Ontario and 25 external zones for the year 2012 are modeled on the network of 35,254 road links and 14,444 associated nodes. Several scenarios of incrementally reduced capacity on specific critical links are devised and simulated. The NRI is calculated for each scenario to identify the level of network robustness. The locational effects of the capacity reductions were explored with the help of maps to assess the change in traffic volumes of the simulated scenarios relative to the base case. As expected, traffic diffuses or shifts to neighboring links when capacities are reduced. These results can be useful in infrastructure planning and the design of alternative routes to minimize the negative impact on traffic flows when disruptions occur.

In recent years, the field of transportation research has received increased interest from researchers and modeling methods have seen significant development. This thesis presents the development of a statistical microsimulation model for trip generation in the Windsor, Ontario Census Metropolitan Area (CMA). A novel methodology was developed to collect information from local firms using a combination phone and web-survey. Establishment-level data about business characteristics and commercial vehicle activities in the study area was collected from 171 establishments for analysis. Ordered logit models were used to determine the factors affecting the number of inbound and outbound commercial vehicle trips. The modeling results show that establishment characteristics are more effective in representing outbound movements than inbound. The model results are useful in explaining some of the factors giving rise to commercial trip generation, as well as revealing areas where further research is required, for a more complete understanding of commercial behaviours.

Functional foods play a crucial role in contemporary dietary strategies. This study investigates the incorporation of oregano oil, a bioactive extract that is known for its antimicrobial and antioxidant properties, into gelatin-based gummy jellies to develop functional food products with controlled release properties. The jellies were evaluated for mass uniformity, swelling index, disintegration time, and tensile strength under simulated oral and gastric conditions. The results showed that oregano oil significantly reduced the swelling index (e.g., 128.76 ± 0.67% at pH 5) and prolonged the disintegration time (e.g., 6–18 min across pH environments), highlighting its potential for controlled release. The mechanical strength remained stable (5.2 ± 0.3 N), ensuring structural integrity. These findings suggest that oregano-oil-enriched gummy jellies offer health benefits, although further studies are needed to explore their long-term stability and bioavailability.