The present paper reports experimental densities and kinematic viscosities of ten binary mixtures of 1-hexanol, ethylbenzene, octane, p-xylene, and chlorobenzene at 293.15 K and 298.15 K. The experimental data were obtained using Cannon-Ubbelohde viscometers and Anton-Paar DMA 60 density meter under temperature control. The experimental data were correlated with five different models: Allan-Teja, GC-UNIMOD, the Generalized Corresponding States Principle (GCSP), generalized McAllister three-body interaction, and an Artificial Neural Network (ANN) viscosity model. Among the tested models, the generalized McAllister three-body interaction model yielded the most accurate predictions, with an overall average absolute deviation of 3.9%. The Allan-Teja correlation exhibited the largest deviations for binary mixtures containing chlorobenzene. Two specialized artificial neural networks (ANN) models were developed to predict kinematic viscosities at 293.15 K and 298.15 K: one trained on 1-hexanol-containing mixtures and the other on non-associating hydrocarbon mixtures. Each model employed a 6–4–1 feedforward architecture with backpropagation training. The class-specific ANN models achieved average %AAD values of 3.3% and 1.6%, respectively. However, these models are limited to the mixture classes on which they were trained and cannot be generalized to other systems.

River crossing bridges in low-gradient floodplains can be affected by limited conveyance, backwater control, and scour-related foundation risk. This study evaluates a proposed IL 13 bridge replacement over the Mid Fork Saline River, Illinois, using HEC-RAS 1D steady-flow modeling, hydrologic inputs from USGS StreamStats for a drainage area of 236.45 mi², bridge opening analysis, multiple-opening interpretation, and HEC-18 scour assessment. Natural, existing, and proposed conditions were compared under design floods and Ohio River tailwater scenarios. The proposed bridge increased the effective waterway opening under all evaluated hydraulic scenarios, with increases of approximately 68.5–79.5% under the no-tailwater case, 76.1–76.9% under the 10-year Ohio River tailwater case, and 71.7–72.1% under the 50-year Ohio River tailwater case. Bridge opening velocity decreased by about one-third, indicating lower local hydraulic intensity and improved conveyance through the main opening. Contraction scour was not controlling, while computed pier scour decreased by approximately 8–10% and the controlling right abutment scour decreased slightly. Because empirical HEC-18 scour equations can have large uncertainty, commonly approaching an order of a factor of two in practical scour prediction, these reductions are interpreted only as comparative trends. They do not provide a basis for reducing foundation design requirements, but they indicate that the proposed replacement does not worsen the controlling scour response. Overall, the replacement improves hydraulic compatibility, reduces local hydraulic stress, and does not worsen the governing scour response. The study supports SDG 9, SDG 11, and SDG 13 in a hydraulic-infrastructure sense by promoting resilient bridge serviceability, safer transport connectivity, and adaptation-oriented flood risk assessment; however, full life-cycle carbon, cost, and network-resilience metrics were outside the scope.