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Vessel Behavior, Navigational Constraint Exposure, and Cargo Economics in the Port of Virginia

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Date

2026-09-17

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Virginia Tech

Abstract

This dissertation examines how vessel movement behavior changed in the Port of Virginia approach area between 2019 and 2024, how selected navigational conditions were associated with distinct behavioral signatures, and how those changes translate into scenario-based operational and economic exposure. Organized as a three-manuscript study, the dissertation combines approximately 9.69 million cleaned Automatic Identification System observations with Virginia Pilot Association movement and draft records, publicly charted bathymetry, and transparent maritime risk, fuel, and cargo-capacity assumptions.

Chapter 2 establishes the behavioral foundation. Relative to the 2019 baseline, mean vessel speed declined from 8.34 knots to 5.74 knots in 2024, mean course-over-ground-to-heading divergence increased from 19.94 to 37.47 degrees, mean course-change rate increased from 2.21 to 3.20 degrees per minute, and turning-event frequency rose from 13.68 percent to 20.11 percent. The annual pattern was uneven, with the largest simultaneous year-to-year changes occurring between 2021 and 2022. Condition-based comparisons further showed that Whale-season, CVOW, and Depth indicators were not behaviorally interchangeable: the CVOW condition developed the strongest later-year corridor-level burden signature, while the localized Depth core displayed a profile consistent with possible anticipatory route selection or avoidance.

Chapter 3 translates the AIS-observed changes into two operational consequence pathways. A relative CVOW concentration index increased by 47.6 percent between 2019 and 2024. Under the chapter's central illustrative calibration, this change corresponds to approximately $0.24 million in incremental annual collision-risk exposure. Under an illustrative adverse fuel-rate scenario, the observed 31 percent speed reduction, combined with an assumed 20-nautical-mile approach segment and 2,000 annual transits, produces a conditional annual fuel-cost penalty of $1.32 million, approximately 9,320 additional metric tons of carbon dioxide, and an associated carbon-cost equivalent of $0.47 million. The direction of the actual fleet-level fuel effect cannot be determined without vessel-specific fuel curves.

Chapter 4 evaluates the cargo-capacity pathway using class-specific vessel movement and draft records. The 2024 modeled exposure population includes 40 container movements and 335 outbound coal movements, for a total of 375 movements exceeding the modeled 45-foot threshold and falling within the applicable class-specific upper bounds. Under the central assumption that 50 percent of potentially exposed movements are assigned to cargo reduction, annual Pathway 3 exposure is $136.45 million, with low and high routing-share scenarios of $68.23 million and $204.68 million. The dissertation treats these values as economic exposure rather than as observed realized loss, and treats the six-foot effective-depth-loss and 20 percent under-keel-clearance inputs as explicit scenario assumptions rather than as measured site conditions or universal operating requirements.

Taken together, the dissertation contributes an integrated empirical and scenario-based framework that moves from observed vessel behavior to condition-specific interpretation and then to safety, efficiency, emissions, and cargo-capacity consequences. The results show that navigational constraints can remain physically passable while materially changing the economic quality of access. Three results were not anticipated in the original framework design: the largest simultaneous year-to-year behavioral inflection occurred in 2022 rather than at the 2020 pilot-project completion; the localized Depth indicator produced a counterintuitive lower-burden signature rather than the higher within-area burden originally expected; and cargo-capacity exposure accounted for approximately 98.5 percent of modeled incremental economic exposure under the central scenario, a dominance that the framework structure did not predetermine. The framework is intended to support marine spatial planning, port operations, and prospective evaluation of offshore infrastructure while making the distinction between observed evidence and modeled assumptions explicit.

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Keywords

Automatic Identification System (AIS), vessel behavior, navigational constraints, Port of Virginia, offshore wind, maritime safety, cargo-capacity exposure

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