Heather Nachtmann’s research while affiliated with University of Arkansas at Fayetteville and other places

This work considers the operation of an IWTS involving waterways, ports and locks. Through simulation and optimization, the optimal sequence of maintenance and repair actions on these locks over a specific planning horizon is determined to maximize the throughput of the IWTS for the same period. https://rosap.ntl.bts.gov/view/dot/73207

The inland waterway transportation system (IWTS) plays an essential role in the multi-modal transportation system of the United States. The IWTS consists of multiple interconnected infrastructures, such as locks and dams, that are necessary for day-today operations. However, the confluence of weather conditions, water levels, and system operating requirements often causes unexpected disruptions of the IWTS. To minimize the number of unplanned closures of locks and dams, it is necessary to develop optimal preventive maintenance strategies based on a collection of desired transportation objectives, performance metrics, and external factors. The present work constructs a simulation environment to mimic the operation of the IWTS of the McClellan-Kerr Arkansas River corridor. Based on this simulation tool, a framework for training and testing a Deep Reinforcement Learning model to find the optimal maintenance strategy is developed with the goal of minimizing the expected total vessel delays in the system.

The McClellan–Kerr Arkansas River Navigation System (MKARNS) is challenged by an aging infrastructure and by limited maintenance budgets, all of which cause transportation delays. In this study, the Maritime Transportation Simulator (MarTranS), which is a hybrid of agent-based modeling, discrete-event simulation, system dynamics, and multiregional input-output analysis, was adopted to model the relationship between the components of the system and economic impact factors. Real-world scenarios were analyzed to explore the economic impacts of various patterns of investment in the MKARNS. These scenarios include a base scenario (in which the system infrastructure remains unchanged and no future investments are made), investment scenarios (e.g., investing in deepening of the navigation channel, port expansion, and lock/dam rehabilitation), and a demand-change scenario focused on the impacts of the Panama Canal expansion. The results reveal that the MKARNS under current circumstances is not sustainable in the long term and that future economic investment is needed if it is to continue operations. In addition, among the different system components, locks/dams are the primary sources of system delays, so these should be targeted for investment and reconstruction to sustain and enhance the beneficial economic impacts of the system.

Container on Barge (COB) facilitates intermodal transportation by transporting shipping containers on barge tows. COB has seen rapid expansion globally over the past 20 years, providing a cost-efficient, environmentally friendly, and congestion-reducing mode of container transportation. European countries have led COB transportation in both study and application over the past two decades. However, increasing interest is observed in both the USA and Asia. In this literature review and comparative analysis, 135 COB-focused peer-reviewed articles are reviewed and analyzed to systematically describe the development and current status of COB transportation research. The relevant literature is analyzed to reveal publication rates and titles, geographical regions of interest, research questions, applied methodologies, advantages of COB transportation, and key success factors. The aim of our effort is to provide information on various aspects of COB development among different regions in the world and to summarize the existing literature to support and guide future COB development.

The United States inland waterway transportation system is comprised of 12,000 miles of navigable waterways that connect and move freight between 38 states and the global supply chain. When investing in inland waterway infrastructure, engineering managers should aim to maximize all benefits associated with the investment, including flood protection, water supply, hydropower generation, recreation, and environmental impact benefits. In this article, we formulate an initial qualitative value model for inland waterway infrastructure investment decisions, based on a value-focused thinking approach that enables engineering managers to holistically evaluate project investment alternatives. For circumstances involving limited resources, a portfolio optimization model is formulated to maximize the total value associated with project investments, while considering budget and minimally acceptable benefit constraints. To demonstrate an application of our approach, we present a case study based on the McClellan Kerr Arkansas River Navigation System.

The inland waterways in the United States (U.S.) transport approximately 20% of coal, 22% of petroleum products, and 60% of farm exports making these waterways a significant contributor to the U.S. multimodal transportation system. In this study, data of extreme natural events affecting the U.S. inland waterways are collected and used to predict possible occurrences of such events using a spatio-temporal statistical model. A simulation tool incorporating this model is developed to investigate the impact of waterway disruptions on the interconnected multimodal transportation systems. A case study on the lower Mississippi River and the McClellan–Kerr Arkansas River Navigation System along with the related highways is provided to illustrate the use of the simulation tool for operation simulation and interdependence modeling of the multimodal transportation network. This tool provides a flexible means for quickly evaluating the performance of such Interdependent Critical Infrastructures (ICIs) and assisting in decision making.

Inland waterways are a cost-effective and environmentally friendly mode of freight transportation. Natural and man-made events can disrupt navigation and may halt barge traffic. Our research provides decision support during inland waterway disruption response to minimize cargo value loss through the development of a decomposition-based sequential heuristic (DBSH). The DBSH integrates the Analytic Hierarchy Process and linear programming to prioritize cargo and allocate barges to terminals. Compared to an existing approach, the DBSH is superior when solving large-scale decision scenarios, achieving reduced cargo value loss while drastically improving computational time.