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  • Standardized NEON Organismal Data for Biodiversity Research

    Abstract: Understanding patterns and drivers of species distribution and abundance, and thus biodiversity, is a core goal of ecology. Despite advances in recent decades, research into these patterns and processes is limited by a lack of standardized, high-quality, empirical data spanning large spatial scales and long time periods. The NEON fills this gap by providing freely available observational data generated during robust and consistent organismal sampling of several sentinel taxonomic groups within 81 sites distributed across the US and will be collected for at least 30 years. The breadth and scope of these data provide a unique resource for advancing biodiversity research. To maximize the potential of this opportunity, however, it is critical that NEON data be accessible and easily integrated into investigators’ workflows and analyses. To facilitate its use for biodiversity research and synthesis, we created a workflow to process and format NEON organismal data into the ecocomDP (ecological community data design pattern) format available through the ecocomDP R package; provided the standardized data as an R data package (neonDivData). We briefly summarize sampling designs and data wrangling decisions for the major taxonomic groups included. Our workflows are open-source so the biodiversity community may: add additional taxonomic groups; modify the workflow to produce datasets appropriate for their own analytical needs; and regularly update the data packages as more observations become available. Finally, we provide two simple examples of how the standardized data may be used for biodiversity research. By providing a standardized data package, we hope to enhance the utility of NEON organismal data in advancing biodiversity research and encourage the use of the harmonized ecocomDP data design pattern for community ecology data from other ecological observatory networks.
  • Neural Ordinary Differential Equations for Rotorcraft Aerodynamics

    Abstract: High-fidelity computational simulations of aerodynamics and structural dynamics on rotorcraft are essential for helicopter design, testing, and evaluation. These simulations usually entail a high computational cost even with modern high-performance computing resources. Reduced order models can significantly reduce the computational cost of simulating rotor revolutions. However, reduced order models are less accurate than traditional numerical modeling approaches, making them unsuitable for research and design purposes. This study explores the use of a new modified Neural Ordinary Differential Equation (NODE) approach as a machine learning alternative to reduced order models in rotorcraft applications—specifically to predict the pitching moment on a rotor blade section from an initial condition, mach number, chord velocity and normal velocity. The results indicate that NODEs cannot outperform traditional reduced order models, but in some cases they can outperform simple multilayer perceptron networks. Additionally, the mathematical structure provided by NODEs seems to favor time-dependent predictions. We demonstrate how this mathematical structure can be easily modified to tackle more complex problems. The work presented in this report is intended to establish an initial evaluation of the usability of the modified NODE approach for time-dependent modeling of complex dynamics over seen and unseen domains.
  • Enabling Understanding of Artificial Intelligence (AI) Agent Wargaming Decisions through Visualizations

    Abstract: The process to develop options for military planning course of action (COA) development and analysis relies on human subject matter expertise. Analyzing COAs requires examining several factors and understanding complex interactions and dependencies associated with actions, reactions, proposed counteractions, and multiple reasonable outcomes. In Fiscal Year 2021, the Institute for Systems Engineering Research team completed efforts resulting in a wargaming maritime framework capable of training an artificial intelligence (AI) agent with deep reinforcement learning (DRL) techniques within a maritime scenario where the AI agent credibly competes against blue agents in gameplay. However, a limitation of using DRL for agent training relates to the transparency of how the AI agent makes decisions. If leaders were to rely on AI agents for COA development or analysis, they would want to understand those decisions. In or-der to support increased understanding, researchers engaged with stakeholders to determine visualization requirements and developed initial prototypes for stakeholder feedback in order to support increased understanding of AI-generated decisions and recommendations. This report describes the prototype visualizations developed to support the use case of a mission planner and an AI agent trainer. The prototypes include training results charts, heat map visualizations of agent paths, weight matrix visualizations, and ablation testing graphs.
  • Financing Natural Infrastructure: The Elizabeth River Project, Chesapeake Bay, VA

    Purpose: Knowledge gaps surrounding natural infrastructure (NI) life cycles and performance thwart widespread implementation of NI in civil works projects. In particular, information about funding or financing the scoping, design, construction, monitoring, and adaptive management of NI projects constitutes a key need as there is no standard process for securing funds. This technical note is part of a series documenting successful examples of funding NI projects and sharing lessons learned about a variety of funding and financing methods to increase the implementation of NI projects. The research effort is a collaboration between the Engineering With Nature® (EWN®) and Systems Approach to Geomorphic Engineering (SAGE) programs of the US Army Corps of Engineers (USACE). This technical note explores how the Elizabeth River Project (ERP), a nonprofit organization based in Norfolk, Virginia, developed a homeowner cost-sharing program to fund NI projects—living shorelines, rain gardens, and riparian buffers—within an urban watershed.
  • The Use of Rhodamine Water Tracer (RWT) Dye to Improve Submersed Herbicide Applications

    Abstract: The inert fluorescent dye rhodamine water tracer (RWT) has been widely used in freshwater aquatic systems for many years to quantify bulk water exchange patterns and as a tracer for submersed herbicide movement. The dye is well-suited for tracer work due to its high solubility and detectability in water (<0.01 μg/L). Federal guidelines limit the aqueous concentration 0f RWT to <10 μg/L at drinking water intakes. The dye has proven to be harmless to aquatic organisms and humans in low concentrations and is relatively inexpensive. Since 1991, RWT has been used by Engineer Re-search and Development Center (ERDC) researchers to simulate aqueous herbicide applications in large, hydrodynamic systems in over 12 states. Such simulations have improved the effectiveness of herbicide treatments by linking in situ water exchange processes with appropriate herbicide selection and application rates. Understanding these parameters can be critical for mitigating herbicide exposure in environmentally sensitive settings and around potable water and irrigation intakes. A data-based estimate of water exchange patterns usually results in successful submersed herbicide applications—both with target-plant efficacy and limited injury to nontarget vegetation. Using RWT dye to simulate submersed herbicide applications is an important predictive and real-time tool in both experimental and operational settings.
  • Development and Testing of the Sediment Distribution Pipe (SDP): A Pragmatic Tool for Wetland Nourishment

    Abstract: Standard dredging operations during thin layer placement (TLP) projects are labor intensive as crews are necessary to periodically move the outfall location, which can have lasting adverse effects on the marsh surface. In an effort to increase efficiency during TLP, a novel Sediment Distribution Pipe (SDP) system was investigated. This system offers multiple discharge points along the pipeline to increase the sediment distribution while reducing pipeline movements. An SDP Modeling Application (SDPMA) was developed to assist in the design of SDP field applications by quickly assessing the pressure and velocity inside the discharge pipe and approximating the slurry throw distances. An SDP field proof of concept was performed during a two-phase TLP on Sturgeon Island, New Jersey, in 2020. The SDPMA was shown to be an accurate method of predicting performance of the SDP. The SDP was successful at distributing dredge material across the placement site; however, further research is warranted to better quantify performance metrics.
  • Uncrewed Survey-Vessel Conversion

    Purpose: The purpose of this study was to investigate the uses of an uncrewed survey vessel to maintain mission readiness of all federal navigation channels and ports. Developing an uncrewed survey vessel capable of collecting data in a riverine environment may increase the efficiency and resiliency of the US Army Corps of Engineers (USACE) missions and USACE districts to conduct surveys during post natural disasters and pandemics. This document describes the installation, enhancement, and modification of the commercial-off-the-shelf (COTS) system, the Sea Machines SM300, on a US Army Engineer Research and Development Center (ERDC) survey vessel to create a semiautonomous survey capability.
  • Embracing Biodiversity on Engineered Coastal Infrastructure through Structured Decision-Making and Engineering With Nature

    Abstract: Extreme weather variation, natural disasters, and anthropogenic actions negatively impact coastal communities through flooding and erosion. To safeguard coastal settlements, shorelines are frequently reinforced with seawalls and bulkheads. Hardened shorelines, however, result in biodiversity loss and environmental deterioration. The creation of sustainable solutions that engineer with nature is required to lessen natural and anthropogenic pressures. Nature-based solutions (NbS) are a means to enhance biodiversity and improve the environment while meeting engineering goals. To address this urgent need, the US Army Corps of Engineers (USACE) Engineering With Nature® (EWN) program balances economic, environmental, and social benefits through collaboration. This report presents how design and engineering practice can be enhanced through organized decision-making and landscape architectural renderings that integrate engineering, science, and NbS to increase biodiversity in coastal marine habitats. When developing new infrastructure or updating or repairing existing infrastructure, such integration can be greatly beneficial. Further, drawings and renderings exhibiting EWN concepts can assist in decision-making by aiding in the communication of NbS designs. Our practical experiences with the application of EWN have shown that involving landscape architects can play a critical role in effective collaboration and result in solutions that safeguard coastal communities while maintaining or enhancing biodiversity.
  • Coastal Modeling System User’s Manual

    Abstract: The Coastal Modeling System (CMS) is a suite of coupled 2D numerical models for simulating nearshore waves, currents, water levels, sediment transport, morphology change, and salinity and temperature. Developed by the Coastal Inlets Research Program of the US Army Corps of Engineers, the CMS provides coastal engineers and scientists a PC-based, easy-to-use, accurate, and efficient tool for understanding of coastal processes and for designing and managing of coastal inlets research, navigation projects, and sediment exchange between inlets and adjacent beaches. The present technical report acts as a user guide for the CMS, which contains comprehensive information on model theory, model setup, and model features. The detailed descriptions include creation of a new project, configuration of model grid, various types of boundary conditions, representation of coastal structures, numerical methods, and coupled simulations of waves, hydrodynamics, and sediment transport. Pre- and postmodel data processing and CMS modeling procedures are also described through operation within a graphic user interface—the Surface Water Modeling System.
  • Use of Sediment Tracers to Evaluate Sediment Plume at Beaufort Inlet and Adjacent Beaches, North Carolina

    Abstract: This report documents a numerical modeling investigation on the transport of sediment material placed on designated disposal sites adjacent to Beaufort Inlet, North Carolina. Historical and newly collected wave and hydrodynamic data around the inlet are assembled and analyzed. The data sets are used to calibrate and validate a coastal wave, hydrodynamic and sediment transport model, the Coastal Modeling System. Model alternatives are developed corresponding to different material placement sites. Sediment transport and sediment plume distribution are evaluated within and around the immediate vicinity of the Beaufort Inlet estuarine system for a representative summer and winter month. Results of model simulations show that high flows occur along navigation channels and low flows occur outside the inlet in open ocean area. Sand materials placed in nearshore sites tend to be trapped in and move along navigation channels entering the inlet. In offshore placement sites the sediment plume shows slow spreading and no significant sand migration from its release locations. Simulations for the summer and winter month present similar distribution patterns of sediments originating from placement sites.