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  • Characterizing Snow Surface Properties Using Airborne Hyperspectral Imagery for Autonomous Winter Mobility

    Abstract: With changing conditions in northern climates it is crucial for the United States to have assured mobility in these high-latitude regions. Winter terrain conditions adversely affect vehicle mobility and, as such, they must be accurately characterized to ensure mission success. Previous studies have attempted to remotely characterize snow properties using varied sensors. However, these studies have primarily used satellite-based products that provide coarse spatial and temporal resolution, which is unsuitable for autonomous mobility. Our work employs the use of an Unmanned Aerial Vehicle (UAV) mounted hyperspectral camera in tandem with machine learning frameworks to predict snow surface properties at finer scales. Several machine learning models were trained using hyperspectral imagery in tandem with in-situ snow measurements. The results indicate that random forest and k-nearest neighbors models had the lowest Mean Absolute Error for all surface snow properties. A Pearson correlation matrix showed that density, grain size, and moisture content all had a significant positive correlation to one another. Mechanically, density and grain size had a slightly positive correlation to compressive strength, while moisture had a much weaker negative correlation. This work provides preliminary insight into the efficacy of using hyperspectral imagery for characterizing snow properties for autonomous vehicle mobility.
  • Phenology of Competitive Interactions and Implications for Management of the Invasive Wetland Plant Alternanthera philoxeroides

    Purpose: Phenological differences between invading plants and members of recipient communities may increase the success of invaders because of priority effects. Thus, the application of management when the invader has a phenological advantage (for example, early in the year) can benefit other species by increasing resource availability. This technical note summarizes results from a combination of field observations and a mesocosm experiment to explore whether phenological differences between the invasive wetland plant, alligatorweed (Alternanthera philoxeroides [Mart.] Grseb.), and resident species contribute to alligatorweed success. We documented over two years the early-season growth of alligatorweed and other species at 12 sites in Louisiana, USA. We then conducted a subsequent mesocosm competition experiment between alligatorweed and a common wetland emergent species, spotted lady’s thumb (Persicaria maculosa [L.] Small), over a full year to detect differences in timing of growth and competitive interactions under two fertilizer levels.
  • Environmental Factors Affecting Coastal and Estuarine Submerged Aquatic Vegetation (SAV)

    Abstract: Submerged aquatic vegetation (SAV) growing in estuarine and coastal marine systems provides crucial ecosystem functions ranging from sediment stabilization to habitat and food for specific species. SAV systems, however, are sensitive to a number of environmental factors, both anthropogenic and natural. The most common limiting factors are light limitation, water quality, and salinity, as reported widely across the literature. These factors are controlled by a number of complex processes, however, varying greatly between systems and SAV populations. This report seeks to conduct an exhaustive examination of factors influencing estuarine and coastal marine SAV habitats and find the common threads that tie these ecosystems together. Studies relating SAV habitats in the United States to a variety of factors are reviewed here, including geomorphological and bathymetric characteristics, sediment dynamics, sedimentological characteristics, and water quality, as well as hydrologic regime and weather. Tools and methods used to assess each of these important factors are also reviewed. A better understanding of fundamental environmental factors that control SAV growth will provide crucial information for coastal restoration and engineering project planning in areas populated by SAVs.
  • Technical Guide for the Development, Evaluation, and Modification of Stream Assessment Methods for the Corps Regulatory Program

    ABSTRACT: The U.S. Army Corps Regulatory Program considers the loss (impacts) and gain (compensatory mitigation) of aquatic resource functions as part of Clean Water Act Section 404 permitting and compensatory mitigation decisions. To better inform this regulatory decision-making, the Regulatory Program needs transparent and objective approaches to assess the function and condition of aquatic resources, including streams. Therefore, the Regulatory Program needs function-based stream assessments (1) to characterize a stream’s condition or function, (2) to improve understanding of the impact of a proposed action on an aquatic resource, and/or (3) to inform the development of stream compensatory mitigation tools rooted in stream condition and/or function. A function-based stream assessment can provide regulatory decision makers with the resources to objectively consider alternatives, minimize impacts, assess un-avoidable impacts, determine mitigation requirements, and monitor the success of mitigation projects. A multiagency National Committee on Stream Assessment (NCSA) convened to create these guidelines to inform the development of new methods and evaluation of both national-level and regional methods currently in use. The resulting guidelines present nine phases, including rationale and recommendations to facilitate work efforts. The NCSA hopes that this technical guide promotes transparency, technical defensibility, and consistent application of stream assessments in the Regulatory Program.
  • Acoustic Nondestructive Testing and Measurement of Tension for Steel Reinforcing Members

    Abstract: Many concrete structures contain internal post-tensioned steel structural members that are subject to fracturing and corrosion. The major problem with conventional tension measurement techniques is that they use indirect and non-quantitative methods to determine whether there has been a loss of tension. We have developed an acoustics-based technology and method for making quantitative tension measurements of an embedded, tensioned steel member. The theory and model were verified in the laboratory using a variety of steel rods as test specimens. Field tests of the method were conducted at three Corps of Engineers dams, located in Oklahoma, Georgia, and Illinois. Measurements of the longitudinal and shear velocity were able to be made on rods up to 50 ft long. Not all rods of this length were able to be measured and the quality and consistency of the signal varied. There were fewer problems measuring the longitudinal velocity than shear velocity. While the tension predictions worked in the laboratory tests, the tension could not be accurately calculated for any of the field sites. This is because we were not able to obtain the longitudinal or shear velocities in an unstressed state or precise measurements of the longitudinal and shear velocities due to the lack of knowledge of the precise length of the rods in the tensioned state.
  • Thermal Camera Reliability Study: FLIR Pro One

    Purpose: The purpose of the effort described herein is to verify the reliability of the FLIR One Pro Gen 3 (FLIR One) unit through systematic experiments that compare the temperature perceived by the unit to the temperature measured by contact sensors on different materials through a range of temperatures.
  • Accelerating the Tactical Decision Process with High-Performance Computing (HPC) on the Edge: Motivation, Framework, and Use Cases

    Abstract: Managing the ever-growing volume and velocity of data across the battlefield is a critical problem for warfighters. Solving this problem will require a fundamental change in how battlefield analyses are performed. A new approach to making decisions on the battlefield will eliminate data transport delays by moving the analytical capabilities closer to data sources. Decision cycles depend on the speed at which data can be captured and converted to actionable information for decision making. Real-time situational awareness is achieved by locating computational assets at the tactical edge. Accelerating the tactical decision process leverages capabilities in three technology areas: (1) High-Performance Computing (HPC), (2) Machine Learning (ML), and (3) Internet of Things (IoT). Exploiting these areas can reduce network traffic and shorten the time required to transform data into actionable information. Faster decision cycles may revolutionize battlefield operations. Presented is an overview of an artificial intelligence (AI) system design for near-real-time analytics in a tactical operational environment executing on co-located, mobile HPC hardware. The report contains the following sections, (1) an introduction describing motivation, background, and state of technology, (2) descriptions of tactical decision process leveraging HPC problem definition and use case, and (3) HPC tactical data analytics framework design enabling data to decisions.
  • Alternative Analysis for Construction Progress Data Spatial Visualization

    Abstract: The U.S. Army Corps of Engineers (USACE) construction projects have multiple stakeholders that collaborate with project delivery team members during the execution of these projects. Many of these stakeholders are located across the U.S., which makes virtual interactions a common communication method for these teams. These interactions often lack spatial visualization, which can add complications to the progress reports provided and how the information is received/interpreted. The visualization of project progress and documents would be invaluable to the stakeholders on critical projects constructed by the USACE. This research was conducted to determine alternatives for migrating Resident Management System (RMS) data into a portal web viewer. This report provides proposed solutions to creating these links in efforts to better harmonize data management and improve project presentation.
  • Determination of Residual Low-Order Detonation Particle Characteristics from IMX-104 Mortar Rounds

    ABSTRACT: The environmental fate and transport of energetic compounds on military training ranges are largely controlled by the particle characteristics of low-order detonations. This study demonstrated a method of command detonation, field sampling, laboratory processing, and analysis techniques for characterizing low-order detonation particles from 60 mm and 81 mm mortar rounds containing the insensitive munition formulation IMX-104. Particles deposited from three rounds of each caliber were comprehensively sampled and characterized for particle size, energetic purity, and morphology. The 60 mm rounds were command-detonated low order consistently (seven low-order detonations of seven tested rounds), with consumption efficiencies of 62%–80% (n = 3). The 81 mm rounds detonated low order inconsistently (three low-order detonations of ten tested rounds), possibly because the rounds were sourced from manufacturing test runs. These rounds had lower consumption efficiencies of 39%–64% (n = 3). Particle-size distributions showed significant variability between munition calibers, between rounds of the same caliber, and with distance from the detonation point. The study reviewed command-detonation configurations, particle transfer losses during sampling and particle-size analysis, and variations in the energetic purity of recovered particles. Overall, this study demonstrated the successful characterization of IMX-104 low-order detonation particles from command detonation to analysis.
  • Incorporating Terrain Roughness into Helicopter Landing Zone Site Selection by Using the Geomorphic Oscillation Assessment Tool (GOAT) v1.0

    ABSTRACT: The Geomorphic Oscillation Assessment Tool (GOAT) quantifies terrain roughness as a mechanism to better explain forward arming and refueling point (FARP) suitability for Army aviation. An empirically driven characteristic of FARP consideration, surface roughness is a key discriminator for site utility in complex terrain. GOAT uses a spatial sampling of high-resolution elevation and land cover data to construct data frames, which enable a relational analysis of component and aggregate site suitability. By incorporating multiple criteria from various doctrinal sources, GOAT produces a composite quality assessment of the areal options available to the aviation commander. This report documents and demonstrates version 1.0 of the GOAT algorithms developed by the U.S. Army Engineer Research and Development Center (ERDC). These details will allow users familiar with R to implement it as a stand-alone program or in R Studio.