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  • Imagery Classification for Autonomous Ground Vehicle Mobility in Cold Weather Environments

    Abstract: Autonomous ground vehicle (AGV) research for military applications is important for developing ways to remove soldiers from harm’s way. Current AGV research tends toward operations in warm climates and this leaves the vehicle at risk of failing in cold climates. To ensure AGVs can fulfill a military vehicle’s role of being able to operate on- or off-road in all conditions, consideration needs to be given to terrain of all types to inform the on-board machine learning algorithms. This research aims to correlate real-time vehicle performance data with snow and ice surfaces derived from multispectral imagery with the goal of aiding in the development of a truly all-terrain AGV. Using the image data that correlated most closely to vehicle performance the images were classified into terrain units of most interest to mobility. The best image classification results were obtained when using Short Wave InfraRed (SWIR) band values and a supervised classification scheme, resulting in over 95% accuracy.
  • Methodology for the Analysis of Geospatial and Vehicle Datasets in the R Language

    Abstract: The challenge of autonomous off-road operations necessitates a robust understanding of the relationships between remotely sensed terrain data and vehicle performance. The implementation of statistical analyses on large geospatial datasets often requires the transition between multiple software packages that may not be open-source. The lack of a single, modular, and open-source analysis environment can reduce the speed and reliability of an analysis due to an increased number of processing steps. Here we present the capabilities of a workflow, developed in R, to perform a series of spatial and statistical analyses on vehicle and terrain datasets to quantify the relationship between sensor data and vehicle performance in winter conditions. We implemented the R-based workflow on datasets from a large, coordinated field campaign aimed at quantifying the response of military vehicles on snow-covered terrains. This script greatly reduces processing times of these datasets by combining the GIS, data-assimilation and statistical analyses steps into one efficient and modular interface.
  • Artificial Ground Freezing Using Solar-Powered Thermosyphons

    Abstract: Thermosyphons are an artificial ground-freezing technique that has been used to stabilize permafrost since the 1960s. The largest engineered structure that uses thermosyphons to maintain frozen ground is the Trans Alaska Pipeline, and it has over 124,000 thermosyphons along its approximately 1300 km route. In passive mode, thermosyphons extract heat from the soil and transfer it to the environment when the air temperature is colder than the ground temperature. This passive technology can promote ground cooling during cold winter months. To address the growing need for maintaining frozen ground as air temperatures increase, we investigated a solar-powered refrigeration unit that could operate a thermosyphon (nonpassive) during temperatures above freezing. Our tests showed that energy generated from the solar array can operate the refrigeration unit and activate the hybrid thermosyphon to artificially cool the soil when air temperatures are above freezing. This technology can be used to expand the application of thermosyphon technology to freeze ground or maintain permafrost, particularly in locations with limited access to line power.
  • Sabine Pass to Galveston Bay, TX Pre-Construction, Engineering and Design (PED): Coastal Storm Surge and Wave Hazard Assessment: Report 4 – Freeport

    Abstract: The US Army Corps of Engineers, Galveston District, is executing the Sabine Pass to Galveston Bay Coastal Storm Risk Management (CSRM) project for Brazoria, Jefferson, and Orange Counties regions. The project is currently in the Pre-construction, Engineering, and Design phase. This report documents coastal storm water level (SWL) and wave hazards for the Freeport CSRM structures. Coastal SWL and wave loading and overtopping are quantified using high-fidelity hydrodynamic modeling and stochastic simulations. The CSTORM coupled water level and wave modeling system simulated 195 synthetic tropical storms on three relative sea level change scenarios for with- and without-project meshes. Annual exceedance probability (AEP) mean values were reported for the range of 0.2 to 0.001 for peak SWL and wave height (Hm0) along with associated confidence limits. Wave period and mean wave direction associated with Hm0 were also computed. A response-based stochastic simulation approach is applied to compute AEP values for overtopping for levees and overtopping, nappe geometry and combined hydrostatic and hydrodynamic fluid pressures for floodwalls. CSRM crest design elevations are defined based on overtopping rates corresponding to incipient damage. Survivability and resilience are evaluated. A system-wide hazard level assessment was conducted to establish final recommended system-wide elevations.
  • Demonstration of Subsurface Passive Acoustic Monitoring (SPAM) to Survey for and Estimate Populations of Imperiled Underwater-calling Frogs

    Abstract: The management and recovery of threatened and endangered amphibians on Department of Defense (DoD) lands relies on an understanding of their distribution and abundance. Fortunately, most anuran species can be surveyed acoustically using vocalizations during the breeding season. This work demonstrated the use of subsurface passive acoustic monitoring (SPAM) to survey for rare underwater-calling, at-risk anuran species on DoD installations. We evaluated the performance of SPAM relative to traditional passive acoustic monitoring (PAM) (microphone) and human manual calling survey (MCS) methods. Results showed that SPAM outperformed PAM and MCS in validation experiments where calls were generated underwater; SPAM was less successful than PAM and MCS in the field demonstration. Most leopard frog calls were apparently produced in air despite previous reports of extensive underwater-calling behavior. This project highlights how acoustic information can help address a data gap in the ecology of at-risk species, which can help refine future survey methodology and management efforts. Ultimately, the utility of SPAM for underwater-calling species will depend on the focal species, the landscape where it occurs, and technological considerations available to the surveyor. SPAM is more expensive than traditional methods but, in some situations, may be the only way to effectively detect species.
  • ROS Integrated Object Detection for SLAM in Unknown, Low-Visibility Environments

    Abstract: Integrating thermal (or infrared) imagery on a robotics platform allows Unmanned Ground Vehicles (UGV) to function in low-visibility environments, such as pure darkness or low-density smoke. To maximize the effectiveness of this approach we discuss the modifications required to integrate our low-visibility object detection model on a Robot Operating System (ROS). Furthermore, we introduce a method for reporting detected objects while performing Simultaneous Localization and Mapping (SLAM) by generating bounding boxes and their respective transforms in visually challenging environments.
  • Joint Chilean and US Mobility Testing in Extreme Environments

    Abstract: Vehicle mobility in cold and challenging terrains is of interest to both the US and Chilean Armies. Mobility in winter conditions is highly vehicle dependent with autonomous vehicles experiencing additional challenges over manned vehicles. They lack the ability to make informed decisions based on what they are “seeing” and instead need to rely on input from sensors on the vehicle, or from Unmanned Aerial Systems (UAS) or satellite data collections. This work focuses on onboard vehicle Controller Area Network (CAN) Bus sensors, driver input sensors, and some externally mounted sensors to assist with terrain identification and overall vehicle mobility. Analysis of winter vehicle/sensor data collected in collaboration with the Chilean Army in Lonquimay, Chile during July and August 2019 will be discussed in this report.
  • Houston Ship Channel Expansion Improvement Project – Navigation Channel Improvement Study: Ship Simulation Results

    Abstract: In 2020, the US Army Engineer Research and Development Center (ERDC), Coastal and Hydraulics Laboratory, provided technical oversight during a navigation study to assist the Galveston District evaluation of different channel widening alternatives for larger ships transiting the Houston Ship Channel (HSC), Texas. The widening proposals encompassed several areas of the HSC including the Bay Section, the Bayport Ship Channel, Barbours Cut Channel, and the Bayou Section. The study was performed at the San Jacinto College Maritime Technology and Training Center (SJCMTTC) Ship/Tug Simulator (STS) Facility in La Porte, TX. The SJCMTTC STS is a real-time simulator; therefore, events on the simulator happen at the same time rate as real life. A variety of environmental forces act upon the ship during the simulation transit. These include currents, wind, waves, bathymetry, and ship-to-ship interaction. Online simulations of the project were conducted at SJCMTTC over a 3-week period – May through June 2020. Several mariners including Houston Pilots and G&H tugboat Captains participated in the testing and validation exercises. ERDC oversight was performed remotely because of the COVID-19 pandemic. Results in the form of engineering observations, track plots, and pilot interviews were reviewed to develop final conclusions and recommendations regarding the final design.
  • Mobile Harbor, Alabama Navigation Study: Ship Simulation Report

    Abstract: Mobile Bay is a large estuary located in the southwest corner of Alabama, which connects to the Gulf of Mexico. Mobile Harbor contains the only port in the state that supports ocean-going vessels. Some of the larger vessels calling on the port experience transit delays and limited cargo capacity, so a study was conducted by the US Army Corps of Engineers, Mobile District (CESAM), and the Alabama State Port Authority to investigate channel improvements. In 2017, the US Army Engineer Research and Development Center (ERDC) assisted CESAM in screening proposed deepening and widening alternatives in Mobile Bay by completing a Feasibility Level Ship Simulation (FLSS) study using the ERDC Ship/Tow Simulator. These lower-resolution databases from the FLSS study were used as a foundation to complete a more robust navigation study in 2020 to test the proposed modifications to Mobile Harbor. During this study, three main areas were focused on: a bend easing, a passing lane, and a turning basin. Testing of the proposed design was evaluated over the course of 2 weeks with eight pilots. Assessment of the proposed modifications was accomplished through analysis of ship simulations completed by experienced local pilots, discussions, track plots, run sheets, and final pilot surveys.
  • Solid-phase microextraction (SPME) for determination of geosmin and 2-methylisoborneol in volatile emissions from soil disturbance

    Abstract: A method is described here for the concentration and determination of geosmin and 2-methylisoborneol (2-MIB) from the gaseous phase, with translation to field collection and quantification from soil disturbances in situ. The method is based on the use of solid-phase microextraction (SPME) fibers for adsorption of volatile chemicals from the vapor phase, followed by desorption into a gas chromatograph-mass spectrometer (GC-MS) for analysis. The use of a SPME fiber allows simple introduction to the GC-MS without further sample preparation. Several fiber sorbent types were studied and the 50/30 μm DVB/CAR/PDMS was the best performer to maximize the detected peak areas of both analytes combined. Factors such as extraction temperature and time along with desorption temperature and time were explored with respect to analyte recovery. An extraction temperature of 30 ◦C for 10 min, with a desorption temperature of 230 ◦C for 4 min was best for the simultaneous analysis of both geosmin and 2-MIB without complete loss of either one. The developed method was used successfully to measure geosmin and 2-MIB emission from just above disturbed and undisturbed soils, indicating that this method detects both compounds readily from atmospheric samples. Both geosmin and 2-MIB were present as background concentrations in the open air, while disturbed soils emitted much higher concentrations of both compounds. Surprisingly, 2-MIB was always detected at higher concentrations than geosmin, indicating that a focus on its detection may be more useful for soil emission monitoring and more sensitive to low levels of soil disturbance.