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The ERDC Library supports the mission-related research needs of ERDC scientists and engineers at three physical locations with a centralized library catalog and web site. It also hosts an online digital repository of ERDC-authored reports.

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Category: Research
  • Quantifying the Effect of Subcritical Water Repellency on Sorptivity: A Physically Based Model

    Abstract: Soil water wettability or water repellency is a phenomenon that can affect infiltration and, ultimately, runoff. Thus, there is a need to develop a model that can quantitatively capture the influence of water repellency on infiltration in a physically meaningful way and within the framework of existing infiltration theory. The analytical model developed in this study relates soil sorptivity (an infiltration parameter) with contact angle (a direct measure of water repellency) for variably saturated media. The model was validated with laboratory experiments using a silica sand of known properties treated to produce controlled degrees of water repellency. The measured contact angle and sorptivity values closely matched the model‐predicted values. Further, the relationship between the frequently used water drop penetration time test (used to assess water repellency) and sorptivity was illustrated. Finally, the direct impact of water repellency on saturated hydraulic conductivity was investigated due to its role in infiltration equations and to shed light on inconsistent field observations. It was found that water repellency had minimal effect on the saturated hydraulic conductivity of structureless sand. A quantitative model for infiltration incorporating the effect of water repellency is particularly important for post‐fire hydrologic modeling of burned areas exhibiting water repellent soils.
  • Increased Rainfall Stimulates Permafrost Thaw Across a Variety of Interior Alaskan Boreal Ecosystems

    Abstract: Earth’s high latitudes are projected to experience warmer and wetter summers in the future but ramifications for soil thermal processes and permafrost thaw are poorly understood. Here we present 2750 end of summer thaw depths representing a range of vegetation characteristics in Interior Alaska measured over a 5-year period. This included the top and third wettest summers in the 91-year record and three summers with precipitation close to mean historical values. Increased rainfall led to deeper thaw across all sites with an increase of 0.7 ± 0.1 cm of thaw per cm of additional rain. Disturbed and wetland sites were the most vulnerable to rain-induced thaw with ~1 cm of surface thaw per additional 1 cm of rain. Permafrost in tussock tundra, mixed forest, and conifer forest was less sensitive to rain-induced thaw. A simple energy budget model yields seasonal thaw values smaller than the linear regression of our measurements but provides a first-order estimate of the role of rain-driven sensible heat fluxes in high-latitude terrestrial permafrost. This study demonstrates substantial permafrost thaw from the projected increasing summer precipitation across most of the Arctic region.
  • Mercury Isotopes Reveal Atmospheric Gaseous Mercury Deposition Directly to the Arctic Coastal Snowpack

    Abstract: Springtime atmospheric mercury depletion events (AMDEs) lead to snow with elevated mercury concentrations (>200 ng Hg/L) in the Arctic and Antarctic. During AMDEs gaseous elemental mercury (GEM) is photochemically oxidized by halogens to reactive gaseous mercury which is deposited to the snowpack. This reactive mercury is either photochemically reduced back to GEM and re-emitted to the atmosphere or remains in the snowpack until spring snowmelt. GEM is also deposited to the snowpack and tundra vegetation by reactive surface uptake (dry deposition) from the atmosphere. There is little consensus on the proportion of AMDE-sourced Hg versus Hg from dry deposition that is released in spring runoff. We used mercury stable isotope measurements of GEM, snowfall, snowpack, snowmelt, surface water, vegetation, and peat from a northern Alaska coastal watershed to quantify Hg sources. Although high Hg concentrations are deposited to the snowpack during AMDEs, we estimate that ∼76 to 91% is released back to the atmosphere prior to snowmelt. Mercury deposited to the snowpack as GEM comprises the majority of snowmelt Hg and has a Hg stable isotope composition similar to Hg deposited by reactive surface uptake of GEM into the leaves of trees in temperate forests. This GEM-sourced Hg is the dominant Hg we measured in the spring snowpack and in tundra peat permafrost deposits.
  • Rough River Outlet Works Physical Model Study

    Abstract: The US Army Corps of Engineers, Louisville District, requested the support and assistance of the US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory (CHL), in the evaluation of the hydraulic performance of the replacement Outlet Works for Rough River Dam. To support the design effort, CHL constructed a 1:25.85 scale physical model. The proposed features of the model in the domain are the curved approach channel, intake structure, transition, curved conduit, stilling basin, concrete apron, and retreat channel. Tests performed to evaluate the hydraulic performance illuminated a few design concerns. To address these issues, several key design changes were made. These included the retreat channel slope, end sill design, and transition design.
  • Complex Network Analysis for Early Detection of Failure Mechanisms in Resilient Bio-structures

    Abstract: Bio-structures owe their remarkable mechanical properties to their hierarchical geometrical arrangement as well as heterogeneous material properties. This dissertation presents an integrated, interdisciplinary approach that employs computational mechanics combined with flow network analysis to gain fundamental insights into the failure mechanisms of high performance, light-weight, structured composites by examining the stress flow patterns formed in the nascent stages of loading for the rostrum of the paddlefish. The data required for the flow network analysis was generated from the finite element analysis of the rostrum. The flow network was weighted based on the parameter of interest, which is stress in the current study. The changing kinematics of the structural system was provided as input to the algorithm that computes the minimum-cut of the flow network. The proposed approach was verified using two classical problems three- and four-point bending of a simply-supported concrete beam. The current study also addresses the methodology used to prepare data in an appropriate format for a seamless transition from finite element binary database files to the abstract mathematical domain needed for the network flow analysis. A robust, platform-independent procedure was developed that efficiently handles the large datasets produced by the finite element simulations. Results from computational mechanics using Abaqus and complex network analysis are presented.
  • Rotor Blade Design Framework for Airfoil Shape Optimization with Performance Considerations

    Abstract: A framework for optimizing rotor blade airfoil shape is presented. The framework uses two digital workflows created within the Galaxy Simulation Builder (GSB) software package. The first is a workflow enabling the automated creation of a surrogate model for predicting airfoil performance coefficients. An accurate surrogate model for the rapid generation of airfoil coefficient tables has been developed using linear interpolation techniques that is based on C81Gen and ARC2D CFD codes. The second workflow defines the rotor blade optimization problem using GSB and the Dakota numerical optimization library. The presented example uses a quasi-Newton optimization algorithm to optimize the tip region of the UH-60A main rotor blade with respect to vehicle performance. This is accomplished by morphing the blade tip airfoil shape for optimum power, subject to a constraint on the maximum pitch link load.
  • A Physics-Informed Neural Network for Sound Propagation in the Atmospheric Boundary Layer

    Abstract: We describe what we believe is the first effort to develop a physics-informed neural network (PINN) to predict sound propagation through the atmospheric boundary layer. PINN is a recent innovation in the application of deep learning to simulate physics. The motivation is to combine the strengths of data-driven models and physics models, thereby producing a regularized surrogate model using less data than a purely data-driven model. In a PINN, the data-driven loss function is augmented with penalty terms for deviations from the underlying physics, e.g., a governing equation or a boundary condition. Training data are obtained from Crank-Nicholson solutions of the parabolic equation with homogeneous ground impedance and Monin-Obukhov similarity theory for the effective sound speed in the moving atmosphere. Training data are random samples from an ensemble of solutions for combinations of parameters governing the impedance and the effective sound speed. PINN output is processed to produce realizations of transmission loss that look much like the Crank-Nicholson solutions. We describe the framework for implementing PINN for outdoor sound, and we outline practical matters related to network architecture, the size of the training set, the physics-informed loss function, and challenge of managing the spatial complexity of the complex pressure.
  • Helicopter Rotor Blade Multiple-Section Optimization with Performance Considerations

    Abstract: This paper presents advancements in a surrogate-based, rotor blade design optimization framework for improved helicopter performance. The framework builds on previous successes by allowing multiple airfoil sections to designed simultaneously to minimize required rotor power in multiple flight conditions. Rotor power in hover and forward flight, at advance ratio 𝜇 = 0.3, are used as objective functions in a multi-objective genetic algorithm. The framework is constructed using Galaxy Simulation Builder with optimization provided through integration with Dakota. Three independent airfoil sections are morphed using ParFoil and aerodynamic coefficients for the updated airfoil shapes (i.e., lift, drag, moment) are calculated using linear interpolation from a database generated using C81Gen/ARC2D. Final rotor performance is then calculated using RCAS. Several demonstrative optimization case studies were conducted using the UH-60A main rotor. The degrees of freedom for this case are limited to the airfoil camber, camber crest position, thickness, and thickness crest position for each of the sections. The results of the three-segment case study show improvements in rotor power of 4.3% and 0.8% in forward flight and hover, respectively. This configuration also yields greater reductions in rotor power for high advance ratios, e.g., 6.0% reduction at 𝜇 = 0.35, and 8.8% reduction at 𝜇 = 0.4.
  • Historic Landscape Management Plan for the Fort Huachuca Historic District National Historic Landmark and Supplemental Areas

    Abstract: The U.S. Congress codified the National Historic Preservation Act of 1966 (NHPA) to provide guidelines and requirements for preserving tangible elements of our nation’s past. This preservation was done primarily through creation of the National Register of Historic Places (NRHP), which contains requirements for federal agencies to address, inventory, and evaluate their cultural resources, and to determine the effect of federal undertakings on properties deemed eligible or potentially eligible for the NRHP. This work inventoried and evaluated the historic landscapes within the National Landmark District at Fort Huachuca, Arizona. A historic landscape context was developed; an inventory of all landscapes and landscape features within the historic district was completed; and these landscapes and features were evaluated using methods established in the Guidelines for Identifying and Evaluating Historic Military Landscapes (ERDC-CERL 2008) and their significance and integrity were determined. Photographic and historic documentation was completed for significant landscapes. Lastly, general management recommendations were provided to help preserve and/or protect these resources in the future.
  • Meteorological Property and Temporal Variable Effect on Spatial Semivariance of Infrared Thermography of Soil Surfaces for Detection of Foreign Objects

    Abstract: The environmental phenomenological properties responsible for the thermal variability evident in the use of thermal infrared (IR) sensor systems is not well understood. The research objective of this work is to understand the environmental and climatological properties contributing to the temporal and spatial thermal variance of soils. We recorded thermal images of surface temperature of soil as well as several meteorological properties such as weather condition and solar irradiance of loamy soil located at the Cold Regions Research and Engineering Lab (CRREL) facility. We assessed sensor performance by analyzing how recorded meteorological properties affected the spatial structure by observing statistical differences in spatial autocorrelation and dependence parameter estimates.