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Category: Publications: Cold Regions Research and Engineering Laboratory (CRREL)
  • Additive Regulated Concrete for Thermally Extreme Conditions

    Abstract: This study details a multiprong effort to validate the Cold Regions Research and Engineering Laboratory’s solution for concrete construction and repair in cold weather, Additive Regulated Concrete for Thermally Extreme Conditions (ARCTEC). ARCTEC is the product of several years of research and consists of a testing and simulation workflow which generates scenario-sensitive guidance for use of accelerating admixtures in concrete. This report details efforts to validate ARCTEC using real-world, full-scale, field demonstrations. These demonstrations were used to collect data on the behavior of concrete obtained through conventional supply chains, to assess the accuracy of the simulation component of the workflow, and test efficacy of ARCTEC guidance in achieving frost protection. Results indicate that ARCTEC is at a high level of maturity, and provides additive dosage guidance that ensures frost protection and strength development in concrete placed where overnight lows fall as low as 0°F. The effort and cost required to implement ARCTEC as a cold weather protection strategy is minimal, and significantly less burdensome than conventional methods. Any cold region installation with a winter construction or repair needs and access to conventional concrete supply chains could field ARCTEC, and reduce the cost and schedule constraints associated with winter construction.
  • Beyond Glacier-Wide Mass Balances: Parsing Seasonal Elevation Change into Spatially Resolved Patterns of Accumulation and Ablation at Wolverine Glacier, Alaska

    Abstract: We present spatially distributed seasonal and annual surface mass balances of Wolverine Glacier, Alaska, from 2016 to 2020. Our approach accounts for the effects of ice emergence and firn compaction on surface elevation changes to resolve the spatial patterns in mass balance at 10 m scale. We present and compare three methods for estimating emergence velocities. Firn compaction was constrained by optimizing a firn model to fit three firn cores. Distributed mass balances showed good agreement with mass-balance stakes (RMSE = 0.67 m w.e., r = 0.99, n = 41) and ground-penetrating radar surveys (RMSE = 0.36 m w.e., r = 0.85, n = 9024). Fundamental differences in the distributions of seasonal balances highlight the importance of disparate physical processes, with anomalously high ablation rates observed in icefalls. Winter balances were found to be positively skewed when controlling for elevation, while summer and annual balances were negatively skewed. We show that only a small percent of the glacier surface represents ideal locations for mass-balance stake placement. Importantly, no suitable areas are found near the terminus or in elevation bands dominated by icefalls. These findings offer explanations for the often-needed geodetic calibrations of glaciological time series.
  • Snow-Impacted National Inventory of Dams by GAGESII Watershed

    Abstract: This Engineering Research and Development Center (ERDC) Technical Note describes the development of a set of locations within the contiguous United States (CONUS) where snowmelt is a component of the annual streamflow. The locations are selected from the US Geological Survey (USGS) Geospatial Attributes of Gages for Evaluating Streamflow II (GAGESII) and National Inventory of Dams (NID) data sets. The 30-year normal snow regimes were used to identify all GAGESII watersheds that have any of the basin delineated as transitional (rain/snow), snow dominated, or perennial snow zones. NID dams that are within snow affected GAGESII watersheds are included in the data set. The purpose of this ERDC Technical Note is to describe the development of a comprehensive data set of CONUS GAGESII and dam infrastructure affected by snow changing regimes.
  • Application of Multi-fidelity Methods to Rotorcraft Performance Assessment

    Abstract: We present a Python-based multi-fidelity tool to estimate rotorcraft performance metrics. We use Gaussian-Process regression (GPR) methods to adaptively build a surrogate model using a small number of high-fidelity CFD points to improve estimates of performance metrics from a medium-fidelity comprehensive analysis model. To include GPR methods in our framework, we used the EmuKit Python package. Our framework adaptively chooses new high-fidelity points to run in regions where the model variance is high. These high-fidelity points are used to update the GPR model; convergence is reached when model variance is below a pre-determined level. To efficiently use our framework on large computer clusters, we implemented this in Galaxy Simulation Builder, an analysis tool that is designed to work on large parallel computing environments. The program is modular, and is designed to be agnostic to the number and names of dependent variables and to the number and identifying labels of the fidelity levels. We demonstrate our multi-fidelity modeling framework on a rotorcraft collective sweep (hover) simulation and compare the accuracy and time savings of the GPR model to that of a simulation run with CFD only.
  • Spherical Shock Waveform Reconstruction by Heterodyne Interferometry

    Abstract: The indirect measurement of shock waveforms by acousto-optic sensing requires a method to reconstruct the field from the projected data. Under the assumption of spherical symmetry, one approach is to reconstruct the field by the Abel inversion integral transform. When the acousto-optic sensing modality measures the change in optical phase difference time derivative, as for a heterodyne Mach–Zehnder interferometer, e.g., a laser Doppler vibrometer, the reconstructed field is the fluctuating refractive index time derivative. A technique is derived that reconstructs the fluctuating index directly by assuming plane wave propagation local to a probe beam. With synthetic data, this approach is compared to the Abel inversion integral transform and then applied to experimental data of laser-induced shockwaves. Time waveforms are reconstructed with greater accuracy except for the tail of the waveform that maps spatially to positions near a virtual origin. Furthermore, direct reconstruction of the fluctuating index field eliminates the required time integration and results in more accurate shock waveform peak values, rise times, and positive phase duration.
  • Data-Driven Modeling of Groundwater Level Using Machine Learning

    Purpose: This US Army Engineer Research and Development Center (ERDC), Coastal and Hydraulics Laboratory engineering technical note (CHETN) documents a preliminary study on the use of specialized machine learning (ML) methods to model the variations in groundwater level (GWL) with time. This approach uses historical groundwater observation data at seven gage locations in Wyoming, USA, available from the USGS database and historical data on several relevant meteorological variables obtained from the ERA5 reanalysis dataset produced by the Copernicus Climate Change Service (usually referred to as C3S) at the European Center for Medium-Range Weather Forecasts to predict future GWL values for a desired period of time. The results presented in this report indicate that the ML method has the potential to predict both short-term (4-hourly) as well as daily variations in GWL several days into the future for the chosen study region, thus alleviating the need for employing sophisticated process-based numerical models with complicated model structure configurations.
  • Experimental and Numerical Analyses of Soil Electrical Resistivity under Subfreezing Conditions

    Abstract: The engineering behavior of frozen soils is critical to the serviceability of civil infrastructure in cold regions. Among various geophysical techniques, electrical resistivity imaging is a promising technique that is cost effective and provides spatially continuous subsurface information. In this study, under freeze–thaw conditions, we carry out lab–scale 1D electrical resistivity measurements on frost–susceptible soils with varying water content and bulk density properties. We use a portable electrical resistivity meter for temporal electrical resistivity measurements and thermocouples for temperature monitoring. Dynamic temperature-dependent soil properties, most notably unfrozen water content, exert significant influences on the observed electrical resistivity. Below 0 ◦C, soil resistivity increases with the decreasing temperature. We also observe a hysteresis effect on the evolution of electrical resistivity during the freeze–thaw cycle, which effect we characterize with a sigmoidal model. At the same temperature, electrical resistivity during freezing is consistently lower than that during thawing. We have implemented this sigmoidal model into a COMSOL finite element model at both laboratory and field scales which enables the simulation of soil electrical resistivity response under both short–term and long–term sub–freezing conditions. Atmospheric temperature variations induce soil temperature change, and thereby phase transition and electrical resistivity change, with the rate of change being a function of the depth of investigation and soil properties include initial water content and initial temperature. This study advances the fundamental understanding of the electrical behaviors of frozen soils and enhance the application of electrical geophysical investigations in cold regions.
  • Application of Limited-Field-Data Methods in Reservoir Volume Estimation: A Case Study

    Abstract: The conventional approach to estimating lake or reservoir water volumes hinges on field data collection; however, volume estimation methods are available that use little or no field data. Two such methods—the simplified V-A-h (volume-area-height) and the power function—were applied to a set of six anthropogenic reservoirs on the Fort Jackson, South Carolina, installation and checked against a validation data set. Additionally, seven interpolation methods were compared for differences in total volume estimation based on sonar data collected at each reservoir. The simplified V-A-h method overestimated reservoir volume more than each technique in the power function method, and the categorical technique underestimated the most reservoir volumes of all three techniques. Each method demonstrates high Vₑᵣᵣ variability among reservoirs, and Vₑᵣᵣ for the Power Function techniques applied here is consistent with that found in previous research in that it is near or less than 30%. Compared with Vₑᵣᵣ in other studies evaluating the simplified V-A-h method, Vₑᵣᵣ in this study was found to be 10%–20% higher.
  • Ecological Modeling of Microbial Community Composition under Variable Temperatures

    Abstract: Soil microorganisms interact with one another within soil pores and respond to external conditions such as temperature. Data on microbial community composition and potential function are commonly generated in studies of soils. However, these data do not provide direct insight into the drivers of community composition and can be difficult to interpret outside the context of ecological theory. In this study, we explore the effect of abiotic environmental variation on microbial species diversity. Using a modified version of the Lotka-Volterra Competition Model with temperature-dependent growth rates, we show that environmentally relevant temperature variability may expand the set of temperature-tolerance phenotype pairs that can coexist as two-species communities compared to constant temperatures. These results highlight a potential role of temperature variation in influencing microbial diversity. This in turn suggests a need to incorporate temperature into predictive models of microbial communities in soil and other environments. We recommend future work to parameterize the model applied in this study with empirical data from environments of interest, and to validate the model predictions using field observations and experimental manipulations.
  • Extreme Cold Weather Airfield Damage Repair Testing at Goose Bay Air Base, Canada

    Abstract: Rapid Airfield Damage Recovery (RADR) technologies have proven successful in temperate and subfreezing temperatures but have not been evaluated in extreme cold weather temperatures near 0°F. To address this capability gap, laboratory-scale and full-scale testing was conducted at these temperatures. Methods developed for moderate climates were adapted and demonstrated alongside methods that used snow harvested on-site as compacted backfill. After only a few days of training, seven experimental repairs were conducted by Canadian airmen at Goose Bay Air Base in Labrador, Canada, and load tested with a single-wheel C-17 load cart. Existing RADR technologies performed adequately despite the freezing temperatures, with the main tactic, techniques, and procedures modification being an increased cure time for the rapid-setting concrete surface material. Compacted snow-water slurry methods also performed well, demonstrating their ability to withstand over 500 passes of single-wheel C-17 traffic after sufficient freezing time.