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Category: Publications: Cold Regions Research and Engineering Laboratory (CRREL)
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  • Active Layer and Permafrost Microbial Community Coalescence Increases Soil Activity and Diversity in Mixed Communities Compared to Permafrost Alone

    Abstract: Permafrost is experiencing rapid degradation due to climate warming. Dispersal of microbial communities from the seasonally-thawed active layer soil into newly thawed permafrost may influence community assembly and increase carbon release from soils. We conducted a laboratory soil mixing study to understand how carbon utilization, heterotrophic respiration, and microbial community structure were affected when active layer and permafrost soils were mixed in varying proportions. Active layer soil and permafrost collected from two sites in Alaska were mixed in five different ratios and incubated for 100 days at 10°C. Respiration rates were highest in the 100% active layer soils, averaging 19.8 µg C-CO2 g−1 dry soil d−1 across both sites, and decreased linearly as the ratio of permafrost increased. Mixing of the two soil layers resulted in utilization of a more diverse group of carbon substrates compared to permafrost alone. Additionally, combining active layer and permafrost soils increased microbial diversity and resulted in communities resembling those from the active layer when soils were mixed in equal ratios. Understanding the effects of active layer-permafrost mixing on functional potential and soil organic matter decomposition will improve predictions of carbon-climate feedbacks as permafrost thaws in these regions.
  • Airborne Bacteria over Thawing Permafrost Landscapes in the Arctic

    Abstract: Rapid warming in the Arctic, outpacing global rates, is driving significant changes in cryospheric landscapes, including the release of long-preserved microorganisms. This study focuses on thawing permafrost in Northern Alaska, where microbes previously preserved in frozen soils are introduced into thermokarst lakes, rivers, and coastal waters and may also become airborne as bioaerosols. We present the first microbial composition measurements of bioaerosols in Alaska, identifying their local sources, such as soils, water bodies, and vegetation. Although sea/brackish water is the dominant bioaerosol contributor, we provide the first evidence of permafrost microbial signatures in bioaerosols from permafrost-laden regions. Permafrost is highly enriched with ice nucleating particles (INPs), which play a crucial role in cloud formation, precipitation processes, and radiation budget despite their relatively low atmospheric concentrations. With rising Arctic temperatures, increased permafrost thaw could result in higher levels of airborne permafrost-derived microbes and biological INPs active at warmer subzero temperatures. This, in turn, could enhance precipitation, further accelerating the permafrost thaw. Our findings emphasize the complex interactions between terrestrial changes and atmospheric processes, revealing a potential feedback loop that could intensify permafrost thaw and its broader environmental impacts.
  • Nanofiber Fabrication by Electrospinning Technology: Optimization, Characterization, and Application

    Abstract: This project explores electrospinning (ES) as one of the most successful technologies to produce nanofiber materials. Electrospun nanofibers are used in various military technologies, including advanced filtration systems, impact-resistant protective gear, thermal insulation, radar absorption for camouflage and stealth, antimicrobial wound dressings, drug-delivery patches, rapid healing, efficient solar cells, and self-cleaning materials for regeneration. Researchers at the US Army Engineer Research and Development Center (ERDC) investigated electrospinning effects on morphology, crystallinity and distribution of metal oxides for photocatalytic activities, and magnetic and mechanical properties in reinforcing composites. This study includes the following fabricated electrospun mats: -iron and titanium oxide (Fe3O4 and TiO2) with polyvinyl alcohol (PVA) -graphene, graphene oxide, and reduced graphene oxide with polyvinylidene fluoride (PVDF) -graphene-polyacrylonitrile (PAN) -metal-organic frameworks (MOF), graphene-MXene with PAN The research presented herein includes electrospinning theory, process, and parameters; sol–gel technology in solution preparation; and electrospinning sample characterization to guide readers in the fabrication of electrospun fibers with targeted characteristics. Future studies explore electrospun MOFs and MXene, a class of two-dimensional inorganic compounds with transition metal carbides, nitrides, or carbonitrides composites. These studies are invaluable for advancing military programs and enhancing warfighter support and civil works.
  • Local Integrated-Technology Energy System to Meet Operational Needs (LITES ON) Project

    Abstract: The ability to reliably charge battery systems, whether for vehicles, mission support equipment, or stationary purposes, is especially important in remote and cold regions. The US Army Cold Regions Research and Engineering Laboratory (CRREL) project team evaluated and documented the performance of potential photovoltaic (PV) battery charging configurations (e.g., controller component) for use in such regions, especially as backup alternatives to other grid-connected charging stations that support Army installations, with a unique focus on the power electronics components of the system. In addition to its potential to support building energy resilience, this work complements other work that considers electrification of the DoD fleet of vehicles and the needed grid-connected infrastructure. This work adds to the growing information available on lithium ion (Li-ion) battery performance in cold regions by monitoring the battery performance as part of the test configuration. The results help better inform design and performance requirements needed for cold regions applications as well as the acquisition of such systems.
  • A Revised Landform Map for Areas Prone to Dust Emission in the Southwestern United States

    Abstract: An area’s landform composition can provide insight into its dust emission potential. In 2017, geomorphologists from the Desert Research Institute provided the US Army Engineer Research and Development Center with a 32-class landform map for portions of the Mojave and Sonoran Deserts in the southwest United States (SWUS) to support air quality and dust hazard modeling applications. We collaborated with the University of California to independently assess the map. Our review identified opportunities to improve the dataset, such as using a simpler landform classification system and revising individual geomorphic unit assignments to ensure consistent labeling across the study area. This report describes our approaches for refining the SWUS map and documents the updated 15-class landform map that resulted from our efforts.
  • Applicability of Two-Phase Modeling with Compression Experiments for Snow Compaction Dynamics

    Abstract: Compaction is a rheological process which has been modeled using a 1-D two-phase continuum framework. However, it has been posed as a promising method for modeling densification of snow into glacial ice, where the conventional model is empirical or semi-empirical. We explored the applicability of a one-dimensional two-phase continuum framework for modeling snow compaction through theoretical and laboratory methods by analyzing and simplifying theory, then experimentally constraining the model coefficient. We found the limit of slow compaction is reached such that air evacuation during the compaction process does not impede the deformation of ice grains. Model-data comparisons are performed using data from a series of uniaxial compression experiments of snow samples under a range of compaction rates and densities at –10° and –20 °C. By defining a linear effective pressure function, we constrain the model parameter by tuning against the data. While our model follows proper simplification of theory, temperature and microstructural dependence are determined by the model parameter in a rheological formulation with the strain rate; much scatter still exists. Within the selected range of compaction rates and densities, a 1-D two-phase model with a continuum framework alone does not likely capture important processes involved in the compaction process.
  • Acoustic Winter Terrain Classification for Offroad Autonomous Vehicles

    Abstract: Autonomous vehicles can experience extreme changes in performance when operating over winter surfaces, and require accurate classification to transit them safely. In this work we consider acoustic classification of winter terrain, and demonstrate that a simple and efficient frequency-space analysis exposed to a small convolutional neural network, rather than recurrent architectures or temporally-varying spectrogram inputs, is sufficient to provide near-perfect classification of deep snow, hardpacked surfaces and ice. Using a dual-microphone configuration, we also show that acoustic classification performance is due to a combination of vehicle noises and vehicle-terrain interaction noises, and that engine sounds can serve as a particularly powerful classification cue for offroad environments.
  • Evaluating and Improving Snow in the National Water Model, Using Observations from the New York State Mesonet

    Abstract: This study leverages observations from NYSM to evaluate and improve representation of snow within the NWM and its associated land surface model. Distributed NWM simulations were ran and analyzed, forced by gridded meteorological analyses, and Noah-MP point simulations, forced by NYSM observations. Distributed NWM runs, with a baseline configuration, show substantial SWE biases caused by biases in meteorological forcing used, imperfect representation of snow processes, and mismatches between land cover in the model and NYSM station locations. Noah-MP point simulations, using baseline configuration, reveal a systematic positive bias in SWE accumulation. Noah-MP point simulations, with improved precipitation phase partitioning, reveal a systematic negative bias in SWE ablation rates. Sensitivity experiments highlight uncertain parameters within Noah-MP that strongly affect ablation rates and show particularly large sensitivity to snow albedo decay time-scale parameter, which modulates snow albedo decay rates. Distributed NWM experiments, with precipitation phase partitioning and TAU0 adjusted based on Noah-MP point simulation results, show qualitatively similar sensitivities. However, the distributed experiments do not show clear improvements when compared to SWE and streamflow observations. This is likely due to some combination of sources of bias in the baseline-distributed run and biases in other parameterized processes unrelated to snow in the NWM.
  • Cracking Performance Characterisation of Aramid Fiber-Reinforced Asphalt Mixtures Using Digital Image Correlation

    Abstract: Conventional index-based testing of asphalt mixtures cannot accurately capture local deformation in a sample, limiting the usage of standard test measurements. The non-contact-based measurements proved effective to capture local deformation fields. This study aimed to capture the fatigue and thermal cracking behaviour of fiber-reinforced asphalt mixture by utilising digital image correlation (DIC). One binder (PG76-22), a diabase aggregate and three fibers (polyolefin/ aramid fibers (PFA) at 0.05% dosage and Sasobit-coated aramid fibers at 0.01% and 0.02% dosage) were used to prepare a total of four mixtures (one control and three FRAM). All these mixtures were produced at a local batch plant following manufacturer-recommended mixing methods. DIC analysis was performed for three-point bending beam (3PB) and disk shape compact tension (DCT) tests at intermediate temperature (25°C) and low temperatures of −12°C and −18°C. Based on index values from DCT and 3PB, the thermal and fatigue cracking performance enhancement was not significant. However, DIC analysis showed that, regardless of testing temperature, the crack propagated in a random pattern for FRAM, whereas the crack followed a relatively straight path for the control mix. Finally, based on DIC strain contours, FRAM mixtures exhibit distributed strain over a larger area compared to the control mix.
  • C-Band Radar Measurements in a Snow-Covered Boreal Forest Environment

    Abstract: Sled-based side-looking C-band radar profiles were collected around Fairbanks, Alaska, in March 2023 during the NASA SnowEx campaign to improve the conceptual understanding of C-band radar wave interactions with snow in a boreal forest environment. Seven transects with different vegetation and ground conditions were studied. Significant volume scattering from snow was observed in this shallow snowpack, indicating sensitivity at lower snow depths (SDs) which are common in high-latitude snowpacks. Manual removal of the snowpack decreased the backscatter by more than 2 dB in all polarizations, with a larger decrease in the cross-polarization, supporting the potential use of Sentinel-1 to retrieve SD.