10 Sep 2025

Detachment and Transport of Composition B Detonation Particles in Rills

Abstract: The partial detonation of munitions used in military exercises leaves behind energetic particles on the surface of soil. Energetic particles deposited by incomplete detonations can then dissolve and be transported by overland flow and potentially contaminate ground and surface waters. The objective of this study was to evaluate the mechanisms of transport of Composition B, a formulation that includes TNT and RDX during overland flow. The transport of Composition B was examined using a rill flume with three flow rates and four energetic particle sizes. After each erosion simulation, energetic particles remaining on the soil surface were measured along with energetics dissolved in runoff, in suspended sediment, and in infiltration. Smaller particle sizes led to greater transport in both solution and sediment. The properties of the energetic compounds also influenced transport. More TNT was transported in runoff than RDX, likely due to TNT’s higher solubility and dissolution rates, however, overall, dissolved energetics in runoff and infiltration accounted for very little of the total transport. Most transport of Composition B was the result of the physical movement of energetic particles and flakes by erosion forces. This study’s results allow for improved prediction of Composition B transport during overland flow.

10 Sep 2025

Cellulose Nanofibers Impart Melt Resistance to Ice Through Optical and Thermal Mechanisms

Abstract: Ice is ubiquitous in cold regions with historical significance as a key structural material. Contemporary efforts to leverage ice for the construction of large structures have incorporated cellulose-based reinforcing materials to increase strength. While an increased resistance to melting has been observed, it has not been investigated. Herein, we provide evidence that cellulose nanofibers (CNFs), as a heterogeneous component to synthetic ices, increase melt resistance through optical and thermal mechanisms. Specifically, we investigated the effect of 0.1−1.0 wt % CNFs on the reflectance, thermal conductivity, and melt rate of ice. The presence of CNFs increased reflectance of ice from 20 to 70% at 640 nm. Thermophysical measurements revealed that CNFs both slow melting and facilitate freezing and do not statistically affect the specific heat capacity of ice. Measurements with light flash analysis revealed that CNFs reduce thermal conductivity up to 10%. Overall CNFs reduced the melt rate of ice by 10× with only 1.0 wt % CNF. These results demonstrate that insoluble CNFs impart melt resistance to ice by both optical and thermal mechanisms, results that provide an interesting combination of controls for ice stability and formation to optimize ice material properties for high performance applications in cold regions.

9 Sep 2025

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.

2 Sep 2025

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.

29 Aug 2025

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.

22 Aug 2025

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.

13 Aug 2025

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.

12 Aug 2025

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.

12 Aug 2025

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.

12 Aug 2025

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.