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.

11 Aug 2025

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.

7 Aug 2025

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.

4 Aug 2025

Acoustic and Seismic Wave Transmission Throughout the Multidomain Environment: Experimental Design, Methods, and Construction of a Prototypical Littoral Zone

Abstract: The future operational environment is projected to be a multidomain, transparent battlefield in which the Army must be able to act as both a supported and supporting force. An accurate detection and interpretation of acoustic and seismic signals propagating across land-air-water (LAW) interfaces are required to meet future requirements of a fully “transparent” domain. The LAW domains converge at the significant contested littoral zones. Historically, interpreting signals crossing media boundaries has been studied by stovepiping each distinct medium. These fragmented perspectives led to discrepancies in boundary and adjacent media descriptions and media-specific governing physics. No comprehensive physics framework exists to accurately predict how disorderly waveforms freely traverse LAW media boundaries. To understand these complex phenomena, a highly controlled physical experiment was designed and implemented. Repeatable controls were conducted. Epistemic uncertainty was decreased, and high waveform fidelity was maintained in the experimental setup by not interfering with wave transmission or sensor accuracy between controls. This report summarizes the experimental design, implementation, challenges, and repeatability.

28 Jul 2025

Predicting Frozen Ground and Thaw Risk from Standard Land Model Output: Data, Algorithms, and GeoWATCH Implementation

Abstract: The Geospatial Weather Affected Terrain Conditions and Hazards (GeoWATCH) tool provides real-time mobility predictions at 30 m resolution on demand for any location on the globe. This tool combines dynamic weather data provided by the Air Force 557 Weather Wing (557WW) with static terrain data to downscale soil moisture from global and regional scales to resolutions better suited for terrain analysis applications. Frozen and thawing ground data layers were recently incorporated into the GeoWATCH framework to better support terrain assessment for Warfighter functions in cold regions. This report documents our approach for diagnosing the frozen and thawing ground data layers and provides examples. First, using data from controlled land-surface model simulations, we established simple curve-fitting formulas relating soil temperature to frozen water content. We then added the new formulas to the GeoWATCH code so that end users can generate frozen soil products on demand. Finally, GeoWATCH uses the resultant frozen soil product with a series of soil layers to determine the risk of actively thawing soil and springtime mud conditions. While the new overlays are not integrated into the GeoWATCH mobility diagnostic calculations, they provide insight into soil state conditions critical for operations and weather-based risk assessment in cold regions.