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

Assessing Shorelines Extracted from Satellite Imagery Using Coincident Terrestrial Lidar Linescans

Abstract: Previous analyses comparing CoastSat satellite-derived shorelines to morphological data highlighted site-specific errors in outputs related to concurrent wave runup conditions. We present a comparison of lidar-derived runup and beach elevation data to CoastSat satellite-derived waterlines extracted using two image sources and two threshold algorithms. Results show SDW extracted using Otsu thresholds correlated better with lidar-derived waterlines, SDW extracted using the weighted peaks threshold were consistently positioned in the upper swash and correlated better with a runup bulk statistic. Assigning the best-fit runup bulk statistic as the waterline elevation to weighted peaks SDW resulted in SDS with less scatter than the Otsu SDW. Horizontal errors for converted datum-referenced shoreline were lowest when SDW were converted to SDS using best-fit measured runup bulk statistics and a measured slope. For weighted peaks SDW from both image sources, assigning the best-fit parameterized runup bulk statistic and an average slope in the SDW to SDS conversion reduced error by ∼ 20% to ∼ 35% when compared to tidal elevation and average slope. These findings confirm runup corrections can improve native SDS outputs, although the magnitude of final shorelines error depended on specific imagery product, local beach slope, threshold technique, runup parametrization, and chosen reference contour.

12 Aug 2025

Applying the Working with Nature Philosophy to Navigation Infrastructure Projects

Abstract: In 2008, the World Association for Waterborne Transport Infrastructure published a position paper describing a Working with Nature philosophy aimed to change how the sector approaches navigation and port infrastructure projects. In 2018, Pianc published guidance on implementing WwN. Pianc’s guidance presents a six-step process that encourages consideration of site-specific ecosystem characteristics and WwN opportunities at early stages of project development, early stakeholder engagement and integration of WwN into the development of project objectives before design begins. By incorporating WwN applications during conception, the WwN approach provides the most promising opportunities to affect positive outcomes for the environment. This holistic understanding of ecosystem processes and socioeconomic interactions realises environmental impacts can be minimised while concomitantly seeking opportunities to enhance ecosystem functions at various spatial and temporal scales. Project delivery thus goes beyond avoiding or compensating for negative project impacts and seeks multi-sector ecosystem and socioeconomic benefits. Applied in practice, WwN can increase habitat functionality, reduce energy associated with construction or maintenance, and enhance the short- and long-term delivery of ecosystem services. Projects consistent with the WwN philosophy achieve their underlying engineering objectives, alongside various co-benefits, consistent with the environmental, societal and economic sustainability pillars.

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

Carbon Nanotube-Based Segregated Thermoplastic Nanocomposites Structured via Electromagnetic Melt Processing

Abstract: The EM-processed TPNCs prepared with EM-susceptible carbon nanotubes exhibited a significant enhancement in transport and mechanical properties, outperforming conventionally processed TPNCs. Thus, EM-processed TPNCs demonstrated an ultralow electrical percolation threshold and a remarkable increase in volume electrical conductivity of 8 orders of magnitude at only 1.0 wt % CNT loading. This highlights the superior network formation, level of segregation, and structuring enabled by EM processing. Differential scanning calorimetry and X-ray diffraction revealed EM-processed TPNCs exhibited higher crystallinity and a predominantly α crystal phase compared to hot-pressed TPNCs. Microstructural inspection by electron microscopy disclosed EM processing led to segregated but interconnected multiscale networks of a thin and well-defined CNT interphase that encompassed from the nanoscale of CNTs to the macroscopic scale of TPNCs. The EM-processed TPNCs developed a statistically higher stiffness and in certain cases, even better strength than hot-pressed TPNCs. However, EM-processed TPNCs displayed significantly lower ductility, owing to their higher crystallinity, more brittle crystal α phase, and potential formation of microvoids in the bulk of the TPNCs inherent to the unoptimized EM processing. This work provides an understanding of an alternative and unconventional processing method capable of achieving higher structuring in nanocomposites with advanced multifunctional properties.

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.

11 Aug 2025

3D Printing of Ultra-High-Performance Concrete: Shape Stability for Various Printing Systems

Abstract: Attention is on concrete 3D printing for its potential in structure optimization, life-cycle extension, emission reduction, and cost savings. Previous studies tailor a mix to a specific printing system and evaluate printability based on measurements of pumpability, extrudability, and buildability. For this investigation, an experimental program was conducted using various printing systems on a nano-modified UHPC mix. A medium-scale gantry and a large-scale ABB robotic arm were utilized, piston-type extruder and an auger system were employed, various nozzles, including circular and rectangular designs, were tested, and a cavity and Thom-Katt pump were used. Results indicated the shape stability of the UHPC mix is influenced by the printing system. Furthermore, the use of a circular nozzle demonstrated different shape stabilities when the extrusion system was changed from a piston-type extruder to an auger system. Additionally, the method of material pumping to the extrusion system was found to be critical for shape stability of printed layers. The mix failed to maintain its shape post-extrusion when using the cavity pump, which was attributed to higher strain rates imposed on material during the pumping process. This issue was not observed when the piston-type pump was used.

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.