30 Sep 2022

Buried-Object-Detection Improvements Incorporating Environmental Phenomenology into Signature Physics

Abstract: The ability to detect buried objects is critical for the Army. Therefore, this report summarizes the fourth year of an ongoing study to assess environmental phenomenological conditions affecting probability of detection and false alarm rates for buried-object detection using thermal infrared sensors. This study used several different approaches to identify the predominant environmental variables affecting object detection: (1) multilevel statistical modeling, (2) direct image analysis, (3) physics-based thermal modeling, and (4) application of machine learning (ML) techniques. In addition, this study developed an approach using a Canny edge methodology to identify regions of interest potentially harboring a target object. Finally, an ML method was developed to improve automatic target detection and recognition performance by accounting for environmental phenomenological conditions, improving performance by 50% over standard automatic target detection and recognition software.

8 Sep 2022

Ground-penetrating Radar Studies of Permafrost, Periglacial, and Near-surface

Abstract: Installations built on ice, permafrost, or seasonal frozen ground require careful design to avoid melting issues. Therefore, efforts to rebuild McMurdo Station, Antarctica, to improve operational efficiency and consolidate energy resources require knowledge of near-surface geology. Both 200 and 400 MHz ground-penetrating radar (GPR) data were collected in McMurdo during January, October, and November of 2015 to detect the active layer, permafrost, excess ice, fill thickness, solid bedrock depth, and buried utilities or construction and waste debris. Our goal was to ultimately improve surficial geology knowledge from a geotechnical perspective. Radar penetration ranged between approximately 3 and 10 m depth for the 400 and 200 MHz antennas, respectively. Both antennas successfully detect buried utilities and near-surface stratified material to ~0.5–3.0 m whereas 200 MHz profiles were more useful for mapping deeper stratified and un-stratified fill over bedrock. Artificially generated excess ice which appears to have been created from runoff, water pooling and refreezing, aspect shading from buildings, and snowpack buried under fill, are prevalent. Results show that McMurdo Station has a complex myriad of ice-rich fill, scoria, fractured volcanic bedrock, permafrost, excess ice, and buried anthropogenically generated debris, each of which must be considered during future construction.

7 Sep 2022

Extracting Sintered Snow Properties from MicroCT Imagery to Initialize a Discrete Element Method Model

Abstract: Modeling snow’s mechanical behavior is important for many cold regions engineering problems. Because snow’s microstructure plays a significant role in its mechanical response, it is imperative to initialize models with accurate bond characteristics and realistic snow-grain geometries to precisely capture the microstructure interactions. Previous studies have processed microcomputed tomography scans of snow samples with a watershed method to extract grain geometries. This approach relies on identification of seed points to segment each grain. Our new methodology, called the “moving window method,” does not require prior knowledge of the snow-grain-size distribution to identify seed points. We use the interconnectivity of the segmented grains to identify bond characteristics. We compare the resultant grain-size and bond-size distributions to the known grain sizes of the laboratory-made snow samples. The grain-size distributions from the moving window method closely match the known grain sizes, while both results from the traditional method produce grains that are too large. We propose that the bond net-work identified using the traditional method underestimates the number of bonds and overestimates bond radii. Our method allows us to segment realistic snow grains and their associated bonds, without prior knowledge of the samples, from which we can initialize numerical models of the snow.

6 Sep 2022

Short-range Near-surface Seismic Ensemble Predictions and Uncertainty Quantification for Layered Medium

Abstract: To make a prediction for seismic signal propagation, one needs to specify physical properties and subsurface ground structure of the site. This information is frequently unknown or estimated with significant uncertainty. This paper describes a methodology for probabilistic seismic ensemble prediction for vertically stratified soils and short ranges with no in situ site characterization. Instead of specifying viscoelastic site properties, the methodology operates with probability distribution functions of these properties taking into account analytical and empirical relationships among viscoelastic variables. This yields ensemble realizations of signal arrivals at specified locations where statistical properties of the signals can be estimated. Such ensemble predictions can be useful for preliminary site characterization, for military applications, and risk analysis for remote or inaccessible locations for which no data can be acquired. Comparison with experiments revealed that measured signals are not always within the predicted ranges of variability. Variance-based global sensitivity analysis has shown that the most significant parameters for signal amplitude predictions in the developed stochastic model are the uncertainty in the shear quality factor and the Poisson ratio above the water table depth.

6 Sep 2022

Brine, Englacial Structure, and Basal Properties near the Terminus of McMurdo Ice Shelf, Antarctica

Abstract: We collected ∼1300 km of ground-penetrating radar profiles over McMurdo Ice Shelf, Antarctica, using frequencies between 40 and 400 MHz to determine extent, continuity and depth to the brine. We also used profiles to determine meteoric ice thickness and locate englacial features, which may suggest ice shelf instability. The brine extends 9–13 km inland from the ice shelf terminus and covers the entire region between Ross, White and Black Islands. Jump unconformities and basal fractures exist in the brine and ice shelf, respectively, suggesting prior fracturing and re-suturing. One 100 MHz profile, the most distal from the ice shelf edge while still being situated over the brine, simultaneously imaged the brine and bottom of meteoric ice. This suggests a negative brine salinity gradient moving away from the terminus. The meteoric ice bottom was also imaged in a few select locations through blue ice in the ablation zone near Black Island. We suggest that brine, sediment-rich ice and poor antenna coupling on rough ice attenuates the signal in this area. When combined with other recent mass-balance and structural glaciology studies of MIS, our results could contribute to one of the most high-resolution physical models of an ice shelf in Antarctica.

31 Aug 2022

Photographic Aerial Transects of Fort Wainwright, Alaska

Abstract: This report presents the results of low-altitude photographic transects conducted over the training areas of US Army Garrison Fort Wainwright, in the boreal biome of central Alaska, to document baseline land-cover conditions. Flights were conducted via a Cessna™ 180 on two flight paths over portions of the Tanana Flats, Yukon, and Donnelly Training Areas and covered 486 mi (782 km) while documenting GPS waypoints. Nadir photographs were made with two GoPro™ cameras operating at 5 sec time-lapse intervals and with a handheld digital camera for oblique imagery. This yielded 6,063 GoPro photos and 706 oblique photos. Each image was intersected with a land-cover-classification map, collectively representing 38 of the 44 cover categories.

30 Aug 2022

Automated Detection of Austere Entry Landing Zones: A “GRAIL Tools” Validation Assessment

Abstract: The Geospatial Remote Assessment for Ingress Locations (GRAIL) Tools software is a geospatial product developed to locate austere entry landing zones (LZs) for military aircraft. Using spatial datasets like land classification and slope, along with predefined LZ geometry specifications, GRAIL Tools generates binary suitability filters that distinguish between suitable and unsuitable terrain. GRAIL Tools combines input suitability filters, searches for LZs at user‐defined orientations, and plots results. To refine GRAIL Tools, we: (a) verified software output; (b) conducted validation assessments using five unpaved LZ sites; and (c) assessed input dataset resolution on outcomes using 30 and 1‐m datasets. The software was verified and validated in California and the Baltics, and all five LZs were correctly identified in either the 30 or the 1‐m data. The 30‐m data provided numerous LZs for consideration, while the 1‐m data highlighted hazardous conditions undetected in the 30‐m data. Digital elevation model grid size affected results, as 1‐m data produced overestimated slope values. Resampling the data to 5 m resulted in more realistic slopes. Results indicate GRAIL Tools is an asset the military can use to rapidly assess terrain conditions.

30 Aug 2022

Determination of Residual Low-Order Detonation Particle Characteristics from Composition B Mortar Rounds

Empirical measurements of the spatial distribution, particle-size distribution, mass, morphology, and energetic composition of particles from low-order (LO) detonations are critical to accurately characterizing environ-mental impacts on military training ranges. This study demonstrated a method of generating and characterizing LO-detonation particles, previously applied to insensitive munitions, to 81 mm mortar rounds containing the conventional explosive formulation Composition B. The three sampled rounds had estimated detonation efficiencies ranging from 64% to 82% as measured by sampled residual energetic material. For all sampled rounds, energetic deposition rates were highest closer to the point of detonation; however, the mass per radial meter varied. The majority of particles (>60%), by mass, were <2 mm in size. However, the spatial distribution of the <2 mm particles from the point of detonation varied between the three sampled rounds. In addition to the particle-size-distribution results, several method performance observations were made, including command-detonation configurations, sampling quality control, particle-shape influence on laser-diffraction particle-size analysis (LD-PSA), and energetic purity trends. Overall, this study demonstrated the successful characterization of Composition B LO-detonation particles from command detonation through combined analysis by LD-PSA and sieving.

30 Aug 2022

Live-Fire Validation of Command-Detonation Residues Testing Using a 60 mm IMX-104 Munition

Abstract: Command detonation (i.e., static firing) provides a method of testing munitions for their postdetonation residues early in the acquisition process. However, necessary modifications to the firing train and cartridge orientation raise uncertainty whether command detonation accurately represents residue deposition as it occurs during live-fire training. This study collected postdetonation residues from live-fired 60 mm IMX-104 mortar cartridges and then compared estimated energetic-compound deposition rates between live fire and prior command detonations of the same munition. Average live-fire deposition rates of IMX-104 compounds deter-mined from 11 detonations were 3800 mg NTO (3-nitro-1,2,4-triazol-5-one), 34 mg DNAN (2,4-dinitroanisole), 12 mg RDX (1,3,5-Trinitroperhydro-1,3,5-Triazine), and 1.9 mg HMX (1,3,5,7-Tetranitro-1,3,5,7-Tetrazocane) per cartridge. Total live-fire residue deposition (mean ± standard deviation: 3800 ± 900 mg/cartridge) was not significantly different from command detonation using a representative fuze simulator (3800 ± 900 mg/cartridge, n = 7, p = 0.76) but was significantly different from command detonation using a simplified fuze simulator (2200 ± 500 mg/cartridge, n = 7, p < 0.01). While the dominant residue compound NTO was broadly similar between live fire and command detonation, the minor residue compounds RDX and DNAN were underestimated during command detonation by a factor of approximately three to seven.

25 Aug 2022

McMurdo Snow Roads and Transportation: Final Program Summary

Abstract: The snow roads at McMurdo Station, Antarctica, are the primary transportation corridors for moving personnel and material to and from the airfields servicing intra- and intercontinental air traffic. The majority of the road system is made of snow overlying a snow, firn, and icy subsurface and is particularly susceptible to deterioration during the warmest parts of the austral summer when above-freezing temperatures can occur for several days at a time. Poor snow-road conditions can seriously limit payloads for all types of ground vehicles. The US Army Cold Regions Research and Engineering Laboratory (CRREL) studied the McMurdo snow roads for the National Science Foundation Office of Polar Programs as part of the Snow Roads and Transportation (SRT) program. The goals of the SRT program was to improve construction, maintenance, and use of the McMurdo’s snow roads, with particular attention on minimizing warm-season deterioration. This is the final report of the SRT program, summarizing the program’s activities and findings and emphasizing those parts of the program not previously documented in CRREL Reports, conference papers, or journal articles.