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Category: Publications: Cold Regions Research and Engineering Laboratory (CRREL)
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  • Numerical Modeling of Mesoscale Infrasound Propagation in the Arctic

    Abstract: The impacts of characteristic weather events and seasonal patterns on infrasound propagation in the Arctic region are simulated numerically. The methodology utilizes wide-angle parabolic equation methods for a windy atmosphere with inputs provided by radiosonde observations and a high-resolution reanalysis of Arctic weather. The calculations involve horizontal distances up to 200 km for which interactions with the troposphere and lower stratosphere dominate. Among the events examined are two sudden stratospheric warmings, which are found to weaken upward refraction by temperature gradients while creating strongly asymmetric refraction from disturbances to the circumpolar winds. Also examined are polar low events, which are found to enhance negative temperature gradients in the troposphere and thus lead to strong upward refraction. Smaller-scale and topographically driven phenomena, such as low-level jets, katabatic winds, and surface-based temperature inversions, are found to create frequent surface-based ducting out to 100 km. The simulations suggest that horizontal variations in the atmospheric profiles, in response to changing topography and surface property transitions, such as ice boundaries, play an important role in the propagation.
  • Data Acquisition Software for Impedance Tube Measurements

    Abstract: Transmission impedance tube measurements are necessary to measure the asymmetric acoustic property known as Willis coupling. However, software is required to measure and store data from an impedance tube for acoustic material characterization. This report details the overall structure of custom-developed software built from low-level functions. Software libraries from the data acquisition system as well as the HDF5 file system are the basis for the code. A command line user interface guides a user through the necessary steps in data collection.
  • A Review of Airfield Pavement Drainage Guidance

    Abstract: Inadequate drainage conditions may lead to airfield pavement deterioration. A thorough review of existing pavement drainage guidance and literature was necessary to identify key drainage considerations such as surface drainage infrastructure, pavement drainage layer thickness, use of geotextiles, and performance in freeze–thaw climates. Existing airport drainage guidance is provided by the Unified Facilities Criteria (UFC), the Federal Aviation Administration (FAA), and the Tri-Service Pavements Working Group (TSPWG). Pavement drainage guidance is buried within regulations for pavement de-sign and can, at times, be split awkwardly to accommodate pavement guidance that is split between rigid and flexible designs. Most airfield pavement guidance has been adapted from guidance for highway design. Most guidance is also strength based, with little to no attention paid to material erodibility (a potential cause of pavement deterioration). This review also found very little reference to repairing, rather than completely replacing, damaged subsurface drainage layers. Further research is needed to assess the use of geofabrics and moisture in freeze–thaw conditions on drainage layers and surface structures. With further research, the retrofit and repair of existing subpavement systems might become a more economical solution to drainage-caused pavement deterioration issues than complete reconstruction.
  • Development and Validation of a Balanced Mix Design Approach for CIR Mixtures Using Full-Scale Testing

    Abstract: The main goal of this study was to improve the performance of cold in-place recycling (CIR) mixtures by using a balanced mix design (BMD) approach. This study involved preparing and testing CIR mixtures in the lab at varying contents of bituminous additives and constant content of 1% cement and 3% water. Eight combinations of CIR mixtures were produced for this study using two binders (emulsion and foamed asphalt), compaction efforts (30 and 70 gyrations), and curing processes (72 hours at 140°F and 50°F). Results showed that asphalt pavement analyzer, semicircular bend, and indirect tensile strength tests presented the highest correlation with the change of binder contents. The study successfully used the developed BMD for designing CIR mixtures and selecting their optimum binder contents. It then used three balanced CIR mixtures to construct full-scale pavement sections to validate the BMD approach in the field. A heavy vehicle simulator was used to apply different accelerated loadings on each section. Results showed that the CIR section with 2% binder presented the best rutting performance under truck loading and the highest rutting susceptibility under aircraft loading. Conversely, the CIR section with 3% binder presented the highest cracking resistance under both truck and aircraft loading.
  • Resilience in Distributed Sensor Networks

    Abstract: With the advent of cheap and available sensors, there is a need for intelligent sensor selection and placement for various purposes. While previous research was focused on the most efficient sensor networks, we present a new mathematical framework for efficient and resilient sensor network installation. Specifically, in this work we formulate and solve a sensor selection and placement problem when network resilience is also a factor in the optimization problem. Our approach is based on the binary linear programming problem. The generic formulation is probabilistic and applicable to any sensor types, line-of-site and non-line-of-site, and any sensor modality. It also incorporates several realistic constraints including finite sensor supply, cost, energy consumption, as well as specified redundancy in coverage areas that require resilience. While the exact solution is computationally prohibitive, we present a fast algorithm that produces a near-optimal solution that can be used in practice. We show how such formulation works on 2D examples, applied to infrared (IR) sensor networks designed to detect and track human presence and movements in a specified coverage area. Analysis of coverage and comparison of sensor placement with and without resilience considerations is also performed.
  • Practical Guidance for Numerical Modeling in FUNWAVE-TVD

    Purpose: This technical note describes the physical and numerical considerations for developing an idealized numerical wave-structure interaction modeling study using the fully nonlinear, phase-resolving Boussinesq-type wave model, FUNWAVE-TVD (Shi et al. 2012). The focus of the study is on the range of validity of input wave characteristics and the appropriate numerical domain properties when inserting partially submerged, impermeable (i.e., fully reflective) coastal structures in the domain. These structures include typical designs for breakwaters, groins, jetties, dikes, and levees. In addition to presenting general numerical modeling best practices for FUNWAVE-TVD, the influence of nonlinear wave-wave interactions on regular wave propagation in the numerical domain is discussed. The scope of coastal structures considered in this document is restricted to a single partially submerged, impermeable breakwater, but the setup and the results can be extended to other similar structures without a loss of generality. The intended audience for these materials is novice to intermediate users of the FUNWAVE-TVD wave model, specifically those seeking to implement coastal structures in a numerical domain or to investigate basic wave-structure interaction responses in a surrogate model prior to considering a full-fledged 3-D Navier-Stokes Computational Fluid Dynamics (CFD) model. From this document, users will gain a fundamental understanding of practical modeling guidelines that will flatten the learning curve of the model and enhance the final product of a wave modeling study. Providing coastal planners and engineers with ease of model access and usability guidance will facilitate rapid screening of design alternatives for efficient and effective decision-making under environmental uncertainty.
  • Cold Regions Vehicle Start: Cold Performance of Ultracapacitor-Based Batteries for Stryker Vehicles

    Abstract: Reliable vehicle start is necessary to support mission success, especially for response time. At Department of Defense installations in cold regions, vehicles using rechargeable battery and starter technologies have significant issues starting in the cold. Ultracapacitor engine start modules (ESMs) are an alternate technology to rechargeable lead-acid or lithium-ion batteries. The project develops a performance baseline for the ESM used in the M1126 Stryker Combat Vehicle under cold conditions. To test the performance of the ESMs in a cold room, a mechanical load system was constructed to replicate the load of starting a Stryker engine and instrumented with sensors to monitor parameters such as voltage, torque, and temperature. The ESMs were tested with the load system at temperatures from 24°C to −40°C. The results of the tests showed that there was some degradation of the ultracapacitor’s performance at the colder temperatures, which was expected, but no permanent damage. This work provides a test protocol and capability to evaluate next-generation vehicle battery systems for cold regions applications. Additionally, the ESM cold performance data establish a baseline to compare next-generation vehicle battery storage systems and to support cold regions missions and identify potential performance requirements for future vehicle battery system acquisition.
  • Landform Identification in the Chihuahuan Desert for Dust Source Characterization Applications: Developing a Landform Reference Data Set

    Abstract: ERDC-Geo is a surface erodibility parameterization developed to improve dust predictions in weather forecasting models. Geomorphic landform maps used in ERDC-Geo link surface dust emission potential to landform type. Using a previously generated southwest United States landform map as training data, a classification model based on machine learning (ML) was established to generate ERDC-Geo input data. To evaluate the ability of the ML model to accurately classify landforms, an independent reference landform data set was created for areas in the Chihuahuan Desert. The reference landform data set was generated using two separate map-ping methodologies: one based on in situ observations, and another based on the interpretation of satellite imagery. Existing geospatial data layers and recommendations from local rangeland experts guided site selections for both in situ and remote landform identification. A total of 18 landform types were mapped across 128 sites in New Mexico, Texas, and Mexico using the in situ (31 sites) and remote (97 sites) techniques. The final data set is critical for evaluating the ML-classification model and, ultimately, for improving dust forecasting models.
  • Automated Ground-Penetrating-Radar Post-Processing Software in R Programming

    Abstract: Ground-penetrating radar (GPR) is a nondestructive geophysical technique used to create images of the subsurface. A major limitation of GPR is that a subject matter expert (SME) needs to post-process and interpret the data, limiting the technique’s use. Post-processing is time-intensive and, for detailed processing, requires proprietary software. The goal of this study is to develop automated GPR post-processing software, compatible with Geophysical Survey Systems, Inc. (GSSI) data, in open-source R programming. This would eliminate the need for an SME to process GPR data, remove proprietary software dependencies, and render GPR more accessible. This study collected GPR profiles by using a GSSI SIR4000 control unit, a 100 MHz antenna, and a Trimble GPS. A standardized method for post-processing data was then established, which includes static data removal, time-zero correction, distance normalization, data filtering, and stacking. These steps were scripted and automated in R programming, excluding data filtering, which was used from an existing package, RGPR. The study compared profiles processed using GSSI soft-ware to profiles processed using the R script developed here to ensure comparable functionality and output. While an SME is currently still necessary for interpretations, this script eliminates the need for one to post-process GSSI GPR data.
  • Investigations into the Ice Crystallization and Freezing Properties of the Antifreeze Protein ApAFP752

    Abstract: Antifreeze proteins (AFPs) allow biological organisms, including insects, fish, and plants, to survive in freezing temperatures. While in solution, AFPs impart cryoprotection by creating a thermal hysteresis (TH), imparting ice recrystallization inhibition (IRI), and providing dynamic ice shaping (DIS). To leverage these ice-modulating effects of AFPs in other scenarios, a range of icing assays were performed with AFPs to investigate how AFPs interact with ice formation when tethered to a surface. In this work, we studied ApAFP752, an AFP from the beetle Anatolica polita, and first investigated whether removing the fusion protein attached during protein expression would result in a difference in freezing behavior. We performed optical microscopy to examine ice-crystal shape, micro-structure, and the recrystallization behavior of frozen droplets of AFP solutions. We developed a surface chemistry approach to tether these proteins to glass surfaces and conducted droplet-freezing experiments to probe the interactions of these proteins with ice formed on those surfaces. In solution, ApAFP752 did not show any DIS or TH, but it did show IRI capabilities. In surface studies, the freezing of AFP droplets on clean glass surfaces showed no dependence on concentration, and the results from freezing water droplets on AFP-decorated surfaces were inconclusive.