8 Nov 2022

A 𝘬-Means Analysis of the Voltage Response of a Soil-Based Microbial Fuel Cell to an Injected Military-Relevant Compound (Urea)

Abstract: Biotechnology offers new ways to use biological processes as environmental sensors. For example, in soil microbial fuel cells (MFCs), soil electro-genic microorganisms are recruited to electrodes embedded in soil and produce electricity (measured by voltage) through the breakdown of substrate. Because the voltage produced by the electrogenic microbes is a function of their environment, we hypothesize that the voltage may change in a characteristic manner given environmental disturbances, such as the contamination by exogenous material, in a way that can be modelled and serve as a diagnostic. In this study, we aimed to statistically analyze voltage from soil MFCs injected with urea as a proxy for gross contamination. Specifically, we used 𝘬-means clustering to discern between voltage output before and after the injection of urea. Our results showed that the 𝘬-means algorithm recognized 4–6 distinctive voltage regions, defining unique periods of the MFC voltage that clearly identify pre- and postinjection and other phases of the MFC lifecycle. This demonstrates that 𝘬-means can identify voltage patterns temporally, which could be further improve the sensing capabilities of MFCs by identifying specific regions of dissimilarity in voltage, indicating changes in the environment.

7 Nov 2022

Cold Regions Vehicle Start: Next-Generation Lithium-Ion Battery Technologies for Stryker Vehicles

Abstract: Operating vehicles in extremely cold environments is a significant problem for not only the public but also the military. The Department of Defense has encountered issues when trying to reliably cold start large, heavy-duty military vehicles, specifically the M1126 Stryker Combat Vehicle, in cold regions. As noted in previous work, the issue stems from the current battery technology’s limited temperature range. This current project utilized the protocol established in the previous phase to evaluate next-generation lithium-ion battery technologies for use in cold regions. Selected battery technologies met necessary military specifications for use in large military combat vehicles and were evaluated using a mechanical load system developed in previous work to simulate the starting of a Stryker engine. This work also evaluated the performance of the existing battery technology of a Stryker under Alaskan winter temperatures, which will verify the accuracy of the simulated cold room testing on the mechanical load system. The results of the tests showed that while the system was able to reliably operate down to −20°C, the battery management system encountered challenges at the lower end of the temperature range. This technology has a potential to reliably support cold regions operations but needs further evaluation.

7 Nov 2022

Dissolution of NTO, DNAN, and Insensitive Munitions Formulations and Their Fates in Soils: SERDP ER-2220

Abstract: The US military is interested in replacing TNT (2,4,6-trinitrotoluene) and RDX (1,3,5-hexahydro-1,3,5-trinitro-1,3,5-triazine) with DNAN (2,4-dinitroanisole) and NTO (3-nitro-1,2,4-triazol-5-one), which have similar explosive characteristics but are less likely to detonate unintentionally. Although these replacements are good explosives, basic information about their fate and transport was needed to evaluate their environmental impact and life-cycle management. This project measured their dissolution, photodegradation, and how aqueous solutions interact with soils, data critical to determining exposure potential and, consequently, risk.

4 Nov 2022

Environmentally Informed Buried Object Recognition

The ability to detect and classify buried objects using thermal infrared imaging is affected by the environmental conditions at the time of imaging, which leads to an inconsistent probability of detection. For example, periods of dense overcast or recent precipitation events result in the suppression of the soil temperature difference between the buried object and soil, thus preventing detection. This work introduces an environmentally informed framework to reduce the false alarm rate in the classification of regions of interest (ROIs) in thermal IR images containing buried objects. Using a dataset that consists of thermal images containing buried objects paired with the corresponding environmental and meteorological conditions, we employ a machine learning approach to determine which environmental conditions are the most impactful on the visibility of the buried objects. We find the key environmental conditions include incoming short-wave solar radiation, soil volumetric water content, and average air temperature. For each image, ROIs are computed using a computer vision approach and these ROIs are coupled with the most important environmental conditions to form the input for the classification algorithm. The environmentally informed classification algorithm produces a decision on whether the ROI contains a buried object by simultaneously learning on the ROIs with a classification neural network and on the environmental data using a tabular neural network. On a given set of ROIs, we have shown that the environmentally informed classification approach improves the detection of buried objects within the ROIs.

2 Nov 2022

Willis Coupling in One-dimensional Layered Bulk Media

Abstract: Willis coupling, which couples the constitutive equations of an acoustical material, has been applied to acoustic metasurfaces with promising results. However, less is understood about Willis coupling in bulk media. In this paper a multiple-scales homogenization method is used to analyze the source and interpretation of Willis coupling in one-dimensional bulk media without any hidden degrees of freedom, or one-dimensional layered media. As expected from previous work, Willis coupling is shown to arise from geometric asymmetries, but is further shown to depend greatly on the measurement position. In addition, a discussion of the predicted material properties, including Willis coupling, of macroscopically inhomogeneous media is presented.

25 Oct 2022

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.

13 Oct 2022

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.

11 Oct 2022

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.

6 Oct 2022

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.

5 Oct 2022

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.