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Archive: April, 2025
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  • Analysis Tools and Techniques for Evaluating Quality in Synthetic Data Generated by the Virtual Autonomous Navigation Environment

    Abstract: The capability to produce high-quality labeled synthetic image data is an important tool for building and maintaining machine learning datasets. However, ensuring computer-generated data is of high quality is very challenging. This report describes an effort to evaluate and improve synthetic image data generated by the Virtual Autonomous Navigation Environment’s Environment and Sensor Engine (VANE::ESE), as well as documenting a set of tools developed to process, analyze, and train models from, image datasets generated by VANE::ESE. Additionally, the results of several experiments are presented, including an investigation into using explainable AI techniques, and direct comparisons of various models trained on multiple synthetic datasets.
  • Potential Benefits of Subaqueous Soil Data on Department of Defense Installations

    Purpose: Many domestic and international US Department of Defense (DoD) installations are located in coastal areas. Recent advances in the classification and mapping of subaqueous soils, which occur in shallow freshwater and marine environments, has the potential to benefit US military operations in several different ways. This technical note communicates the importance of subaqueous soil classification and describes how subaqueous soil information can inform the management of natural resources, infrastructure and transportation, mitigation of coastal storm risk, protection of the coast from natural threats, and the understanding of nearshore environments in the US and abroad.
  • Evaluation of NiTech FG-NDGB Pelletized Asphalt for Rapid Airfield Damage Recovery Applications

    Purpose: The NiTech Corporation’s FG-NDGB Pelletized Asphalt (PA), herein referred to as NiTech PA, was identified as a surfacing material for Rapid Airfield Damage Recovery (RADR) applications by the US Air Force Civil Engineer Center (AFCEC). AFCEC tasked the US Army Engineer Research and Development Center (ERDC) with evaluating NiTech PA by conducting full-scale crater repairs and applying simulated F-15E aircraft loads. The properties of the repair material were also to be obtained via laboratory characterization testing.
  • Assessment of Neural Network Augmented Reynolds Averaged Navier Stokes Turbulence Model in Extrapolation Modes

    Abstract: A machine-learned model enhances the accuracy of turbulence transport equations of RANS solver and applied for periodic hill test case. The accuracy is investigated in extrapolation modes. A parametric study is also performed to understand the effect of network hyperparameters on training and model accuracy and to quantify the uncertainty in model accuracy due to the non-deterministic nature of the neural network training. For any network, less than optimal mini-batch size results in overfitting, and larger than optimal reduces accuracy. Data clustering is an efficient approach to prevent the machine-learned model from over-training on more prevalent flow regimes, and results in a model with similar accuracy. Turbulence production is correlated with shear strain in the free-shear region, with shear strain and wall-distance and local velocity-based Reynolds number in the boundary layer regime, and with streamwise velocity gradient in the accelerating flow regime. The flow direction is key in identifying flow separation and reattachment regime. Machine-learned models perform poorly in extrapolation mode. A priori tests reveal model predictability improves as the hill dataset is partially added during training in a partial extrapolation model. These also provide better turbulent kinetic energy and shear stress predictions than RANS in a posteriori tests. Before a machine-learned model is applied for a posteriori tests, a priori tests should be performed.
  • Sensor Fusion for Aerial Robotic Systems

    Abstract: As uncrewed aerial vehicle (drone) use expands across industries so also does the complexity of sensor payloads. At present, there are no commercially available products for the management and fusion of multisensor data. Sensor Fusion for Aerial Robotic Systems (SFARS) is a sensor agnostic, modular platform for intelligent multisensor data fusion and processing. At the time of writing, SFARS exists as a root codebase, a PC application for processing of previously collected drone data and as a prototype hardware platform for real-time drone deployment. This report serves as a technical users guide to the design, development, and implementation of the suite of SFARS software.
  • Resilience and Efficiency for the Nanotechnology Supply Chains Underpinning COVID-19 Vaccine Development

    Abstract: Nanotechnology facilitated the development and scalable commercialization of many SARS-CoV-2 vaccines. However, the supply chains underpinning vaccine manufacturing have demonstrated brittleness at various stages of development and distribution. Whereas such brittleness leaves the broader pharmacological supply chain vulnerable to significant and unacceptable disruption, strategies for supply chain resilience are being considered across government, academia, and industry. How such resilience is understood and parameterized, however, is contentious. Our review of the nanotechnology supply chain resilience literature, synthesized with the larger supply chain resilience literature, analyzes current trends in implementing and modeling resilience and recommendations for bridging the gap in the lack of quantitative models, consistent definitions, and trade-off analyses for nano supply chains.
  • Smart Cities–A Structured Literature Review

    Abstract: Smart cities are rapidly evolving concept-transforming urban developments. They use advanced technologies and data analytics to improve quality of life, increase efficiency of infrastructure and services, and promote sustainable economic growth. They integrate multiple domains to create an interconnected and intelligent urban environment. The implementation of smart city solutions in international contexts was also analyzed and proposes strategies to overcome implementation challenges. The integration of technology and data-driven solutions has potential to revolutionize urban living by providing personalized and accessible services. However, it also presents challenges, including data privacy concerns, unequal access to technology, and the need for collaboration across private, public, and government sectors. This study provides insights into the current state and future prospects of smart cities and presents an analysis of challenges and opportunities. We also propose a concise definition for smart cities: “Smart cities use digital technologies, communication technologies, and data analytics to create an efficient and effective service environment that improves urban quality of life and promotes sustainability.” As cities grow and face increasingly complex challenges, the integration of advanced technologies and data-driven solutions can create more sustainable communities.
  • Review of Mississippi River Sediment-Sampling Protocols

    Abstract: The Mississippi River sediment data protocols located in the US Army Corps of Engineer (USACE), St Louis, Memphis, Vicksburg, and New Orleans Districts, were reviewed and evaluated. The review included both USACE and US Geological Survey (USGS) sampling sites. The purpose of this review was to evaluate the reported historical sediment data and to provide guidance for moving forward with an accurate and consistent sediment data collection program. The review was focused on the reliability of the reported historical data and its usefulness for use in sedimentation studies related to long-term aggradation, degradation, and dredging. Recommendations to implement effective sediment data collection, laboratory analyses, and reporting were provided.
  • Living Shoreline in USACE Projects: A Review

    Abstract: The term living shoreline (LS) refers to the practice of shoreline stabilization using natural elements (e.g., vegetation, oysters, logs, etc.) in a way that maintains continuity and connectivity between terrestrial and aquatic habitats. This report provides a review of LS practices to assess the applicability of these engineering techniques for US Army Corps of Engineers (USACE) projects. Specifically, this review examines the current state of knowledge regarding LS efforts through evaluation of peer-reviewed literature, agency reports, web tools, applications, and relevant guidance. It is important to gain a deeper understanding of the potential ecological, engineering, environmental, and socioeconomic benefits in comparison with traditional gray infrastructure shoreline stabilization techniques. The National Oceanic and Atmospheric Administration (NOAA) encourages the use of LS as a shoreline stabilization technique along sheltered coasts (i.e., coasts not exposed to open ocean wave energy) to preserve and improve habitats and maintain their ecosystem services at the land–water interface. Research has examined aspects of LSs, but there are relevant knowledge gaps yet to be explored. Overall, there is a lot of information from different sources on LSs with limited application to USACE projects. Therefore, a consolidated planning and design consideration report specific to USACE is recommended.
  • Field Evaluations of Diquat for Controlling Submersed Flowering Rush in Lake Pend Oreille, Idaho

    Abstract: The invasive plant flowering rush (Butomus umbellatus L.) was first observed in Lake Pend Oreille, Idaho, within the Columbia River basin in 2008, and it covered several hundred hectares by 2016. Dense infestations of this perennial weed destroy native plant communities and seriously degrade fish and wildlife habitat. Sometimes growing as an emergent on saturated soils or in shallow water, the plant also forms persistent submersed stands in deeper water, which is the typical growth form in Lake Pend Oreille. In 2016, field trials evaluated the herbicide diquat dibromide, formulated as the product Reward, for controlling submersed flowering rush. A 4 ha plot in Oden Bay was treated with diquat at a rate of 18.7 L/ha in late summer 2016 and again in 2017 using a subsurface injection method by boat. Water exchange processes were measured in treated plots in 2017 with rhodamine WT dye mixed with the herbicide. Flowering rush shoots were reduced by 87% in 2016 and 29% in 2017. No adverse effects were measured on water quality (temperature, dissolved oxygen, pH, and conductivity). Diquat should be added to the project’s operational management strategy for controlling flowering rush in Lake Pend Oreille.