30 Apr 2025

Corps Shoaling Analysis Tool (CSAT) User Guide

Abstract: The Corps Shoaling Analysis Tool (CSAT) is a suite of computational routines for evaluating shoaling rates in navigation channels maintained by the US Army Corps of Engineers (USACE). This is achieved using survey data from the eHydro enterprise hydrographic survey database. At the local scale, CSAT’s outputs are useful for understanding historical shoaling trends and identifying shoaling hotspots, while enterprise-level shoaling forecasts support Operations and Maintenance (O&M) planning over a 5-year time horizon. This user guide provides practical, step-by-step instructions for new CSAT users who wish to download, install, and run the tool. Later sections provide insight into CSAT’s advanced features while also describing the methods and assumptions that underlie the calculations.

29 Apr 2025

Tools for Inlet Geomorphic Mapping: An Overview and Application at East Pass, Florida and Fire Island Inlet, New York

Abstract: The purpose of this Coastal and Hydraulics Engineering Technical Note (CHETN) is to highlight emerging tools for inlet geomorphic mapping and describe the workflows used to implement the tools. The Coastal Inlets Research Program (CIRP) maintains the US Coastal Inlets Atlas, which houses technical information (e.g., physical processes, navigation channel position, federal authorization for management purposes) on tidal inlets. Future expansion of the Atlas should include ready-made products that address a call from coastal inlet managers and practitioners to map inlet geomorphic change and features more accurately. The methods and workflows demonstrated in this document represent the first step towards expanding the US Coastal Inlets Atlas.

29 Apr 2025

Toward Objectives and Metrics for Supporting US Army Corps of Engineers Civil Works Asset Management Decision-Making Tradeoffs

Abstract: The United States Army Corps of Engineers (USACE) is responsible for the maintenance, repair, and replacement of $250 billion worth of assets. As budgets shrink and infrastructure becomes increasingly costly to maintain, USACE Civil Works (CW) must develop innovative asset management (AM) strategies to sustain these assets while also delivering maximum value to USACE and the nation. As a result, USACE-CW AM is seeking metrics capable of demonstrating the benefit of maintenance, repair, and replacement project alternatives for all USACE business lines (BLs) to support budget decision-making. This report presents 10 objectives and 51 metrics for potential use in a future USACE-CW value model. This report describes the structure and function of USACE-CW as it relates to the budget decision-making process. Next, past attempts at revising the budget decision-making process are reviewed, and the current budget framework is examined. Last, 10 objectives and 51 associated metrics are presented that represent the mission of USACE-CW and measure the attainment of this mission. Collectively, this information can support budget decision-making by helping facilitate portfolio decision analytics, resulting in a defensible decision-making process and yielding high-value budget decisions.

25 Apr 2025

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.

21 Apr 2025

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.

21 Apr 2025

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.

17 Apr 2025

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.

16 Apr 2025

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.

15 Apr 2025

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.

15 Apr 2025

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.