7 May 2026

An All-Hazards Return on Investment (ROI) Model to Evaluate U.S. Army Installation Resilient Strategies

Abstract: The paper describes our project to develop, verify, and deploy an All-Hazards Return of Investment (ROI) model for the U.S. Army Engineer Research and Development Center (ERDC) to provide army installations with a decision support tool for evaluating strategies to make existing installation facilities more resilient. The need for increased resilience to extreme weather caused by climate change was required by U.S. code and DoD guidance, as well as an army strategic plan that stipulated an ROI model to evaluate relevant resilient strategies. During the project, the ERDC integrated the University of Arkansas designed model into a new army installation planning tool and expanded the scope to evaluate resilient options from climate to all hazards. Our methodology included research on policy, data sources, resilient options, and analytical techniques, along with stakeholder interviews and weekly meetings with installation planning tool developers. The ROI model uses standard risk analysis and engineering economics terms and analyzes potential installation hazards and resilient strategies using data in the installation planning tool. The ROI model calculates the expected net present cost without the resilient strategy, the expected net present cost with the resilient strategy, and ROI for each resilient strategy. The minimum viable product ROI model was formulated mathematically, coded in Python, verified using hazard scenarios, and provided to the ERDC for implementation.

4 May 2026

An Investigation of Causes of Inaccuracy of Infrared Radiation Cameras for Large-Scale Additive Manufacturing Applications

Abstract: In additive manufacturing, accurate temperature data are needed for both real-time feedback for print operators and understanding the thermomechanical behavior for prediction and part quality characterization. Through the collection of accurate temperature data, thermal models can be validated to predict process-induced properties of parts. Infrared radiation (IR) is used to determine the temperature of a surface. Because IR cameras measure thermal radiation from a distance without contact, they are safe to use in high-temperature environments like 3D printing. An investigation of reported temperature values for multiple cameras during one print showed a decreasing trend for cameras close to the printer’s heat sources, which was not reflective of the printing process, and a discrepancy of ±20°C when printing at 200°C across overlapping camera views. Two more prints were studied to determine whether this camera behavior was unique to that print and geometry. The analysis showed the same results across all three prints, with camera-reported values having inconsistencies for a single layer, a subset of layers, and the scale of the print. Multiple possibilities for the cameras’ variances were explored. The IR cameras were determined to require further calibration and experimentation before reported temperature values can be treated as physical temperature values.

29 Apr 2026

Deep Learning Approaches for Buried Object Detection in Infrared Imagery

Abstract: Artificial intelligence and machine learning techniques are increasingly utilized to detect buried objects in thermal infrared imagery. This task relies heavily on the quality and diversity of the training dataset, requiring datasets that capture variability present in real-world environments. Synthetic imagery offers a means to expose algorithms to a greater range of conditions than is often available in real-world data alone. This study evaluates the performance of three open-source object detection models—Faster Region-Based Convolutional Neural Network (R-CNN), You Only Look Once (YOLOv8), and Single Shot Multibox Detector—trained using real-world, synthetic, and hybrid datasets. Real-world imagery was collected from a single field site, while synthetic data were generated using the Virtual Environmental Simulation for Physics-Based Analysis software suite. Model performance was evaluated using Intersection over Union and confidence scores. Models trained exclusively on synthetic datasets with limited scene diversity, when tested on real-world imagery from the same location, produce high false-positive and false-negative rates. Detection performance im-proved significantly for Faster R-CNN and YOLOv8 when trained using a hybrid dataset combining real-world and synthetic data. Analysis of red-green-blue histograms revealed differences in pixel intensity distributions between real and synthetic imagery, indicating areas for improving synthetic data generation.

29 Apr 2026

Forward Operating Remote Camera for Engineering—Construction Assurance and Monitoring (FORCE-CAM), Generation 1

Abstract: This research delivered a first-generation, real-time construction monitoring capability, enabling visual situational awareness for off-site subject matter experts. The live-streamed and recorded data can be visualized from a remote computer desktop to aid in identifying non-conformance issues during active paving operations or during concrete damage assessment and repair operations. Experimentation on asphalt paving and skid-steer construction equipment using direct electro-optical and thermal sensors provided validation of the efficacy of this solution.

22 Apr 2026

Statistical Analysis of Large Format Additively Manufactured Polyethylene Terephthalate Glycol with 30% Carbon Fiber Tensile Data

Abstract: In large format additive manufacturing (LFAM), a keener understanding of the relationship between the manufacture method and material temperature dependency is needed for the production of large polymer parts. Statistical analyses supported by material properties and a meso-structural understanding of LFAM are applied to elucidate tensile data trends. The data from LFAM polyethylene terephthalate glycol with 30% carbon fiber (CF) (PETG CF30%) panels (diagonal, horizontal, and vertical in the x-y print plane) and injection-molded specimens tensile tested at six different testing temperatures (room temperature, 40 ◦C, 50 ◦C, 60 ◦C, 70 ◦C, and 80 ◦C) were used for statistical analyses. A standard deviation, a coefficient of variation, and a two-way and one-way analyses of variance (ANOVA) were conducted. The manufacturing method (44.2%) and temperature (47.4%) have a strong effect on the ultimate tensile strength, in which temperature (82.6%) dominates Young’s modulus. To explain the difference between the ultimate tensile strength of vertical, diagonal, and horizontal specimens at room temperature, a visual inspection of the specimen failure was conducted and the maximum stress at the crack tip was calculated analytically. The decreased strength in the diagonal specimens resulted from the reliance on interlaminar adhesion strength. Future work will consider the effect of the void space variation on tensile strength variance.

8 Apr 2026

Powering the Monitorization of Uninterruptible Power Supplies

Purpose: The danger of invasive species and the ecological impact on natural environments can be seen throughout the world. In the United States, the invasive species problem is being addressed in the Mississippi River and the tributaries that feed it where invasive carp were introduced and invaded, threatening native species and ecosystems. To battle invasive species’ movement into naïve watersheds, the underwater Acoustic Deterrent System (uADS) was developed by the US Army Corps of Engineers (USACE) to stem the migration of the invasive carp through navigation locks. This project serves as a vital effort to preserve the natural balance of aquatic life in the Mississippi River and those waterways that are connected to it. The project highlights the crucial need for systems that monitor the health of the hardware that keeps the project alive in the event of power failure or other disasters. The ability for researchers to quickly check the health of various systems, receive notification of failure, and see visualizations of hardware data is indispensable when a failure with a poor response time could allow these species to move through points where the system is in place. This paper will discuss the process of using containerization to address the monitorization needs of such systems and how containerization may allow for systems to be created quickly while still allowing for easy access to the needed data.

23 Mar 2026

Experimental Evaluation of Corroded Steel Beams Retrofitted with Fiber-Reinforced Polymers

Abstract: Corrosion represents one of the main threats to steel structures working in harsh conditions. It compromises the safety and integrity of marine structures, reducing their lifespan and increasing their maintenance cost. Recent studies investigated the use of fiber-reinforced polymers to repair corroded steel structures; however, these studies showed unmatured debonding behavior, stopping short of examining the impact of these repairs on the ductility of different steel elements. In this study, we conduct a series of full-scale experimental tests to investigate the impact of chemical corrosion on steel beams as well as the impact of repairing the beams using carbon fiber–reinforced polymer (CFRP) and basalt fiber–reinforced polymer (BFRP) in enhancing the beams’ structural performance. Corrosion, introduced to the beams’ tension flange and web elements, is used to establish a baseline dataset that captures the impact of repairs on corroded steel surfaces. The results show that the reduction of the flange and web section lowers the beams’ yielding load by 10% and 1%, respectively, compared with a beam with a full cross section. CFRP and BFRP patches can partially restore the corroded beams’ ductility; however, the fracture of the CFRP patches reduces the beam strength by 31% compared with its ultimate strength.

18 Mar 2026

An Updated Irwin Sensor for Measurement of Surface Shear Velocity

Abstract: Accurate and efficient collection of field data related to aeolian processes is critical for improving wind erosion predictions and related management decisions. The Irwin sensor has been used in numerous wind tunnel and field studies to indicate surface shear velocity. However, the sensitivity of the sensor makes them difficult to maintain in a range of environmental conditions. This study presents a new generation of Irwin sensor incorporating updated electronics, battery operation, wireless data transmission, and streamlined field deployment and removal. A total of 20 sensors were manufactured and calibrated in a wind tunnel at the Engineer Research and Development Center. A subset of the sensors was calibrated using a PI-SWERL, which confirmed the two calibration methods converge on similar values for flat smooth test surfaces. The updated sensors were installed around a mesquite shrub at the Jornada Experimental Range, New Mexico, USA from February to July 2023. We found that initial data from the sensors accurately captured spatial patterns of surface shear velocity surrounding the shrub. The improvements to the sensor reduced workload for both deployment and maintenance, and reduced disturbance at the field site. We discuss potential opportunities to use the improved sensor network in a range of geomorphological research areas including quantifying aeolian sediment transport, building and parameterizing wind erosion models that incorporate spatial dependencies, and improving predictive tools for landform change.

25 Feb 2026

AIS Analysis of Waterway Utilization Based on Vessel Type and Class

Abstract: The purpose of this technical note (TN) is to provide an overview of a method used to classify waterway segments based on remotely-sensed vessel traffic on those waterway segments. Vessel traffic was evaluated using data from Automatic Identification System (AIS) broadcasts, which originate at transceivers onboard vessels and can be received by terrestrial shore sites or satellites. AIS is used by most ocean-going commercial vessels, while use by inland vessels varies according to domestic regulations.

18 Feb 2026

Mesh Convergence Study of Adaptive Hydraulics (AdH) Version 5.9

Abstract: This report details performance and convergence tests of the Adaptive Hydraulics (AdH) v5.9 software suite on the Engineer Research and Development Center ONYX Cray X40/50 supercomputer. In particular, the performance of a recently developed monolithic model coupling AdH framework between the Richards equation for variable groundwater and surface water flows or for overland sloped conditions is studied. The effort is part of a quality assurance test of a recently restructured version of AdH. The report also includes a scalability analysis of AdH on a Cray system.