12 Mar 2025

Old River Control Low Sill Structure: Monitoring and Performance

Abstract: The Old River Low Sill Structure (ORLSS) is located approximately 25 mi south of Vidalia, LA, and is part of the Old River Control Complex. The structure is founded on steel piles and is a 566-foot-long concrete structure constructed in 1959. The structure resembles a dam with 11, 44-foot-wide gates to prevent migration of the Mississippi River’s current course to a hydraulically shorter course down the Atchafalaya River. A re-analysis was undertaken by the US Army Engineer Research and Development Center to investigate the current level of stability and the potential for adjusting the operating limitations placed on the structure because of damage during the 1973 flood. The investigation was performed by reviewing the design and post-design stability analyses, analyzing performance data, and performing an updated stability analysis. The stability analysis was performed with monitoring data that spanned several decades. Using historic monitoring data in the stability analysis, with a wide range of loading conditions, it was shown that uplift conditions were not as severe as previously considered. Performance data coupled with the stability analysis show that the structural performance supports the current operating conditions.

6 Mar 2025

Effect of Fighter Aircraft Traffic on Full-Depth Reclamation with Thin Surface Layers

Abstract: The US Army Engineer Research and Development Center (ERDC) constructed a full-scale test section to evaluate the effectiveness of different pavement surface technologies in sustaining fighter aircraft traffic. A deteriorated thin asphalt pavement was recycled utilizing full-depth reclamation (FDR) techniques with cement stabilization. Relatively thin surfacing solutions constructed with either conventional hot mix asphalt (HMA) or nontraditional surface materials were placed on the FDR layer and trafficked with a single-wheel F-15 load cart. Rutting behavior, instrumentation response, and nondestructive evaluation measurements were monitored during traffic. Experimental results showed that thin surface treatments and microsurfacing materials placed on FDR layers were capable of supporting an extremely limited number of F-15 operations, and the generation of foreign object debris (FOD) was a major concern. A 4 in. thick HMA layer was required to sustain a meaningful number of F-15 operations, that is, approximately 3,000, and a 2 in. thick HMA layer was required to sustain approximately 100 F-15 passes. An analysis using the Airfield Pavement Evaluation subroutine in PCASE suggested that existing stabilized equivalency factors were reasonable when the minimum asphalt layer thickness was specified. A reduced equivalency factor was observed when the asphalt layer thickness was less than the minimum thickness.

3 Mar 2025

Full-Depth Reclamation Equipment Evaluation and Expedient Pavement Reconstruction Process Development

Abstract: Full-depth reclamation (FDR) is a rehabilitation approach that can be readily applied to rapidly restore the structural capacity of heavily distressed or structurally deficient airfield asphalt pavements. This report presents a market survey of compact FDR construction equipment that could be deployed in contingency environments. Current equipment inventories from the US Air Force and Marine Corps were reviewed to identify gaps in terms of equipment for pavement reconstruction via the FDR technique. Additionally, a field demonstration was conducted to assess the effectiveness and productivity of FDR reclaimers on representative airfield asphalt pavements. A preliminary reconstruction process and a spreadsheet based calculator were developed to estimate construction times for the FDR technique. Examples of pavement reconstruction scenarios were generated to illustrate the FDR process as well as identify an approach with optimized construction times. The information in this report aims to assist in the implementation of reconstruction specifications for the FDR technique as applicable to expedient construction projects in contingency environments.

28 Feb 2025

The 2023 Joint Airfield Damage Repair Symposium (JADRS) at Fort Liberty, North Carolina

Abstract: The US Army Engineer Research and Development Center (ERDC) and the 20th Engineer Brigade, 27th Engineer Battalion, executed the Joint Airfield Damage Repair Symposium from 5 to 14 June 2023. The event was a training experience for personnel executing pavement-repair tasks and a planning and coordination exercise for senior military and civilian leaders developing technologies and plans for airfield damage repair (ADR). The participants included 14 trainers, 8 staff members, 48 observers, and 145 trainees from the US Army, Air Force, Navy, and Marines. The Military Occupational Specialty of most Army trainees was 12N, Horizontal Construction Engineer. The symposium also included a workshop attended by more than 20 organizations representing all branches of the US Military. Breakout sessions were used to develop strategies to address gaps in ADR materials, training, and doctrine. At the end of the symposium, the 27th Engineer Battalion identified needs for an updated joint doctrine detailing the capabilities residing within each service branch and defining their roles and responsibilities, equipment up-grades based on commercially available products that would enhance efficiency for ADR missions, positioning ADR materials in strategic locations to reduce the logistical burden of delivery, and lighter, more expeditionary ADR kits across each service.

28 Feb 2025

Repair of Damaged Continuity Joints Using Ultra-High Performance, Fiber Reinforced Self-Consolidating, and Magnesium–Aluminum–Liquid–Phosphate Concretes

Abstract: Bridge elements known to develop damage over time are individual continuity joints connecting girders. Replacing damaged joints is an expensive and invasive process and a need exists to design a less invasive repair method. This study focused on evaluating an encapsulation repair method for continuity joints that would not require extensive demolition of the bridge deck to implement and could potentially be constructed without bridge closure. Approximately half scale connected bridge girder specimens were constructed and purposely damaged to create similar crack patterns to those seen in bridges. Once damaged, a set of three specimens was repaired using the encapsulation method with three different high performance materials, ultra-high performance concrete (UHPC), fiber reinforced self-consolidating concrete (FRSCC), and magnesium–aluminum–liquid–phosphate (MALP) concrete. Of the three repaired specimens for each material, one was tested in positive moment bending and two in negative moment bending, similar to in situ conditions. The results appear to indicate that using each of the tested materials as an encapsulation repair for damaged continuity joints is viable to re-establish continuity and load capacity. However, the UHPC repairs’ resistance to cracking could indicate the best performance by further protecting the continuity joint reinforcing steel from water ingress.

30 Jan 2025

Rapid Assessment Tools for Estimating Trafficability of Low Volume Roads

Abstract: Rapid assessment of low-volume road surfaces remains a challenge when attempting to forecast allowable vehicle crossings. Variations in soil type, compaction effort, and moisture content of the soil can greatly affect trafficability, and predictive equations for soil deformation under vehicle loads often have reduced reliability for low-strength materials. Portable tools to characterize soil stiffness and corresponding relationships to load-induced deformation are needed. In this effort, researchers performed comparative testing of multiple rapid assessment tools as potential devices for giving estimations of vehicle trafficability. The test devices included a Clegg hammer and light weight deflectometer as instruments that measure response from impulse loading. Silty sand with and without chemical stabilization (using cement) at varying moisture content were used for testing. These soil states represented very weak conditions capable of supporting fewer than 50 vehicle passes to moderate strength conditions capable of supporting several thousand vehicle passes. Data from full-scale tests were used to correlate allowable traffic with data obtained from the rapid assessment tools. Recommendations from the effort include ranges of response data to categorize low-volume road surfaces based on their ability to handle ranges of vehicle loadings.

30 Jan 2025

Improved Trafficability Over Soft Soils Using Ground Matting

Abstract: Soft soils pose mobility challenges, even for vehicles designed with superior off-road capabilities. When numerous vehicles travel the same path, permanent deformation of the soil can result in rut depths that exceed vehicle ground clearance. These challenges can be overcome by modifying ground conditions to improve bearing capacity or spreading wheel loads over a greater area. Researchers at the U.S. Army Engineer Research and Development Center conducted field tests to quantify the performance benefits of a ground matting system made of connected fiberglass panels designed to improve vehicle mobility on soft soils. Soil conditions included silt, sand, and highly organic soil with varying strength. Test vehicles included wheeled trucks with gross weights of approximately 6350 kg per axle. Performance of the matting system was assessed by the number of allowable vehicle crossings with and without matting present. Results from testing showed that allowable number of vehicles increased by at least a factor of ten on the weakest soils. Data presented herein includes geotechnical site characterization, soil deformation as a function of traffic, and material characteristics for the fiberglass matting system.

17 Dec 2024

Full-Scale Demonstration of the Modernized Bridge Supplemental Set

Abstract: The Overhead Cable System (OCS) serves as the main anchorage system of the Bridge Supplemental Set and is used to hold the Improved Ribbon Bridge (IRB) against river flow. Several improvements have been made to OCS components and employment procedures, theoretically allowing the OCS to operate safely within most environments. However, the modernized OCS had yet to be constructed over an actual river, making it necessary to conduct a full-scale capability demonstration. Range W2 of Camp Ripley was selected as the test site because the 200th Multi-Role Bridge Company agreed to support the demonstration during an ongoing training cycle. A site reconnaissance trip revealed environmental obstacles on each bank, which made the site a unique test for the modernized OCS. The OCS model, a software package developed to analyze the loading imposed by river drag force on the OCS, was used to design a unique layout that circumvents Camp Ripley’s environmental challenges. The OCS was successfully deployed over Camp Ripley’s wet gap flowing at a river speed of 3.5 ft/s, and the IRB supported vehicular traffic for 3 hr before safe disassembly. Several lessons were learned regarding system deployment, and data were collected to facilitate technical manual development.

19 Nov 2024

Deep Learning Approach for Accurate Segmentation of Sand Boils in Levee Systems

Abstract: Sand boils can contribute to the liquefaction of a portion of the levee, leading to levee failure. Accurately detecting and segmenting sand boils is crucial for effectively monitoring and maintaining levee systems. This paper presents SandBoilNet, a fully convolutional neural network with skip connections designed for accurate pixel-level classification or semantic segmentation of sand boils from images in levee systems. In this study, we explore the use of transfer learning for fast training and detecting sand boils through semantic segmentation. By utilizing a pretrained CNN model with ResNet50V2 architecture, our algorithm effectively leverages learned features for precise detection. We hypothesize that controlled feature extraction using a deeper pretrained CNN model can selectively generate the most relevant feature maps adapting to the domain, thereby improving performance. Experimental results demonstrate that SandBoilNet outperforms state-of-the-art semantic segmentation methods in accurately detecting sand boils, achieving a Balanced Accuracy (BA) of 85.52%, Macro F1-score (MaF1) of 73.12%, and an Intersection over Union (IoU) of 57.43% specifically for sand boils. This proposed approach represents a novel and effective solution for accurately detecting and segmenting sand boils from levee images toward automating the monitoring and maintenance of levee infrastructure.

19 Nov 2024

Widened Attention-Enhanced Atrous Convolutional Network for Efficient Embedded Vision Applications under Resource Constraints

Abstract: Onboard image analysis enables real-time autonomous capabilities for unmanned platforms including aerial, ground, and aquatic drones. Performing classification on embedded systems, rather than transmitting data, allows rapid perception and decision-making critical for time-sensitive applications such as search and rescue, hazardous environment exploration, and military operations. To fully capitalize on these systems’ potential, specialized deep learning solutions are needed that balance accuracy and computational efficiency for time-sensitive inference. This article introduces the widened attention-enhanced atrous convolution-based efficient network (WACEfNet), a new convolutional neural network designed specifically for real-time visual classification challenges using resource-constrained embedded devices. WACEfNet builds on EfficientNet and integrates innovative width-wise feature processing, atrous convolutions, and attention modules to improve representational power without excessive over-head. Extensive benchmarking confirms state-of-the-art performance from WACEfNet for aerial imaging applications while remaining suitable for embedded deployment. The improvements in accuracy and speed demonstrate the potential of customized deep learning advancements to unlock new capabilities for unmanned aerial vehicles and related embedded systems with tight size, weight, and power constraints. This research offers an optimized framework, combining widened residual learning and attention mechanisms, to meet the unique demands of high-fidelity real-time analytics across a variety of embedded perception paradigms.