10 Jun 2022

Operations & Maintenance (O&M) Facility Data Exchange Pilot Expansion to BUILDER SMS

Abstract: The Army has many enterprise Operation and Maintenance (O&M) systems that require manual input of the same facility data collected through-out the facility life cycle. This manual input of data costs Army installations valuable time and labor. A standardized approach to deliver the O&M information in a consistent, accurate, timely, and digital method for expedited input into the numerous systems is needed. A United States Army Corps of Engineers (USACE)-led team consisting of O&M subject matter experts within USACE and industry developed a standardized process for collecting and exchanging facility data for downstream applications. The process is defined in the Engineering and Construction Bulletin (ECB) 2018-6 and includes utilization of Unified Facilities Guide Specification (UFGS) 01 78 24.00 10. An initial pilot study verified that asset data collected during facility construction could effectively be imported into the Army General Fund Enterprise Business System (GFEBS). This second pilot study focused on facilitating the import of facility asset and equipment data collected during construction into the BUILDER Sustainment Management System (SMS) web-based software application. The project scope included investigation of current Army installations’ processes as they relate to BUILDER SMS as well as initial testing of information transfer approaches.

10 Jun 2022

Inland Waterway Network Mapping of AIS Data for Freight Transportation Planning

Abstract: Travel demand models (TDMs) with freight forecasts estimate performance metrics for competing infrastructure investments and potential policy changes. Unfortunately, freight TDMs fail to represent non-truck modes with levels of detail adequate for multi-modal infrastructure and policy evaluation. Recent expansions in the availability of maritime movement data, i.e. Automatic Identification System (AIS), make it possible to expand and improve representation of maritime modes within freight TDMs. AIS may be used to track vessel locations as timestamped latitude–longitude points. For estimation, calibration and validation of freight TDMs, this work identifies vessel trips by applying network mapping (map-matching) heuristics to AIS data. The automated methods are evaluated on a 747-mile inland waterway network, with AIS data representing 88% of vessel activity. Inspection of 3820 AIS trajectories was used to train the heuristic parameters including stop time, duration and location. Validation shows 84·0% accuracy in detecting stops at ports and 83·5% accuracy in identifying trips crossing locks. The resulting map-matched vessel trips may be applied to generate origin–destination matrices, calculate time impedances, etc. The proposed methods are transferable to waterways or maritime port systems, as AIS continues to grow.

2 Jun 2022

Probabilistic Neural Networks that Predict Compressive Strength of High Strength Concrete in Mass Placements using Thermal History

Abstract: This study explored the use of artificial neural networks to predict UHPC compressive strengths given thermal history and key mix components. The model developed herein employs Bayesian variational inference using Monte Carlo dropout to convey prediction uncertainty using 735 datapoints on seven UHPC mixtures collected using a variety of techniques. Datapoints contained a measured compressive strength along with three curing inputs (specimen maturity, maximum temperature experienced during curing, time of maximum temperature) and five mixture inputs to distinguish each UHPC mixture (ce-ment type, silicon dioxide content, mix type, water to cementitious material ratio, and admixture dosage rate). Input analysis concluded that predictions were more sensitive to curing inputs than mixture inputs. On average, 8.2% of experimental results in the final model fell outside of the predicted range with 67.9%of these cases conservatively underpredicting. The results support that this model methodology is able to make sufficient probabilistic predictions within the scope of the provided dataset but is not for extrapo-lating beyond the training data. In addition, the model was vetted using various datasets obtained from literature to assess its versatility. Overall this model is a promising advancement towards predicting mechanical properties of high strength concrete with known uncertainties.

26 May 2022

Growth Assessments of Starry Stonewort (Nitellopsis obtusa) in Various Substrate Types for Large-scale Cultivation Studies

Purpose: The purpose of this study was to compare multiple substrate types to optimize cultivation conditions for the invasive macroalga Nitellopsis obtusa (Desv. in Loisel.) J. Groves, commonly known as starry stonewort. Large-scale cultivation will allow for tiered approaches to management evaluation research while minimizing the influence of confounding variables.

26 May 2022

Spatial and Temporal Variability of the Alligatorweed Pathogen, Alternaria alternantherae, in Louisiana

Abstract: Alligatorweed leaf spot is a disease of invasive Alternanthera philoxeroides(Alligatorweed) in the southern US, caused by Alternaria alternantherae. However, little is known about when or where this pathogen naturally occurs. To better understand this species’life history, we examined temporal (every 2–3 weeks) and spatial (latitudinal) patterns of A. alternantherae occurrence at sites in Louisiana for 2 y. Pathogen presence reflectedclear within-year temporal and spatial patterns. Overall, the percentage of leaves infectedwith A. alternantherae was low during spring each year (0–20% infected) but increasedthroughout summer (maximum of 50% infected), and plants in northern sites had lowerfrequency of infection relative to southern sites until later in the year (late summer/early fall) but only in 1 of the 2 years of our study. The mean proportion of leaves infected with A. alternantherae declined with latitude both years (P = 0.01) and variability increasedwith latitude (P = 0.04), a pattern suggestive of range limitation in northern areas. We estimate a northern distributional limit of 34°N for A. alternantherae in Louisiana, but Alligatorweed occurs farther north. Although we did not directly examine disease impacts to Alligatorweed during the study, they may be greatest in southern areas, where the pathogenis more common early and throughout the growing season, and thus may be less likely to provide control in northern infestations of the invasive Alligatorweed.

25 May 2022

Improving Container Shipment Analysis

Abstract: US Army Corps of Engineers (USACE) deep-draft navigation economic analyses use assumptions about the sensitivity of vessel operations to channel modification to estimate national economic development benefits. The complexity and proprietary nature of carrier deployment decisions and loading practices adds uncertainty to USACE navigation studies. This report attempts to provide an overview of containership deployment and loading practices as it relates to USACE navigation studies to improve the quality of deep-draft economics. The report relies on trade data, vessel order books, and carrier interviews to study the impact of channel modification on vessel loading and deployment. The report makes recommendations for developing deployment and loading inputs for future economic evaluations.

23 May 2022

Ballistic Protection Using Snow

Abstract: Small (5.56 mm, 7.62 mm and 9 mm) and medium (12.7 mm) arms rounds were fired at snow-filled 1.5m cubic gabions in a mid-winter condition in Fairbanks, Alaska. The rounds were excavated and penetration by each ammunition type was measured. A distribution and average of penetration depth was determined. All 320 rounds fired were captured within 1.5m after entering the snow barrier. Comparison with published models of ballistics penetration of snow showed mixed results with several matching our data within 10% and all but one within 32%. However, most of these models are simplistic in that they accommodate limited variables and therefore may not be expected to perform well in all settings. We conclude that snow-based ballistics protection structures can be quickly and efficiently erected in suitable environments and with minimal size, can provide reliable protection against small and medium arms fire.

20 May 2022

Southern Flying Squirrels (Glaucomys volans) as Major Predators of Avian Nest Boxes

Abstract: Bird population dynamics are strongly affected by the ability to successfully reproduce, and nest predation is the primary cause of reproductive failure for most birds. Efforts to understand nest predation and manage its effects on species of conservation concern require knowledge of the ecology of associated predator assemblages. Recently, studies using cameras to record events at nests have illuminated this previously under-studied avian life stage, but such studies have been largely limited to open-cup nests. Cavity nests may be depredated by a different suite of predators and incubating or brooding females occupying such nests may be more vulnerable to predation relative to open-cup nests. Here, we used motion-activated, infrared trail cameras to record predators of artificial nest boxes in a Pinus palustris Mill. (Longleaf Pine) forest in southern Alabama. Although Glaucomys Volans L. (Southern Flying Squirrel) have only rarely been captured on film preying on nests, we found them to be responsible for the vast majority (84%) of bird-nest depredations at nest boxes, and these depredations contributed to a surprisingly low overall rate of nest success (~20%). These results may have implications for the conservation of birds that nest in artificial cavities in Longleaf Pine forests and highlight the importance of further studies on predator assemblages and their effects on nesting birds.

20 May 2022

Low-Sill Control Structure Gate Load Study

Abstract: The effort performed here describes the process to determine the gate lifting loads at the Low-Sill Control Structure. To measure the gate loads, a 1:55 Froude-scaled model of the Low-Sill Control Structure was tested. Load cells were placed on 3 of the 11 gates. Tests evaluated the gate loads for various hydraulic heads across the structure. A total of 109 tests were conducted for 14 flows with each flow having two gate settings provided by the United States Army Corps of Engineers, New Orleans District. The load data illustrated the potential for higher gate lifting loads (GLL) to occur at the mid-range gate opening (Go) for Gates 3 and 6. While for Gate 10, the highest GLL (452 kips, maximum load in testing) was at a Go = 4.2 ft. Conversely, for the low-flow bays, the highest load occurred at Go = 24.86 ft.

18 Apr 2022

Sustainable Harmful Algal Bloom Mitigation by 3D Printed Photocatalytic Oxidation Devices (3D-PODs)

Abstract: The impacts of Harmful Algal Blooms (HAB), often caused by cyanobacteria (Figure 1), on water resources are increasing. Innovative solutions for treatment of HABs and their associated toxins are needed to mitigate these impacts and decrease risks without introducing persistent legacy contaminants that cause collateral ecosystem impacts. This technical note (TN) identifies novel opportunities enabled by Additive Manufacturing (AM), or 3D printing, to produce high surface area advanced material composites to rapidly prototype sustainable environmental solutions for aquatic nuisance species control. This innovative research explores deployment of 3D-printable polymer composite structures containing nano-scale photocatalysts for targeted open water treatment of HABs that are customizable to the site-of-concern and also retrievable, reusable, and sustainable. The approach developed to control cyanobacteria HAB events has the potential to augment or replace broadcast, non-specific chemical controls that otherwise put non-target species and ecological resources at long-term risk. It can also augment existing UV-treatment HAB treatment control measures. The expected research outcome is a novel, effective, and sustainable HAB management tool for the US Army Corps of Engineers (USACE) and resource managers to deploy in their HAB rapid response programs. The research will provide a framework for scale-up into other manufacturing methods (e.g., injection molding) to produce the devices in bulk (quickly and efficiently). Research for this project title “Mitigation of Harmful Algal Bloom Toxins using 3D Printed Photocatalytic Materials (FY21-23)” was sponsored by the US Army Engineer Research Development Center’s (ERDC) Aquatic Nuisance Species Research Program (ANSRP).