Engineer Research and Development Center - U.S. Army
Recent publications
Climate change and the increasing complexity of society necessitate rethinking of siloed threat scenarios in emergency response planning. Incorporating a compounding threat model into disaster response by leveraging network science techniques and dynamic data can help account for the complexity and disproportionate nature of hurricane impacts.
The use of modular munition storage systems for military purposes has grown significantly in the recent years. They have improved the flexibility and decreased the logistical burden of both domestic and international missions. This study aims at developing a modernized, economic, and effective way of using modular systems to temporarily store munitions in an operational environment. This design had to ensure that (1) no sympathetic detonation of munition stored in adjacent cells would occur, (2) the danger radii due to the fragmentation and the blast overpressure could be reduced, and (3) the proposed solution would be practical. Based on recent events, the use of the HESCO® Bastion, a commonly found modular hardening system in modern operations, will be considered in this research. The combined effects of blast and fragments were both taken into consideration to properly develop and model the loading scenario on the system. Calculations based on analytical models and experimental data were then performed to properly characterize and quantify the system response.
Metallic tungsten (W) is a highly dense material of increasing importance to the U.S. Army as a strategic, non-radioactive replacement for depleted uranium. While there is a growing body of evidence regarding the mechanistic behavior of ionic W (formed after the spontaneous oxidation of metal) in the environment, predicting its environmental fate remains challenging, owing to the widespread geochemical heterogeneity of soils. Therefore, we developed W adsorption prediction models by creating different functional “compositions” of the chemical and physical characteristics for different soil “types” (a non-specific yet commonly used to term to designate different soils). A relatively small dataset consisting of twenty soils (possessing six different soil “types” from across the U.S.) were evaluated for W adsorption behavior. Physical and chemical soil data were separated into water-extracted (WE), bulk, and particle-size distribution (PSD) compositions, and center log-ratio (clr) transformed. Classification models built using extremely randomized trees (ERT) showed that the compositions' accuracies were WE > Bulk > PSD at the Order and Suborder levels. W's adsorption isotherms were constructed using batch equilibrium experiments and modeled against the Langmuir model, where Smax = calculated adsorption maximum, K1/L = inverse Langmuir affinity coefficient. Afterward, both the ERT and ensemble, or stacked, ERT models (by addition of Order and/or Suborder taxonomic labels as ensemble classifiers) were developed for predicting the Smax and K1/L parameters based on the different compositions. In general, model accuracies were substantially increased by the addition of the labels (stacked models). Feature importance calculations pointed to a wide range of potential chemical mechanisms simultaneously controlling W adsorption, laying the groundwork for more detailed in-situ elemental speciation studies. Overall, this work showcased a new technological capability allowing for accurately predicting W adsorption on a wide variety of morphological soil designations. Capsule: This work found that soil morphological designations greatly improved the accuracy of Langmuir adsorption predictions of CoDA-transformed characterization data.
The purpose of this study was to evaluate a proprietary (PUHPC) and non-proprietary (NPUHPC) UHPC mix for chloride ion penetration, freeze–thaw resistance, and scaling resistance to assess durability. Also, large-scale specimens were subjected to an impressed current to accelerate corrosion of embedded reinforcing steel to evaluate the severity of the potential for halo effect when using each concrete as a repair material for aged concrete. Each of the UHPC mixes outperformed conventional concrete in every test. Also, the PUHPC and NPUHPC had similar durability performance, and the NPUHPC outperformed the PUHPC in corrosion resistance, despite having a lower compressive strength.
Insect and pollinator populations are vitally important to the health of ecosystems, food production, and economic stability, but are declining worldwide. New, cheap, and simple monitoring methods are necessary to inform management actions and should be available to researchers around the world. Here, we evaluate the efficacy of a commercially available, close‐focus automated camera trap to monitor insect–plant interactions and insect behavior. We compared two video settings—scheduled and motion‐activated—to a traditional human observation method. Our results show that camera traps with scheduled video settings detected more insects overall than humans, but relative performance varied by insect order. Scheduled cameras significantly outperformed motion‐activated cameras, detecting more insects of all orders and size classes. We conclude that scheduled camera traps are an effective and relatively inexpensive tool for monitoring interactions between plants and insects of all size classes, and their ease of accessibility and set‐up allows for the potential of widespread use. The digital format of video also offers the benefits of recording, sharing, and verifying observations. Declines in insect and pollinator populations have led to a need for high‐quality, accessible monitoring. We found that off‐the‐shelf, close‐range game cameras can significantly improve insect‐plant monitoring.
Introduction and spread of the halophyte Spartina alterniflora is one of the largest continental-scale biological invasion events in Asia and the Americas. Rapid globalization and broad environmental tolerance of the species increase the chance of novel invasions. Thus, we aimed to identify susceptible regions to inform prevention and control activities. A comprehensive global occurrence dataset and corresponding bioclimatic variables were used to characterize the species' climatic niche and predict current and future potential distributions. Conservatism of climatic niche between native and non-native ranges was tested, and climatic niche dynamics were analysed at spatial and temporal scales. The ensemble of eight species distribution models and eight climate change models was used to map the potential distribution of S. alterniflora under current and future climate conditions. We investigated the susceptibility of threatened ecosystems like mangroves and protected areas to S. alterniflora invasion to better inform management decisions. Our study revealed wide climatic tolerance and significant niche expansion of the species from humid regions of its native range to dry and arid environments of its non-native range with a very short lag period. With a marginal increase in temperature and precipitation in the future, range expansion was predicted towards higher latitude and more inland areas. The mangroves area, salt marshes, and protected areas that are at risk of ongoing and future invasions were identified. Given the invasion potential of S. alterniflora, the areas identified as climatically susceptible for the species’ establishment, both in current and future climates, should be prioritized for management actions.
Carbon nanofillers, such as carbon nanotubes (CNTs) and graphene (G) sheets, have long held interest for reinforcement of polymer matrices. However, a number of factors, including polymer interaction and nanofiller agglomeration, limited the potential of these carbon nanofillers for polymer reinforcement. Recent research highlights that CNT-G complexes potentially improve the dispersion and interaction of the nanofillers with polymer matrices, such as nylon 6, but the effects on the properties remain poorly examined. This study uses molecular dynamics (MD) simulation with the Polymer Consistent Force Field (PCFF) to examine the effects of uniformly-dispersed CNT, single layer graphene, and CNT-G on the mechanical properties of amorphous nylon 6 nanocomposites. For all nanofillers, bulk modulus remained unaffected by increasing concentrations of carbon nanofiller where values were dependent on the interaction energy/atom of the nanofiller with the polymer matrix. Young’s moduli increased linearly with addition of carbon nanofillers, indicating that agglomeration of the nanofillers causes the plateaus seen in experimental research. CNT-G nanofillers significantly improved bulk and Young’s moduli of the nylon 6 nanocomposite compared to CNT or graphene. Predicted mechanical property trends agree moderately well with experimental results until agglomeration occurs where discrepancies are attributed to crystallinity effects and nanofiller alignments.
DNA contained in animal scat provides a wealth of information about the animal, and DNA metabarcoding of scat collections can provide key information about animal populations and communities. Next‐generation DNA sequencing technologies and DNA metabarcoding provide an efficient means for obtaining information available in scat samples. We used Multifaceted DNA Metabarcoding (MDM) of noninvasively collected bat guano pellets from a Myotis lucifugus colony on Fort Drum Military Installation, New York, USA, and from two mixed‐species bat roosts on Fort Huachuca Military Installation, Arizona, USA, to identify attributes such as bat species composition, sex ratios, diet, and the presence of pathogens and parasites. We successfully identified bat species for nearly 98% of samples from Fort Drum and 90% of samples from Fort Huachuca, and identified the sex for 84% and 67% of samples from these same locations, respectively. Species and sex identification matched expectations based on prior censuses of bat populations utilizing those roosts, though samples from some species were more or less common than anticipated within Fort Huachuca roosts. Nearly 62% of guano samples from Fort Drum contained DNA from Pseudogymnoascus destructans, where bats with wing damage from White‐nose Syndrome (WNS) were commonly observed. Putative dietary items were detected in a majority of samples from insectivorous bats on Fort Drum (81%) and Fort Huachuca (63%). A minority of guano samples identified as the nectarivorous Leptonycteris yerbabuenae (28%) provided DNA sequences from putative forage plant species. Finally, DNA sequences from both putative ecto‐ and endoparasite taxa were detected in 35% and 56% of samples from Fort Drum and Fort Huachuca, respectively. This study demonstrates that the combination of noninvasive sampling, DNA metabarcoding, and sample and locus multiplexing provide a wide array of data that are otherwise difficult to obtain.
The proliferation of poly- and perfluorinated alkyl substances (PFASs) has resulted in global concerns over contamination and bioaccumulation. PFAS compounds tend to remain in the environment indefinitely, and research is needed to elucidate the ultimate fate of these molecules. We have investigated the model humic substance and model clay surfaces as a potential environmental sink for the adsorption and retention of three representative PFAS molecules with varying chain length and head groups. Utilizing molecular dynamics simulation, we quantify the ability of pyrophyllite and the humic substance to favorably adsorb these PFAS molecules from aqueous solution. We have observed that the hydrophobic nature of the pyrophyllite surface makes the material well suited for the sorption of medium- and long-tail PFAS moieties. Similarly, we find a preference for the formation of a monolayer on the surface for long-chain PFAS molecules at high concentration. Furthermore, we discussed trends in the adsorption mechanisms for the fate and transport of these compounds, as well as potential approaches for their environmental remediation.
In this paper, we introduce a numerical method for approximating the dispersive Serre–Green–Naghdi equations with topography using continuous finite elements. The method is an extension of the hyperbolic relaxation technique introduced in Guermond et al. (J Comput Phys 450:110809, 2022). It is explicit, second-order accurate in space, third-order accurate in time, and is invariant-domain preserving. It is also well balanced and parameter free. Special attention is given to the convex limiting technique when physical source terms are added in the equations. The method is verified with academic benchmarks and validated by comparison with laboratory experimental data.
Rejuvenators are used in the asphalt industry to improve the performance and durability of aged binders and facilitate the use of recycled asphalt materials. The purpose of this study was to evaluate the impact of rejuvenator type and dose on the laboratory performance of asphalt binders. For this study, recycled asphalt pavement (RAP) and extracted RAP binder were obtained from an airfield reconstruction project located in Atlantic City, NJ. One petroleum-based (aromatic extract) and three organic-based (corn oil, tall oil, and modified vegetable oil) rejuvenators were evaluated in this study. Each rejuvenator was used at two different rejuvenator doses (6% and 12% by total RAP binder weight) and was aged at three different levels. Performance grade testing, frequency sweep tests, critical temperature differential (ΔT c ), and Fourier transform infrared spectroscopy (FTIR) tests were conducted. Results showed that the use of rejuvenators lowered the high and low performance grade of extracted RAP binders, in particular organic-based rejuvenators had a greater impact on the performance grade. ΔT c was also improved through the use of rejuvenators. In fact, the extracted RAP binder exceeded the high severity ΔT c threshold (−5°C), whereas the rejuvenated RAP binders improved ΔT c to values greater than the low severity threshold (−2.5°C). Similar findings were observed from the Glover-Rowe parameter as well, in which rejuvenated RAP binders improved the cracking resistance of the extracted RAP binder. When assessing the aging susceptibility, modified vegetable oil and corn oil rejuvenators showed the smallest change in performance between aging levels.
Brines at or near the surface of present-day Mars are a potential explanation for seasonally recurring dark streaks on the walls of craters, termed recurring slope lineae (RSL). Deliquescence and freezing point depression are possible drivers of brine stability, attributable to the high salinity observed in martian regolith including chlorides and perchlorates. Investigation of life, which may inhabit RSL, and the cellular mechanisms necessary for survival, must consider the tolerance of highly variable hydration, freeze-thaw cycles, and high osmolarity in addition to the anaerobic, oligotrophic, and irradiated environment. We propose the saltpan, an ephemeral, hypersaline wetland as an analogue for putative RSL hydrology. Saltpan sediment archaeal and bacterial communities showed tolerance of the Mars-analogous atmosphere, hydration, minerology, salinity, and temperature. Although active growth and a shift to well-adapted taxa were observed, susceptibility to low-concentration chloride and perchlorate addition suggested that such a composition was insufficient for beneficial water retention relative to added salt stress.
Runway roughness poses significant risks to aircraft and aircraft personnel. Roughness irregularities can be found in both civilian and military airfields, from rutting to bomb-damaged repairs. Various methods exist for determining roughness criteria, such as discrete surface deviation evaluation and dynamic response models. Although validated dynamic response models such as TAXI-G were used extensively in the HAVE BOUNCE program from the 1970s up to the late 1990s, modern military aircraft have not undergone the same formal analysis. This paper presents the mathematical formulation and validation of the WESTAX dynamic response model. The computer program is capable of simulating the responses of different critical aircraft components while trafficking over idealized runway profiles. The validation results showed that the numerical model was capable of closely matching field data over single- and double bump events. The findings suggest that the WESTAX dynamic response model is a capable candidate for establishing aircraft roughness limits.
Plain Language Summary Extreme climatic events (e.g., extreme rainfall, wind) by their nature occur over a much larger space than they are measured with point‐scale in situ gauges. Geographic and climatic variables (aka, covariates; e.g., elevation, temperature, pressure) that are associated with the extreme event type can be used to assist in properly modeling how the event varies over a given space. However, the selection of which geographic and climatic covariates should be included in spatial analysis of extremes is often left to manual selection and, in the case of extreme precipitation, is limited to only a few covariates (i.e., latitude, longitude, mean precipitation). Moreover, the use of a larger set of variables is often avoided due to the computational burden that is introduced. We demonstrate the use of elastic‐net regularization for automating the selection of geographical and climatic covariates for modeling the distribution of extreme event parameters spatially, and for reducing the computational time needed for selecting the best performing set of covariates.
The shear wave velocity () and the compressional wave velocity () are extensively used to understand the near-surface geologic structure, derive small-strain elastic moduli of soils, and perform a wide range of geophysical, geotechnical, and geo-environmental analyses. While the dependency of and on water content or degree of saturation is well recognized, the variability of wave velocity measurements and derived elastic moduli within different saturation levels remains yet to be understood. The main objective of this study is to examine the effect of degree of saturation on the statistical distribution of measured wave velocities and the derived small-strain elastic moduli in unsaturated soils. For this purpose, 360 ultrasonic laboratory tests, an extensive array, were performed on a poorly graded fine-to-medium sand over seven full wetting-drying cycles. The laboratory-measured data were used, along with a suite of statistical tests, to evaluate the statistical distribution and variability of the vp and vs measurements and the derived elastic variables--including vp/vs ratio, shear modulus (G), Young's modulus (E), Poisson’s ratio (μ), and bulk modulus (K). The results show that many of the assumptions regarding the quantification of vp and vs measurements and elastic moduli used in geophysical, geotechnical, and geo-environmental analyses may not be valid. The vp and vs data are best represented by lognormal and Weibull distributions, respectively, yet the subsequently derived elastic properties may require more than one distribution type to adequately represent the statistical behavior for different saturation regimes and relationships.
Kernel theory is a demonstrated tool that has made its way into nearly all areas of machine learning. However, a serious limitation of kernel methods is knowing which kernel is needed in practice. Multiple kernel learning (MKL) is an attempt to learn a new tailored kernel through the aggregation of a set of valid known kernels. There are generally three approaches to MKL: fixed rules, heuristics, and optimization. Optimization is the most popular; however, a shortcoming of most optimization approaches is that they are tightly coupled with the underlying objective function and overfitting occurs. Herein, we take a different approach to MKL. Specifically, we explore different divergence measures on the values in the kernel matrices and in the reproducing kernel Hilbert space (RKHS). Experiments on benchmark datasets and a computer vision feature learning task in explosive hazard detection demonstrate the effectiveness and generalizability of our proposed methods.
Many salmonids are listed as threatened or endangered under the U.S. Endangered Species Act (ESA), with habitat loss and alteration likely responsible for their declines. As a result, salmonid hatcheries have proliferated to help mitigate the loss of wild populations. Research aimed at understanding factors contributing to population declines, including studies designed to improve juvenile downstream passage, has often relied on hatchery-origin fish because of restricted access to wild fish. However, differences between hatchery-origin and wild fish could confound results. This led to the development of the Wild Fish Surrogate Program, where we use alternative rearing tactics to produce juvenile fish more like wild Chinook Salmon, Oncorhynchus tshawytscha, for research by varying growth, diet, feeding, density, cover, and tank complexity. Here, we describe methods that have been successful in producing target wild fish phenotypes, in particular related to smoltification and movement, and provide information on the quality and phenotypic accuracy of wild fish surrogates through four case studies (morphology, fin condition, body composition, and behavior). We show that wild fish surrogates had more similar body shape to wild fish compared to hatchery fish and had intermediate body lipid levels. Compared to hatchery fish, we also show that wild fish surrogates had larger and more symmetrical fins and were less likely to cross an aversive zone to be near conspecifics. Although wild fish surrogates were not always intermediate in their phenotypes or behavior, they did not significantly differ in their caudal fin length asymmetry or behavior compared to wild fish. We outline how such a program can be expanded beyond the program objectives and beyond salmonids. This generalization is important, as it can be implemented in other systems with ESA-listed populations where research using wild fish could inform and improve mitigation efforts or for hatchery programs to produce more wild-like phenotypes.
Hurricanes this century have produced almost a trillion dollars in damages in the U.S., often to critical infrastructure that requires large costs and unacceptable times to repair or replace. There is a need for resilient protection of critical infrastructure where the protection must have the “ability to anticipate, absorb, adapt to, and/or rapidly recover from a potentially disruptive event” and be cost-effective. Coastal infrastructure can be protected by moving infrastructure back from the ocean (retreat), building protective structures, or by beach nourishment to effectively move the ocean back from the infrastructure. Retreat is very costly and highly unpopular on developed shores. Structures are expensive and lack resilience because their failure is usually catastrophic and repair slow. Beach nourishment is the favored protection option on developed shorelines because it significantly reduces infrastructure damage, provides resilient protection, and is cost effective with a high return on investment. The aftermath of Hurricane Sandy provided an example of the tremendous reduction of infrastructure damage due to beach nourishment. Dr. Stewart Farrell, director of the Coastal Research Center in New Jersey, reported: “It really, really works. Where there was a federal beach fill in place, there was no major damage — no homes destroyed. Where there was no beach nourishment, the destruction was complete. Older homes were ripped from foundations and tossed about.” A post-Sandy analysis showed that Corps of Engineers’ beach nourishment projects saved an estimated $1.3 billion in avoided damages. Beach nourishment provides resilient protection. It is partially self-healing, because during a storm some of the sand moves to offshore bars where it causes waves to break and reduces infrastructure damage, and then much of it returns to shore after the storm passes. It can be repaired relatively rapidly by use of a mobile dredge to replace net sand loss. It is a highly adaptable approach to climate change because its rate of sand placement can be varied to raise profiles to offset increased sea level rise. Beach nourishment pays for itself as nice, wide beaches sit in readiness to protect critical coastal infrastructure from storms, while in the meantime, tourists typically generate more than $100 in taxes annually to local, state, and the federal governments for every $1 these governments invest in beach nourishment.
Our society is currently facing an unprecedented number of environmental and societal challenges. Stakeholder and community engagement can help identify priority issues and needs at local levels. One approach to engage stakeholders and communities in the contexts of environmental, health, and societal challenges is to leverage outreach and extension programs. Within this context, and to help identify priority issues to focus subsequent research and extension programs in North Carolina (NC), a survey was conducted with extension agents to identify priority issues as they relate to environmental health and risks and related needs. Based on responses from 66 study participants that represented half of the 100 NC counties, we found that Water pollution, Flooding, Natural resources management, and Engaging stakeholders were top priority issues across all environmental health and risk topics. Participants also identified that practices of Engaging stakeholders as well as Assessing, Managing, and Communicating risks were increasingly important. Participants indicated they needed a moderate-to-significant amount of guidance across a range of areas related to assessing, managing, communicating, and making decisions regarding environmental health and risk topics, as well as engaging with local communities. Outcomes from this work can not only help inform subsequent research and outreach efforts at local scales, but this work demonstrates a simple, low-cost approach to elicit perspectives and priorities can be leveraged in other states and regions with established stakeholder and community outreach programs more broadly. Supplementary information: The online version contains supplementary material available at 10.1007/s10669-022-09864-0.
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399 members
Trudy J Estes
  • Environmental Laboratory
Rajeev Agrawal
  • Information Technology Laboratory
Natàlia Garcia-Reyero
  • Environmental Laboratory
Kurt A Gust
  • Environmental Laboratory
Guilherme R Lotufo
  • Environmental Laboratory
3909 Halls Ferry Road, 39180-3188, Vicksburg, MS, United States
Head of institution
Dr. David Pittman