Engineer Research and Development Center News Releases

Adaptive Covariance Tapering for Large Datasets and Application to Spatial Interpolation of Storm Surge

Press Operations — Tue, 11 Aug 2026 20:40:00 GMT

Abstract: Covariance tapering is a popular approach for accommodating computational efﬁciency for the application of Gaussian process -based spatial interpolation for large datasets. This is accomplished by introducing sparsity in the GP covariance matrix, through the introduction of a compactly supported taper function. The support of the taper function around each spatial node is deﬁned through the taper range variable. The latter is selected to achieve the desired degree of global sparsity in the covariance matrix, and deﬁnes the number of connected neighbors around each node. For problems with irregular nodal density, adaptive covariance tapering can be used to improve accuracy for the taper implementation. In this case, the taper ranges of the taper function have spatial variability, allowing uniform local sparsity to be achieved despite the data irregularities. The optimization of the taper ranges to accomplish this objective has a computational burden that is dependent on the size of the database, prohibiting its application to very large datasets. This paper formally considers the adoption of adaptive covariance tapers for such datasets. Though algorithmic developments are general, the problem is discussed for a speciﬁc application, the spatial interpolation of storm surge. For establishing computational efﬁciency in the optimization of the taper ranges we propose to utilize only a small subset of nodes, termed inducing points. An adaptive, iterative formulation is further developed to support the selection of the inducing points, shown to be critical for achieving the desired local sparsity for the remaining points. At each iteration, the taper range selection is performed using the current subset of inducing points, the achieved sparsity across all nodes is estimated, and then new inducing points are added within the sub-regions for which the discrepancy from the target local sparsity is the largest. The latter points are considered to have the highest expected utility as inducing points. Adding inducing points in close proximity is avoided through the inclusion of a clustering step. The implementation is demonstrated for interpolation of peak storm surge along the New Jersey coast, using two different domains, one with 64,379 nodes and one with 271,669 nodes.

Eight Recommendations to Enhance Biodiversity Outcomes of Nature-Based Solutions at Multiple Scales

Press Operations — Tue, 11 Aug 2026 20:38:00 GMT

Abstract: Ambitions to mainstream Nature-based Solutions (NbS) and achieve global implementation are hampered by the lack of transdisciplinary integration across disciplines and practice. Ecological knowledge, including an under-standing of how biodiversity can support, and be supported by, NbS design and implementation remains an under-studied component of the NbS concept despite its critical importance. Starting with a brief primer on the major roles that biodiversity plays in NbS performance, we present eight recommendations for enhancing biodiversity in NbS planning and implementation. This narrative expert synthesis draws from an interdisciplinary literature search and decades of experience across landscape ecology, environmental engineering, urban planning, wildlife management, ecological restoration, and conservation science. Recommendations emphasize the importance of considering the ecological mechanisms that support biodiversity (i.e., viable populations of coexisting species) and understanding the role of organismal life history, species interactions, habitat preferences, and metapopulation dynamics in determining NbS features’ ecological resilience and contributions to biodiversity enhancement (i.e., IUCN Global Standard Criterion 3). We also emphasize the importance of assessing biodiversity across spatial scales and dimensions (e.g., functional, phylogenetic) and monitoring and ecological management for anticipating and adapting to unexpected outcomes, invasive species, and ecosystem dis-services. This review is intended to increase connections between ecological science, conservation biology, and NbS implementation to support more biodiverse projects with more robust, resilient, and multifunctional performance and greater contributions to global conservation.

Continental-scale mapping of forest tree density in North America using remote sensing and deep learning with uncertainty quantification

Press Operations — Tue, 11 Aug 2026 15:57:00 GMT

Abstract: Accurate, spatially consistent estimates of tree density remain elusive at continental scales, limiting our ability to assess forest structure, carbon stocks, and biodiversity. Existing global assessments have relied on simpliﬁed statistical models and sparse, heterogeneous ground data that are insufﬁcient to capture nonlinear ecological interactions and spatial variability. To address these limitations, we integrated more than 600,000 harmonized ground-based forest inventory plots with satellite-derived vegetation indices, climate surfaces, soil properties, and topographic covariates to develop a deep learning framework for high-resolution mapping of tree density across North America. We evaluated four modeling approaches—generalized linear models, ridge regression, random forest, and a feedforward neural network. Among all models tested, the FFNN achieved the highest predictive accuracy, and was used to produce a wall-to-wall tree density map at 3 km resolution for the continent. We estimated that the total number of forest trees with diameter at breast height ≥ 10 cm across North America ranges from 339 to 514 billion, substantially lower than the widely cited estimate of 603 billion trees reported by Crowther et al. (2015). When smaller stems were included, totals more than doubled, reaching 738 billion to 1.12 trillion trees. We quantiﬁed uncertainty using Monte Carlo Dropout, generating pixel-level error estimates and conﬁdence intervals. Spatial patterns reveal high tree densities in boreal and temperate forests, intermediate densities in mixed broadleaf regions, and relatively low densities in deserts, Mediterranean systems, and tundra. Compared to the global GLM-based benchmark by Crowther et al. (2015), our deep learning framework achieves markedly higher predictive accuracy, aligns more closely with national forest inventory statistics, and provides explicit uncertainty quantiﬁcation, supporting applications in carbon accounting, biodiversity modeling, and ecosystem monitoring at scales through region speciﬁc calibration and validation.

AFM Analysis of Rejuvenated Graphene Nanoplatelets for Nanoscale Reinforcement and Microwave-Induced Healing in Asphalt Binders

Press Operations — Tue, 11 Aug 2026 15:54:00 GMT

Abstract: Understanding nanoscale mechanisms governing reinforcement and healing in asphalt binders is essential for developing durable pavements. This study investigates graphene nanoplatelets (GnP) and rejuvenator-infused graphene (GnP-Rej) in a PG 67–22 binder using PF-QNM atomic force microscopy under unaged, PAV-aged, and microwave-treated conditions. GnP reﬁned binder morphology, reducing surface roughness from ~2.1 nm to ~1.44 nm at 0.24 wt% and increasing stiffness through molecular conﬁnement, with saturation beyond ~0.1 wt% due to agglomeration. Aging increased peri- and para-phase modulus by ~68% and ~61%, respectively, while GnP and GnP-Rej mitigated these effects. GnP-Rej exhibited dual-function behavior, enhancing local compliance and interfacial mobility. Microwave activation increased adhesion by up to ~51% without signiﬁcant modulus change. The adhesion-based healing index conﬁrmed consistent nanoscale recovery, with maximum healing observed at 0.24 wt% GnP-Rej. These results indicate that healing is governed by adhesion-controlled nanoscale recovery and provide mechanistic insight into the relationship between nanoscale behavior and improved asphalt performance.

Geotechnical evaluation of overwash chenier beach deposits

Press Operations — Tue, 11 Aug 2026 15:52:00 GMT

Abstract: This study evaluates the long-term geotechnical effects of segmented breakwaters on shell-rich chenier deposits in southwestern Louisiana. The analysis integrates in-situ lightweight dynamic cone penetrometer (PANDA DCPT) proﬁles with multi-scale laboratory tests to compare a breakwater-protected (Hybrid) transect against an exposed (Natural) shoreline. Results indicate that the peak friction angle and maximum dilatancy of shell-hash occur at a site-speciﬁc optimal median grain size (D50) of approximately 1.0 mm, which geometrically coincides with the minimum void ratio. Shear strength inversely correlates with the coefﬁcient of uniformity (Cu). In ﬁner sediments with wider gradations (D50 < 1.0 mm), excess void ﬁllers act as a lubricant that facilitates particle rearrangement and lowers shear strength. Conversely, in coarser mixtures (D50 > 1.0 mm), strength is reduced not by lubrication, but due to a loose, highly porous skeleton lacking sufﬁcient contact points. At the ﬁeld scale, PANDA DCPT proﬁles revealed distinct differences between the two sites. The protected transect retained a thinner, geotechnically weaker shell layer, ranging from 0.2 to 0.8 m thick. In contrast, the exposed shoreline maintained a robust thickness of 0.4 to 1.0 m. Although breakwaters effectively attenuate incoming wave energy, they disrupt natural winnowing processes and trap poorly sorted ﬁner sediments. This hydrodynamic alteration shifts the soil fabric and introduces a coastal management trade-off. While breakwaters successfully limit short- term retreat, they produce a geotechnically weaker substrate that is susceptible to remobilization during future extreme wave events. Consequently, predictive morphodynamic models must dynamically refresh these coupled physical parameters to accurately assess the long-term resilience of engineered shorelines.

Establishing Native Submersed Aquatic Vegetation at Times Beach, Buffalo, New York

Press Operations — Tue, 11 Aug 2026 15:38:00 GMT

Purpose: Establishing native submersed aquatic vegetation (SAV) in reservoirs, lakes, and ponds involves several considerations, including sources and types of transplant propagules, fluctuating water levels, and herbivory (Smart et al. 1998). Over the past 20 years, US Army Engineer Research and Development Center (ERDC) Environmental Lab researchers have developed methods for establishing native SAV that address these issues. While consistently and successfully applied in the southern United States (Dick et al. 2005), their applicability to northern waterbodies remains untested. This two-part demonstration study evaluated several SAV establishment techniques in a constructed wetland adjacent to Lake Erie, Buffalo, New York.

Tacoma Harbor Navigation Improvement Project: Ship Simulation Study

Press Operations — Tue, 04 Aug 2026 18:24:00 GMT

Abstract: The US Army Engineer Research and Development Center (ERDC), in collaboration with the US Army Corps of Engineers Seattle District, conducted a preengineering design (PED)–level ship simulation study. The study aimed to validate and finalize proposed modifications to the federally maintained waterways in the Blair Waterway in the Port of Tacoma, Washington, and to assess the potential effects of such modifications on navigation. The proposed designs incorporate recommendations from feasibility-level ship simulations that ERDC con-ducted by in 2019. The proposed modifications to the Port of Tacoma include channel deepening, realignment, widening, and enlargement of the Blair Waterway turning basin. Additionally, the study evaluated the potential effects of a beneficial use of dredged material site, referred to as East Commencement Habitat Opportunity (ECHO), which would be located near the entrance to the Hylebos Waterway.

Modeling Evaluation of a Bird Island Design in Hampton Roads, Virginia

Press Operations — Tue, 04 Aug 2026 18:22:00 GMT

Abstract: This report documents a numerical modeling investigation on the sediment transport and morphology changes surrounding designed marine habitats for seabirds in Hampton Roads, Virginia. It assembles and analyzes historical and newly collected wave and hydrodynamic data from the study area. The datasets are used to calibrate and validate coastal wave, hydrodynamic, and sediment transport models. It describes developments of model alternatives that correspond to different bird island designs. It evaluates current and sediment transport fields and seabed volume changes around the island under a representative normal year (2020) and under a storm simulation condition for a 50 yr return synthetic storm with corresponding sea level rise. Model simulations show weak current and sediment transport fields prior to the island construction. With alternative designs of the island, model results show significant changes in magnitudes and spatial distributions of current and sediment transport rate. Analysis of model bed volume changes demonstrates different erosion and deposition trends under the normal environment and under the storm simulation condition. The island design and configuration, including island orientation, island slopes, and material coverage, respond differently to the impact of physical forcing applied in the modeling.

Environmental Data Intelligence Ecosystem (EDIE):Software Requirements Specification (SRS) v1.0

Press Operations — Mon, 03 Aug 2026 18:11:00 GMT

Abstract: The objective of this report is to evaluate the software requirements necessary to define the minimal viable product supporting the Environmental Data Intelligence Ecosystem (EDIE) software suite. The EDIE is designed to aid alignment of Defense State Memorandum of Agreement systems with Formerly Used Defense Sites systems and any future Environmental Division software packages into one common environment. Further the EDIE application will consolidate access and authentication, at the system level, to align with necessary Single Sign On requirements. The EDIE systems will serve as a hub for common communication and information dissemination among Environmental tools and systems.

Customer Support Ticketing Analysis and Comparisons

Press Operations — Mon, 03 Aug 2026 18:09:00 GMT

Abstract: This report evaluates existing tools capable of satisfying the needs of our customer, whilst also identifying the possibilities of creating our own solution from scratch. As a vast majority of businesses use some form of information technology service management, many options already exist to solve this problem. We identify core values important to our customer and evaluate three different solutions and how they will support those values.

Mississippi Coastal Improvements Program (MsCIP) Barrier Island Restoration Long-Term Directional Wave, Circulation, and Water Level Analysis

Press Operations — Mon, 03 Aug 2026 18:06:00 GMT

Abstract: The Mississippi Sound barrier islands, including Ship Island, protect the Mississippi coast from wave-induced erosion during storms. Hurricane Camille (1969) breached Ship Island, and Hurricane Katrina (2005) widened the Camille Cut, increasing the mainland coast’s exposure to waves. To protect the coast, the US Army Corps of Engineers filled the cut with sand and restored Ship Island to its pre-Camille condition in 2020. To evaluate changes in wave height and potential changes in tides and residual currents, field observations via moorings and roving surveys were conducted pre- (2014–2016) and postrestoration (2022–2024). The tidal range and currents were found to be similar pre- and postrestoration, with slight decreases behind Ship Island. Behind and in front of Ship Is-land, the tidal ellipses shifted to being more shore parallel. The residual currents were primarily wind driven and showed little change in magnitude and direction around Ship Island during both summer and winter conditions. Waves passing through the Camille Cut were reduced, and the ratio of significant wave height behind to in front of Ship Island decreased from 0.40 to 0.25 following restoration. The Ship Island restoration reduced wave heights without significantly changing the tidal and residual currents in the Mississippi Sound.

An Innovative Approach of Vibration Testing of Concrete Structure Using Performance Based Evaluation Techniques

Press Operations — Mon, 03 Aug 2026 18:04:00 GMT

Abstract: Many of our nation’s critical water resource infrastructures have already surpassed their intended design lives. Therefore, there is a critical need to develop assessment procedures that will transform dam operations and stabilization mechanisms that can extend the service life of these vital structures. These actions are crucial for ensuring safe and secure public services. Performance-based testing using a cold gas thruster (CGT) is a new and innovative nondestructive testing technique that is being implemented to better assess critical infrastructure. The CGT is an instrument that delivers a high-magnitude, short-duration impulse load that produces an impulse response in the structure. Using these dynamic responses, the structure’s behavioral response and key performance indicators can be determined. Furthermore, a high-fidelity numerical model that accurately predicts behaviors can be developed with the use of these dynamic responses.

Size, Weight, Power, and Cost (SWaP-C) Evaluation for Global Navigation Satellite System (GNSS) Receivers and Antennas

Press Operations — Mon, 27 Jul 2026 13:34:00 GMT

Abstract: The purpose of this technical note is to provide a brief assessment of Global Navigation Satellite System (GNSS) receivers and antennas, focused specifically on vertical positioning. The work compares multiple GNSS receivers at various cost points and antennas of different types during static testing against a known benchmark. Results show that high-cost GNSS receivers do provide better results than low-cost GNSS receivers, but there are likely use cases that the low-cost receiver should provide adequate results. The geodetic-survey GNSS-type antenna provide better results than the helical-style antennas, but similarly, there are use cases that justify usage of the smaller and lighter helical-style antennas.

Feasibility of a Photothermal Noncontact Dry Film Thickness Measurement Device for Automated Inspection of Department of Defense Coating Systems on Steel Substrates

Press Operations — Fri, 24 Jul 2026 13:32:00 GMT

Abstract: The quality and reliability of coatings for steel structures are critical to the longevity of the Department of Defense’s infrastructure. Coatings are the first line of defense against the environmental degradation of steel and require inspection. Nondestructive techniques (NDT) are commonly employed to assess a coating’s condition and inform maintenance decisions. This study sought to examine a photothermal (PT) noncontact NDT method to measure coating dry film thickness, with potential for robotic vehicle attachment. The performance of the noncontact method was com-pared to a trusted contact nondestructive method within a laboratory environment. This study evaluated the method’s accuracy, consistency, repeatability, and limitations. Results demonstrated the noncontact NDT method’s capabilities and limitations. The research highlights the challenges associated with implementing noncontact NDT for complex coating systems and informs future development efforts.

Advances in Spatiotemporal Storm Surge Emulation: Database Imputation and Multi-Mode Latent Space Projection

Press Operations — Thu, 23 Jul 2026 20:24:00 GMT

Abstract: Surrogate models, also known as metamodels or emulators, have emerged as a valuable tool for storm surge hazard estimation. They are developed using numerical model results from a database of synthetic storms and have the potential to provide highly-accurate and efficient surge predictions for new storms beyond those in the database. Frequently, metamodels need to provide spatiotemporal predictions for the storm surge evolution over time, across a large geographic domain represented through appropriately chosen save points (SPs). This paper focuses on a specific type of metamodel, Gaussian process (GP) emulation, that has been proven versatile in past studies for this specific application. The development of the spatiotemporal metamodel in this setting may involve: (a) an imputation step to fill in missing data, associated with instances that nearshore and onshore SPs are dry; and (b) a dimensionality reduction step for projection to a latent space to improve the computational efficiency for the metamodel calibration and predictions. Advances are established across both these aspects by treating spatiotemporal storm surge responses as a three-dimensional tensor (across storm, time, and spatial domains), and by integrating techniques designed specifically for this tensor structure. For data imputation, low-rank tensor completion (LRTC) is adopted. LRTC leverages response correlations across all tensor dimensions, leading to improved imputation performance compared to established alternatives (for example, geospatial interpolation), by ensuring time-series smoothness between the imputed data and the available data in the original database. A combination of LRTC with imputation based on geospatial interpolation is also discussed. As a dimensionality reduction technique, higher-order singular value decomposition (HOSVD) is applied to separately reduce the spatial and temporal dimensions of the database, enabling the preservation of principal information associated with response correlation separately from each dimension within the latent space. Compared to the past use of principal component analysis for the augmented spatiotemporal dimensions, the separation promoted through HOSVD improves the latent output ability to capture complex surge variations, accommodating higher prediction accuracy for the metamodels developed based on this enhanced latent output structure. To improve efficiency in the metamodel calibration, different strategies are examined for grouping the HOSVD-based latent outputs. Beyond advancements associated with the metamodel development, the improvement in accuracy of the predicted surge time-series around its peak is also considered by introducing a correction step using predictions from a supplementary metamodel developed to strictly predict the peak-surge. The proposed advances are demonstrated using the Coastal Hazards System–North Atlantic (CHS-NA) database.

Snow Model Complexity Evaluation for Real-Time Streamflow Forecasting

Press Operations — Wed, 22 Jul 2026 19:49:00 GMT

Abstract: The prediction and forecasting of ﬂooding within snow-dominated watersheds is critical to understanding the risk to downstream infrastructure and population centers and providing the public accurate and timely ﬂood warnings. The ability for ﬂood and water resource management agencies like the U.S. Army Corps of Engineers (USACE) to accurately forecast ﬂooding events has become increasingly important due to growing likelihood of rain-on-snow (ROS) ﬂooding events in recent years. Three snow methods, in ascending order of complexity, i) Temperature Index (TI), ii) Hybrid (RTI), and iii) Energy Balance (EB), can be used to model snowpack and streamﬂow, however, to our knowledge a comprehensive comparison of all three snow methods using the same modeling framework has never been published. We used the USACE Hydrologic Engineering Center’s Hydrological Modeling System (HEC-HMS) with a pseudo-bootstrapping approach to determine the ability of each snow method to model three water years with signiﬁcant ROS ﬂooding events in the Truckee River watershed. Comparing four model validation statistics (KGE, NSE, RSR, and PBIAS) we found minimal differences between the snow methods in their ability to simulate snow water equivalent and streamﬂow at distinct locations within the Truckee River watershed. Our results also indicate that the calibration period is an important factor in the simulation skill of all three snow methods. Total model time (model set up, calibration, and computational time) for the Hybrid and Energy Balance methods was 5-7x and 8-10x longer than the TI method. Using our results, we provide recommended use cases for each snow method.

Observing the Effect of Morphology on the Elastic Properties of New Snow Using a Non-Contacting Laser Ultrasound System

Press Operations — Wed, 22 Jul 2026 19:46:00 GMT

Abstract: Quantifying micromechanical and microstructural properties of snow is crucial, as they control bulk thermal, electrical and mechanical properties. Snow density can provide an estimate of mechanical properties, while direct observation of snow microstructure is necessary to determine mechanical properties. We utilized a novel non-contacting laser ultrasound system, providing high-frequency acoustic waveform measurements, to observe mechanical properties at the microscale. We investigated the temporal relationship between p-wave velocity, snow crystal type, p-wave modulus, stiffness and specific surface area (SSA). We created homogeneous snow samples, each composed of a single type of precipitation particle, compacted to a density of 250 kg m-3. We measured wave propagation through these snow samples and observed changes in p-wave speed during equilibrium metamorphism. We also measured SSA with the InfraSnow Sensor, as well as micromechanical properties with the SnowMicroPenetrometer. With these data, we observed changes in mechanical properties, with up to a factor of 2 increase in elastic modulus depending on crystal type during a period of 72 hours. Estimated elastic moduli increased over time, as expected and in agreement with previous work. Needles and columns had faster p-wave velocities, implying larger elastic modulus, compared to plates and dendrites, and had a higher rate of change within the first hour.

Cold-Weather Asphalt Paving for Roadways and Airfields: Phase 1—Compaction Window and Density Achievement (Laboratory Investigation)

Press Operations — Wed, 22 Jul 2026 19:44:00 GMT

Abstract: Cold-weather asphalt paving is commonly restricted because rapid mixture cooling reduces workability and shortens the compaction window. This study evaluated whether warm-mix asphalt (WMA) combined with heated-drum roller compaction could preserve a usable compaction window and achieve a specification-relevant density at ambient and base temperatures as low as 20°F, which is 25°F below the 45°F Unified Facilities Guide Specifications (UFGS) underlying-surface temperature limit for lifts less than 3 in. Three plant-produced WMA mixtures were compacted as 2 in. slabs using a heated-drum hydraulic roller under controlled ambient and base temperatures from 20°F–85°F and roller delays of 0–20 min after placement. Embedded thermocouples measured precompaction cooling and thermal response during rolling. Density was evaluated using cores extracted from each compacted slab. After quality-control screening, approximately 97% of specimens achieved the 6.0%–8.0% air voids target across all conditions, including at 20°F. Statistical analysis showed that mix, temperature, and delay significantly affected density; the mix-by-temperature interaction was also significant, whereas the temperature-by-delay interaction was not, indicating progressive rather than threshold-based behavior. The heated drum provided localized thermal input at the roller–mat interface despite continued bulk cooling. Results support managing cold-weather paving through compaction-window preservation, mixture-specific evaluation, and outcome-based density verification.

Demonstration Validation of Air Supercritical Water Oxidation (AirSCWO 6) PFAS Destruction: Aqueous Film-Forming Foam Treatment by 374Water AirSCWO Technology

Press Operations — Tue, 21 Jul 2026 17:28:00 GMT

Abstract: The Department of Defense (DoD) faces significant environmental challenges regarding the disposal of legacy aqueous film-forming foam (AFFF) containing persistent PFAS. This project, led by the US Army Engineer Re-search and Development Center (ERDC), evaluates the performance of the 374Water AirSCWO™ 6 system in destroying PFAS within AFFF. During the demonstration, 100 gal. of AFFF were treated, successfully meeting US EPA maximum contaminant levels (MCLs) for PFAS in the liquid effluent. The system achieved a destruction removal efficiency of 99.9993% for total PFAS as analyzed via the total oxidizable precursor (TOP) Assay (42 PFAS). Stack emissions remained below 500 g/h for vola-tile fluorinated compounds as measured by Other Test Method (OTM)–50. While the demister condensate exceeded US EPA PFAS MCLs, the total volume was negligible at less than 0.5 L. Energy efficiency analysis showed a consumption of 1.15 MWh per cubic meter of AFFF per order of magnitude of 42 PFAS destroyed and 12.9 kWh per gram of PFAS destroyed. Treatment costs varied and may range from $47 to $238 per gallon of AFFF. These results demonstrate the effectiveness of super-critical water oxidation technology for a safer disposal of legacy AFFF concentrates.

ACE-Mat: Medium- and Full-Scale Testing over Weak Soils

Press Operations — Mon, 20 Jul 2026 19:44:00 GMT

Abstract: The US Army lacks the capability to rapidly repair and upgrade damaged roads along mobility corridors in contested, complex environments. Damaged low-volume roads are often encountered in military operational scenarios for transporting troops, supplies, equipment, and materials. Airfield matting is a unique solution for rapid construction of airfields in austere environments. The study presented in this report used medium-scale testing to evaluate the performance of the US Army Corps of Engineers’ ACE-Mat over varying soil strengths for rapid road repair scenarios. Tests were run using cyclic plate loading, simulating the load and tire pressure of a common bridge transporter military vehicle. Tests were completed on the mat and directly on the soil for comparison. An additional full-scale field test was completed to validate the medium-scale testing. The results of all tests indicate that the ACE-Mat provides exceptional performance improvement of weak soils.