14 Nov 2024

Application of Deep Learning for Segmenting Seepages in Levee Systems

Abstract: Seepage is a typical hydraulic factor that can initiate the breaching process in a levee system. If not identified and treated on time, seepages can be a severe problem for levees, weakening the levee structure and eventually leading to collapse. Therefore, it is essential always to be vigilant with regular monitoring procedures to identify seepages throughout these levee systems and perform adequate repairs to limit potential threats from unforeseen levee failures. This paper introduces a fully convolutional neural network to identify and segment seepage from the image in levee systems. To the best of our knowledge, this is the first work in this domain. Applying deep learning techniques for semantic segmentation tasks in real-world scenarios has its own challenges, especially the difficulty for models to effectively learn from complex backgrounds while focusing on simpler objects of interest. This challenge is particularly evident in the task of detecting seepages in levee systems, where the fault is relatively simple compared to the complex and varied background. We addressed this problem by introducing negative images and a controlled transfer learning approach for semantic segmentation for accurate seepage segmentation in levee systems.

6 Nov 2024

Time-Series Forecasting Methods: A Review

Abstract: Time-series forecasting techniques are of fundamental importance for predicting future values by analyzing past trends. The techniques assume that future trends will be similar to historical trends. Forecasting involves using models fit on historical data to predict future values. Time-series models have wide-ranging applications, from weather forecasting to sales forecasting, and are among the most effective methods of forecasting, especially when making decisions that involve uncertainty about the future. To evaluate forecast accuracy and to compare among models fitted to a time series, three performance measures were used in this study: mean absolute error (MAE), mean square error (MSE), and root-mean-square error (RMSE).

5 Nov 2024

Improving Aquatic Placement Practices for Beneficial Use of Dredged Material in the Great Lakes

Abstract: The Great Lakes Navigation System is an economically critical waterway. To maintain safe and navigable waterways, approximately 3–5 million yd3 (2.3–3.8 million m3) of sediments are dredged annually. The US Army Corps of Engineers (USACE) and others now recognize that beneficial use of these sediments can achieve positive economic, environmental, and social outcomes. However, historically less than 25% of dredged sediments have been beneficially used in the nearshore environment. Improvements are needed in dredged material management practices in the Great Lakes to achieve the goal of using 70% of dredged sediments beneficially by 2030. Therefore, to overcome these challenges this report reviews beneficial use of dredged material projects with the goal of improving and in-creasing beneficial-use-placement practices in the Great Lakes. Identified needs to advance beneficial-use placement in the Great Lakes include the following: (1) improved modeling of sediment-placement methods; (2) better documentation regarding the cost, benefits, and drawbacks of various placement methods; (3) demonstration of some sediment-placement techniques used successfully in other coastal environments; and (4) monitoring before and after conditions, particularly for sediments that contain greater than 10% fines. Several demonstration projects should be implemented to obtain information addressing the data gaps.

5 Nov 2024

Innovations of Cellular Automata

Purpose: In the past several years, there has been a rather substantial uptick in the amount of research within the realm of cellular automata due to its ability to produce complex, self-organizing behavior from simplistic rulesets. The capability to produce this behavior is essential to understanding artificial life and intelligence. This uptick has resulted in numerous novel directions for experimentation within this computational playground. This work summarizes a few of the most impactful directions that have resulted from this research.

31 Oct 2024

Geotechnical Investigation of Mare Island Naval Cemetery

Abstract: The Mare Island Naval Cemetery is located just outside of Vallejo, California. This historic naval cemetery was inspected in November 2022, and signs of slope instability were identified. Two follow-up inspections were conducted by geotechnical engineers and geologists from the US Army Engineer Research and Development Center. A preliminary site investigation showed that desiccation cracking was present and that seepage at the toe of the cemetery slope could contribute to long-term stability issues. Historic vegetation had also recently been cleared, exposing the soils and headstones. If left unaddressed, these factors could lead to slope instability at the site. Increased monitoring, regular surveys, seepage remediation, and reestablishment of vegetation are recommended to prevent future instabilities.

30 Oct 2024

Development of an Inertial Profiler Specification for Airfield Pavement Construction

Abstract: The US Army Engineer Research and Development Center (ERDC) developed a test method and specification for measuring the smoothness of newly constructed airfield pavements using the inertial profiler. The limitations inherent in the currently accepted measurement system, the California-type profilograph, are detailed in this report. The effort detailed herein draws attention not only to the superior repeatability of the inertial profiler but also to the device’s ability to report true surface profile more accurately than the California-type profilograph. Correlations were drawn between the two devices with high (greater than 0.8) goodness-of-fit, and recommendations were made pertaining to the use of inertial profilers in place of California-type profilographs. These recommendations were not only founded on the data collected and analyzed in this effort but are also consistent with the current state of practice for other federal agencies, such as the Federal Aviation Administration and the Federal Highway Administration.

30 Oct 2024

Flood Resilience of Individual Traditional Building Materials

Abstract: The Construction Engineering Research Laboratory of the Engineer Research and Development Center is addressing emergency response and disaster relief capabilities in collaboration with the National Park Service, specifically related to the flood hardening and rehabilitation of historical structures. This report describes efforts to enhance the available data for assessing the resilience of individual historical building materials against flood conditions. In the context of official classification language, the experiments described by this report intended to mimic the effects of moving black water containing mold and sewage but lacking other harmful pollutants. Methods resemble those prescribed by ASTM standards E3075-16 and D7789-12, with minor adjustments to improve variable isolation. Pieces of individual historical building materials were scientifically subjected to simulated floods containing biological surrogates of mold and sewage. Water absorption by the materials and viability of bacteria and mold were measured throughout the experiment. Additional study is required to fully understand flood resilience of historical coatings on a variety of substrates.

29 Oct 2024

Influence of Fines Content on the Progression of Backward Erosion Piping

Abstract: Backward erosion piping is a form of internal erosion that endangers the structural stability of levees and dams. Understanding the factors that influence this form of erosion can result in improved risk assessment and more appropriate modifications to new and existing structures. Historically, it has been assumed that the presence of silt size particles would reduce the gradient required for erosion. This study investigated the influence of fines content on backward erosion piping through a series of laboratory experiments on silty sands. Laboratory results show that as the fines content increased in the samples, so too did the gradient required to produce and progress piping to failure. The results indicate that a new factor is needed to properly account for silt content in backward erosion piping (BEP) risk assessment of silty sands.

18 Oct 2024

Automated Change Detection in Ground-Penetrating Radar using Machine Learning in R

Abstract: Ground-penetrating radar (GPR) is a useful technique for subsurface change detection but is limited by the need for a subject matter expert to process and interpret coincident profiles. Use of a machine learning model can automate this process to reduce the need for subject matter expert processing and interpretation. Several machine learning models were investigated for the purpose of comparing coincident GPR profiles. Based on our literature review, a Siamese Twin model using a twinned convolutional network was identified as the optimum choice. Two neural networks were tested for the internal twinned model, ResNet50 and MobileNetV2, with the former historically having higher accuracy and the latter historically having faster processing time. When trained and tested on experimentally obtained GPR profiles with synthetically added changes, ResNet50 had a higher accuracy. Thanks to this higher accuracy, less computational processing was needed, leading to ResNet50 needing only 107 s to make a prediction compared to MobileNetV2 needing 223 s. Results imply that twinned models with higher historical accuracies should be investigated further. It is also recommended to test Siamese Twin models further with experimentally produced changes to verify the changed detection model’s accuracy is not merely specific to synthetically produced changes.

17 Oct 2024

Building Control Graphics Criteria Update: Standards and Criteria Project 23T12

Abstract: This US Army Corps of Engineers (USACE) Standards and Criteria effort recommends updates to the building-graphics-related content in Unified Facilities Criteria (UFC) 3-470-01 and Unified Facilities Guide Specifications (UFGS) 25 10 10. Building graphics serve as the primary facility interface and are required for any HVAC controls integration project to a base-wide system; however, the current lack of criteria significantly limits their effectiveness and regularly yields inconsistent, low-quality tools for end users. This project developed “Guiding Principles” of good HVAC graphics along with the criteria language to assist the DoD in procuring and implement-ing good graphics. This report includes extensive illustrations to demonstrate good versus poor implementations of the proposed criteria. The intent is not to establish DoD-level graphics standards with these images but give a litmus test to designers and quality assurance staff for what right (and wrong) looks like. Primary recommendations are for graphics drawings designer responsibilities and contractor shop drawing requirements where installation standards are unavailable. Both designer criteria and spec-level functionality are defined using the Guiding Principles developed in this report. Future re-search topics are also described for enhanced trending capabilities, development of standard HVAC system-level performance indicators, and cloud-based connections to ongoing commissioning (OCx) systems.