6 Jul 2023

A General-Purpose Multiplatform GPU-Accelerated Ray Tracing API

Abstract: Real-time ray tracing is an important tool in computational research. Among other things, it is used to model sensors for autonomous vehicle simulation, efficiently simulate radiative energy propagation, and create effective data visualizations. However, raytracing libraries currently offered for GPU platforms have a high level of complexity to facilitate the detailed configuration needed by gaming engines and high-fidelity renderers. A researcher wishing to take advantage of the performance gains offered by the GPU for simple ray casting routines would need to learn how to use these ray tracing libraries. Additionally, they would have to adapt this code to each GPU platform they run on. Therefore, a C++ API has been developed that exposes simple ray casting endpoints that are implemented in GPU-specific code for several contemporary device platforms. This API currently supports the NVIDIA OptiX ray tracing library, Vulkan, AMD Radeon Rays, and even Intel Embree. Benchmarking tests using this API provide insight to help users determine the optimal backend library to select for their ray tracing needs. HPC research will be well-served by the ability to perform general purpose raytracing on the increasing amount of graphics and machine learning nodes offered by the DoD High Performance Computing Modernization Program.

22 May 2023

Advances in Dredged Material Evaluations for Inland and Ocean Aquatic Placement: Modernized Processes and Supportive Tools

Abstract: As part of the US Army Corps of Engineers’ mission to evaluate and move dredged material (DM) to maintain navigation channels, environmental evaluation of the prospective material is required by the Code of Federal Regulations. While existing guidance manuals provide useful guidance to DM regulators, they are over 30 years old and not reflective of the latest science. However, efforts to update procedures and publish the documents individually or as a combined dredging manual have been thus far unsuccessful. These issues, coupled with a lack of consistent reporting and decision documentation, lead to delays arising from challenges addressing project-specific issues not clearly covered within the existing guidance, revisiting previously resolved issues or negotiating disputes between permitting authorities. This technical report provides a path toward modernization of the environmental compliance aspects of DM evaluation guidance in part through software executables guiding the management and decision process and through a structured, evidence-based approach. The value added is an updated approach to DM testing and evaluation decisions.

21 Apr 2023

Early Life-Cycle Prediction of Reliability

Abstract: The intent of this project is to investigate a variety of approaches for the development of a basic model for the early life-cycle prediction of reliability (pre-Milestone A). The United States Department of Defense (DoD) currently utilizes an acquisition framework in which system development advances through a series of checkpoints known as milestones. Each milestone represents a decision point, with Milestone A being the earliest in the life cycle. At Milestone A, also known as the risk-reduction decision, the DoD evaluates design concepts while also committing funds to the maturation of technologies in an effort to mitigate future risks. Typically, little is known about the particular system to be developed at this point in the acquisition life cycle, but DoD regulations require program man-agers to submit system reliability information (OUSD[A&S] 2015). Traditional reliability predictions, however, require extensive knowledge of the system of interest to produce accurate results. This level of knowledge is unavailable at or before Milestone A, there-fore, there is a need to create models and methodologies for the prediction of system reliability. This report provides an overview of a variety of methods investigated to improve the prediction of early life cycle reliability.

23 Mar 2023

Experimental Fatigue Evaluation of Underwater Steel Panels Retrofitted with Fiber Polymers

Abstract: Many steel structures are susceptible to fatigue loading and damage that potentially threaten their integrity. Steel hydraulic structures (SHS) experience fatigue loading during operation and exposure to harsh environmental conditions that can further reduce fatigue life through stress corrosion cracking and corrosion fatigue, for example. Dewatering to complete inspections or repairs to SHS is time consuming and leads to economic losses, and current repair methods, such as rewelding, often cause new cracks to form after relatively few cycles, requiring repeated inspection and repair. The use of bonded carbon fiber–reinforced polymer (CFRP) to repair fatigue cracks in metallic structures has been successful in other industries; recent work suggests that this method offers a more reliable repair method for SHS. Studies regarding CFRP retrofits of SHS indicate that early bond failure often controls the degree of fatigue life extension provided by the repair. This study aims to extend previous studies and increase the fatigue life of repaired steel components by employing methods to improve CFRP bonding. Additionally, using basalt reinforced polymer (BFRP) instead of CFRP is proposed. BFRP is attractive for SHS because it does not react galvanically and has excellent resistance to chemically active environments.

21 Mar 2023

An Ontology for an Epigenetics Approach to Prognostics and Health Management

Abstract: Techniques in prognostics and health management have advanced considerably in the last few decades, enabled by breakthroughs in computational methods and supporting technologies. These predictive models, whether data-driven or physics-based, target the modeling of a system’s aggregate performance. As such, they generalize assumptions about the modelled system’s components, and are thus limited in their ability to represent individual components and the dynamic environmental factors that affect composite system health. To address this deficiency, we have developed an epigenetics-inspired knowledge representation for engineered system state that encompasses components and environmental factors. Epigenetics is concerned with explaining how environmental factors affect the expression of an organism’s genetic material. The field has derived important insights into the development and progression of disease states based on how environmental factors impact genetic material, causing variations in how a gene is expressed. The health of an engineered system is similarly influenced by its environment. A foundation for a new approach to prognostics based on epigenetics must begin by representing the entities and relationships of an engineered system from the perspective of epigenetics. This paper presents an ontology for an epigenetics-inspired representation of an engineered system. An ontology describing the epigenetics of an engineered system will enable the composition of a formal model and the incremental development of a more robust, causal reasoning system.

22 Dec 2022

2021 Guided Wave Inspection of California Department of Water Resources Tainter Gate Post-Tensioned Trunnion Anchor Rods: Oroville Dam

Abstract: The Engineering and Test Branch within the Division of Operations and Maintenance of the California Department of Water Resources (DWR) and U.S. Army Corps of Engineers (USACE), Sacramento District, tasked the Sensor Integration Branch (SIB) at the Engineer Research and Development Center (ERDC) to perform nondestructive testing (NDT) on the trunnion anchor rods at Oroville Dam through the use of ultrasonic guided waves. This is the fourth year of this NDT. The results of the testing are presented along with qualitative analysis in determining whether a rod is intact or compromised. Analysis is based upon the expected results from other rods at the site, knowledge of rod response at other sites, data gathered from the trunnion rod research test bed at ERDC, and comparison to the previous year’s effort.

16 Dec 2022

Helicopter Rotor Blade Planform Optimization Using Parametric Design and Multi-Objective Genetic Algorithm

Abstract: In this paper, an automated framework is presented to perform helicopter rotor blade planform optimization. This framework contains three elements, Dakota, ParBlade, and RCAS. These elements are integrated into an environment control tool, Galaxy Simulation Builder, which is used to carry out the optimization. The main objective of this work is to conduct rotor performance design optimizations for forward flight and hover. The blade design variables manipulated by ParBlade are twist, sweep, and anhedral. The multi-objective genetic algorithm method is used in this study to search for the optimum blade design; the optimization objective is to minimize the rotor power required. Following design parameter substitution, ParBlade generates the modified blade shape and updates the rotor blade properties in the RCAS script before running RCAS. After the RCAS simulations are complete, the desired performance metrics (objectives and constraints) are extracted and returned to the Dakota optimizer. Demonstrative optimization case studies were conducted using a UH-60A main rotor as the base case. Rotor power in hover and forward flight, at advance ratio 𝜇𝜇 = 0.3, are used as objective functions. The results of this study show improvement in rotor power of 6.13% and 8.52% in hover and an advance ratio of 0.3, respectively. This configuration also yields greater reductions in rotor power for high advance ratios, e.g., 12.42% reduction at 𝜇𝜇 = 0.4.

6 Dec 2022

Publications of the U.S. Army Engineer Research and Development Center; Appendix G: FY22 (October 2021-September 2022)

Abstract: Publications issued October 2021 through September 2022 by the US Army Engineer Research and Development Center (ERDC) are listed. The publications are grouped according to the technical laboratories or technical program for which they were prepared. Procedures for obtaining ERDC reports are included in the Preface.

2 Dec 2022

In Situ and Time

Abstract: Large-scale HPC simulations with their inherent I/O bottleneck have made in situ visualization an essential approach for data analysis, although the idea of in situ visualization dates back to the era of coprocessing in the 1990s. In situ coupling of analysis and visualization to a live simulation circumvents writing raw data to disk for post-mortem analysis -- an approach that is already inefficient for today's very large simulation codes. Instead, with in situ visualization, data abstracts are generated that provide a much higher level of expressiveness per byte. Therefore, more details can be computed and stored for later analysis, providing more insight than traditional methods. This workshop encouraged talks on methods and workflows that have been used for large-scale parallel visualization, with a particular focus on the in situ case.

30 Nov 2022

Risk-Based Prioritization of Operational Condition Assessments: Methodology and Case Study Results

Abstract: USACE operates, maintains, and manages more than $232 billion of the Nation’s water resource infrastructure. USACE uses the Operational Condition Assessment (OCA) to allocate limited resources to assess condition of this infrastructure in efforts to minimize risks associated with performance degradation. The analysis of risk associated with flood risk management (FRM) assets includes consideration of how each asset contributes to its associated FRM watershed system, understanding the consequences of the asset’s performance degradation, and a determination of the likelihood that the asset will perform as expected given the current OCA condition ratings of critical components. This research demonstrates a proof-of-concept application of a scalable methodology to model the probability of a dam performing as expected given the state of its gates and their components. The team combines this likelihood of degradation with consequences generated by the application of designed simulation experiments with hydrological models to develop a risk measure. The resulting risk scores serve as an input for a mixed-integer optimization program that outputs the optimal set of components to conduct OCAs on to minimize risk in the watershed. This report documents the results of the application of this methodology to two case studies.