Publication Notices

Notifications of the Newest Publications and Reports Released by ERDC

Contact ERDC Library

 

erdclibrary@ask-a-librarian.info

601.501.7632 - text
601.634.2355 - voice

 

ERDC Library Catalog

Not finding what you are looking for? Search the ERDC Library Catalog

Results:
Category: Publications: Information Technology Laboratory (ITL)
Clear
  • 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.
  • 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.
  • The Impact of Practitioners’ Personality Traits on Their Level of Systems-Thinking Skills Preferences

    Abstract: In this study, we used a structural equation modeling method to investigate the relationship between systems engineers and engineering managers’ Systems-Thinking (ST) skills preferences and their Personality Traits (PTs) in the domain of complex system problems. As organizations operate in more and more turbulent and complex environments, it has become increasingly important to assess the ST skills preferences and PTs of engineers. The current literature lacks studies related to the impact of systems engineers and engineering managers’ PTs on their ST skills preferences, and this study aims to address this gap. A total of 99 engineering managers and 104 systems engineers provided the data to test four hypotheses posed in this study. The results show that the PTs of systems engineers and engineering managers have a positive impact on their level of ST skills preferences and that the education level, the current occupation type, and the managerial experience of the systems engineers and engineering managers moderate the main relationship in the study.
  • A Fuzzy Epigenetic Model for Representing Degradation in Engineered Systems

    Abstract: Degradation processes are implicated in a large number of system failures, and are crucial to understanding issues related to reliability and safety. Systems typically degrade in response to stressors, such as physical or chemical environmental conditions, which can vary widely for identical units that are deployed in different places or for different uses. This situational variance makes it difficult to develop accurate physics-based or data-driven models to assess and predict the system health status of individual components. To address this issue, we propose a fuzzy set model for representing degradation in engineered systems that is based on a bioinspired concept from the field of epigenetics. Epigenetics is concerned with the regulation of gene expression resulting from environmental or other factors, such as toxicants or diet. One of the most studied epigenetic processes is methylation, which involves the attachment of methyl groups to genomic regulatory regions. Methylation of specific genes has been implicated in numerous chronic diseases, so provides an excellent analog to system degradation. We present a fuzzy set model for characterizing system degradation as a methylation process based on a set-theoretic representation for epigenetic modeling of engineered systems. This model allows us to capture the individual dynamic relationships among a system, environmental factors, and state of health .
  • Ship Simulator of the Future in Virtual Reality

    Introduction: The Army’s modernization priorities include the development of augmented reality and virtual reality (AR/VR) simulations for enabling the regiment and increasing soldier readiness. The use of AR/VR technology at the U.S. Army Engineer Research and Development Center (ERDC) is also growing in the realm of military and civil works program missions. The ERDC Coastal and Hydraulics Laboratory (CHL) has developed a ship simulator to evaluate bay channels across the world; however, the current simulator has little to no physical realism in nearshore coastal regions (Figure 1). Thus, the ERDC team is researching opportunities to advance ship simulation to deliver the Ship Simulator of the Future (SSoF). The SSoF will be equipped with a VR mode and will more accurately resolve nearshore wave phenomena by ingesting precalculated output from a Boussinesq-type wave model. This initial prototype of the SSoF application is intended for research and development purposes; however, the technologies employed will be applicable to other disciplines and project scopes, including the Synthetic Training Environment (STE) and ship and coastal structure design in future versions.
  • South Pole Station Snowdrift Model

    Abstract: The elevated building at Scott-Amundsen South Pole Station was designed to mitigate the effects of windblown snow on it and the surrounding infrastructure. Because the elevation of the snow surface increases annually, the station is periodically lifted on its support columns to maintain its design height above the snow surface. To assist with planning these lifts, this effort developed a computational model to simulate snowdrift formation around the elevated building. The model uses computational fluid dynamics methods and synthetic wind record generation derived from statistical analysis of meteorological data. Simulations assessed the impact of several options for the lifting operation on drifts surrounding the elevated building. Simulation results indicate that raising the eastern-most building section (Pod A), or the entire station all at once, can reduce drift accumulation rates over the nearby arches structures. Long-term analyses, spanning 5–6 years, determine whether an equilibrium drift condition may be reached after a long period of undisturbed drift development. These simulations showed that after about 6 years, the rate of growth of the upwind drift slows, appearing to approach an equilibrium condition. However, the adjacent drifts were still increasing in depth at a roughly linear rate, indicating that equilibrium for those drifts was still several seasons away.
  • SAGE-PEDD Theory Manual: Modeling Windblown Snow Deposition around Buildings

    Abstract: Numerical modeling of snowdrifting is a useful tool for assessing the im-pact of building design on operations and facility maintenance. Here we outline the theory for the SAGE-PEDD snowdrift model that has applica-tion for determining snowdrift accumulation around buildings. This model uses the SAGE computational fluid dynamics code to determine the flow field in the computational domain. A particle entrainment, dis-persion, and deposition (PEDD) model is coupled to SAGE to simulate the movement and deposition of the snow within the computational do-main. The report also outlines areas of future development that upgrades to the SAGE-PEDD model should address.
  • SAGE-PEDD User Manual

    Abstract: SAGE-PEDD is a computational model for estimating snowdrift shapes around buildings. The main inputs to the model are wind speed, wind direction, building geometry and initial ground or snow-surface topography. Though developed mainly for predicting snowdrift shapes, it has the flexibility to accept other soil types, though this manual addresses snow only. This manual provides detailed information for set up, running, and viewing the output of a SAGE-PEDD simulation.
  • The Forefront : A Review of ERDC Publications, Summer 2022

    Abstract: : As the main research and development organization for the US Army Corps of Engineers (USACE), the Engineer Research and Development Center (ERDC) helps solve our nation’s most challenging problems. With seven laboratories under the ERDC umbrella, ERDC expertise spans a wide range of disciplines. This provides researchers an amazing network of collaborators both within labs and across them. Many of the publications produced by ERDC through the Information Technology Laboratory’s Information Science and Knowledge Management Branch (ISKM), the publishing authority for ERDC, are a testament to the power of these partnerships. Therefore, in this issue of The Forefront, we wanted to highlight some of those collaborations, across ERDC and beyond. Colored flags at the top of each page indicate the laboratories involved in each report (see the end of this issue for a full list of the laboratories and their lab colors), in addition to USACE red for district collaborators and gray for others. Through these collaborations, ERDC is continuing to demonstrate its value nationally and internationally. Questions about the reports highlighted in The Forefront or others published by ERDC? Contact the ISKM virtual reference desk at erdclibrary@ask-a-librarian.info or visit ERDC Knowledge Core, ISKM’s online repository, at https://erdc-library.erdc.dren.mil/. For general questions about editing and publishing at ERDC, you are also welcome to reach out to me at Emily.B.Moynihan@usace.army.mil. We look forward to continuing to be a resource for ERDC and seeing all the remarkable research that is yet to come.
  • Leveraging Production Visualization Tools In Situ

    Abstract: The visualization community has invested decades of research and development into producing large-scale production visualization tools. Although in situ is a paradigm shift for large-scale visualization, much of the same algorithms and operations apply regardless of whether the visualization is run post hoc or in situ. Thus, there is a great benefit to taking the large-scale code originally designed for post hoc use and leveraging it for use in situ. This chapter describes two in situ libraries, Libsim and Catalyst, that are based on mature visualization tools, VisIt and ParaView, respectively. Because they are based on fully featured visualization packages, they each provide a wealth of features. For each of these systems we outline how the simulation and visualization software are coupled, what the runtime behavior and communication between these components are, and how the underlying implementation works. We also provide use cases demonstrating the systems in action. Both of these in situ libraries, as well as the underlying products they are based on, are made freely available as open-source products. The overviews in this chapter provide a toehold to the practical application of in situ visualization.