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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Verification and Validation of the New Dynamic Mooring Modules Available in FAST v8: Preprint

The open-source aero-hydro-servo-elastic wind turbine simulation software, FAST v8, was recently coupled to two newly developed mooring dynamics modules: MoorDyn and FEAMooring. MoorDyn is a lumped-mass-based mooring dynamics module developed by the University of Maine, and FEAMooring is a finite-element-based mooring dynamics module developed by Texas A&M University. This paper summarizes the work performed to verify and validate these modules against other mooring models and measured test data to assess their reliability and accuracy. The quality of the fairlead load predictions by the open-source mooring modules MoorDyn and FEAMooring appear to be largely equivalent to what is predicted by the commercial tool OrcaFlex. Both mooring dynamic model predictions agree well with the experimental data, considering the given limitations in the accuracy of the platform hydrodynamic load calculation and the quality of the measurement data.

17 WIND ENERGY↗
DOE OSTI2016

Achieving Actionable Results from Available Inputs: Metamodels Take Building Energy Simulations One Step Further

Modeling commercial building energy usage can be a difficult and time-consuming task. The increasing prevalence of optimization algorithms provides one path for reducing the time and difficulty. Many use cases remain, however, where information regarding whole-building energy usage is valuable, but the time and expertise required to run and post-process a large number of building energy simulations is intractable. A relatively underutilized option to accurately estimate building energy consumption in real time is to pre-compute large datasets of potential building energy models, and use the set of results to quickly and efficiently provide highly accurate data. This process is called metamodeling. In this paper, two case studies are presented demonstrating the successful applications of metamodeling using the open-source OpenStudio Analysis Framework. The first case study involves the U.S. Department of Energy's Asset Score Tool, specifically the Preview Asset Score Tool, which is designed to give nontechnical users a near-instantaneous estimated range of expected results based on building system-level inputs. The second case study involves estimating the potential demand response capabilities of retail buildings in Colorado. The metamodel developed in this second application not only allows for estimation of a single building's expected performance, but also can be combined with public data to estimate the aggregate DR potential across various geographic (county and state) scales. In both case studies, the unique advantages of pre-computation allow building energy models to take the place of topdown actuarial evaluations. This paper ends by exploring the benefits of using metamodels and then examines the cost-effectiveness of this approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Verification and Validation of the New Dynamic Mooring Modules Available in FAST v8

The open-source aero-hydro-servo-elastic wind turbine simulation software, FAST v8, was recently coupled to two newly developed mooring dynamics modules: MoorDyn and FEAMooring. MoorDyn is a lumped-mass-based mooring dynamics module developed by the University of Maine, and FEAMooring is a finite-element-based mooring dynamics module developed by Texas A&M University. This paper summarizes the work performed to verify and validate these modules against other mooring models and measured test data to assess their reliability and accuracy. The quality of the fairlead load predictions by the open-source mooring modules MoorDyn and FEAMooring appear to be largely equivalent to what is predicted by the commercial tool OrcaFlex. Both mooring dynamic model predictions agree well with the experimental data, considering the given limitations in the accuracy of the platform hydrodynamic load calculation and the quality of the measurement data.

17 WIND ENERGY↗
DOE OSTI2013

Closeout of CRADA JSA 2012S004: Chapter 5, Integrated Control System, of the document of the ESS Conceptual Design Report, publicly available at https://europeanspallationsource.se/accelerator-documents

The integrated control system (ICS) is responsible for the whole ESS machine and facility: accelerator, target, neutron scattering instruments and conventional facilities. This unified approach keeps the costs of development, maintenance and support relatively low. ESS has selected a standardised, field-proven controls framework, the Experimental Physics and Industrial Control System (EPICS), which was originally developed jointly by Argonne and Los Alamos National Laboratories. Complementing this selection are best practices and experience from similar facilities regarding platform standardisation, control system development and device integration and commissioning. The components of ICS include the control system core, the control boxes, the BLED database management system, and the human machine interface. The control system core is a set of systems and tools that make it possible for the control system to provide required data, information and services to engineers, operators, physicists and the facility itself. The core components are the timing system that makes possible clock synchronisation across the facility, the machine protection system (MPS) and the personnel protection system (PPS) that prevent damage to the machine and personnel, and a set of control system services. Control boxes are servers that control a collection of equipment (for example a radio frequency cavity). The integrated control system will include many control boxes that can be assigned to one supplier, such as an internal team, a collaborating institute or a commercial vendor. This approach facilitates a clear division of responsibilities and makes integration much easier. A control box is composed of a standardised hardware platform, components, development tools and services. On the top level, it interfaces with the core control system components (timing, MPS, PPS) and with the human-machine interface. At the bottom, it interfaces with the equipment and parts of the facility through a set of analog and digital signals, real-time control loops and other communication buses. The ICS central data management system is named BLED (beam line element databases). BLED is a set of databases, tools and services that is used to store, manage and access data. It holds vital control system configuration and physics-related (lattice) information about the accelerator, target and instruments. It facilitates control system configuration by bringing together direct input-output controller (IOC) con guration and real-time data from proton and neutron beam line models. BLED also simplifies development and speeds up the code-test-debug cycle. The set of tools that access BLED will be tailored to the needs of different categories of users, such as ESS staff physicists, engineers, and operators; external partner laboratories; and visiting experimental instrument users. The human-machine interface is vital to providing a high-quality experience to ICS users. It encompasses a wide array of devices and software tools, from control room screens to engineer terminal windows; from beam physics data tools to post-mortem data analysis tools. It serves users with a wide range of skills from widely varied backgrounds. The Controls Group is developing a set of user profiles to accommodate this diverse range of use-cases and users.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2017

Availability of Neutronics Benchmarks in the ICSBEP and IRPhEP Handbooks for Computational Tools Testing

In the past several decades, numerous experiments have been performed worldwide to support reactor operations, measurements, design, and nuclear safety. Those experiments represent an extensive international investment in infrastructure, expertise, and cost, representing significantly valuable resources of data supporting past, current, and future research activities. Those valuable assets represent the basis for recording, development, and validation of our nuclear methods and integral nuclear data [1]. The loss of these experimental data, which has occurred all too much in the recent years, is tragic. The high cost to repeat many of these measurements can be prohibitive, if not impossible, to surmount. Two international projects were developed, and are under the direction of the Organisation for Co-operation and Development Nuclear Energy Agency (OECD NEA) to address the challenges of not just data preservation, but evaluation of the data to determine its merit for modern and future use. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) was established to identify and verify comprehensive critical benchmark data sets; evaluate the data, including quantification of biases and uncertainties; compile the data and calculations in a standardized format; and formally document the effort into a single source of verified benchmark data [2]. Similarly, the International Reactor Physics Experiment Evaluation Project (IRPhEP) was established to preserve integral reactor physics experimental data, including separate or special effects data for nuclear energy and technology applications [3]. Annually, contributors from around the world continue to collaborate in the evaluation and review of select benchmark experiments for preservation and dissemination. The extensively peer-reviewed integral benchmark data can then be utilized to support nuclear design and safety analysts to validate the analytical tools, methods, and data needed for next-generation reactor design, safety analysis requirements, and all other front- and back-end activities contributing to the overall nuclear fuel cycle where quality neutronics calculations are paramount.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗