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At least 1,171 records · Page 65

Automated Work Package: Initial Wireless Communication Platform Design, Development, and Evaluation

The Department of Energy’s Light Water Reactor Sustainability Program is developing the scientific basis to ensure long-term reliability, productivity, safety, and security of the nuclear power industry in the United States. The Instrumentation, Information, and Control (II&C) pathway of the program aims to increase the role of advanced II&C technologies to achieve this objective. One of the pathway efforts at Idaho National Laboratory (INL) is to improve the work packages execution process by replacing the expensive, inefficient, bulky, complex, and error-prone paper-based work orders with automated work packages (AWPs). An AWP is an automated and dynamic presentation of the work package designed to guide the user through the work process. It is loaded on a mobile device, such as a tablet, and is capable of communicating with plant equipment and systems to acquire plant and procedure states. The AWP replaces those functions where a computer is more efficient and reliable than a human. To enable the automatic acquisition of plant data, it is necessary to design and develop a prototype platform for data exchange between the field instruments and the AWP mobile devices. The development of the platform aims to reveal issues and solutions generalizable to large-scale implementation of a similar system. Topics such as bandwidth, robustness, response time, interference, and security are usually associated with wireless communication. These concerns, along with other requirements, are listed in an earlier INL report. Specifically, the targeted issues and performance aspects in this work are relevant to the communication infrastructure from the perspective of promptness, robustness, expandability, and interoperability with different technologies.

Automated Work Packages↗

Plenario: An Open Data Discovery and Exploration Platform for Urban Science

The past decade has seen the widespread release of open data concerning city services, conditions, and activities by government bodies and public institutions of all sizes. Hundreds of open data portals now host thousands of datasets of many different types. These new data sources represent enormous po- tential for improved understanding of urban dynamics and processes—and, ultimately, for more livable, efficient, and prosperous communities. However, those who seek to realize this potential quickly discover that discovering and applying those data relevant to any particular question can be extraordinarily dif- ficult, due to decentralized storage, heterogeneous formats, and poor documentation. In this context, we introduce Plenario, a platform designed to automating time-consuming tasks associated with the discovery, exploration, and application of open city data—and, in so doing, reduce barriers to data use for researchers, policymakers, service providers, journalists, and members of the general public. Key innovations include a geospatial data warehouse that allows data from many sources to be registered into a common spatial and temporal frame; simple and intuitive interfaces that permit rapid discovery and exploration of data subsets pertaining to a particular area and time, regardless of type and source; easy export of such data subsets for further analysis; a user-configurable data ingest framework for automated importing and periodic updating of new datasets into the data warehouse; cloud hosting for elastic scaling and rapid creation of new Plenario instances; and an open source implementation to enable community contributions. We describe here the architecture and implementation of the Plenario platform, discuss lessons learned from its use by several communities, and outline plans for future work.

Catlett, Charlie↗

Synthetic Diagnostics Platform for Fusion Plasma and a Two-Dimensional Synthetic Electron Cyclotron Emission Imaging Code

Magnetic confinement fusion is one of the most promising approaches to achieve fusion energy. With the rapid increase of the computational power over the past decades, numerical simulation have become an important tool to study the fusion plasmas. Eventually, the numerical models will be used to predict the performance of future devices, such as the International Thermonuclear Experiment Reactor (ITER) or DEMO. However, the reliability of these models needs to be carefully validated against experiments before the results can be trusted. The validation between simulations and measurements is hard particularly because the quantities directly available from both sides are different. While the simulations have the information of the plasma quantities calculated explicitly, the measurements are usually in forms of diagnostic signals. The traditional way of making the comparison relies on the diagnosticians to interpret the measured signals as plasma quantities. The interpretation is in general very complicated and sometimes not even unique. In contrast, given the plasma quantities from the plasma simulations, we can unambiguously calculate the generation and propagation of the diagnostic signals. These calculations are called synthetic diagnostics, and they enable an alternate way to compare the simulation results with the measurements. In this dissertation, we present a platform for developing and applying synthetic diagnostic codes. Three diagnostics on the platform are introduced. The reflectometry and beam emission spectroscopy diagnostics measure the electron density, and the electron cyclotron emission diagnostic measures the electron temperature. The theoretical derivation and numerical implementation of a new two dimensional Electron cyclotron Emission Imaging code is discussed in detail. This new code has shown the potential to address many challenging aspects of the present ECE measurements, such as runaway electron effects, and detection of the cross phase between the electron temperature and density fluctuations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Wireless sensor platform

A wireless sensor platform and methods of manufacture are provided. The platform involves providing a plurality of wireless sensors, where each of the sensors is fabricated on flexible substrates using printing techniques and low temperature curing. Each of the sensors can include planar sensor elements and planar antennas defined using the printing and curing. Further, each of the sensors can include a communications system configured to encode the data from the sensors into a spread spectrum code sequence that is transmitted to a central computer(s) for use in monitoring an area associated with the sensors.

97 MATHEMATICS AND COMPUTING↗

MULTILAYER PLANT-IN-CHIP PLATFORM FOR NON-DESTRUCTIVE VISUALIZATION OF ROOT MORPHOLOGY DURING CO-CULTURE WITH BENEFICIAL BACTERIA

The interaction between plants and their associated microbiomes is difficult to visualize in situ and requires a transparent culturing platform that can capture the length and time scales in which these dynamic relationships occur. We have used lab-on-a-chip technology to create such a platform and have successfully co-cultured Arabidopsis thaliana with beneficial bacteria. Here we quantify the changes in root morphology over time and discuss the potential of the system to characterize the kinetics and spatial distribution of root colonization.

Aufrecht, Jayde A.↗

The EGS Data Collaboration Platform: Enabling Scientific Discovery

Collaboration in the digital age has been stifled in recent years. Reasonable responses to legitimate security concerns have created a virtual landscape of silos and fortified castles incapable of sharing information efficiently. This trend is unfortunately opposed to the geothermal scientific community's migration toward larger, more collaborative projects. To facilitate efficient sharing of information between team members from multiple national labs, universities, and private organizations, the 'EGS Collab' team has developed a universally accessible, secure data collaboration platform and has fully integrated it with the U.S. Department of Energy's (DOE) Geothermal Data Repository (GDR) and the National Geothermal Data System (NGDS). This paper will explore some of the challenges of collaboration in the modern digital age, highlight strategies for active data management, and discuss the integration of the EGS Collab data management platform with the GDR to enable scientific discovery through the timely dissemination of information.

97 MATHEMATICS AND COMPUTING↗

openECA Platform and Analytics Alpha Test Results

The objective of the Open and Extensible Control and Analytics (openECA) Platform for Phasor Data project is to develop an open source software platform that significantly accelerates the production, use, and ongoing development of real-time decision support tools, automated control systems, and off-line planning systems that (1) incorporate high-fidelity synchrophasor data and (2) enhance system reliability while enabling the North American Electric Reliability Corporation (NERC) operating functions of reliability coordinator, transmission operator, and/or balancing authority to be executed more effectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗

openECA Platform and Analytics Beta Demonstration Results

The objective of the Open and Extensible Control and Analytics (openECA) Platform for Phasor Data project is to develop an open source software platform that significantly accelerates the production, use, and ongoing development of real-time decision support tools, automated control systems, and off-line planning systems that (1) incorporate high-fidelity synchrophasor data and (2) enhance system reliability while enabling the North American Electric Reliability Corporation (NERC) operating functions of reliability coordinator, transmission operator, and/or balancing authority to be executed more effectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗

PCS: A Productive Computational Science Platform

As modern supercomputers continue to be increasingly heterogeneous with diverse computational accelerators, software becomes a critical aspect necessary to fully exploit these accelerators while not increasing the effort and time required to make variable scientific discovery in the face of complicated programming environments introduced by these accelerators. This paper presents PCS, a productive computational science platform for cluster-scale heterogeneous computing. The PCS platform by design follows a basic principle that, multiple programming models in a unified programming environment, is essential to facilitate large-scale, accelerator-aware, heterogeneous computing for next- generation scientific applications. We propose a new scheme — Edge Neural Network — for managing regularity in large dataflow graphs using higher-order bulk synchronous operators, providing a foundation for formalizing computational models for cluster-wide dataflow programming of heterogeneous clusters.

36 MATERIALS SCIENCE↗

PCS: A Productive Computational Science Platform

As modern supercomputers continue to be increasingly heterogeneous with diverse computational accelerators, software becomes a critical aspect necessary to fully exploit these accelerators while not increasing the effort and time required to make variable scientific discovery in the face of complicated programming environments introduced by these accelerators. This paper presents PCS, a productive computational science platform for cluster-scale heterogeneous computing. The PCS platform by design follows a basic principle that, multiple programming models in a unified programming environment, is essential to facilitate large-scale, accelerator-aware, heterogeneous computing for next-generation scientific applications. We propose a new scheme — Edge Neural Network — for managing regularity in large dataflow graphs using higher-order bulk synchronous operators, providing a foundation for formalizing computational models for cluster-wide dataflow programming of heterogeneous clusters.

Ojika, David↗

VEXS, An Open Platform for the Study of Continuous-Energy Cross-Section Lookup Algorithms on GPU’s

A significant bottleneck in continuous-energy neutron transport simulations is the cross-section lookup problem, especially in the case of those occurring in depleted fuel regions. Several algorithms have been developed over the years to solve this problem on more traditional CPU-based platforms, however new computational architectures such as GPUs may not benefit as significantly from these algorithms. As there is increasing interest in using these new computational architectures as a core part of large simulations, the relative efficacy of these algorithms compared to one another is an interesting area of research. Additionally, implementations of these algorithms are sometimes inaccessible to interested scientists outside of the nuclear engineering field given the export-controlled nature of the codes they are implemented in. In this paper, we describe our work to extend an existing open-source platform for cross-section lookup simulation, XSBench, to GPUs. We also describe our adaptation of the original codebase to handle more realistic datasets, and our efforts to accommodate different in-memory data layouts in order to more closely approximate those implementations used in production codes. Finally, we compare our results with those obtained from Shift, a GPU-enabled Monte Carlo transport solver developed for large neutron transport simulations.

Shriver, Forrest↗

SkyBAAM Large-Scale Fieldable Deposition Platform System Architecture

Oak Ridge National Laboratory (ORNL) is currently developing a concrete deposition system for infrastructure-scale printed objects. This system, called SkyBAAM, uses a cable driven motion platform to manipulate the print head. This work focuses on the general aspects of the system architecture, including arrangement of the cable driven platform, general high-level control methodology, and system accuracy, along with concrete deposition methods. Results and demonstration prints will be shown.

Chesser, Phillip↗

PCS: A Productive Computational Science Platform

As modern supercomputers continue to be increasingly heterogeneous with diverse computational accelerators, software becomes a critical aspect necessary to fully exploit these accelerators while not increasing the effort and time required to make variable scientific discovery in the face of complicated programming environments introduced by these accelerators. This paper presents PCS, a productive computational science platform for cluster-scale heterogeneous computing. The PCS platform by design follows a basic principle that, multiple programming models in a unified programming environment, is essential to facilitate large-scale, accelerator-aware, heterogeneous computing for next- generation scientific applications. We propose a new scheme - Edge Neural Network - for managing regularity in large dataflow graphs using higher-order bulk synchronous operators, providing a foundation for formalizing computational models for cluster-wide dataflow programming of heterogeneous clusters.

36 MATERIALS SCIENCE↗

Sensors with Intelligent Measurement Platform and Low-cost Equipment (SIMPLE) – Performance Characterization

Design and performance of a digital signal processing platform for enhancing off-the-shelf voltage and current sensors are presented. The platform was developed for enabling advanced distribution grid applications with existing low-cost sensors. This digital sensor system leverages a variety of off-the-shelf voltage and current sensing technologies, analog-to-digital conversion, and sensor correction algorithms to yield more accurate and reliable digital measurements that support a multitude of applications and use cases. Sample performance and accuracy results are provided, including measurements at power frequency and higher harmonics. The system extends the native performance of the medium voltage sensors used in the system, for example, broadening measurement bandwidth beyond a few kHz, appropriate for measuring switching surges and harmonics on medium voltage distribution systems. The digital sensor system is installed and characterized in the field with a high-bandwidth optical calibration system to determine site-dependent calibration and performance issues.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Investigation of Nonlinear Difference-Frequency Wave Excitation on a Semisubmersible Offshore-Wind Platform with Bichromatic-Wave CFD Simulations: Preprint

The natural surge and pitch frequencies of semisubmersible offshore wind platforms are typically designed to be below the wave frequencies to avoid direct excitation. However, surge or pitch resonance can be excited by the nonlinear low-frequency loads generated by irregular incident waves. Second-order potential-flow models with added Morison drag have been found to underpredict this low-frequency excitation and response. As part of the OC6 project, Computational Fluid Dynamics (CFD) simulations were performed to enable a better understanding of the low-frequency loads and the limitations of lower-fidelity models. The focus of the current paper is to set up a computationally cost-effective CFD simulation of a fixed semisubmersible platform to investigate nonlinear difference-frequency loads and establish the corresponding uncertainty in the results. Due to the high computing cost, CFD simulations of irregular waves can be challenging. Instead, simulations were performed with bichromatic waves having a shorter repeat period. A preliminary comparison with Quadratic Transfer Functions from second-order potential-flow theory shows that CFD models consistently predict higher nonlinear wave loads at the difference frequency, likely due to flow separation and viscous drag not accounted for in potential-flow theory.

2nd order↗

State and Local Planning for Energy (SLOPE) Platform

This fact sheet outlines the basic overview features, purpose, and additional information for the State and Local Planning for Energy (SLOPE) Platform. SLOPE is a collaboration between nine U.S. Department of Energy (DOE) technology offices and the National Renewable Energy Laboratory (NREL), integrates and delivers jurisdictionally resolved potential and projection data on energy efficiency, renewable energy, and sustainable transportation in an easy-to-access online platform to enable data-driven state and local energy planning and decision-making.

48 EE - Weatherization and Intergovernmental Progr↗

Two-DoF Model-Informed Controller Gain Tuning for Several Floating Wind Platforms

Much effort has recently been put into the development of collective blade pitch controllers for floating offshore wind turbines, with the aim of overcoming negative damping issues that arise with traditional control methods. One proposed approach to this challenge involves using a two-degree-of-freedom model to inform the gain schedule of a nacelle velocity feedback term in an otherwise conventional proportional-integral controller. The model uses tower-top fore-aft and rotor angular displacements, and is used to calculate a nacelle velocity feedback gain that results in a specified increase in platform pitch damping. Earlier performance evaluations of this tuning method were favorable, suggesting its potential as an easy way for researchers to obtain an adequate controller. This paper expands on those previous results by examining the performance of the tuning method relative to baseline controllers for several hull configurations, and for several prescribed increases in platform pitch damping. Simulations were run in OpenFAST for several load cases above rated wind speed and show results consistent with trends in the earlier study. The tuning method is thus shown to be adaptable to many different types of hulls, making it useful for the evaluation of prototype designs.

artificial intelligence↗

Toward Simulating Turbulent Wall-Bounded Flows at High Reynolds Numbers on Exascale Platforms

Given that wall resolved LES (WRLES) of high Reynolds number flows will continue to be intractable on even exascale computing platforms, there is considerable effort to make hybrid RANS/LES (HRLES) methods the tool of choice for predictive simulations of high-Re separated flows. The fidelity of HRLES depends on the ability of the subgrid model to account for the effects of the filtered scales on the resolved scales, and on the numerical schemes that are used to evolve the Navier-Stokes equations. While higher-order numerical schemes, with low dissipation/dispersion errors (and higher arithmetic intensity), are commonly used for canonical flow simulations (on simpler geometries), the bulk of the high-Re flow simulations on complex geometry still employ nominally second-order accurate schemes in structured/unstructured flow solvers. Hence, there is a need for better sub-grid models that can improve the predictive capability of both the higher-order flow solvers and existing second-order accurate flow solvers, for simulating turbulent separated flows. This talk is about ongoing efforts to develop HRLES subgrid models from DNS/WRLES simulations of canonical flows over curved and sharply discontinuous surfaces and their ability to predict high-Re flows on current petascale platforms.

Balakrishnan, Ramesh↗