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DOE OSTI2012

AVESTAR Center for Operational Excellence of Clean Energy Plants

To address challenges in attaining operational excellence for clean energy plants, the U.S.Department of Energy’s National Energy Technology Laboratory has launched a world-class facility for Advanced Virtual Energy Simulation Training and Research (AVESTAR™). The AVESTAR Center brings together state-of-the-art, real time,high-fidelity dynamic simulators with operator training systems and 3D virtual immersive training systems into an integrated energy plant and control room environment. This presentation will highlight the AVESTAR Center simulators, facilities, and comprehensive training, education, and research programs focused on the operation and control of high-efficiency, near-zero-emission energy plants.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

C3F: Collaborative Container-based Model Coupling Framework

Solving complex real-world grand challenge problems requires in-depth collaboration of researchers from multiple disciplines. Such collaboration often involves harnessing multiscale and multi-dimensional data and combining models from different fields to simulate systems. However, the progress on this front has been limited mainly due to significant gaps in domain knowledge and tools that are typically employed in silos of the domains. Researchers from different fields face considerable barriers to understanding and reusing each other’s data/models in order to collaborate effectively. For example, in solving the global sustainability problems, researchers from hydrology, climate science, agriculture, and economics need to run their respective models to study different components of the global and local food, energy and water systems while, at the same time, need to interact with other researchers and integrate the results of one model with another. Developing this kind of model coupling workflow calls for (1) a large amount of data being processed and exchanged across domains and organizations, (2) identifying and processing the output of one model to make it ready for integration into another model, (3) controlling the workflow dynamically so that it runs until a certain convergence condition or other criteria is met, and (4) close collaboration among the modelers to explore, tune, and test the configuration and data transformation needed to link the models. We have developed C3F, a flexible collaborative model coupling framework to help researchers accelerate their model integration and linking efforts by leveraging advanced cyberinfrastructure such as high-performance computing and virtual containers. In this paper, we describe our experience and lessons learned in developing this cyberinfrastructure solution to support the linking of Water Balance Model (WBM) and SIMPLE-G agricultural economic model in an NSF funded INFEWS project and a DOE-funded Program on Coupled Human and Earth Systems (PCHES) to study the implications of groundwater scarcity for food-energy-water systems. The C3F model coupling framework can be extended to facilitate other model linkages as well.

containerization↗

DOE OSTI2026

Genesis Data Card Schema, Template and Supporting Tools

Genesis Data Cards provide a standardized template and schema for documenting scientific datasets in support of discovery, access, interoperability, reusability, governed use, and AI usability. This release of the Genesis Data Card repository includes a versioned Markdown template, a LinkML schema with generated Pydantic and JSON artifacts, schema documentation, and example completed data cards. Validation tooling is provided to ensure that completed data cards conform to the schema prior to submission. Accompanying documentation for the structured metadata is provided as a Field Reference Guide. The schema and accompanying template provided in this repository address the call for actionable context that enables humans and AI systems to find, access, interpret, cite, and reuse data, and, when appropriate, integrate it into AI and machine learning workflows. The data card is intended to serve as a common metadata artifact intended to support standardized, cross-program dataset documentation across Department of Energy (DOE)-aligned efforts, including but not limited to Genesis Mission-related implementations, the Office of Science, National Nuclear Security Administration (NNSA), and Advanced Simulation and Computing (ASC) data governance and stewardship initiatives.

data card↗

DOE OSTI2016

A High-Fidelity Approach for the Simulation of Flow-Induced Vibration

Flow-induced vibration (FIV) is a widespread problem in energy systems becausethey rely on fluid movement for energy conversion. Vibrating structures may be damaged as fatigue or wear occur. Given the importance of reliable components in the nuclear industry, flow-induced vibrations have long been a major concern in the safety and operation of nuclear reactors. In particular,nuclear fuel and steam generators have been known to suffer from flow-induced vibrations and related failures. Over the past five years, the Nuclear EnergyAdvanced Modeling and Simulation program has developed the integrated multiphysics code suite SHARP. The goal of developing such a tool is to perform multiphysics modeling of the components inside a reactor core, the full reactor core or portions of it, and be able to achieve that with various levelsof fidelity. This flexibility allows users to select the appropriate level of fidelity for their computational resources and design constraints.In particular SHARP contains high-fidelity single-physics codes for structural mechanics and fluid mechanics calculations: the structural mechanics implicit code Diablo and the computational fluid dynamics spectral element code Nek5000. Both codes are state-of-the-art.highly scalable (up to millions of processors in the case of Nek5000) tools that have been extensively validated. These tools form a strong basis on which to build an FIV modeling capability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

The disCO2ver Platform: Curating Data and Tools for Geologic Carbon Sequestration and Deep Subsurface Research Systems

The U.S. DOE National Energy Technology Laboratory has invested 12+ years of development into the data repository and digital laboratory, the Energy Data eXchange (EDX, edx.netl.doe.gov). Supporting a variety of research areas across the DOE Office of Fossil Energy and Carbon Management, the platform has successfully curated and preserved thousands of data products from DOE research. The Carbon Storage Program has successfully supported data curation, upload, and publishing of data products on EDX for many years, demonstrating a success story of how resources like EDX can effectively help with long term preservation and publishing of DOE data products. EDX continues to shift towards cloud-supported infrastructure, taking a hybrid approach combining on-premises compute and storage integrated with cloud-hosted services. The integration of cloud compute and hybrid architecture enables the development of EDX-hosted platforms that tailor the data and tools hosted on them to a specific community, enables implementation of machine learning tools for data discovery and filtering, and enables the hosting of virtual (online user interface) tools. Geologic carbon sequestration (GCS) research continues to scale up in response to the current administration goals to reduce greenhouse gas emissions and transition the energy economy. Over the last year, EDX’s disCO2ver platform has been developed in response to the need for access to data products and tools to support the scaling up of GCS research. disCO2ver provides access to data resources and tools, produced by DOE and outside authoritative external resources. The platform also provides a user-access control component for the virtualization and cloud hosting of tools. Tools that need to be virtualized, to eliminate the need for users to download the tool and use local compute resources, is essential to supporting big-data analysis and machine learning that is becoming common place in carbon storage modeling, risk analysis, and data publishing practices. This talk will review the EDX’s disCO2ver platform and the current work ongoing to curate data and tools to support GCS and deep subsurface systems research.

Morkner, Paige↗

DOE OSTI2024

IER-518: Data Analysis for High Multiplication Subcritical Experiments [Slides]

This presentation begins with a discussion of goals & motivation. This lecture then covers: experimental configurations, computational models, experimental measurements and simulations. Finally, this presentation concludes with data analysis & results plus a conclusion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

SIGMA Release v1.2 - Capabilities, Enhancements and Fixes

In this report, we present details on SIGMA toolkit along with its component structure, capabilities, and feature additions in FY15, release cycles, and continuous integration process. These software processes along with updated documentation are imperative to successfully integrate and utilize in several applications including the SHARP coupled analysis toolkit for reactor core systems funded under the NEAMS DOE-NE program.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Nuclear Data: What is the big deal? [Slides]

This presentation begins with a look at the practical application: differential and integral data. It also includes a nuclear data evaluation: cross section formalisms, data processing and cross section library generation, computer tools, and criticality safety assessment: nuclear data. The presentation ends with some concluding remarks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2012

AVESTAR Center for Operational Excellence of Clean Energy Plants

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

SU-E-T-419: Workflow and FMEA in a New Proton Therapy (PT) Facility

Purpose: Workflow is an important component in the operational planning of a new proton facility. By integrating the concept of failure mode and effect analysis (FMEA) and traditional QA requirements, a workflow for a proton therapy treatment course is set up. This workflow serves as the blue print for the planning of computer hardware/software requirements and network flow. A slight modification of the workflow generates a process map(PM) for FMEA and the planning of QA program in PT. Methods: A flowchart is first developed outlining the sequence of processes involved in a PT treatment course. Each process consists of a number of sub-processes to encompass a broad scope of treatment and QA procedures. For each subprocess, the personnel involved, the equipment needed and the computer hardware/software as well as network requirements are defined by a team of clinical staff, administrators and IT personnel. Results: Eleven intermediate processes with a total of 70 sub-processes involved in a PT treatment course are identified. The number of sub-processes varies, ranging from 2-12. The sub-processes within each process are used for the operational planning. For example, in the CT-Sim process, there are 12 sub-processes: three involve data entry/retrieval from a record-and-verify system, two controlled by the CT computer, two require department/hospital network, and the other five are setup procedures. IT then decides the number of computers needed and the software and network requirement. By removing the traditional QA procedures from the workflow, a PM is generated for FMEA analysis to design a QA program for PT. Conclusion: Significant efforts are involved in the development of the workflow in a PT treatment course. Our hybrid model of combining FMEA and traditional QA program serves a duo purpose of efficient operational planning and designing of a QA program in PT.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2014

Comparison of Fission Product Release Predictions Using PARFUME with Results from the AGR-1 Irradiation Experiment

This report documents comparisons between post-irradiation examination measurements and model predictions of silver (Ag), cesium (Cs), and strontium (Sr) release from selected tristructural isotropic (TRISO) fuel particles and compacts during the first irradiation test of the Advanced Gas Reactor program that occurred from December 2006 to November 2009 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). The modeling was performed using the particle fuel model computer code PARFUME (PARticle FUel ModEl) developed at INL. PARFUME is an advanced gas-cooled reactor fuel performance modeling and analysis code (Miller 2009). It has been developed as an integrated mechanistic code that evaluates the thermal, mechanical, and physico-chemical behavior of fuel particles during irradiation to determine the failure probability of a population of fuel particles given the particle-to-particle statistical variations in physical dimensions and material properties that arise from the fuel fabrication process, accounting for all viable mechanisms that can lead to particle failure. The code also determines the diffusion of fission products from the fuel through the particle coating layers, and through the fuel matrix to the coolant boundary. The subsequent release of fission products is calculated at the compact level (release of fission products from the compact) but it can be assessed at the particle level by adjusting the diffusivity in the fuel matrix to very high values. Furthermore, the diffusivity of each layer can be individually set to a high value (typically 10-6 m2/s) to simulate a failed layer with no capability of fission product retention. In this study, the comparison to PIE focused on fission product release and because of the lack of failure in the irradiation, the probability of particle failure was not calculated. During the AGR-1 irradiation campaign, the fuel kernel produced and released fission products, which migrated through the successive layers of the TRISO-coated particle and potentially through the compact matrix. The release of these fission products was measured in PIE and modeled with PARFUME.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Optimal Operator Training Reference Models for Human-in-the-loop Systems

The human operator is an integral part of a stable and safe power system. While there is increasing attention paid to automation improvements, the importance of understanding and training human operators may be understated. This paper discusses a project to enhance operator training programs by evaluating human performance relative to a reference operator model identified using optimal control theory. Along with establishing a simple computer-based operator workstation for future training purpose, this paper describes the optimal control response design methodology for a human-in-the-loop power system experiment. The overall system model is presented. An optimal controller synthesis methodology is applied to the model system and the optimal controller is designed. The performance of the optimal controller is then compared to human subject performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Job Scheduler-Driven Power Gateway for High Performance Computing

Power gateways in the form of a microgrid can incorporate multiple distributed energy resources (DER) in either grid forming or grid following mode and support high performance computing (HPC) power profiles including the large load-follow requirements observed in multi-user HPC systems. The microgrid’s flexibility to operate in either grid forming or grid following mode and to actively switch between these modes enables baseline power from multiple non-baseline DER while maintaining high power quality metrics for the HPC system. But this enormous flexibility in demand response and time of use shifting is generally programmed independently of any integration with an HPC job scheduler which can better inform the load shaping by the microgrid. While there are many existing approaches where the HPC job scheduler takes in information from the grid to make queue scheduling decisions, this work takes the opposite view and explores a scheduler where the jobs in the queue can directly impact the settings of the grid. Several HPC scheduler strategies are tested where the jobs in the queue directly impact the settings of a microgrid designed for HPC operation which is driving a datacenter with three classes of HPC architectures. The scheduler operation is shown using a microgrid with 64 kW of solar capacity and 320 kWh of battery over a period of 21 days operating with significant low-follow swings, a throttled grid, cloudy conditions, switching between grid following and grid forming modes, and a wide range of battery states-of-charge all while maintaining high quality power metrics. The scheduler provides a mechanism for the job queue to directly impact a power gateway like a microgrid and to improve HPC power outcomes such as maximizing renewable energy usage

microgrid↗

DOE OSTI2018

Plant Modernization Pathway: FY 2019 External Review Summary Report

This report describes an external review conducted by the Light Water Reactor Sustainability Program Plant Modernization Pathway (referred to as Pathway) to solicit feedback on the topics and results of the ongoing Instrumentation and Control (I&C) research program. This review was held in conjunction with the Nuclear Energy Institute (NEI) Digital I&C Working Group meeting that was held at Idaho National Laboratory on October 16–17, 2018. Members of the Nuclear Regulatory Commission (NRC) staff working on digital I&C issues through their Integrated Action Plan also attended. The NEI and NRC agreed that the meeting participants would serve as an external review panel for the purpose of obtaining expert input on the value and timing of the research projects. Five major research areas were presented, along with demonstrations of new technologies in the Human Systems Simulation Laboratory and the Computer-Assisted Virtual Environment. Following the presentations, the external review was conducted by referring to a set of summary slides of the five research areas, and allowing each participant to enter ratings and comments on a survey form as each area was addressed. Fourteen forms were returned. These feedback forms were analyzed by the Pathway who compiled and responded to the data and comments, which are documented in this report. The participants also had opportunity to provide comments on the LWRS Program as a whole and to suggest additional research topics of value. The feedback provided by the external review participants is taken to be a strong endorsement of the types of projects being conducted by the Pathway, the value they hold for the operating nuclear plants, and the general timing of need. The feedback aligns well with the priorities, levels of efforts allocated for the research projects, and project schedules of the current Pathway research program. The feedback also provides realistic observations on the practicality of some aspects of implementing these technologies. The Pathway will consider all of the feedback and address the recommended research topics that have been identified by the external review participants. Pathway research plans will be adjusted as warranted.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2012

Integrating Empirical-Modeling Approaches to Improve Understanding of Terrestrial Ecology Processes

Recent decades have seen tremendous increases in the quantity of empirical ecological data collected by individual investigators, as well as through research networks such as FLUXNET (Baldocchi et al., 2001). At the same time, advances in computer technology have facilitated the development and implementation of large and complex land surface and ecological process models. Separately, each of these information streams provides useful, but imperfect information about ecosystems. To develop the best scientific understanding of ecological processes, and most accurately predict how ecosystems may cope with global change, integration of empirical and modeling approaches is necessary. However, true integration - in which models inform empirical research, which in turn informs models (Fig. 1) - is not yet common in ecological research (Luo et al., 2011). The goal of this workshop, sponsored by the Department of Energy, Office of Science, Biological and Environmental Research (BER) program, was to bring together members of the empirical and modeling communities to exchange ideas and discuss scientific practices for increasing empirical - model integration, and to explore infrastructure and/or virtual network needs for institutionalizing empirical - model integration (Yiqi Luo, University of Oklahoma, Norman, OK, USA). The workshop included presentations and small group discussions that covered topics ranging from model-assisted experimental design to data driven modeling (e.g. benchmarking and data assimilation) to infrastructure needs for empirical - model integration. Ultimately, three central questions emerged. How can models be used to inform experiments and observations? How can experimental and observational results be used to inform models? What are effective strategies to promote empirical - model integration?

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

DEFT: a program for operators in EFT

We describe a Python-based computer program, DEFT, for manipulating operators in effective field theories (EFTs). In its current incarnation, DEFT can be applied to 4-dimensional, Poincaré invariant theories with gauge group SU(3)×SU(2)×U(1), such as the Standard Model (SM), but a variety of extensions (e.g. to lower dimensions or to an arbitrary product of unitary gauge groups) are conceptually straightforward. Amongst other features, the program is able to: (i) check whether an input list of Lagrangian operators (of a given dimension in the EFT expansion) is a basis for the space of operators contributing to S-matrix elements, once redundancies (such as Fierz-Pauli identities, integration by parts, and equations of motion) are taken into account; (ii) generate such a basis (where possible) from an input algorithm; (iii) carry out a change of basis. We describe applications to the SM (where we carry out a number of non-trivial cross-checks) and extensions thereof, and outline how the program may be of use in precision tests of the SM and in the ongoing search for new physics at the LHC and elsewhere. The code and instructions can be downloaded from http://web.physics.ucsb.edu/~dwsuth/DEFT/.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2012

Detection of transcriptional triggers in the dynamics of microbial growth: application to the respiratorily versatile bacterium Shewanella oneidensis

The capacity of microorganisms to respond to variable external conditions requires a coordination of environment-sensing mechanisms and decision-making regulatory circuits. Here, we seek to understand the interplay between these two processes by combining high-throughput measurement of time-dependent mRNA profiles with a novel computational approach that searches for key genetic triggers of transcriptional changes. Our approach helped us understand the regulatory strategies of a respiratorily versatile bacterium with promising bioenergy and bioremediation applications, Shewanella oneidensis, in minimal and rich media. By comparing expression profiles across these two conditions, we unveiled components of the transcriptional program that depend mainly on the growth phase. Conversely, by integrating our time-dependent data with a previously available large compendium of static perturbation responses, we identified transcriptional changes that cannot be explained solely by internal network dynamics, but are rather triggered by specific genes acting as key mediators of an environment-dependent response. These transcriptional triggers include known and novel regulators that respond to carbon, nitrogen and oxygen limitation. Our analysis suggests a sequence of physiological responses, including a coupling between nitrogen depletion and glycogen storage, partially recapitulated through dynamic flux balance analysis, and experimentally confirmed by metabolite measurements. Our approach is broadly applicable to other systems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

ARIES Network Requirements Review

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all of its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. On May 1, 2021, ESnet and the DOE Office of Energy Efficiency and Renewable Energy (EERE), organized an ESnet requirements review of the ARIES (Advanced Research on Integrated Energy Systems) platform. Preparation for this event included identification of key stakeholders to the process: program and facility management, research groups, technology providers, and a number of external observers. These individuals were asked to prepare formal case study documents in order to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗